2866 JOURNAL OF CLIMATE VOLUME 17

Summer Patterns in and the Relationship to Global Sea Surface Temperatures

AMIR SHABBAR AND WALTER SKINNER Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada

(Manuscript received 10 October 2003, in ®nal form 9 February 2004)

ABSTRACT Canadian summer (June±August) Palmer Drought Severity Index (PDSI) variations and winter (December± February) global (SST) variations are examined for the 63-yr period of 1940±2002. Extreme wet and dry Canadian summers are related to anomalies in the global SST pattern in the preceding winter season. Large-scale relationships between summer PDSI patterns in Canada and previous winter global SST patterns are then analyzed using singular value decomposition (SVD) analysis. The matrix for the covariance eigenproblem is solved in the EOF space in order to obtain the maximum covariance between the singular values of the SST and the PDSI. The robustness of the relationship is established by the Monte Carlo technique, in which the time expansion of the primary EOF analysis is shuf¯ed 1000 times. Results show that the leading three SVD-coupled modes explain greater than 80% of the squared covariance between the two ®elds. The interannual El NinÄo±Southern Oscillation (ENSO), the Paci®c decadal oscillation (PDO), and the interrelationship between the two play a signi®cant role in the determination of the summer moisture availability in Canada. These Paci®c Ocean processes are re¯ected in the second and third SVD modes, and together explain approximately 48% of the squared covariance. It is found that the warm ENSO (El NinÄo) events lead to a summer moisture de®cit in the western two-thirds of Canada. Conversely, cold ENSO (La NinÄa) events produce an abundance of summer moisture, mainly in extreme western Canada and in the southeastern portions of the . The ®rst SVD mode strongly relates to the trend in global SSTs and multidecadal variation of the Atlantic SST, explaining approximately one-third of the squared covariance. It is re¯ective of both the warming trend in the global southern oceans and the in¯uences of the Atlantic multidecadal oscillation (AMO) variability. The 6-month lag relationship between the PDSI and large-scale SSTs provides a basis for developing long- range forecasting schemes for drought in Canada. A two-tier forecast scheme, in which the SST is predicted by an ocean model or a coupled , can potentially further increase the lead time of drought forecasting.

1. Introduction essary for predicting seasonal drought severity, as well as for planning for impacts due to future . Prolonged drought can have a serious impact on the Drought is often de®ned in terms of its primary in- Canadian economy, natural environment, and society, ¯uences (such as agricultural productivity, , especially in western Canada where drought-related reservoir levels, and stream¯ow) or by its economic losses were in excess of 1.8 billion dollars in 1988 impacts. It can be described as a signi®cant de®cit in (Wheaton and Arthur 1989). Economic losses and other moisture availability over an extended period of several impacts due to the 2001±02 drought are estimated at months arising from lower-than-normal rainfall and/or 6.14 billion dollars (S. Kulshreshtha 2003, personal higher-than-normal air temperature. The change in the communication). The uncertainty of drought prediction balance between evaporation and precipitation may re- contributes to substantial crop insurance payouts every sult from changes in the , which year. A better understanding of the spatial distribution may be teleconnected to long-term ocean variability. of drought, and its frequency, intensity, and duration in This de®nition is complicated, however, when attempts Canada is, thus, required. Increased knowledge of the are made to compare in regions with differing relationship of drought intensity, duration, and spatial atmospheric moisture regimes. Thus, an index stan- extent to large-scale ocean±atmosphere forcing is nec- dardized to regional and local climatology is required when approaching studies on a national to continental spatial scale. A number of different indices have been Corresponding author address: Amir Shabbar, Meteorological Ser- developed to quantify drought, each with its own vice of Canada, Environment Canada, 4905 Dufferin Street, Toronto, ON M3H 5T4, Canada. strengths and weaknesses (Heim 2002). E-mail: [email protected] Two of the most commonly used are the Palmer

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Drought Severity Index (PDSI) and the Standard Pre- United States drought patterns during the twentieth cen- cipitation Index (SPI). The PDSