Annual Report on the Climate System 2016

March 2017

Japan Meteorological Agency

Preface

The Japan Meteorological Agency is pleased to publish the Annual Report on the Climate

System 2016. The report summarizes 2016 climatic characteristics and climate system conditions worldwide, with coverage of specific events including the effects of the summer

2014 – spring 2016 El Niño event and notable aspects of Japan’s climate in summer 2016. I am confident that the report will contribute to the understanding of recent climatic conditions and enhance awareness of various aspects of the climate system, including the causes of extreme climate events.

Teruko Manabe Director, Climate Prediction Division Global Environment and Marine Department Japan Meteorological Agency

Contents

Preface 1. Explanatory notes ··························································································· 1 1.1 Outline of the Annual Report on the Climate System ······································· 1 1.2 Climate in Japan ···················································································· 1 1.3 Climate around the world ························································ ·············· 2 1.4 Atmospheric circulation ············· ···························································· 3 1.5 Oceanographic conditions ··········· ··············································· ·········· 5 1.6 Snow cover and sea ice ······································································· 5

2. Annual summaries of the 2016 climate system ········································· ··· 6 2.1 Climate in Japan ················ ··········· ···················································· 6 2.2 Climate around the world ···································································· 12 2.3 Extratropical circulation ·············· ····················································· 19 2.4 Tropical circulation and convective activity ··· ················ ··················· ·· ·· 2 4 2.5 Oceanographic conditions ········· ······················· ··················· ··············· 33 2.6 Stratospheric circulation in boreal winter ····················································· 36 2 .7 Summary of the Asian summer monsoon ··················· ··············· ······· ······· ·· 41 2.8 Arctic sea ice conditions ············································································ 45 2.9 Snow cover in the Northern Hemisphere ························································· 47

3. Analysis of specific events ········································································· 49 3.1 T he El Niño event ending boreal spring 2016 and its effects ······················· 49 3.2 Extreme climate conditions in Japan in August 2016 ····································· 68

1. Explanatory notes phenomenon. Average temperatures over Japan are first

1.1 Outline of the Annual Report on the Climate derived based on temperature deviations from the 1971 – System 2000 average of the 15 stations, and are then adjusted to The Japan Meteorological Agency (JMA) has the 1981 – 2010 baseline. The observatories at Miyazaki published the Annual Report on the Climate System on and Iida were relocated in May 2000 and May 2002, the Tokyo Climate Center website1 since 2007. The aim respectively. For these stations, any discontinuity in the of such provision is to share information on the climate temperature time series is adjusted to cancel out the system and recent related conditions with national influence of the moves. meteorological services, research institutes, universities and other interested parties. 1.2.2 Climatological normal and rank This report summarizes 2016 climatic characteristics The seasonal characteristics of Japan’s climate are and climate system conditions worldwide, with coverage summarized in Section 2.1, which reports temperature of specific events including the effects of the summer anomalies, precipitation ratios and sunshine duration 2014 – spring 2016 El Niño event and notable aspects of ratios derived from daily observations made at 154 Japan’s climate in summer 2016. surface meteorological stations. Regional averages are For more detailed climate information, see the calculated for the four divisions of northern Japan, various products provided via the Tokyo Climate eastern Japan, western Japan and Okinawa/Amami as Center/JMA website at well as for the eleven subdivisions of Hokkaido, Tohoku, http://ds.data.jma.go.jp/tcc/tcc/index.html. Kanto-koshin, Hokuriku, Tokai, Kinki, Chugoku, Shikoku, northern part of Kyushu, southern part of The following sections describe the data sources and Kyushu and Okinawa. For precipitation ratios and analysis methods used in the compilation of this report. sunshine duration ratios, the divisions of northern, Climatological normals are averages for the period from eastern and western Japan are further divided into the 1981 to 2010. Unless otherwise noted, anomalies are Pacific side and the Sea of Japan side (Fig. 1.2-1). Tables deviations from normals. on regional climate conditions contain regional averages

and rankings of temperature anomalies, precipitation 1.2 Climate in Japan ratios and sunshine duration ratios. The ranking The descriptions in this section mainly relate to categories are “below normal,” “near normal” and Section 2.1. “above normal,” each of which has an equal relative 1.2.1 Average temperature over Japan frequency of occurrence (33%) for the period from 1981 Annual anomalies of the average surface temperature to 2010. The bottom and top 10% of the “below normal” over Japan since 1898 are illustrated in Section 2.1.1. and “above normal” categories are defined as The anomalies shown are calculated from temperatures “significantly below normal” and “significantly above recorded at 15 meteorological observatories (Abashiri, normal,” respectively. Nemuro, Suttsu, Yamagata, Ishinomaki, Fushiki, Iida, Choshi, Sakai, Hamada, Hikone, Miyazaki, Tadotsu, Naze and Ishigakijima) selected from among those deemed to be least influenced by the urban heat island

1 http://ds.data.jma.go.jp/tcc/tcc/products/clisys/arcs.html

Fig. 1.2-1 Operational climatological regions and station locations

1.3 Climate around the world (NOAA) for the period before 2001. The SSTs are 1° × The descriptions in this section mainly relate to 1° grid values derived from COBE-SST datasets (JMA Section 2.2. The regions used in this report are defined as 2006), and values in areas partly covered by sea ice are shown in Fig. 1.3-1. excluded. In the calculation of global averages, land surface temperature anomalies and SST anomalies 1.3.1 Global average temperature against the 1971 – 2000 baseline are incorporated into 5° Annual anomalies of the global average surface × 5° grid values, which are weighed in proportion to the temperature since 1891 are illustrated in Section 2.2.1. area of the relevant grids, and the grid values are The anomalies shown are derived from a combined averaged over the globe. The global averages are dataset of near-surface air temperatures over land and sea adjusted to the 1981 – 2010 baseline. The annual values surface temperatures (SSTs). The over-land air are accompanied by 90% confidence intervals based on temperatures are based on on-site observation data estimated errors attributable to the inhomogeneity of data derived from monthly CLIMAT reports for the period availability (Ishihara 2007). from 2001 onward, and from Global Historical Climate Network (GHCN) datasets produced by the National Oceanographic and Atmospheric Administration

2 1.3.2 Data and climatological normals precipitation are calculated by dividing the total number Figures on world climatic conditions are based on of extreme events observed at stations by the total CLIMAT reports. Historical datasets are derived from number of available observation data for each 5° × 5° GHCN datasets and CLIMAT reports (from June 1982 grid box. Frequencies are represented by semicircles. For onward, prior to GHCN datasets). grid boxes where fewer than ten observations are Data and information on disasters are based on available, no semicircle is shown. Since the frequency of official reports from the United Nations and national extreme events is expected to be about 3% on average, governments, and from databases of research institutes occurrence is considered to be above normal when the (Emergency Events Database (EM-DAT)). figure is 10% or more.

1.3.3 Extreme climate events 1.4 Atmospheric circulation JMA defines an extreme climate event as a The descriptions in this section mainly relate to phenomenon likely to happen only once every 30 years Sections 2.3, 2.4, 2.6, 2.7 and 2.8 and Chapter 3. or longer. For monthly/seasonal mean temperatures, extremely high (or low) temperatures are deemed to be 1.4.1 Data and climatological normals those with an anomaly greater than 1.83 times the Atmospheric circulation data are based on the results standard deviation based on the period 1981 – 2010. For of six-hourly global objective analysis conducted at 00, monthly/seasonal precipitation totals, extremely heavy 06, 12 and 18 UTC using data from the Japanese 55-year (or light) precipitation is that above (or below) any value reanalysis (JRA-55; Kobayashi et al. 2015). The normal observed during the period 1981 – 2010. is the 1981 – 2010 average of JRA-55 data (JMA 2011).

1.3.4 Annual figures 1.4.2 Atmospheric circulation and convection For annual mean temperature anomalies shown in Wave activity flux (Takaya and Nakamura 2001) Section 2.2.2, categories are defined by the annual mean indicates the propagation of Rossby wave packets. temperature anomaly against the normal divided by its Tropical convective activity is inferred from outgoing standard deviation and averaged in 5° × 5° grid boxes. longwave radiation (OLR). It can be assumed that lower For annual total precipitation, categories are defined by values of OLR indicate enhanced convective activity the ratio of annual precipitation to the normal averaged in except in the mid- and high latitudes during the winter 5° × 5° grid boxes. For frequencies of extreme events season and in high-altitude areas. The original OLR data based on monthly observations for the year, the ratios of are from observations conducted by NOAA’s extremely high/low temperature and heavy/light polar-orbiting satellites.

Fig. 1.3-1 Names of world regions

According to Helmholtz's theorem in vector analysis, 1.4.3 Atmospheric and oceanic monitoring indices for horizontal wind can be decomposed into rotational and the tropics divergent components. Using the stream function, the Section 2.4 describes the characteristics of rotational component can be written as atmospheric and oceanographic monitoring indices to support analysis of variations related to El Niño-Southern Oscillation (ENSO).

(ψ: stream function; uψ, vψ: rotational components of The Southern Oscillation Index (SOI) is defined as horizontal winds). A positive stream function anomaly the normalized difference in monthly mean sea-level indicates stronger (weaker) clockwise pressure (SLP) anomalies normalized by their standard (counter-clockwise) circulation than the normal, and vice deviations between Tahiti and Darwin. SLP anomalies versa. are calculated based on CLIMAT reports. Using the velocity potential, the divergent component OLR indices are defined as reversed-sign can be written as area-averaged OLR anomalies normalized by their standard deviations (Table 2.4.1). It should be noted that positive and negative OLR index values indicate

(χ: velocity potential; uχ, vχ: divergent components of enhanced and suppressed convective activity, horizontal winds). respectively, compared to the normal. A positive velocity potential anomaly indicates Equatorial zonal wind indices are defined as stronger (weaker) large-scale convergence (divergence) area-averaged zonal wind anomalies normalized by their than the normal, and vice versa. standard deviations. The equatorial intra-seasonal variation associated Asian summer monsoon OLR indices (SAMOI) are with the Madden-Julian Oscillation (MJO) can be derived from OLR anomalies from May to October. determined from the time-longitude cross section of the SAMOI (A), (N) and (W) indicate the overall activity of five-day mean 200-hPa velocity potential. the Asian summer monsoon, its northward shift and its westward shift, respectively. SAMOI definitions are as

4 follows: 1.6 Snow cover and sea ice SAMOI (A) = (–1) × (W + E) The descriptions in this section relate to Sections 2.8 SAMOI (N) = S – N and 2.9. SAMOI (W) = E – W The number of days of snow cover is determined W, E, N and S indicate area-averaged OLR anomalies for based on observations by the Special Sensor the respective regions shown in Fig. 1.4-1 normalized by Microwave/Imager (SSM/I) and the Special Sensor their standard deviations (JMA 1997). Microwave Imager Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) polar-orbiting satellites. The algorithm for the analysis was developed by JMA. The sea ice extent is based on observations conducted by SSM/I and SSMIS and by the Scanning Multichannel Microwave Radiometers (SMMRs) on board the Nimbus satellites.

References Ishihara, K., 2007: Estimation of standard errors in global average surface temperatures (in Japanese), Weather Service Bulletin, Vol. 74, 19 – 26. Fig. 1.4-1 Asian Summer Monsoon OLR Index (SAMOI) JMA, 1997: Monthly Report on Climate System, June 1997. areas JMA, 2006: Characteristics of Global Sea Surface Temperature Data (COBE-SST), Monthly Report on Climate System, Separated Volume No. 12. 1.5 Oceanographic conditions JMA, 2011: JMA’s New Climatological Normals for 1981 – The descriptions in this section relate to Section 2.5. 2010, Data Report on Climate System 2011. Kobayashi, S., Y. Ota, Y. Harada, A. Ebita, M. Moriya, H. Sea surface temperatures (SSTs) are based on Onoda, K. Onogi, H. Kamahori, C. Kobayashi, H. Endo, K. COBE-SST datasets in 1° × 1° grid boxes. The details of Miyaoka, and K. Takahashi, 2015: The JRA-55 Reanalysis: SST analysis and the SST normal have been described General Specifications and Basic Characteristics. J. Meteorol. Soc. Japan, 93, 5 – 48. previously by JMA (2006). Takaya, K. and H. Nakamura, 2001: A formulation of a Ocean heat content is determined using five-day phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying mean datasets of MOVE/MRI.COM-G2 (Multivariate basic flow. J. Atom. Sci., 58, 608 – 627. Ocean Variational Estimation / Meteorological Research Toyoda, T., Y. Fujii, T. Yasuda, N. Usui, T. Iwao, T. Kuragano and M. Kamachi, 2013: Improved Analysis of Institute Community Ocean Model - Global version 2; Seasonal-Interannual Fields Using a Global Ocean Data Toyoda et al. 2013), which was developed at the Assimilation System, Theoretical and Applied Mechanics Japan, 61, 31-48. Oceanography and Geochemistry Research Department of the Meteorological Research Institute (MRI).

5 2. Annual summaries of the 2016 climate system observatories in Japan (Table 2.1-2). 2.1 Climate in Japan Annual precipitation amounts were significantly - As temperatures were generally above normal all above normal on the Pacific side of northern Japan, in over Japan, annual mean temperatures were western Japan and in Okinawa/Amami. This was significantly above normal almost nationwide. attributable to the significant influence of - Four typhoons made landfall on northern Japan in low-pressure systems and fronts in western Japan and August, bringing record heavy rainfall with storms Okinawa/Amami in winter 2015/16 and autumn, and in northern Japan. to the numerous typhoons that approached northern - In autumn, seasonal precipitation amounts were Japan in August. Muroto-misaki (Kochi Prefecture) significantly above normal and seasonal sunshine recorded its highest rainfall amounts since 1920. In durations were significantly below normal in eastern Japan, annual precipitation amounts were near western Japan. normal. Annual sunshine durations were below normal in 2.1.1 Average surface temperature western Japan and above normal in northern Japan The annual anomaly of the average surface and on the Sea of Japan side of eastern Japan due to temperature over Japan (i.e., that averaged over 15 high-pressure systems that tended to cover northern observatories confirmed as being relatively unaffected Japan in spring. Durations were near normal on the by urbanization) for 2016 was +0.88°C above the Pacific side of eastern Japan and in Okinawa/Amami. 1981 – 2010 average, making it the highest since 1898. On a longer time scale, annual mean temperatures 2.1.3 Seasonal characteristics over Japan have risen at a rate of about +1.19°C per (a) Winter (December 2015 – February 2016, Fig. century since 1898 (Fig. 2.1-1). 2.1-4 (a)) The record-high temperature recorded in 2016 was In association with a weak winter monsoon, due to year-round warm climatic conditions seasonal temperatures were above normal all over associated with seasonal atmospheric circulation as Japan, especially in eastern and western parts. described in (a) to (d) of Section 2.1-3. Long-term Seasonal snowfall amounts for the Sea of Japan side climate change and tropospheric air temperature were generally below normal and significantly above increase on a global scale due to the El Niño event normal in northern Kyushu due to considerably that peaked strongly during boreal winter 2015/2016 cold-air outbreaks at the end of January. are identified as background factors. Due to the significant influences of low-pressure systems and fronts, seasonal precipitation amounts 2.1.2 Annual characteristics (Table 2.1-1, Fig. 2.1-2, were above normal all over Japan, with Fig. 2.1-3) Okinawa/Amami experiencing record highs (188% of In 2016, temperatures were generally above the normal) for winter since 1946/47. normal all over Japan except for autumn in northern (b) Spring (March – May, Fig. 2.1-4 (b)) Japan. Annual mean temperatures were significantly Seasonal mean temperatures were significantly above normal almost nationwide. In particular, the above normal due to warm southerly winds associated temperature for eastern Japan tied with 2004 as the with dominant high-pressure systems to the east of highest since 1946 (+1.0°C above the normal). Japan and the development of the subtropical high to Temperature records were broken at 16 of 154 the south of Japan.

6 Seasonal sunshine durations were significantly (d) Autumn (September – November, Fig. 2.1-4 (d)) above normal on the Sea of Japan side of eastern Western Japan and Okinawa/Amami experienced Japan and above normal in northern and western record seasonal mean temperatures (+1.3 and +1.2°C Japan due to significant influences from high-pressure above the normal, respectively) for autumn since 1946 systems. due to warm southerly winds. Seasonal precipitation amounts were significantly In association with significant influences from below normal on the Sea of Japan side of eastern low-pressure systems and fronts, western Japan Japan and below normal on the Pacific side of experienced significantly above-normal seasonal northern Japan. Meanwhile, seasonal precipitation precipitation amounts and below-normal seasonal amounts were above normal on the Pacific side of sunshine durations. Seasonal precipitation was 173% western Japan and Okinawa/Amami due to the of the normal on the Sea of Japan side of western influences of low-pressure systems and fronts in Japan (the highest on record for autumn since 1946), April. while seasonal sunshine durations were 74% of the (c) Summer (June – August, Fig. 2.1-4 (c)) normal on the Sea of Japan side of western Japan and Seasonal mean temperatures and sunshine 82% of the normal on the Pacific side of the region durations were above normal all over Japan. In (both the lowest on record for autumn since 1946). Okinawa/Amami, the seasonal mean temperature was Seasonal sunshine durations were also below normal the highest on record for summer since 1946 (+1.1°C in other regions. above the normal) in association with strong solar In northern Japan, seasonal mean temperatures radiation accompanying high sunshine durations. were below normal for the first time since 2002, even Meanwhile, in northern Japan, seasonal with the high temperatures recorded in September, precipitation amounts were significantly above and temperatures remained low after October. normal. On the Pacific side of northern Japan, the figure was 163% of the normal (the highest on record for summer since 1946) in association with the frequent passage of cyclones around northern Japan in June and the approach of numerous typhoons around northern Japan in August. Four typhoons made landfall on the Hokkaido region and Iwate Prefecture, bringing significant rainfall with storms. Hokkaido and Iwate Prefecture experienced record heavy rainfall, which caused serious damage including river overflows and landslides. Seasonal precipitation amounts were also above normal on the Pacific side of western Japan in association with the active Baiu front, which brought frequent heavy rain to the Pacific side of western Japan (Table 2.1-3). At the end of June, Kyushu experienced intermittent heavy rain with flood damage and landslides.

7 Fig. 2.1-1 Long-term change in the annual anomaly of average surface temperature over Japan Anomalies are deviations from the baseline (i.e., the 1981 – 2010 average). The black line indicates the annual anomalies of the average surface temperature for each year. The blue line indicates the five-year running mean, and the red line indicates the long-term linear trend.

Table 2.1-1 Regional average and rank of annual mean temperature anomaly, annual precipitation ratio, and annual sunshine duration ratio for divisions and subdivisions (2016)

Fig. 2.1-2 Five-day running mean temperature anomaly for divisions (January – December 2016)

Table 2.1-2 Number of observatories reporting record monthly and annual mean temperatures, precipitation amounts and sunshine durations (2016) From 154 surface meteorological stations across Japan. Temperature Precipitation amount Sunshine duration

Highest Lowest Heaviest Lightest Longest Shortest January 5 3 February 1 1 1 2 March 3 8 April 2 2 May 25 June 1 6 July 1 1 August 3 8 6 September 1 1 8 October 40 1 1 12 November 1 1 December 5 2 1 Year 16 1

Fig. 2.1-3 Annual climate anomaly/ratio for Japan in 2016

Table 2.1-3 Onset/end of the Baiu (Japan’s rainy season) for individual subdivisions (2016) Area Average Average averaged date of date of Subdivisions Onset of rainy onset of End of rainy end of precipitation season* season* ratio during rainy season rainy season rainy season (1981 – 2010) (1981 – 2010) (%) Okinawa 16 May 9 May 16 June 23 June 84 Amami 16 May 11 May 18 July 29 June 103 Southern 24 May 31 May 18 July 14 July 147 Kyushu Northern 4 June 5 June 18 July 19 July 117 Kyushu Shikoku 4 June 5 June 18 July 18 July 132 Chugoku 4 June 7 June 18 July 21 July 106 Kinki 4 June 7 June 18 July 21 July 103 Tokai 4 June 8 June 28 July 21 July 89 Kanto- 5 June 8 June 29 July 21 July 74 Koushin Hokuriku 13 June 12 June 19 July 24 July 91 Southern 13 June 12 June 29 July 25 July 70 Tohoku Northern 13 June 14 June 29 July 28 July 91 Tohoku * The onset/end of the rainy season normally has a transitional period of about five days. The dates shown in the table denote the middle day of this period.

10 (a) Winter (b) Spring

Fig. 2.1-4 Seasonal anomalies/ratios for Japan in 2016 (a) Winter (December 2015 to February 2016), (b) spring (March to May), (c) summer (June to August), (d) autumn (September to November).

11 2.2 Climate around the world High temperature deviations were seen over

2.2.1 Global average surface temperature wide areas of Eurasia, North America, the Tropical The annual anomaly of the global average Pacific and the Indian Ocean (Fig. 2.2-2). surface temperature for 2016 was +0.45 ± 0.13°C The high temperatures observed in recent years above the 1981 – 2010 average. This was the are thought to be associated with a global warming warmest year since records began in 1891, trend caused by increased atmospheric surpassing the previous record of 2015 (+0.42°C). concentrations of carbon dioxide and other On a longer time scale, global average surface anthropogenic greenhouse gases. The global temperatures have risen at a rate of about +0.72°C temperature is also affected by inter-annual to per century since 1891 (Fig. 2.2-1). decadal-scale natural fluctuations intrinsic to the In 2016, monthly average air temperatures for earth’s climate. The record-high temperatures of January, February, March, April, June and July, and 2016 are partially attributed to the El Niño event seasonal average air temperatures for boreal winter, that continued until boreal spring 2016 and to spring and summer, were also the highest on record global warming. since 1891.

Fig. 2.2-1 Long-term change in the annual anomaly of global average surface temperature Anomalies are deviations from the baseline (i.e., the 1981 – 2010 average). The black dots indicate annual anomalies of the global average surface temperature for each year. The error bars indicate 90% confidence intervals. The blue line indicates the five-year running mean, and the red line indicates the long-term linear trend.

Fig. 2.2-2 Annual mean temperature anomalies in 2016 The circles indicate anomalies of surface temperature averaged in 5° x 5° grid boxes. Anomalies are deviations from the 1981 – 2010 average.

2.2.2 Regional climate Brazil (Fig. 2.2-6). Annual mean temperatures were above normal in Seasonal distribution maps for temperature and many parts of the world and below normal in the precipitation are shown in Figs. 2.2-7 and 2.2-8, southwestern part of Eastern Siberia and in northern respectively. Argentina (Fig. 2.2-3). In particular, extremely high temperatures continued for most of the year in various Major extreme climatic events and weather-related places at low latitudes, and were also frequently observed disasters occurring in 2016 are shown in Fig. 2.2-9, and from the northern part of Central Siberia to the Svalbard related overviews are given below. Islands, from the eastern part of Eastern Siberia to the (1) Heavy rain: the northeastern part of the Korean western coast of Canada, and from northern to Peninsula (August – September) southeastern Australia (Fig. 2.2-4). (2) Cold: in and around eastern Mongolia (January, Annual precipitation amounts were above normal in October – November) eastern China, Mongolia, Central Asia, southeastern (3) Heavy rain: China (April – July) Europe, Indonesia and southern Argentina, and were (4) Warm: the southern Kyushu region of Japan, to below normal in eastern Brazil and southern Chile (Fig. southeastern China (April – June, October, 2.2-5). Extremely high amounts were frequently December) observed in southeastern Europe, from the Midwest to (5) Warm: Southeast Asia (January – May, July – the southern USA and in southeastern Australia, while November) extremely low amounts were frequently observed from (6) Drought: Southeast Asia (January – May) southwestern France to northeastern Spain and in eastern (7) Tropical storm: Sri Lanka, northeastern India and Bangladesh (May)

13 (8) Warm: southern India to Sri Lanka (January – April, February, August – September, November) July – August, October, December) (27) Warm: Micronesia (March – April, June, August) (9) Heat wave (March – May) and wet (July – (28) Warm: northern to southeastern Australia (March – October): India July, September, November) (10) Heavy rain: Pakistan (July – August) (29) Wet: southeastern Australia (January, June, (11) Heavy rain: northern Pakistan to Afghanistan September) (March – April) (30) Warm: in and around New Zealand (February, May, (12) Warm: the northern part of Central Siberia to the September) Svalbard Islands (February, April – July, September) (13) Wet: southeastern Europe (February – March, May – June, October) (14) Dry: southwestern France to northeastern Spain (July – August, October, December) (15) Warm: in and around northern Algeria (January – February, October) (16) Warm: northeastern Saudi Arabia to the southern coast of the Red Sea (March, May – July) (17) Warm: in the western part of Western Africa to the northwestern part of Central Africa (April – June, August – December) (18) Warm: Seychelles to the northeastern part of South Africa (January – April, October) (19) Warm: the eastern part of Eastern Siberia to the western coast of Canada (April – August, October) (20) Wet: the Midwest to the southern USA (March – April, July – August) (21) Warm: the eastern to the southern USA (March, June – October) (22) Warm: the southwestern USA to northwestern Mexico (February – March, October – December) (23) Hurricane: Haiti and the southeastern USA (October) (24) Warm: southern Mexico to Colombia (January – August, October) (25) Warm (February – August) and Dry (February – May): eastern Brazil (26) Warm: in and around central Chile (January –

Fig. 2.2-3 Annual mean temperature anomalies for 2016 Categories are defined by the annual mean temperature anomaly against the normal divided by its standard deviation and averaged in 5° × 5° grid boxes. The thresholds of each category are -1.28, -0.44, 0, +0.44 and +1.28. The normal values and standard deviations were calculated from 1981 – 2010 statistics. Land areas without graphics represent regions for which observation data sample is insufficient or normal data are unavailable.

Fig. 2.2-4 Frequencies of extreme high/low temperature for 2016 shown as upper/lower red/blue semicircles The size of each semicircle represents the ratio of extremely high/low temperature based on monthly observation for the year in each 5° × 5° grid box. As the frequency of extreme high/low temperature is expected to be about 3% on average, occurrence is considered to be above normal for values of 10 – 20% or more.

Fig. 2.2-5 Annual total precipitation amount ratios for 2016 Categories are defined by the annual precipitation ratio to the normal averaged in 5° × 5° grid boxes. The thresholds of each category are 70, 100 and 120%. Land areas without graphics represent regions for which observation data sample is insufficient or normal data are unavailable.

Fig. 2.2-6 Frequencies of extreme heavy/light precipitation amounts for 2016 As same as Fig. 2.2-4, but for monthly values of extremely heavy/light precipitation.

16 (a) Winter (December – February) (b) Spring (March – May)

Fig. 2.2-7 Seasonal mean temperature anomalies for (a) winter (December 2015 – February 2016), (b) spring (March – May), (c) summer (June – August) and (d) autumn (September – November) As same as Fig. 2.2-3, but for seasonal mean temperature anomaly.

(a) Winter (December – February) (b) Spring (March – May)

Fig. 2.2-8 Seasonal total precipitation amount ratios for (a) winter (December 2015 – February 2016, (b) spring (March – May), (c) summer (June – August) and (d) autumn (September – November) As same as Fig. 2.2-5, but for seasonal total precipitation amount ratios.

Fig. 2.2-9 Extreme events and weather-related disasters observed in 2016 Schematic representation of major extreme climatic events and weather-related disasters occurring during the year.

18 2.3 Extratropical circulation calculated from thickness are shown in Fig. 2.3-1. In 2016, the warm conditions observed over wide Temperature anomalies reached the peak of the warm areas of the Northern Hemisphere extra-tropics are conditions with five-month running means near +1 K. presumed to have been associated with the El Niño Temperature anomalies decreased during the second event that continued until spring. This section outlines half of the year, but remained above normal. the seasonal mean characteristics of atmospheric In the zonal mean zonal wind of the Northern circulation observed in these areas. Hemisphere (Fig. 2.3-2, top), the westerly jet stream was generally stronger than normal until October and 2.3.1 Zonal mean temperature anomaly calculated shifted southward in the second half of November. from thickness and zonal wind in the troposphere The stream over Japan shifted northward in April, Tropospheric zonal mean temperature anomalies October and December (Fig. 2.3-2, bottom).

Fig. 2.3-1 Time-series representation of zonal mean temperature anomalies calculated from thickness in the troposphere (2006 to 2016) The top (bottom) panel shows the temperature anomalies in the global mean (the Northern Hemisphere; 90 oN – 30oN), respectively. The thin and thick lines show monthly and five-month running mean values, respectively (unit: K).

Fig. 2.3-2 Time-latitude cross section of five-day running mean 200-hPa zonal wind (December 2015 – December 2016) The top panel shows zonal mean zonal wind, and the bottom panel shows zonal wind averaged over 120 o – 150oE. The black lines and shading show zonal wind at intervals of (top) 10 and (bottom) 15 m/s, respectively. The green lines indicate the normal at intervals of (top) 20 and (bottom) 30 m/s, respectively.

19 2.3.2 Winter (December 2015 – February 2016) Aleutian Low were stronger than normal over the In the 500-hPa height field (Fig. 2.3-3), positive eastern part of their normal extents. Positive anomalies were seen over wide areas of the Northern anomalies were seen over eastern Eurasia, particularly Hemisphere, particularly in Western and Central in January (Fig. 2.3-8). In the lower troposphere, Siberia. The polar vortex was weaker than normal. temperatures were above normal over wide areas of Negative anomalies were seen from Eastern Siberia to the Northern Hemisphere, particularly in the polar the seas south of Alaska and to the west of the UK. region, Alaska and Western and Central Siberia, and Wave trains were dominant over northern Eurasia with below normal over the southeastern part of Eastern clear positive anomalies over Western and Central Siberia (Fig. 2.3-5). In the upper troposphere, the jet Siberia in January (Fig. 2.3-7). In the sea level stream meandered southward over and around China pressure field (Fig. 2.3-4), the Icelandic Low and the and northward to the east of Japan (Fig. 2.3-6).

Fig. 2.3-3 Three-month mean Fig. 2.3-4 Three-month mean sea Fig. 2.3-5 Three-month mean 500-hPa height and anomaly surface pressure and anomaly 850-hPa temperature and anomaly (December 2015 – February 2016) (December 2015 – February 2016) (December 2015 – February 2016) The contours show 500-hPa height at The contours show sea level pressure at The contours show 850-hPa intervals of 60 m. The shading indicates intervals of 4 hPa. The shading temperature at intervals of 4oC. The its anomalies. indicates its anomalies. shading indicates its anomalies. The dot patterns indicate areas with altitudes exceeding 1,600 m.

Fig. 2.3-6 Three-month mean Fig. 2.3-7 Monthly mean 500-hPa Fig. 2.3-8 Monthly mean sea level 200-hPa wind speed and vectors height and anomaly (January 2016) pressure and anomaly (January 2016) (December 2015 – February 2016) As per Fig. 2.3.3, but for monthly As per Fig. 2.3.4, but for monthly The black and brown lines show wind mean. mean. speed and its normal at intervals of 20 m/s and 40 m/s, respectively.

20 2.3.3 Spring (March – May 2016) Pacific High were stronger than normal over the In the 500-hPa height field (Fig. 2.3-9), positive eastern and western parts of their normal extents. In anomalies were seen over wide areas of the Northern the lower troposphere, temperatures were above Hemisphere, particularly over high-latitudes, the normal over wide areas of the Northern Hemisphere, northwestern part of North America, the eastern part particularly over the northwestern part of North of Northern Africa and Japan. Negative anomalies America, the eastern part of North Africa, Central were seen to the southwest of Alaska and in Asia and from Western Russia to Western Siberia (Fig. northeastern Canada. In the sea level pressure field 2.3-11). In the upper troposphere, the jet stream (Fig. 2.3-10), positive anomalies were seen over the shifted southward from its normal extent over and Beaufort Sea, and negative anomalies were seen over around China and northward from Japan to the sea wide areas of Eurasia. The Aleutian Low and the east of Japan (Fig. 2.3-12).

Fig. 2.3-9 Three-month mean 500-hPa Fig. 2.3-10 Three-month mean sea Fig. 2.3-11 Three-month mean height and anomaly (March – May level pressure and anomaly (March – 850-hPa temperature and anomaly 2016) May 2016) (March – May 2016) As per Fig. 2.3-3, but for March – May As per Fig. 2.3-4, but for March – May As per Fig. 2.3-5, but for March – May 2016. 2016. 2016 and with contour intervals of 3oC.

Fig. 2.3-12 Three-month mean 200-hPa wind speed and vectors (March – May 2016) The black and brown lines show wind speed and its normal at intervals of 10 m/s and 20 m/s, respectively.

21 2.3.4 Summer (June – August 2016) from northern Canada to Greenland. The westward In the 500-hPa height field (Fig. 2.3-13), positive extension of the Pacific High was weaker than normal. anomalies were seen over wide areas of the Northern In the lower troposphere, temperatures were above Hemisphere except in the Arctic region, particularly normal over wide areas of the Northern Hemisphere, from the Kamchatka Peninsula to the northeastern part particularly from Eastern Siberia to the Aleutian of the North Pacific, from eastern Canada to Islands, in the northern part of North America and Greenland and in Western Siberia. Clear positive from Western Russia to Western Siberia (Fig. 2.3-15). anomalies around the Kamchatka Peninsula and In the upper troposphere, the jet stream shifted negative anomalies to the southeast of Japan were northward from its normal position over eastern seen in August (Fig. 2.3-17). In the sea level pressure Eurasia in association with the eastward extension of field (Fig. 2.3-14), positive anomalies were seen over the Tibetan High (Fig. 2.3-16). Eurasia, the mid-latitudes of the North Pacific and

Fig. 2.3-13 Three-month mean Fig. 2.3-14 Three-month mean sea Fig. 2.3-15 Three-month mean 500-hPa height and anomaly (June – level pressure and anomaly (June – 850-hPa temperature and anomaly August 2016) August 2016) (June – August 2016) As per Fig. 2.3-3, but for June – August As per Fig. 2.3-4, but for June – As per Fig. 2.3-11, but for June – August 2016. August 2016. 2016.

Fig. 2.3-16 Three-month mean Fig. 2.3-17 Monthly mean 500-hPa 200-hPa wind speed and vectors height and anomaly (August 2016) (June – August 2016) As per Fig. 2.3-7, but for August 2016. As per Fig. 2.3-12, but for June – August 2016.

22 2.3.5 Autumn (September – November 2016) respectively. Over the North Pacific, positive and In the 500-hPa height field (Fig. 2.3-18), clear negative anomalies were seen to the south and north positive anomalies were seen over the eastern of the latitude bands of 40oN, respectively. In the hemisphere side of the polar region and the eastern lower troposphere, temperatures were above normal part of North America, and negative anomalies were over the polar region and central and eastern parts of seen over the mid-latitudes from Central Asia to the North America, and were below normal over the western North Pacific and to the west of North mid-latitudes from eastern Europe to the western America. Clear negative anomalies in the North Pacific (Fig. 2.3-20). In the upper troposphere, mid-latitudes were seen in October (Fig. 2.3-22). In the jet stream was stronger than normal over the the sea level pressure field (Fig. 2.3-19), positive and latitude bands of 40oN from Eurasia to the North negative anomalies were seen over the high latitudes Pacific (Fig. 2.3-21). from Europe to Central Siberia and China,

Fig. 2.3-18 Three-month mean Fig. 2.3-19 Three-month mean sea Fig. 2.3-20 Three-month mean 500-hPa height and anomaly level pressure and anomaly 850-hPa temperature and anomaly (September – November 2016) (September – November 2016) (September – November 2016) As per Fig. 2.3-3, but for September – As per Fig. 2.3-4, but for September – As per Fig. 2.3-5, but for September – November 2016. November 2016. November 2016.

Fig. 2.3-21 Three-month mean Fig. 2.3-22 Monthly mean 500-hPa 200-hPa wind speed and vectors height and anomaly (October 2016) (September – November 2016) As per Fig. 2.3-7, but for October 2016. The black and brown lines show wind speed and its normal at intervals of 15 m/s and 30 m/s, respectively.

23 2.4 Tropical circulation and convective activity U200-CP (for the central Pacific in the upper Tropical circulation was presumed to be troposphere) was generally negative, indicating influenced by the El Niño event that ended in spring easterly wind anomalies, and U200-IN (for the Indian 2016. This section outlines the seasonal mean tropical Ocean in the upper troposphere), U850-WP, CP and circulation and convective activity observed in 2016 EP (for the Pacific in the lower troposphere) were with focus on links to El Niño. generally positive, indicating westerly wind anomalies. The variability of these indices indicates 2.4.1 Tropical indices the impact of the El Niño event on tropical circulation Monthly indices related to tropical circulation are in the first half of 2016. shown in Table 2.4-1 and Fig. 2.4-1 (see Section 1.4.3 The active phase of equatorial intra-seasonal for related definitions). oscillation intermittently propagated eastward The SOI was negative (indicating throughout the year. Clear eastward propagation weaker-than-normal trade winds) until April and events occurred during the period from December remained positive after May except in October and 2015 to August 2016 (Fig. 2.4-2 (a)). Enhanced November. In the first half of 2016, OLR-PH (for the convective activity on a seasonal timescale was area around the Philippines) and OLR-MC (for the observed over the central and eastern Pacific until area around Indonesia) generally remained negative, April, and shifted toward the area from the Indian indicating suppressed convection, and OLR-DL (for Ocean to the Maritime Continent in May (Fig. 2.4-2 the area near the dateline) remained positive, (a)). In association with this convection, westerly indicating enhanced convection. In terms of equatorial wind anomalies also shifted from the central Pacific to zonal wind indices for the first half of the year, the eastern Indian Ocean (Fig. 2.4-2 (b)).

Table 2.4-1 Tropical atmospheric and oceanographic indices (December 2015 – December 2016)

Fig. 2.4-1 Time-series representation of tropical atmospheric and oceanographic indices from 2006 to 2016 Thin and thick lines indicate monthly and five-month running mean values, respectively.

Fig. 2.4-2 Longitude-time cross section of five-day running mean (a) 200-hPa velocity potential anomalies and (b) 850-hPa zonal wind anomalies (December 2015 – December 2016) The contour interval is (a) 4×106m2/s and (b) 2m/s. The blue (red) shading of (a) indicates areas of divergence that are stronger (weaker) than normal. That of (b) shows easterly (westerly) wind anomalies.

26 2.4.2 Winter (December 2015 – February 2016) Continent, respectively (Fig. 2.4-5). In the lower Convective activity was enhanced from the area troposphere, cyclonic circulation anomalies straddling west of the dateline to the eastern equatorial Pacific the equator were seen over western to central parts of and over the Indian Ocean, and was suppressed over the Pacific and anti-cyclonic circulation anomalies and around the Maritime Continent (Fig. 2.4-3). In the straddling the equator were seen over the Maritime upper troposphere, divergence anomalies were seen Continent and the Atlantic (Fig. 2.4-6). Eastward from the area west of the dateline to the eastern propagation of the MJO was seen from the Maritime Pacific and convergence anomalies were seen over Continent to the Indian Ocean during the period from Africa and the Maritime Continent (Fig. 2.4-4). mid-December to mid-January and from the eastern Anti-cyclonic and cyclonic circulation anomalies Indian Ocean to the eastern Pacific in February (Fig. straddling the equator were seen over central to 2.4-2). eastern parts of the Pacific and the Maritime

Fig. 2.4-3 Three-month mean OLR anomalies (December 2015 – February 2016) Original data provided by NOAA.

Fig. 2.4-4 Three-month mean 200-hPa velocity potential and anomalies (December 2015 – February 2016) The contours show the stream function at intervals of 2×106 m2/s, and the shading shows its anomalies. ‘D’ and ‘C’ denote divergence and convergence, respectively. Fig. 2.4-5 Three-month mean 200-hPa stream function and its anomalies (December 2015 – February 2016) The contours show the stream function at intervals of 10×106 m2/s, and the shading shows its anomalies. ‘H’ denotes the center of anti-cyclonic circulation. Fig. 2.4-6 Three-month mean 850-hPa stream function and its anomalies (December 2015 – February 2016) The contours show the stream function at intervals of 2.5×106 m2/s, and the shading shows its anomalies. ‘H’ and ‘L’ denote the center of anti-cyclonic and cyclonic circulation, respectively.

27 2.4.3 Spring (March – May 2016) anomalies straddling the equator were seen over the Convective activity was enhanced from the area central Pacific and the Maritime Continent, west of the dateline to the central Pacific, and was respectively (Fig. 2.4-9). In the lower troposphere, suppressed from the Maritime Continent to the cyclonic circulation anomalies were seen over the western Pacific (Fig. 2.4-7). In the upper troposphere, Indian Ocean and anti-cyclonic circulation anomalies divergence anomalies were seen over the Indian were seen from the Bay of Bengal to the western Ocean and from the dateline to the eastern Pacific, Pacific (Fig. 2.4-10). Eastward propagation of the and convergence anomalies were seen over the MJO was seen from the Indian Ocean to the Pacific in Maritime Continent and from the Atlantic to Africa March and from Africa to the Indian Ocean during the (Fig. 2.4-8). Anti-cyclonic and cyclonic circulation period from early to mid-May (Fig. 2.4-2).

Fig. 2.4-7 Three-month mean OLR anomalies (March – May 2016) As per Fig. 2.4-3, but for March – May 2016.

Fig. 2.4-8 Three-month mean 200-hPa velocity potential and anomalies (March – May 2016) As per Fig. 2.4-4, but for March – May 2016.

Fig. 2.4-9 Three-month mean 200-hPa stream function and anomalies (March – May 2016) As per Fig. 2.4-5, but for March – May 2016.

Fig. 2.4-10 Three-month mean 850-hPa stream function and anomalies (March – May 2016) As per Fig. 2.4-6, but for March – May 2016.

28 2.4.4 Summer (June – August 2016) latitude bands of 40°N, and the northeastward Convective activity was enhanced over the eastern extension of the Tibetan High was stronger than Indian Ocean and suppressed over the western Indian normal (Fig. 2.4-13). In the lower troposphere, Ocean and western to central parts of the equatorial cyclonic circulation anomalies straddling the equator Pacific (Fig. 2.4-11). In the upper troposphere, were seen over the Indian Ocean (Fig. 2.4-14). The divergence anomalies were seen from the eastern westward extension of the Pacific High was weaker Indian Ocean to the southern part of the Maritime than normal. Eastward propagation of the MJO was Continent and convergence anomalies were seen over seen from Africa to the Maritime Continent in June, the western Indian Ocean and the western Pacific (Fig. from the Pacific to the Indian Ocean in July and from 2.4-12). Anti-cyclonic circulation anomalies the Maritime Continent to the Pacific in August (Fig. straddling the equator were seen over the western 2.4-2). Pacific. Wave trains were seen over Eurasia in the

Fig. 2.4-11 Three-month mean OLR anomalies (June – August 2016) As per Fig. 2.4-3, but for June – August 2016.

Fig. 2.4-12 Three-month mean 200-hPa velocity potential and anomalies (June – August 2016) As per Fig. 2.4-4, but for June – August 2016.

Fig. 2.4-13 Three-month mean 200-hPa stream function and anomalies (June – August 2016) As per Fig. 2.4-5, but for June – August 2016.

Fig. 2.4-14 Three-month mean 850-hPa stream function and anomalies (June – August 2016) As per Fig. 2.4-6, but for June – August 2016.

29 2.4.5 Autumn (September – November 2016) straddling the equator were seen from the Indian Convective activity was enhanced over the Ocean to the Maritime Continent (Fig. 2.4-17). In the Maritime Continent and the latitude bands of 10°N – lower troposphere, cyclonic and anti-cyclonic 15°N in the Pacific, and was suppressed over western circulation anomalies straddling the equator were seen to central parts of the Indian Ocean and the equatorial from the eastern Indian Ocean to the Maritime Pacific (Fig. 2.4-15). In the upper troposphere, Continent and the Pacific, respectively (Fig. 2.4-18). divergence anomalies were seen over the Maritime Eastward propagation of the MJO was seen from the Continent and the Atlantic, and convergence eastern Indian Ocean to the Maritime Continent in anomalies were seen over western to central parts of September and from the Pacific to the Indian Ocean in the Indian Ocean and the equatorial Pacific (Fig. November (Fig. 2.4-2). 2.4-16). Anti-cyclonic circulation anomalies

Fig. 2.4-15 Three-month mean OLR anomalies (September – November 2016) As per Fig. 2.4-3, but for September – November 2016.

Fig. 2.4-16 Three-month mean 200-hPa velocity potential and anomalies (September – November 2016) As per Fig. 2.4-4, but for September – November 2016.

Fig. 2.4-17 Three-month mean 200-hPa stream function and anomalies (September – November 2016) As per Fig. 2.4-5, but for September – November 2016.

Fig. 2.4-18 Three-month mean 850-hPa stream function and anomalies (September – November 2016) As per Fig. 2.4-6, but for September – November 2016.

30 2.4.6 Tropical cyclones over the western North Table 2.4-2 Tropical cyclones forming over the western Pacific North Pacific in 2016 Based on information from the RSMC Tokyo-Typhoon In 2016, 26 tropical cyclones (TCs) with Center Maximum maximum wind speeds of 17.2 m/s or higher Number Date Name Category1) wind2) ID (UTC) formed over the western North Pacific (Table 2.4-2), (knots) which was near the normal of 25.6 (1981 – 2010 1601 Nepartak 7/3 – 7/9 TY 110 average). 1602 Lupit 7/23 – 7/24 TS 40 1603 Mirinae 7/26 – 7/28 STS 55 The first named TC of 2016 formed over the 1604 Nida 7/30 – 8/2 STS 60 western North Pacific on July 3, making it the 1605 Omais 8/4 – 8/9 STS 60 second-latest since 1951 after the July 9 record of 1606 Conson 8/9 – 8/15 TS 45 1607 Chanthu 8/13 – 8/17 STS 55 1998. The late start to the typhoon season is 1608 Dianmu 8/17 – 8/19 TS 40 attributed to the atmospheric circulation pattern 1609 Mindulle 8/19 – 8/23 TY 65 over the tropics of the northwestern Pacific Ocean, 1610 Lionrock 8/21 – 8/30 TY 90 1611 Kompasu 8/20 – 8/22 TS 35 which was unfavorable for TC formation as often 1612 Namtheun 9/1 – 9/4 TY 70 seen in the year after El Niño peaks. The number of 1613 Malou 9/6 – 9/7 TS 40 TC formations after July was higher than usual, 1614 Meranti 9/10 – 9/15 TY 120 1615 Rai 9/12 – 9/13 TS 35 making the eventual annual total normal. 1616 Malakas 9/12 – 9/20 TY 95 A total of 11 TCs came within 300 km of the 1617 Megi 9/23 – 9/28 TY 85 Japanese archipelago, which was near the normal of 1618 Chaba 9/29 – 10/5 TY 115 1619 Aere 10/5 – 10/10 STS 60 11.4 (1981 – 2010 average). Six made landfall on 1620 Songda 10/8 – 10/13 TY 100 Japan (against a normal of 2.7), which is the 1621 Sarika 10/13 – 10/19 TY 95 joint-second-highest number on record after the ten 1622 Haima 10/15 – 10/21 TY 115 1623 Meari 11/3 – 11/7 TY 75 recorded in 2004. The tracks of TCs generated in 1624 Ma-on 11/10 – 11/12 TS 35 2016 are shown in Fig. 2.4-19. 1625 Tokage 11/25 – 11/28 STS 50 1626 Nock-ten 12/21 – 12/27 TY 105 1) Intensity classification for tropical cyclones (range of maximum wind speed) TS: Tropical Storm (34 – 47 knots) STS: Severe Tropical Storm (48 – 63 knots) TY: Typhoon (64 knots – ) 2) Estimated maximum 10-minute mean wind speed

Fig. 2.4-19 Tracks of tropical cyclones in 2016 The lines indicate the tracks of tropical cyclones with maximum wind speeds of 17.2 m/s or higher. The numbers in circles indicate points where maximum wind speeds exceeded this value, and those in squares indicate points where they fell below it.

32 2.5 Oceanographic conditions In the North Pacific, remarkably positive SST Throughout 2016, the global average sea surface anomalies were observed near the western coast of temperature (SST) was much higher than normal, North America and from central to eastern parts of the especially until summer. This was partly attributable tropical region. Pacific Decadal Oscillation (PDO)1 to a long-term trend of SST increase caused by global index values were positive throughout the year (Fig. warming and to SST increase in tropical regions of the 2.5-4). In the South Pacific, positive SST anomalies Pacific and the Indian Ocean in association with the were observed near the western coast of South El Niño event that ended in spring 2016. The annual America throughout the year, and remarkably positive mean anomaly was +0.33°C, which was above the SST anomalies were observed east of Australia from previous record of +0.30°C observed in 2015 and was spring to summer and northeast of New Zealand in the highest since 1891. autumn. In the Indian Ocean, remarkably positive SST In the equatorial Pacific, remarkably positive SST anomalies were observed in most regions of the anomalies were observed in central and eastern parts tropical area until spring. Positive anomalies during winter 2015/2016. The positive SST anomalies weakened in the western part during summer. in the eastern part weakened during spring. From Remarkably positive SST anomalies were observed in summer onward, remarkably positive SST anomalies the eastern tropical region from summer onward. In were observed in the western part, and negative SST the North Atlantic, positive SST anomalies were anomalies were observed in central and eastern parts observed east of the USA throughout the year. (Fig. 2.5-1, Fig. 2.5-2 (left)). Remarkably negative SST anomalies were observed The SST deviation from the reference value (the south of Greenland from winter to spring and in climatological mean based on a sliding 30-year autumn (Fig. 2.5-1). period) averaged for the NINO.3 region decreased from +3.0°C in December 2015 to −0.6°C in July 2016, and remained between −0.6 and −0.3°C from August onward (Fig. 2.5-3 (top)). The five-month running mean of the deviation remained at +0.5°C or more from June 2014 to April 2016 and fell below +0.5°C in May. The El Niño event that began in summer 2014 ended in spring 2016. Southern Oscillation Index (SOI) values were negative until April and remained positive from May onward except in October (Fig. 2.5-3 (bottom)). Positive ocean heat content (OHC) anomalies in the central part of the equatorial Pacific propagated eastward during winter 2015/2016 before negative anomalies in the western part propagated eastward during spring. Negative OHC anomalies were observed in most parts in spring and persisted in 1 For details, see the Pacific Decadal Oscillation (PDO) central and eastern parts until autumn (Fig. 2.5-2 index information on the TCC website (http://ds.data.jma.go.jp/tcc/tcc/products/elnino/decadal/pd (right)). o.html).

33 (a) Winter (b) Spring

Fig. 2.5-1 Seasonal mean sea surface temperature anomalies (2016) (a) Winter (Dec. 2015 – Feb. 2016), (b) Spring (Mar. – May), (c) Summer (Jun. – Aug.), (d) Autumn (Sep. – Nov.). The contours and shading show sea surface temperature anomalies at intervals of 0.5°C. Maximum sea ice coverage areas are shaded in gray.

Fig. 2.5-2 Time-longitude cross sections of SST anomalies (left) and ocean heat content anomalies (right: vertically averaged temperature over the top 300 m) along the equator in the Pacific Ocean from 2014 to 2016 The contours and shading show SST anomalies (left) and ocean heat content anomalies (right) at intervals of 0.5°C.

El Niño monitoring index (°C)

Southern Oscillation Index

Fig. 2.5-3 Time-series of the El Niño monitoring index (top: NINO.3 SST deviation from a sliding 30-year mean) and the Southern Oscillation Index (bottom) from 2006 to 2016 The thin lines represent monthly mean values, and the thick lines represent five-month running mean values. The shading indicates El Niño (red) and La Niña (blue) events.

Fig. 2.5-4 Time-series of the PDO index from 1901 to 2016 The red line represents annual mean values for the PDO index, the blue line represents five-year running mean values, and the gray bars represent monthly values.

35 2.6 Stratospheric circulation in boreal winter 2.6-3 (c)), corresponding to the SSW event observed A stratospheric sudden warming (SSW) event is a from late January to mid-February. These phenomenon in which a rapid stratospheric characteristics were also seen in March (Fig. 2.6-3 temperature increase of several tens of Kelvin is (d)), corresponding to the major SSW event observed observed over a period of a few days in the polar from late February to early April. region during winter, and was identified by Richard Scherhag at the Free University of Berlin in 1952. It is caused by enhanced propagation of energy from the troposphere due to planetary-scale wave action (Matsuno 1971). According to the World Meteorological Organization (WMO) definition (WMO 1978), a minor SSW occurs when polar temperatures increase by 25 K or more within a week at any stratospheric level. In addition to this criterion, if the stratospheric zonal mean temperature increases in the poleward direction and net zonal mean zonal winds become easterly north of 60°N at 10-hPa or below, the event is classified as a major SSW. The stratospheric polar vortex was stronger than Fig. 2.6-1 Time-series representation of 30-hPa temperatures over the North Pole from 1 September normal in winter 2015/2016, but a minor SSW event 2015 to 31 August 2016 occurred between late January and mid-February. A The black line shows daily temperatures (unit: oC), and the gray line indicates the climatological mean. major SSW event also occurred between late February and early April (Fig. 2.6-1). This section outlines the characteristics of stratospheric circulation seen in winter 2015/2016, including the period of the two SSW events.

2.6.1 Characteristics of stratospheric circulation In the three-month mean 30-hPa height field from December 2015 to February 2016 (Fig. 2.6-2), annular patterns with negative anomalies in the high latitudes and positive anomalies in the mid-latitudes were observed, indicating a stronger-than-normal polar vortex. The eastward extension of the Aleutian High was stronger than normal. In the monthly mean 30-hPa height field, the polar Fig. 2.6-2 Three-month mean 30-hPa height and vortex was stronger than normal in December and anomaly (December 2015 – February 2016) January (Figs. 2.6-3 (a) and (b)). In February, the The contours show 30-hPa height at intervals of 120 m, and the shading indicates its anomalies. Aleutian High was stronger than normal and the center of the polar vortex shifted toward Eurasia (Fig.

36 (a) Dec. 2015 (b) Jan. 2016 (c) Feb. 2016

(d) Mar. 2016 (e) Apr. 2016

Fig. 2.6-3 Monthly mean 30-hPa height and anomaly for (a) December 2015, (b) January 2016, (c) February 2016, (d) March 2016 and (e) April 2016 The contours show 30-hPa height at intervals of 120 m, and the shading indicates its anomalies.

2.6.2 SSW from late January to mid-February waves over and around the latitude bands of 60°N in In the five-day mean 30-hPa field (Fig. 2.6-4), the the troposphere, contributing to deceleration of the stronger-than-normal polar vortex shifted toward the polar night jet stream in the stratosphere (Fig. area from the Atlantic to Eurasia during the period 2.6-5(a)). Clear planetary wave propagation was seen from the latter half of late January to the first half of from Western and Central Siberia in the troposphere early February in association with the enhancement of to the central and eastern Pacific in the stratosphere the Aleutian High (Fig. 2.6-4 (a) – (c)). Prior to a (Fig. 2.6-5 (b)) in association with the enhancement of prevalent SSW event, 30-hPa temperatures over the the Aleutian High (Fig. 2.6-4 (a) – (c)). In the 500-hPa North Pole rapidly increased in late January (Fig. height field during the same period, an enhanced ridge 2.6-1). was observed over Western and Central Siberia, A value of 100-hPa Eliassen-Palm (E-P) flux 1 indicating a related impact both on cold-air outbreaks (Edmon et al. 1980) in the first half of late January in East Asia and on stratospheric circulation (Fig. shows enhanced upward propagation of planetary 2.6-6). The polar vortex then exhibited enhancement over the polar region in the second half of 1 E-P flux provides a useful framework for diagnosing interaction between eddies and mean flow in the mid-February (Figs. 2.6-4 (d) – (f)), and temperatures Transformed Eulerian Mean (TEM) equation. Convergence over the North Pole were below normal (Fig. 2.6-1). (divergence) of E-P flux corresponds to deceleration (acceleration) of westerly winds in the zonal mean field.

(a) 21 – 25 Jan. (b) 26 – 30 Jan. (c) 31 Jan. – 4 Feb.

(d) 5 – 9 Feb. (e) 10 – 14 Feb. (f) 15 – 19 Feb.

Fig. 2.6-4 Five-day mean 30-hPa height and anomaly for (a) 21 – 25 January, (b) 26 – 30 January, (c) 31 January – 4 February, (d) 5 – 9 February, (e) 10 – 14 February, (f) 15 – 19 February 2016 The contours show 30-hPa height at intervals of 120 m, and the shading indicates its anomalies.

Fig. 2.6-5 (a) Latitude-height cross section of zonal mean zonal wind, E-P flux and zonal wind tendency in line with the divergence/convergence of the E-P flux and (b) longitude-height cross section of height anomalies from the zonal mean and wave activity flux averaged over 50oN – 70oN averaged from 21 to 25 January 2016. In (a), the contours show zonal mean zonal wind at intervals of 10 m/s, the shading indicates divergence/convergence of the E-P flux (yellow: acceleration; green: deceleration) and the vectors denote E-P flux (units: 106 m3/s2 (horizontal); m2/s2 (vertical)) scaled using the square of pressure. The units of vertical axis are ‘hPa’. In (b), the contours show height anomalies at intervals of 100 m and the vectors denote wave activity flux with reference to Plumb (1985) (units: m2/s2 (horizontal); Pa m/s2 (vertical)).

38 2.6.4 Summary The occurrence of the two SSW events during the period from winter 2015/2016 to early spring 2016 was presumed to be associated with an enhanced ridge over and around Western and Central Siberia in the troposphere. Monitoring of temporal evolution for the ridge over Siberia is important to determine its impacts on the enhancement of the Siberian High and the stratospheric circulation.

References Edmon, H. J., B. J. Hoskins and M. E. McIntyre, 1980: Eliassen-Palm cross sections for the troposphere. J. Atmos. Sci., 37, 2600-2616. Matsuno, T., 1971: A dynamical model of stratospheric Fig. 2.6-6 Five-day mean 500-hPa height and anomaly sudden warming. J. Atmos. Sci., 28, 1479-1494. for 21 – 25 January 2016 Plumb, R. A., 1985: On the three-dimensional propagation The contours show 500-hPa height at intervals of 60 m, and of stationary waves. J. Atmos. Sci., 42, 217-229. the shading indicates its anomalies. WMO, 1978: Abridged final report of Commission for Atmospheric Sciences. WMO Rep., 509, 113pp.

2.6.3 Major SSW from late February In the five-day mean 30-hPa field, the polar vortex that was stronger than normal in mid-February shifted toward Eurasia and the Aleutian High was enhanced from the northern part of North America to the polar region in early March (Fig. 2.6-7 (a) – (d)). 30-hPa temperatures over the North Pole rapidly increased in late February again (Fig. 2.6-1) and zonal mean zonal wind turned from westerly to easterly wind in the stratospheric high-latitudes (not shown), and the major SSW event occurred. The wave activity flux fields indicate that the enhanced upward propagation of the planetary waves from Western Siberia in the troposphere to the central to eastern Pacific in the stratosphere (Fig. 2.6-8), Fig. 2.6-9 Five-day mean 500-hPa height and anomaly corresponding to, the enhancement of the Aleutian for 20 – 24 February 2016 High (Fig. 2.6-7 (a) – (d)) as is the case with the SSW The contours show 500-hPa height at intervals of 60 m, and the shading indicates its anomalies. event from late January to mid-February. In the

500-hPa height field during the same period, an enhanced ridge was observed over Western Siberia, indicating its impact on the stratospheric circulation (Fig. 2.6-9).

39 (a) 20 – 24 Feb. (b) 25 Feb. – 1 Mar. (c) 2 – 6 Mar.

(d) 7 – 11 Mar. (e) 12 – 16 Mar. (f) 17 – 21 Mar.

Fig. 2.6-7 Five-day mean 30-hPa height and anomaly for (a) 20 – 24 February, (b) 25 February – 1 March, (c) 2 – 6 March, (d) 7 – 11 March, (e) 12 – 16 March, (f) 17 – 21 March 2016 The contours show 30-hPa height at intervals of 120 m, and the shading indicates its anomalies.

Fig. 2.6-8 (a) Latitude-height cross section and (b) longitude-height cross section averaged over 50oN – 70oN during the period from 20 to 24 February 2016 The elements are the same as Fig. 2.6-5.

40 2.7 Summary of the Asian summer monsoon August and from the northern Kyushu region of Asian summer monsoon monitoring is Japan to eastern China and in southern Indonesia in important because related fluctuations in September. convective activity and atmospheric circulation can A number of major weather-related disasters influence the summer climate in Asia, including were reported from June to September. Japan. This section summarizes the characteristics Heavy rain and flooding in northeastern parts of of the Asian summer monsoon in 2016. D.P.R Korea from late August to early September were brought by the remnants of Typhoon Lionrock, 2.7.1 Temperature and precipitation causing more than 130 fatalities, according to a Four-month mean temperatures based on report from the United Nations Office for the CLIMAT reports covering the monsoon season Coordination of Humanitarian Affairs (OCHA). (June – September) were more than 1°C above China suffered more than 600 fatalities from normal in many parts of East Asia, especially north June to August due to heavy rain over the Yangtze of 30°N. Extremely high monthly temperatures River Basin, over the Yellow River basin and in the were recorded in many areas from June to southern part of the country, and was also hit by September as follows (Fig. 2.7-1): Typhoon Nepartak, according to the Chinese June: Okinawa Islands (Japan) to southern government. Monthly precipitation in July amounted China to 352 mm (1981 – 2010 average: 130.1 mm) at July: northeastern China to central Mongolia, Changsha in Hunan Province and 364 mm (1981 – southern Borneo Island to southern Indonesia, in 2010 average: 174.1 mm) at Shenyang in Liaoning and around southern India Province. August: Kyushu region (Japan) to central China, Heavy rain and flooding also affected eastern Malaysia to central Indonesia, southern India Nepal in July, causing more than 120 fatalities, September: western Mongolia to Pakistan, according to OCHA. western Borneo Island to northern Sumatra Island In India, heavy rain and flooding caused more than 120 fatalities from southern to northern parts Four-month total precipitation amounts for the and elsewhere in July and August, and more than 30 same period were more than 140% of the normal in fatalities in central parts and elsewhere, according to Japan’s Hokkaido region, eastern China, southern the government of India. Monthly precipitation for Mongolia, northern Lao PDR to northern Myanmar, September was 440 mm (1981 – 2010 average: in and around Pakistan, and in and around central 123.0 mm) at Hyderabad in central India. Indonesia. The corresponding numbers were less In Pakistan, heavy rain caused more than 140 than 60% of the normal on the Korean Peninsula fatalities in the northern part from June to August, and in northeastern and central China, southern according to the government of Pakistan. India and southwestern Pakistan (Fig. 2.7-2). These amounts were mostly consistent with the distribution of outgoing longwave radiation (OLR) anomalies (Fig. 2.7-3). Extremely high precipitation based on monthly data was seen in the Hokkaido region of Japan in

Fig. 2.7-1 Four-month mean temperature anomaly (˚C) Fig. 2.7-2 Four-month total precipitation ratio (%) for for June – September 2016 June – September 2016 See Section 1.3.2 for the data source. See Section 1.3.2 for the data source.

2.7.2 Convective activity and atmospheric and the first half of late August). circulation Convective activity over the Maritime Continent Convective activity (inferred from OLR) averaged was enhanced throughout the summer monsoon for June – September 2016 was enhanced from the season. It was suppressed to the east of the eastern Indian Ocean to the Maritime Continent, over Philippines until July and enhanced after August (Fig. the area from the Bay of Bengal to the southwestern 2.7-6). In the lower troposphere, cyclonic circulation Indochina Peninsula and from southern China to the associated with a deep monsoon trough was clearly seas northeast of the Philippines, and was suppressed seen over the seas to the southeast of Japan in August over the western part of the equatorial Pacific (Fig. in response to enhanced convective activity over the 2.7-3). OLR index data (Table 2.7-1) indicate that the western North Pacific (figures not shown). overall activity of the Asian summer monsoon (represented by the SAMOI (A) index) was near Reference Webster, P. J. and S. Yang, 1992: Monsoon and ENSO: normal until August and above normal in September. Selectively interactive systems. Quart. J. Roy. Meteor. The most active convection area was shifted westward Soc., 118, 877 – 926. of its normal position until July (see the SAMOI (W) index). In the upper troposphere, the Tibetan High was stronger than normal over its northeastern part (Fig. 2.7-4 (a)). In the lower troposphere, monsoon circulation over the Indian Ocean was stronger than normal and cyclonic circulation anomalies straddling the equator were seen over the area from the Indian Ocean to the Maritime Continent (Fig. 2.7-4 (b)). Zonal wind shear between the upper and lower troposphere over the North Indian Ocean and southern Asia (Fig. 2.7-5) remained above normal, indicating stronger-than-normal monsoon circulation from mid-May onward (except in the second half of July

42 (a)

(b) Fig. 2.7-3 Four-month mean outgoing longwave radiation (OLR) and its anomaly for June – September 2016 The contours indicate OLR at intervals of 10 W/m2, and the colored shading denotes OLR anomalies from the normal. Negative (cold color) and positive (warm color) OLR anomalies show enhanced and suppressed convection compared to the normal, respectively. Original data are provided by NOAA.

Table 2.7-1 Summer Asian Monsoon OLR Index (SAMOI) values observed from May to October 2016

SAMOI is described in 1.4.3. Summer Asian Monsoon OLR Index (SAMOI) Fig. 2.7-4 Four-month mean stream function and its Year SAMOI (A) SAMOI (N) SAMOI (W) anomaly for June – September 2016 2016 Activity Northward- Westward- (a) The contours indicate the 200-hPa stream function at 6 2 shift shift intervals of 10 × 10 m /s, and the colored shading indicates May 0.4 -0.8 1.2 200-hPa stream function anomalies from the normal. (b) The contours indicate the 850-hPa stream function at Jun. 0.3 -0.5 1.0 intervals of 4 × 106 m2/s, and the colored shading indicates Jul. -0.4 0.1 1.2 850-hPa stream function anomalies from the normal. Warm (cold) shading denotes anticyclonic (cyclonic) circulation Aug. 0.5 0.3 -0.9 anomalies in the Northern Hemisphere and vice versa in the Sep. 1.6 0.8 0.0 Southern Hemisphere.

Oct. 1.1 -0.9 -0.5

Fig. 2.7-5 Time-series representation of the zonal wind shear index between 200 hPa and 850 hPa averaged over the North Indian Ocean and southern Asia (pink rectangle in the right figure: equator – 20ºN, 40ºE – 110ºE) The zonal wind shear index is calculated after Webster and Yang (1992). The thick and thin pink lines indicate seven -day running mean and daily mean values, respectively. The black line denotes the normal, and the gray shading shows the range of the standard deviation calculated for the time period of the normal.

(a) June 2016 (b) July 2016

Fig. 2.7-6 Monthly mean anomalies of outgoing longwave radiation (shading at intervals of 10 W/m2) and 850-hPa stream function (contour at intervals of 2×106m2/s) for (a) June, (b) July, (c) August and (d) September 2016

44 2.8 Arctic sea ice conditions The sea ice extent in the Arctic Ocean has recently shown a decreasing tendency that has been particularly marked in terms of the annual minimum extent (Fig. 2.8-1). The monitoring of Arctic sea ice conditions has become more significant because of their possible influence on the climate as a result of related changes in the radiation budget and heat Fig. 2.8-1 Time-series representation of annual minimum (red line) Arctic sea ice extents from 1979 to exchange between the Arctic Ocean and the 2016 atmosphere. This section outlines the characteristics The dashed line denotes the trend. The trend of the annual minimum for the period from 1979 to 2016 is 9.2×104 of the Arctic sea ice extent seen in 2016 along with km2/year. those of atmospheric circulation.

2.8.1 Presence of sea ice in the Arctic in 2016 The Arctic sea ice extent 1 in 2016 reached its annual maximum on 23 March at 14.74 million square kilometers and its annual minimum on 5 September at 4.09 million square kilometers (Fig. 2.8-2). Both the maximum and minimum sea ice extent was the second smallest since 1979 (Figs. 2.8-1 – 2.8-3). Fig. 2.8-2 Time-series representation of sea ice extents for the Arctic region for 2016 The black line indicates the normal, and the gray shading 2.8.2 Arctic atmospheric circulation and melting of denotes the range of the standard deviation calculated for sea ice the period of the normal. In September 2016, the center of a low-pressure system shifted toward North America and the northward extension of a high-pressure system over Eurasia was stronger than normal in contrast to circulation in August (middle panel, Fig. 2.8-4). In the lower troposphere, above-normal temperatures over a wide area of the high latitudes (Fig. 2.8-5) supported a reduction of sea ice extents for a lower-than-normal level.

Fig. 2.8-3 Sea ice concentration on 5 September 2016 (left) and sea ice extent climatology on 5 September (right) The blue scale in the panel on the left shows deciles of sea ice concentration, and the white areas in the panel on the 1 The sea ice extent is defined as the area in which ice right show sea ice extent climatology. concentration (i.e., the ratio of ice cover in a particular reference area) is 15 – 100%.

Fig. 2.8-4 Monthly mean sea level pressure and its anomalies over the Arctic region in July (left), August (middle) and September (right) 2016 The contours show sea level pressure at intervals of 4 hPa, and the shading indicates its anomalies. ‘H’ and ‘L’ denote the center of a high- and low-pressure system, respectively.

Fig. 2.8-5 Monthly mean 925-hPa temperature and its anomalies over the Arctic region in July (left), August (middle) and September (right) 2016 The contours show 925-hPa temperature at intervals of 3oC, and the shading indicates its anomalies.

46 2.9 Snow cover in the Northern Hemisphere 2.9.1 Related characteristics in 2016 Snow cover has a close and mutual association with In winter (December – February) 2015/2016, there climatic conditions. The albedo of snow-covered ground were fewer days of snow cover than normal in many (i.e., the ratio of solar radiation reflected by the surface) parts of the Northern Hemisphere (Fig. 2.9-1 (a)), and is higher than that of snow-free ground. As a result, the this situation continued until April. In May 2016, there variability of snow cover has an impact on the earth’s were more days of snow cover than normal in and around surface energy budget and radiation balance. In addition, the southern part of Central Siberia (Fig. 2.9-1 (b)). In snow absorbs heat from its surroundings and melts, November 2016, there were more days of snow cover thereby providing soil moisture. The variability of than normal in and around Central Asia and northeastern atmospheric circulation and oceanographic conditions China and fewer than normal in western China and North affects the amount of snow cover. This section outlines America (Fig. 2.9-1 (c)). the characteristics of snow cover in 2016 as well as its long-term variability and related trends.

(a) February 2016 (b) May 2016 (c) November 2016

Fig. 2.9-1 Number of snow-cover days (top) and its anomaly (bottom) for (a) February 2016, (b) May 2016 and (c) November 2016 Statistics on the number of snow-cover days are derived using data from the Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS) on board US Defense Meteorological Satellite Program (DMSP) satellites based on an algorithm developed by the Japan Meteorological Agency. The base period for the normal is 1989 – 2010.

47 2.9.2 Interannual variability and related trends January to April. Fig. 2.9-2 shows interannual variations in the total In Eurasia there is a decreasing trend for April, May, area of monthly snow cover in the Northern Hemisphere June and the period from September to December, while and Eurasia over the 29-year period from 1988 to 2016. no trend is seen for January, February and March. The Northern Hemisphere exhibits a decreasing trend (with a 95% confidence level) for May, June and the period from September to December, while no trend (with a 95% confidence level) is seen for the period from

Fig. 2.9-2 Interannual variations in the total area of monthly snow cover (106 km2) in the Northern Hemisphere (north of 30˚N; left) and Eurasia (30˚N – 80˚N, 0 – 180˚E; right) for February ((a) and (d)), May ((b) and (e)), and November ((c) and (f)) from 1988 to 2016 The blue lines indicate total snow cover area for each year and the black lines show linear trends (95% confidence level).

48 3. Analysis of specific events 1997/98 El Niño event as seen in NINO.3 SST 3.1 The El Niño event1 ending in boreal spring variations. 2016 and its effects Lower-than-normal temperatures were observed in The characteristics of the El Niño event that western Japan throughout the boreal summers of 2014 occurred from boreal summer (June – August) 2014 to and 2015, and higher-than-normal temperatures were spring (March – May) 2016 are described in Section observed in eastern Japan during boreal winter 3.1.1, and various related effects observed from boreal 2015/2016. These characteristics were consistent with winter (December – February) 2015/2016 to autumn common patterns observed in past El Niño events. The (September – November) 2016 are outlined in Section global average surface temperature anomaly in 1998 3.1.2. was the highest since records began in 1891, and this record was again broken in each year of the 3.1.1 2014/15/16 El Niño event2 2014/15/16 El Niño event. The formation of 2016’s (1) Overview first typhoon was also later than normal as similarly The El Niño event starting in summer (June – observed in the El Niño termination years of 1973, August) 2014 and ending in spring (March – May) 1983 and 1998, when record-high NINO.3 SSTs were 2016 covered eight seasons, making it the longest recorded. since 1949 3 . The monthly mean sea surface These climatic characteristics also relate to the temperature (SST) deviation from the climatological descending (ascending) nature of SST anomalies in reference 4 over the El Niño monitoring region NINO.WEST (IOBW) regions in concurrence with (NINO.3 in Fig. 3.1-1) was +3.0°C in the mature stage (subsequent to) the rise in NINO.3 SST anomalies. of November – December 2015, which was the The lifetime of the 2014/15/16 El Niño event in the third-highest on record after the +3.6°C of the course of life is described below. 1987/98 event and the +3.3°C of the 1982/83 event. The amplitudes of SST variations in the (2) SST deviation from climatological reference in monitoring regions of the tropical Indian Ocean individual monitoring regions (IOBW5) and the tropical western Pacific Ocean (Fig. Fig. 3.1-2 shows a time-series representation of 3.1-1), which are important climate effect indicators NINO.3 SST deviation from its climatological for El Niño events, were also as large as those of the reference in past El Niño events. The termination year for each event is set as Year0, and NINO.3 SST 1 JMA judges that an El Niño has begun when the five-month running mean sea surface temperature (SST) deviations are shown from January of Year−2 (two deviation for NINO.3 remains at +0.5°C or more for six months. El Niño periods are expressed in seasonal units. years before Year0) to January of Year+1 (the year 2 Previous El Niño events are identified by their relevant after Year0). The black solid line indicates values for periods (the full four-number expression for the first year and the final two numbers for subsequent years). By way of the 2014/15/16 El Niño event, and the dotted black example, the 1997/98 El Niño event ran from boreal spring 1997 to spring 1998. line indicates the average of the 13 previous events. 3 The second-longest El Niño events after that of These deviations are referred to as NINO.3dev below. 2014/15/16 (eight seasons) were those of 1968/69/70, 1986/87/88, 1982/83 and 1991/92 (six seasons each). In the average of the 13 previous events, 4 SST climatological references are monthly averages of the latest sliding 30- year period for NINO.3, and are NINO.3dev is +0.5°C or above for boreal spring in defined as linear extrapolations with respect to the latest Year−1, which results in the onset of an El Niño event 30-year period for NINO.WEST and IOBW in order to remove the effects of significant long-term warming trends that reaches its mature stage around November – observed in these regions. December of Year−1. The value falls below +0.5°C 5 Indian Ocean Basin-Wide

49 around spring of Year0, resulting in the termination of negative NINO.WESTdev values continued from the event. February 2015 (Year−1), in contrast to the average The 2014/15/16 El Niño event began in 2014 value for the same season. Three negative peaks (Year−2), which was the year before its mature stage. distinctly below the average were observed in March, NINO.3dev varied between +0.2 and +1.0°C, and did in July – October 2015 and in February 2016 (Year0). not show the signs of development commonly seen in Despite the prolonged nature of these below-average past El Niño events. Meanwhile, five-month running values, the negatives eased in boreal spring 2016 averages of NINO.3dev remained at or above +0.5°C (Year0) along with the average and turned positive in from June 2014 onward and between +0.5 and +0.6°C summer 2016 after the end of the El Niño event. for eight of the ten months through to March 2015, Fig. 3.1-4 is the same as Fig. 3.1-2, but for the thereby meeting the criteria for the definition of an El IOBW region. IOBW SST deviations from the Niño event from boreal summer 2014 onward. climatological reference are referred to as IOBWdev After spring 2015 (Year−1), NINO.3dev increased below. at double the rate for the average of the previous 13 In the average of the previous 13 events, events, reaching its positive maximum of +3.0°C (the IOBWdev tended to increase in association with third-highest of the past events) in December 2015. elevated NINO.3dev values around spring of Year−1 The peak values of the four strongest El Niño events when the averaged El Niño event began. Values occurring in 1972/73, 1982/83, 1997/98 and reached their positive peak around January – April of 2014/15/16 considerably exceeded the peak of the Year0 a few months after the mature stage of the El average value of +1.7°C. These stand out from the Niño event (coinciding with the NINO.3dev peak) corresponding values for the 10 other events, which around December of Year−1. In the Pacific Ocean, were equal to or below the average. positive NINO.3dev values eased in boreal spring of NINO.3dev decreased rapidly from January 2016 Year0 resulting in the termination of El the Niño event, (Year0) onward and approached the average of +0.1°C while positive IOBWdev values persisted in the in May, bringing about the end of the El Niño event. Indian Ocean until boreal summer. This is an The value subsequently remained near the average important factor in considering the climate over the (between −0.3 and −0.6°C) from July to November. western North Pacific during boreal summer (Xie et Fig. 3.1-3 is the same as Fig. 3.1-2 except for the al., 2009; Du et al., 2011). NINO.WEST region. NINO.WEST SST deviations from the climatological reference are referred to as NINO.WESTdev below. NINO.WESTdev for the average of the 13 previous events (shown by the dotted black line) turned negative around the summer of Year−1 immediately after the start of the averaged El Niño Fig. 3.1-1 Locations of El Niño monitoring region, western tropical Pacific region, and tropical Pacific event, and exhibited two negative peaks around region September of Year−1 and February of Year0. The NINO.3 indicates El Niño monitoring region (5°S – 5°N, 150°W – 90°W), NINO.WEST indicates the western negative values eased around boreal spring of Year0 tropical Pacific region (equator – 15°N, 130°E – 150°E), as the event ended, and turned positive in the summer and IOBW indicates the tropical Indian ocean (20°S – 20°N, of Year0. During the El Niño event, distinctly 40°E – 100°E).

Fig. 3.1-2 NINO.3 SST deviations from climatological Fig. 3.1-4 Same as Fig. 3.1-2, but for IOBW SST references for past El Niño events deviations Time-series representation of NINO.3 SST deviations from climatological references for January in past El Niño events. The termination year for each event is set to Year0, During the 2014/15/16 El Niño event, IOBWdev and NINO.3 SST deviations are plotted from January of remained near zero after the onset of the event from Year−2 (i.e., two years before Year0) to January of Year+1 boreal summer 2014 (Year−2) to around February (i.e., the year after Year0). The solid black line represents the 2014/15/16 El Niño event, and the dotted black line 2015 (Year−1) before turning positive in spring 2015 represents the average of 13 previous events. The Year0 for (Year−1) in association with the rapid development of each El Niño event is listed to the upper left of the figure. the event, and continued to rise before and after the

event’s mature stage (corresponding to the peak of NINO.3dev). Three months after the peak of NINO.3dev, IOBWdev peaked at +0.72°C in March 2016 (Year0). This IOBWdev was the second highest on record after the +0.74°C value of January 1998 (Year0), and was twice as high as the average. Values rapidly decreased thereafter, and the positive values mostly eased in June 2016 (Year0) a month after the disappearance of positive NINO.3dev values. As mentioned above, the considerably above-average positive IOBWdev values observed during the 2014/15/16 El Niño event continued, but disappeared

earlier than average. During boreal summer 2016 Fig. 3.1-3 Same as Fig. 3.1-2 except for NINO.WEST (Year0), values were near zero and turned negative in SST deviations autumn.

51 (3) Atmospheric and oceanic temporal changes (a) Boreal spring 2014 – spring 2015 To clarify the characteristics of air-sea interaction Strong lower-troposphere westerly wind bursts in the onset, development and termination of the over the western equatorial Pacific in mid-to-late 2014/15/16 El Niño event, time-longitude sections for January 2014 preceded the onset of the 2014/15/16 El areas along the equator (0.5°S – 0.5°N) over the Niño event. These bursts are illustrated in Fig. 3.1-6 Indian and Pacific Oceans for SST anomalies and for (right) as strong westerly anomalies7 of 9 m/s or more. depth averaged temperature anomalies from the ocean Westerly bursts were again observed in late February surface to 300 m are shown in Fig. 3.1-5, and and early March. Warm Kelvin waves below the ocean time-longitude sections for areas near the equator (5°S surface resulting from these bursts migrated eastward – 5°N) for velocity potential anomalies in the upper through the central equatorial Pacific from March to troposphere (200 hPa) and for zonal wind anomalies April 2014 to the eastern part (Fig. 3.1-5, right). in the lower troposphere (850 hPa) are shown in Fig. Eastward migration of weak warm Kelvin waves 3.1-6. Fig. 3.1-7 also shows three-month (seasonal) was subsequently observed, and increased subsurface average latitude-longitude sections covering 14 water temperature anomalies in the uppermost 300 m seasons from boreal spring 2013 to summer 2016 for were seen in the central and eastern equatorial Pacific outgoing long radiation (OLR) and related anomalies from April to July 2014 (Fig. 3.1-5, right; spring and SSTs with related anomalies, along with (MAM) 2014, Fig. 3.1-7, right). In accordance with longitude-depth sections at the equator for the this increase, SST anomalies in the eastern equatorial uppermost 300-m subsurface temperatures and related Pacific increased from May to July 2014 (Fig. 3.1-5, anomalies. left; summer (JJA) 2014, Fig. 3.1-7, center), and Most typical El Niño events, such as that positive anomalies of +1.5°C emerged in the eastern described in Rasmusson and Carpenter (1982), emerge part in June 2014, resulting in the onset of the in boreal spring or summer and develop during 2014/15/16 El Niño event. summer and autumn, passing through the mature stage The area of above-normal convective activity from late autumn to early winter and terminating in observed near Indonesia (100 – 140°E) until boreal winter or spring the year after onset6. Although the winter 2013/2014 moved to the western equatorial 2014/15/16 El Niño event continued for eight seasons Pacific in boreal spring 2014, resulting in from boreal summer 2014 to spring 2016, it did not below-normal convective activity over Indonesia and start early or end late and was almost twice as long as above-normal convective activity over the western typical El Niño events. Consequently, the and central equatorial Pacific. However, the phenomenon is viewed as having been separated into subsequent east-west contrast of convective activity units of around a year from spring to spring, representing a cycle of development and decay. Its 7 A westerly burst is an event in which westerly winds with speeds exceeding 5 m/s or so are observed for around 10 characteristics are described below for (a) spring 2014 days in the lower troposphere over the western equatorial – spring 2015, (b) spring 2015 – spring 2016, and (c) Pacific when easterly trade winds blow under normal conditions. Although several definitions of the term have spring 2016 onward. been utilized in previous research, here it refers to westerly wind anomalies of 9 m/s or more. Easterly wind speeds in the lower troposphere (trade winds) average around 4 – 6 6 Five exceptional periods of past El Niño events were m/s near the date line over the equatorial Pacific, with boreal spring 1953 – autumn 1953, autumn 1968 – winter strength on the eastern side and weakness on the western 1969/1970, autumn 1986 – winter 1987/1988, spring 1982 – side of the date line. For strong westerly wind anomalies of summer 1983 and spring 1991 – summer 1992, whose 9 m/s or more, westerly winds blow in the central equatorial start/end points were unusual. Pacific, resulting in the disappearance of trade winds.

52 between Indonesia and the central equatorial Pacific was not clearly seen, but above-normal convective was unclear, and above-normal values in the western activity was occasionally observed to the west of the equatorial part did not persist (winter (DJF) 2014 – date line, and westerly wind anomalies were seen over summer (JJA) 2014, Fig. 3.1-7, left; Fig. 3.1-6, right). the western equatorial Pacific in July and September In June – July 2014, easterly wind anomalies were 2014 (Fig. 3.1-6). These effects stimulated two weak observed in the central and eastern Pacific, and in July warm Kelvin waves that reached the eastern – August eastward migration of equatorial cold Kelvin equatorial Pacific in October and December 2014, and waves was observed in the ocean subsurface along positive SST anomalies persisted in the eastern and with negative SSTs (Fig. 3.1-5). Displacement of central Pacific (Fig. 3.1-5; Autumn (SON) 2014, Fig. above-normal convection area to the central equatorial 3.1-7, center) Pacific as commonly observed in past El Niño events

Fig. 3.1-5 Time-longitude sections for SST anomalies (left), and subsurface temperature anomalies averaged from ocean surface to the depth of 300 m (right) along the equator (0.5°S – 0.5°N) The data are from November 2013 to October 2016.

Fig. 3.1-6 Time-longitude sections of velocity potential anomalies in the upper troposphere (200 hPa) (left) and zonal wind anomalies in the lower troposphere (850 hPa) (right) along equatorial regions (5°N – 5°S) Negative velocity potential anomalies (left) indicate stronger-than-normal divergence (i.e., above-normal convective activity), and positive values indicate weaker-than-normal divergence (i.e., below-normal convective activity). Positive zonal wind anomalies (right) represent westerly anomalies, and negative values indicate easterly anomalies. The data cover the period from November 2013 to October 2016.

In November and December 2014, above-normal easterly wind anomalies were seen in the western convective activity was observed near Indonesia, and equatorial Pacific (Fig. 3.1-6; winter (DJF) 2015, Fig.

54 3.1-7, left). Cold Kelvin waves stimulated by easterly Niño event, the relative maximum was to the west of wind anomalies reached the eastern equatorial Pacific the date line until early boreal spring 2015, and slowly in January – March 2015, and the SST anomalies there migrated eastward during boreal spring and summer turned negative (Fig. 3.1-5; winter (DJF) 2015, Fig. 2015 in accordance with the development of the event, 3.1-7, center). joining positive anomalies expanding westward from Thus, from boreal spring 2014 to spring 2015, the the eastern Pacific in boreal summer and autumn (Fig. El Niño event continued with no clear air-sea 3.1-5, left). interaction (i.e., no sign of development), and neither This eastward migration of the relative maximum developed nor decayed. During this period, SSTs were SST anomaly near the date line indicates displacement considerably higher than in average years over the of water at temperatures of 28°C or more (referred to entire tropical region in the North Pacific and over the as warm pools) extending from the ocean surface to a entire tropical Indian Ocean, which contributed to the depth of 100 m in the western equatorial Pacific (Fig. record-high global average SST recorded in 2014. At 3.1-7, right). In the course of eastward warm-pool the same time, SSTs remained below normal over the expansion from boreal winter 2014/2015 to autumn central and eastern tropical Pacific in the Southern 2015, ocean subsurface water temperatures of 30°C or Hemisphere in contrast to the above-normal SSTs above and relative maximum water temperature commonly observed in the same area during the anomalies migrated eastward. SST variations development process in past El Niño events. corresponded to those of the ocean subsurface (Fig. 3.1-7, center). (b) Boreal spring 2015 – spring 2016 Ocean subsurface variations closely corresponded From boreal spring 2015 onward, the El Niño to those of atmospheric circulation. In May, June – event developed with continued above-normal July, August and October 2015, four westerly bursts convective activity over the western equatorial Pacific occurred in areas shifting from west to east of the date along with westerly wind anomalies from around line with warm-pool eastward migration (Fig. 3.1-6, January 2015 and the onset of westerly wind burst right). In boreal spring 2015, above-normal activity in late March (Fig. 3.1-6). Ocean subsurface convective activity areas were centered west of the warm Kelvin waves excited by this activity reached date line and expanded to the central and eastern the eastern equatorial Pacific in April – May, and equatorial Pacific. The center of this activity ocean subsurface temperature anomalies subsequently gradually moved eastward and reached the central turned positive in the central – eastern equatorial equatorial Pacific east of the date line during the Pacific (Fig. 3.1-5, right; spring (MAM) 2015, Fig. mature stage of the El Niño event. Convective activity 3.1-7, right). SST anomalies then rose near the near Indonesia turned below normal with the western coast of South America in the eastern displacement of the above-normal area. The clear equatorial Pacific, and in this area positive anomalies contrast of convective activity with the above-normal expanded gradually westward in boreal summer – levels near the date line persisted until boreal spring autumn 2015 (Fig. 3.1-5, left; spring (MAM) 2015 – 2016 when the El Niño event ended (Fig. 3.1-6, left; Autumn (SON) 2015, Fig. 3.1-7, center). spring (MAM) 2015 – spring (MAM) 2016, Fig. 3.1-7, Meanwhile, the relative maximum positive SST left). anomaly was observed near the date line in the The positive SST anomalies in the central and equatorial Pacific. Before the development of the El eastern equatorial Pacific peaked in November –

55 December 2015 before gradually easing from the The area of above-normal convective activity eastern part (Fig. 3.1-5, left). In January 2016, another periodically varied in association with intra-seasonal westerly wind burst was observed over the central oscillations from May to July 2016, and the equatorial Pacific, and ocean subsurface warm Kelvin positive/negative status of zonal wind anomalies in waves stimulated by this burst arrived at the eastern the lower troposphere changed periodically over the equatorial Pacific in January – February 2016. No equatorial Pacific. Meanwhile, westerly wind remarkable warm Kelvin waves were subsequently anomalies in the lower troposphere persisted over the observed. Ocean subsurface cold waters in the Indian Ocean (Fig. 3.1-6). From around August 2016, western equatorial Pacific migrated eastward in easterly wind anomalies were continually observed in March and April, and ocean subsurface water the lower troposphere over the equatorial Pacific. The temperature anomalies in the uppermost 300 m turned seasonally averaged OLR showed common negative over most of equatorial Pacific from the characteristics of past El Niño events in boreal spring western part to the eastern part in April (Fig. 3.1-5, 2016, with convective activity being below normal right; spring (MAM) 2016, Fig. 3.1-7, right). As a near Indonesia and above normal near the date line result, the thermocline8 was shallower than normal over the equatorial Pacific. However, in boreal over most of the equatorial Pacific, and negative SST summer 2016, the area of above-normal convective anomalies expanded westward from the eastern activity near the date line disappeared, and convective equatorial Pacific where the thermocline was at its activity fell below normal over most of the equatorial shallowest. In boreal spring 2016 , the El Niño event Pacific from western to eastern parts. Meanwhile, ended with the easing of positive SST anomalies over convective activity was above normal over the eastern the central and eastern equatorial Pacific (Fig. 3.1-5, Indian Ocean from boreal spring 2016, and the area of left; spring (MAM) 2016, Fig. 3.1-7, center). above-normal activity extended over the eastern Indian Ocean and Indonesia (summer (JJA), Fig. 3.1-7, (c) Boreal summer 2016 left). In boreal summer 2016, the relative minimum negative ocean subsurface temperature anomaly The 2014/15/16 El Niño event is described above moved to the central equatorial Pacific (Fig. 3.1-5, in the context of year units running from spring to right; summer (JJA) 2016, Fig. 3.1-7, right), and SSTs spring, representing the period from before the onset turned below normal from the central to eastern until after the end of the event. The atmospheric and equatorial Pacific (Fig. 3.1-5, left; summer (JJA) 2016, oceanic processes observed in the period from boreal Fig. 3.1-7, center). Meanwhile, ocean subsurface spring 2015 to spring 2016 (described in (b)) temperature anomalies turned positive and SSTs rose correspond to the stages of a typical El Niño event above normal over most of the western tropical from development to decay as described in Pacific, where SST areas of 30°C or more prevailed. Rasmusson and Carpenter (1982), and are in contrast SSTs turned remarkably above normal from the to the period from spring 2014 – spring 2015 eastern Indian Ocean near Indonesia to the (described in (a)). northeastern coast of Australia.

8 The ocean subsurface layer with its steep vertical temperature gradient indicated in 15 – 25°C temperature layers with tight contours (Figure 3.1-7, right).

56 References Du, Y., L. Yang. and S.-P. Xie, 2011: Tropical Indian Ocean Influence on Northwest Pacific Tropical Cyclones in Summer following Strong El Niño. J. Climate, 24, 315-322. Rasmusson, E. M. and T. H. Carpenter, 1982: Variations in Tropical Sear Surface Temperature and Surface Wind Fields Associated with the Southern Oscillation/El Niño. Mon. Wea. Rev., 110, 354-384. Xie, S.-P., K. Hu, J. Hafner, H. Tokinaga, Y. Du, G. Huang, and T. Sampe, 2009: Indian Ocean Capacitor Effect on Indo-Western Pacific Climate during the Summer following El Niño. J. Climate, 22, 730–747.

Fig. 3.1-7 Seasonally averaged latitude-longitude sections for outgoing longwave radiation (OLR) (left) and SST (center), and longitude-depth sections for ocean subsurface temperature along the equatorial Pacific (right) along with their anomalies (boreal spring (March – May) 2013 – autumn (September – November) 2014) Blue and black contours indicate observed values, and shading with white contours indicates anomalies from the normal (i.e., the 1981 – 2010 average). Contour intervals are 20 W/m2 (OLR), 10 W/m2 (OLR anomalies), 1°C (SST and ocean subsurface temperature) and 0.5°C (SST anomalies and ocean subsurface temperature anomalies). Contours for OLR are shown for values of 250 W/m2 or less, with lower values indicating greater convective activity. Green shading indicates regions of above-normal convective activity, and brown shading indicates regions of below-normal convective activity.

Fig. 3.1-7 Continued (boreal winter (December – February) 2014/2015 – summer (June – August) 2016)

59 3.1.2 Influences of the El Niño event on the global observed during the past El Niño events and high-SST climate events in the Indian Ocean. As described in the previous subsection, the El Fig. 3.1-8 shows changes in the NINO.3 index and Niño event peaked in winter 2015/2016 and ended in the IOBW index, which are defined as SST departures spring 2016. SSTs in the Indian Ocean trailed the from the climatological mean based on the latest event by a couple of months and remained above sliding 30-year period averaged over the eastern normal toward spring/summer 2016. Influences from equatorial Pacific and the tropical Indian Ocean, the resulting SST anomalies were extensively felt across the globe, with effects including dry conditions Mar. to May 2015 in Southeast Asia, extremely heavy precipitation along the Yangtze river basin, delayed formation of the first typhoon of the season in the western North Pacific, and far higher-than-normal temperatures over Japan in the first half of winter 2015/2016.

Jun. to Aug. 2015 (1) Development of the El Niño event and associated atmospheric circulation Atmospheric circulation anomalies associated with the event are briefly described here for the period from May to October 2015 (the Asian summer monsoon season) during the development phase and Sep. to Nov. 2015 before the peak, and for the period from April to June (around the onset of the Asian summer monsoon), when SST anomalies in the Indian Ocean peaked in the wake of the event. Also shown are results from statistical analysis of atmospheric circulation

Dec. 2015 to Feb. 2016

Mar. to May 2016

Fig. 3.1-8 NINO.3 and IOBW index fluctuations Thin lines indicate monthly values and thick lines indicate Fig. 3.1-9 3-month mean SST anomalies the five-month moving average. These indices are defined From top to bottom: boreal spring, summer, autumn 2015, as SST anomalies averaged over the areas shown in the winter 2015/2016 and spring 2016. Anomalies are bottom panel. represented with respect to the 1981 – 2010 average.

60 respectively. The NINO.3 index turned positive 3.1-9 indicates seasonal mean SST anomalies around spring 2014 and began to increase rapidly in observed from spring 2015 to spring 2016. spring 2015. Values began to decline after peaking in Fig. 3.1-10 shows stream function anomalies at winter 2015/2016, returned to near-normal in spring 850 hPa composited over the three-month periods of 2016 and turned negative in summer 2016. The IOBW May to July (early Asian summer monsoon), August index surged on the heels of NINO.3, peaking in to October (late Asian summer monsoon) and spring 2016 before declining throughout summer. Fig. December to February (boreal winter) of El Niño years from 1958 – 2012 based on JRA-55 (Kobayashi et al., 2015). The figures show that, during Asian (a) summer monsoon periods, equatorial symmetric cyclonic and anticyclonic circulation anomalies tend to develop in the Pacific and in the area from the Indian Ocean to the Maritime Continent, respectively, in response to convection anomalies associated with El Niño events. This anomaly pattern leads to weaker-than-normal southwesterlies and suppressed

monsoon precipitation over Southeast Asia. In winter, anticyclonic circulation anomalies extend over and to (b) the east of Japan in association with a wave train pattern in the upper troposphere (figure not shown), indicating the mild winters experienced in Japan during El Niño events. A composite map of stream function anomalies at 850 hPa for the three-month periods of April to June in positive IOBW years based on JRA-55, as shown in

Fig. 3.1-11, indicates cyclonic circulation anomalies north of the equator in the Indian Ocean and (c)

Fig. 3.1-10 Composite map for stream function at 850 hPa during El Niño events Three-month mean for (a) early Asian summer monsoon (May to July), (b) late Asian summer monsoon (August to Fig. 3.1-11 Composite map for stream function at 850 October) and (c) boreal winter (December to February). hPa during warm IOBW events Anomalies are represented as deviations from the zonal Three-month mean for April to June. Anomalies are mean. Contours are at intervals of 0.5 x 106 m2/s. Shading represented as deviation from the zonal mean. Contours are denotes statistical confidence. at intervals of 0.5 x 106 m2/s. Shading denotes statistical confidence.

61 equatorial symmetric anticyclonic circulation shown in Fig. 3.1-10 (a) and (b). anomalies over the area from Indochina to the western Anomalies of OLR and stream function at 850 hPa North Pacific. These anticyclonic anomalies are likely for April to June 2016 (around the monsoon onset) are related to equatorial Kelvin waves, which propagate shown in Fig. 3.1-12 (b). The anomaly pattern closely from the Indian Ocean where SSTs remain above resembles that for the positive IOBW shown in Fig. normal in the aftermath of an El Niño event, toward 3.1-11, with cyclonic circulation anomalies in the the western Pacific and induce Ekman divergence Indian Ocean and anticyclonic anomalies and north and south of the equator (Xie et al., 2009). suppressed convection over the area from Indochina Anomalies of outgoing longwave radiation (OLR) to the western tropical North Pacific. and stream function at 850 hPa for May to October 2015 are shown in Fig. 3.1-12 (a). The circulation (2) Influences on the global climate pattern of this period is characterized by cyclonic Some pronounced influences on the global climate circulation anomalies over the Pacific and from atmospheric circulation anomalies associated anticyclonic circulation anomalies centered over with the El Niño event and positive SST anomalies in Indochina, which is quite similar to the situation of the Indian Ocean are described below. anomalies observed in past El Niño summers as (a) Suppressed precipitation over Southeast Asia (a) May to Oct. 2015 Southeast Asia experienced below-normal precipitation from spring 2015 to spring 2016, which adversely affected water resource management and agriculture. In addition to the worst drought conditions for 90 years in Viet Nam (United Nations Food and Agriculture Organization), a state of

W/m 2

(b) Apr. to Jun. 2016

Fig. 3.1-13 Cumulative precipitation averaged over stations in Indochina W/m2 Observation stations are shown on the inset map. The red, Fig. 3.1-12 Anomalies of outgoing longwave radiation yellow and blue lines indicate cumulative precipitation for (shading) and stream function at 850 hPa (contours) 12-month periods starting April 2015, April 2014 and April (a) May to October 2015, and (b) April to June 2016. H and 2011, respectively. Grey lines indicate other years after L denote anticyclonic and cyclonic circulation anomalies, 2000. All data are from SYNOP. 6 2 respectively. Contours are at intervals of 0.5 x 10 m /s.

62 emergency was declared for the Mekong Delta in below-normal precipitation from 2015 to 2016. relation to damage caused by sea water running up the water-deprived river (Unite Nations Country Team (b) Heavy precipitation in the Yangtze River basin Viet Nam). Wildfires were frequently reported in Areas along the middle and lower Yangtze River Indonesia and Malaysia (United States National experienced above-normal precipitation starting in Aeronautic and Space Administration). April 2016. Cumulative precipitation from April 1 Daily cumulative precipitation calculated from averaged over the stations in the basin was the highest Indochina observation station data is shown in Fig. since 1997 (Fig. 3.1-15). Amounts soared from late 3.1-13 for the period from April 1 2015 to March 31 June onward in particular, with the highest cumulative 2016 along with the same period in recent years for 30-day precipitation among the stations for June 21 to comparison. In 2015, precipitation remained below July 20 exceeding 900 mm (Fig. 3.1-16). More than normal from around May, and cumulative 200 fatalities were reported in relation to heavy precipitation for the 12-month period ending March rainfall and landslides from late June to early July, 2016 was the lowest since 2000. according to the government of China. Precipitation totals for the 12 months from April Such an extended period of extremely heavy 2015 to March 2016 were lower than 60% of the precipitation was caused by strong convergence of normal for some stations in Borneo and 60 – 70% for moist air flow from the South China Sea over the stations in Indochina (Fig. 3.1-14). Precipitation was Yangtze River (Fig. 3.1-17). This was induced by also below normal for the southern part of the anticyclonic circulation anomalies over the western Philippines. tropical North Pacific associated with the high SSTs As mentioned previously, southwest summer in the Indian Ocean (Fig. 3.1-12 (b)). monsoon activity in Southeast Asia tends to be weak This pattern of high SSTs in the Indian Ocean, the during El Niño events. The anticyclonic anomalies in anticyclonic circulation anomalies over the western the lower troposphere centered over Indochina, which tropical North Pacific, moist air intrusion from the are considered to be responses to the weak monsoon and similar to atmospheric characteristics seen in past El Niño events (Fig. 3.1-12(a)), were a factor behind

Fig. 3.1-15 Cumulative precipitation averaged over stations in the middle and lower Yangtze River basin Observation stations are shown on the inset map. The red, blue and green lines indicate cumulative precipitation for Fig. 3.1-14 12-month precipitation anomalies for April the periods starting on April 1 of 2016, 1998 and 1999, and 2015 to March 2016 grey lines indicate the same period for all other years since Anomalies are based on CLIMAT reports and represented 1997. The dashed black line indicates the average over the as ratios against the normal. 19 years from 1997 to 2015.

63 South China Sea and water vapor convergence over its maximum wind speed of 17.2 m/s or higher. This southern China resembled the conditions seen in 1998 was the second-latest since 1951, and slightly earlier – another year when the Yangtze River basin was hit than the July 9 date recorded in 1998 (Table 3.1-1). by heavy precipitation. The top four records in Table 3.1-1 coincide with typhoon seasons subsequent to winter when an El Niño event reached its peak and the IOBW index remained high (Fig. 3.1-18). During all these typhoon seasons, pronounced anticyclonic circulation anomalies developed in the lower troposphere and convection activity was suppressed over the western tropical North Pacific as per the pattern in Fig. 3.1-12 (b). In summary, suppressed convective activity over the western North Pacific in association with high SSTs in the Indian Ocean in the wake of the El Niño Fig. 3.1-16 30-day precipitation in the middle and lower event was a factor in the delayed first TC formation of Yangtze River basin The map indicates 30-day precipitation for June 21 to July 2016. 20, 2016, when particularly heavy rainfall was recorded. Red dots denote stations recording the three highest Table 3.1-1 Top 10 years of delayed TC formation precipitation amounts for the 30-day period (Anqing, Time of first TC Wuhan and Macheng) and the highest amount for April 1 to Rank Year formation (UTC) July 24 (Huangshan). 1 1998 06Z, July 9

2 2016 00Z, July 3 3 1973 18Z, July 1 4 1983 06Z, June 25 5 1952 18Z, June 9 6 1984 06Z, June 9 7 1964 06Z, May 15 8 2001 00Z, May 11 9 2006 12Z, May 9 10 2011 12Z, May 7

Fig. 3.1-17 Water vaper flux (arrows) and normalized divergence (shading) anomalies at 850 hPa for April to June 2016 Warm and cool colors indicate divergence and convergence anomalies, respectively. Fig. 3.1-18 IOBW index changes over the last 50 years

(c) Delayed formation of the season’s first typhoon (d) Mild 2015/2016 winter in Japan The first tropical cyclone (TC) of 2016 over the In winter 2015/2016, particularly early in the western North Pacific basin formed on July 3, where a season, significantly above-normal temperatures (Fig. TC is defined as a tropical low pressures system with 3.1-19) and below-normal snowfall were observed

64 across Japan. The monthly mean temperature for The thermal balance over and around Japan shown December averaged over eastern Japan was the in Fig. 3.1-22 corroborates the above as factors highest since 1946. It was reported that the extremely involved in Japan’s mild winter – that is, southerly low snowfall amount adversely affected the winter warm air advection associated with anticyclonic sports industry. Its influence extended to spring and anomalies to the east of the country (Fig. 3.1-22 (a)) summer, when restrictions on river water usage were and temperature anomaly advection associated with put into effect because earlier-than-normal snow the weak cold air mass over the continent (Fig. 3.1-22 disappearance led to low water reserves. (b)). In the first half of winter 2015/2016, convective It can therefore be concluded that influences from activity was suppressed over the Maritime Continent the El Niño event and the internal variability of the and anticyclonic circulation anomalies extended from high-latitude atmosphere (a negative EU phase) were the South China Sea to the seas east of Japan (Fig. factors behind the higher-than-normal temperatures 3.1-20 (a)). This anomaly pattern closely resembled recorded in Japan in the first half of winter 2015/2016. the composite map in Fig. 3.1-10 (c), which depicts Any possible relationship between the polarity of circulation anomaly characteristics seen in past El ENSO and EU still needs to be clarified. Niño events. Meanwhile, negative sea level pressure anomalies References Du, Y., L. Yang. and S.-P. Xie, 2011: Tropical Indian Ocean were seen across Eurasia, indicating a Influence on Northwest Pacific Tropical Cyclones in weaker-than-normal Siberian High (Fig. 3.1-20 (b)). Summer following Strong El Niño. J. Climate, 24, 315-322. The EU index, which is closely correlated with the Kobayashi, S., Y. Ota, Y. Harada, A. Ebita, M. Moriya, H. intensity of the Siberian High, remained in a negative Onoda, K. Onogi, H. Kamahori, C. Kobayashi, H. phase throughout most of December (Fig. 3.1-21 (a)). Endo, K. Miyaoka and K. Takahashi, 2015: The JRA-55 Reanalysis: General Specifications and The negative phase of the EU index (the reverse of the Basic Characteristics. J. Meteorol. Soc. Japan, 93, anomaly pattern shown in Fig. 3.1-21 (b)) is 5-48. Rasmusson, E. M. and T. H. Carpenter, 1982: Variations in consistent with the weak Siberian High and a weak Tropical Sear Surface Temperature and Surface cold air mass over the Eurasian continent. Wind Fields Associated with the Southern Oscillation/El Niño. Mon. Wea. Rev., 110, 354-384. Xie, S.-P., K. Hu, J. Hafner, H. Tokinaga, Y. Du, G. Huang, and T. Sampe, 2009: Indian Ocean Capacitor Effect on Indo-Western Pacific Climate during the Summer following El Niño. J. Climate, 22, 730 – 747.

Fig. 3.1-19 Five-day running mean of area-average temperature anomalies for winter 2015/2016

65 (a) (a)

(b)

(c)

Fig. 3.1-20 (a) Anomalies of OLR (shading) and stream function at 850 hPa (contours) and (b) sea level pressure anomalies for Dec. 2015 to Jan. 2016 Arrows in (a) indicate wave activity flux at 850 hPa in units of m2/s2. Contours in (a) are at intervals of 10 x 106 m2/s (thick) and 2.5 x 106 m2/s (thin).

Fig. 3.1-21 (a) Daily EU index for Nov. 2015 to Feb. 2016 (b) Geopotential height anomalies at 500 hPa regressed onto EU indices (contours) and correlation coefficients (shading) (c) Geopotential height at 500 hPa (contours) and anomalies (shading) for Dec. 2015

(a)

(b)

Fig. 3.1-22 (a) Climatological temperature advection associated with wind anomalies, and (b) temperature anomaly advection associated with climatological winds at 925 hPa (K/day) for Dec. 1 2015 to Jan. 10 2016

67 3.2 Extreme climate conditions in Japan in August 2016 Western Japan experienced hot summer conditions in August 2016, especially in the middle of the month. Meanwhile, primarily due to the approach of typhoons, monthly precipitation was the highest on record on the Pacific side of northern Japan. This section reports on surface climate characteristics and atmospheric circulation observed in August 2016.

3.2.1 Surface climate conditions, SSTs and typhoon activity in and around Japan (1) Surface climate conditions Fig. 3.2-1 shows temperature, precipitation and sunshine duration for Japan in August 2016 as Fig. 3.2-1 Temperature anomalies, precipitation ratios and sunshine duration ratios for August 2016 deviations from or ratios against the normal (i.e., the

1981 – 2010 average). Monthly mean temperatures and sunshine durations were generally above normal all over the country. Western Japan experienced hot summer conditions, especially in mid-August, with monthly mean temperatures +0.9°C above the normal and the second-highest 10-day mean temperature for mid-August since 1961 (+1.6°C above the normal). Monthly sunshine durations against the normal on the Sea of Japan side and the Pacific side of western

Japan were 131% (the second-highest since 1946) and 126% (the third-highest since 1946), respectively. Monthly precipitation amounts were below normal on the Pacific side of western Japan and in Okinawa/Amami. Meanwhile, due to rainfall from typhoons, fronts and moist air inflow, values were significantly above normal in northern Japan. The total on the Pacific side of northern Japan was the highest on record at 231% of the normal since 1946.

Fig. 3.2-2 10-day mean sea surface temperature (top) and its anomaly (bottom) for 11 – 20 August 2016 Sea surface temperatures (unit: °C) are based on the MGDSST dataset. The aqua rectangle indicates the northern part of the East China Sea (30 – 35°N, 120 – 130°E).

68 (2) Sea surface temperature around Japan1 As with the hot conditions in western Japan, SSTs in the northern part of the East China Sea were much higher than normal in association with greater-than-normal solar radiation and weak surface winds. Areas with SSTs exceeding 31°C were seen in mid-August (Fig. 3.2-2). The 10-day mean sea surface temperature in the northern part of the East China Sea Fig. 3.2-3 Tracks of tropical cyclones in August 2016 T05 – T11 are TC identification numbers. The solid lines in mid-August was the highest since 1982 at 29.9°C. show the tracks of TCs with maximum wind speeds of 17.2 m/s or more, and the dashed lines show the tracks of tropical depressions or extratropical cyclones. (3) Typhoon activity in the western North Pacific

Seven tropical cyclones (TCs) with maximum 3.2.2 Atmospheric conditions wind speeds of 17.2 m/s or more formed over the (1) Hot summer conditions in western Japan western North Pacific in August 2016 (Fig. 3.2-3). The active phase of the Madden-Julian Oscillation Four of them (Chanthu (T07), Mindulle (T09), (MJO) propagated eastward from the Maritime Lionrock (T10) and Kompasu (T11)) made landfall on Continent to the Pacific during the period from the Japan in rapid succession. This was the country’s end of July to mid-August 2016 (not shown). The highest monthly landfall total since records began in time-latitude cross section for OLR anomalies 1951 (tying with August 1962 and September 1954). averaged over the 105 – 125°E area (Fig. 3.2-4) Several TCs affected Hokkaido and other parts of indicates that an enhanced convection phase, which northern Japan. Chanthu (T07) made landfall around started to propagate northward in mid-July (Boreal Cape Erimo in Hokkaido on 17 August, Kompasu Summer Intraseasonal Oscillation; BSISO), reached (T11) made landfall on Kushiro City in Hokkaido on the area around the Philippines in August. Convective 21 August, and Mindulle (T09) made landfall on activity from this area to the sea east of the Tateyama City in Chiba Prefecture on 22 August Philippines was enhanced in association with MJO before moving over mainland Japan and making and BSISO (especially in mid-August). This landfall again on the Hidaka district of Hokkaido on enhancement was also probably due in part to August 23. This was the first year in which multiple higher-than-normal sea surface temperatures over the TCs made landfall on Hokkaido since 1951. Hokkaido same area (Fig. 3.2-5). was also affected by Conson (T06), which passed the Fig. 3.2-6 shows 200-hPa stream function region’s Nemuro Peninsula. Lionrock (T10) was the anomalies and divergent wind anomalies, along with first typhoon to make landfall on the Tohoku region latitude-height cross section data for meridional from the Pacific side since 1951. wind/vertical pressure velocity anomalies averaged over the 110 – 130°E area for 8 to 17 August 2016. In the upper troposphere, outward flow from the area over the Philippines is clearly seen in association with enhanced convective activity. The Tibetan High was 1 Based on the Merged satellite and in-situ data Global Daily Sea Surface Temperature (MGDSST; Kurihara et. al, stronger than normal over its northeastern part, and 2006) of JMA. Climatological normal (i.e., the 1981-2010 average) are calculated from MGDSST and COBE-SST anticyclonic circulation anomalies were seen over (JMA, 2006) datasets.

69 northeastern China. These two flows converged over (a) the area from eastern China to the East China Sea (approx. 30 – 35˚N), and downward flows were seen in the mid-troposphere. Fig. 3.2-7 shows vertical temperature advection at 925 hPa. This advection and greater-than-normal solar radiation were considered to be factors behind the hot summer conditions observed from eastern China to western Japan.

(b)

Fig. 3.2-4 Time-latitude cross section for OLR anomalies averaged over the 105 – 125°E area

Fig. 3.2-6 (a) 200-hPa stream function anomalies (shading; unit: 106 m2/s) and divergent wind anomalies (vectors; unit: m/s) (b) Latitude-height cross section for meridional wind/vertical pressure velocity anomalies averaged over the 110 – 130°E area for 8 to 17 August 2016 The green rectangle in (a) indicates the area of 110 – 130°E and 10 – 50°N, and the shading in (b) shows vertical pressure velocity anomalies (unit: Pa/s). Positive (negative) values denote downward (upward) flow anomalies. Vectors for the meridional wind/vertical pressure velocity anomaly are magnified x 100 vertically.

Fig. 3.2-5 Monthly mean sea surface temperature anomalies for August 2016 (unit: °C) Based on the MGDSST dataset

Fig. 3.2-7 Advection of normal temperatures due to vertical pressure velocity anomalies at 925 hPa for 8 to 17 August 2016 (unit: K/day)

70 (2) Record precipitation in northern Japan how high PV air intruded equatorward in a southern or Fig. 3.2-8 (a) shows the 500-hPa height field for southwestern direction over the central Pacific. Such August 2016. The westerly jet stream meandered over air also frequently intruded southward from the a wide area of the Northern Hemisphere, and was mid-latitudes of the central Pacific (not shown), and displaced northward of its normal position over and propagated westward over the subtropical Pacific (Fig. around the Kamchatka Peninsula and southward over 3.2-13). Cyclonic circulation in the lower troposphere Japan and the central Pacific. Blocking highs over was enhanced, and tropical depressions formed west western Siberia (around 60˚E) were seen throughout of the dateline. In this way, high PV migrating from the month, and also developed over and around the the mid-latitudes contributed to enhanced convective Kamchatka Peninsula from mid-August onward (Fig. activity and the formation of more tropical cyclones 3.2-9). In the upper troposphere, propagation of than normal in the central Pacific. quasi-stationary Rossby wave packets along the The westerly jet stream meandered and southerly subtropical jet stream from the cyclonic circulation winds prevailed over the sea to the east of Japan. The anomalies located to the south of the blocking high Pacific High was displaced far eastward of its normal over western Siberia was seen, with anticyclonic position and extended toward the south of the circulation anomalies over northern China and the Kamchatka Peninsula in August 2016 in association Kamchatka Peninsula (Fig. 3.2-8 (b)). Over and with a persistent wave train pattern in the upper around western Siberia and the Kamchatka Peninsula, troposphere extending from Eurasia to the mid-Pacific positive anomalies of 500-hPa height tendency (Fig. 3.2-14). In the lower troposphere, propagation of associated with eddy vorticity flux were seen in the quasi-stationary Rossby wave packets from cyclonic areas where anticyclonic circulation anomalies were circulation anomalies over the sea to the south of observed (Fig. 3.2-8 (c)). This suggests that Japan was seen. This may have been related to the eddy-related feedback may have contributed to the expansion of the Pacific High toward the south of the development and maintenance of these highs. Kamchatka Peninsula (Fig. 3.2-10 (b)). Fig. 3.2-10 shows stream function anomalies, Tropical depressions forming over the sea to the wave activity flux and OLR anomalies in the upper southeast of Japan were upgraded to named tropical and lower troposphere for August 2016. Convective cyclones that moved northward over the sea to the activity was enhanced from the western North Pacific east of Japan and approached or hit the northern part to the area near the dateline around 20˚N. In response of the country. Lionrock (T10) followed a peculiar to this enhancement (a Rossby wave response), path, first moving southwestward over the sea south massive cyclonic circulation associated with a deep of the Kanto region and then making a U-turn over the monsoon trough was seen over a wide area from the Pacific Ocean and moving northwestward in South China Sea to the south of Japan in the lower association with the meandering westerly jet stream troposphere. Convective activity over the seas to the (Fig. 3.2-3). This was the first typhoon to make southeast of Japan (150 – 170˚E, 10 – 30˚N) in August landfall on the Tohoku region from the Pacific side 2016 was enhanced to record levels (Fig. 3.2-11). since 1951. These TCs brought a series of heavy Intrusions of high potential vorticity (PV) air precipitation events and serious damage to northern associated with the trough over the mid-latitude Japan, especially on the Pacific side. central Pacific (the mid-Pacific trough) contributed to the enhanced convective activity. Fig. 3.2-12 shows

71 (a)

(b)

Fig. 3.2-9 Time-longitude cross section showing maximum geopotential height anomalies at 500 hPa in the latitude bands between 40 and 80°N for June to August 2016

(a)

(c)

(b)

Fig. 3.2-8 (a) 500-hPa height (contours at intervals of 60 m) and anomalies (shading) (b) 300-hPa wave activity flux (vectors; unit: m2/s2) and stream function anomalies (contours at intervals of 2 × 106 m2/s) (c) 500-hPa height tendency anomalies associated with eddy vorticity flux (shading; unit: m/day) and 500-hPa height anomalies (contours at intervals of 60 m) for August 2016 H and L in (b) represent anticyclonic and cyclonic Fig. 3.2-10 (a) 200-hPa and (b) 850-hPa stream function 6 2 circulation anomalies, respectively. In (c), eddies are anomalies (contours at intervals of (a) 3 × 10 m /s and 6 2 defined as two- to eight-day band-pass-filtered fields. (b) 1.5 × 10 m /s) and wave activity flux (vectors; unit: 2 2 m /s ) for August 2016 Shading indicates OLR anomalies (unit: W/m2). The green rectangle in (b) indicates the area of 150 – 170°E and 10 – 30°N.

Fig. 3.2-11 Time-series representation of OLR (unit: W/m2) averaged over the area to the southeast of Japan (150 – 170°E, 10 – 30°N) for August from 1979 to 2016 Fig. 3.2-14 Monthly mean sea level pressure (contours at intervals of 4 hPa) and anomalies (shading) for August 2016

3.2.3 Summary The atmospheric circulation conditions discussed here are summarized in Fig. 3.2-15. In the upper troposphere, propagation of quasi-stationary Rossby wave packets from cyclonic circulation anomalies located to the south of the blocking high over western Siberia was seen. The

westerly jet stream meandered over a wide area, 2 Fig. 3.2-12 Monthly mean OLR (shading; unit: W/m ) ridges were seen over north China and the Kamchatka and potential vorticity on the 360-K isentropic surface (contours at intervals of 1 PVU) for August 2016 Peninsula, and troughs were seen over Japan and the central Pacific. In association with intrusions of high PV air from the trough over the mid-latitude central Pacific, convective activity was enhanced from the area southeast of Japan to the area near the dateline at around 20˚N. In response to this enhancement (a Rossby wave response), massive cyclonic circulation was seen over the sea to the south of Japan in the lower troposphere.

Fig. 3.2-13 Time-longitude cross section for potential The Pacific High was displaced far eastward of its vorticity on the 360-K isentropic surface averaged over normal position and extended toward the south of the the 20-30°N area (shading; unit: PVU) and relative vorticity at 850 hPa averaged over the 15 – 25°N area Kamchatka Peninsula. The blocking highs over and -6 -6 (contours at intervals of 10 /s; shown for 2×10 /s or around the Kamchatka Peninsula as well as the more) for August 2016 The blue dots represent genesis points of tropical propagation of quasi-stationary Rossby wave packets depressions later upgraded to named TCs. “T16xx” from cyclonic circulation anomalies over the sea to expresses TC identification numbers. the south of Japan in the lower troposphere may have

contributed to this extension.

73 Tropical depressions forming over the sea to the southeast of Japan were upgraded to named tropical cyclones (TCs) that moved northward over the sea to the east of Japan and brought a series of heavy precipitation events and serious damage to northern Japan. In association with enhanced convective activity over and around the Philippines and the stronger-than-normal Tibetan High over northeastern China, downward flows were seen from eastern China to western Japan in the mid-troposphere. This vertical advection and greater-than-normal solar radiation brought hot summer conditions to western Japan.

Fig. 3.2-15 Characteristics of atmospheric circulation associated with extreme climate conditions in Japan in August 2016

References JMA, 2006: Characteristics of Global Sea Surface Temperature Data (COBE-SST), Monthly Report on Climate System, Separated Volume No. 12. Kurihara, Y., Sakurai, T., and Kuragano, T., 2006: Global daily sea surface temperature analysis using data from satellite microwave radiometer, satellite infrared radiometer and in-situ observations (in Japanese), Weather Service Bulletin, Vol. 73, S1 – S18.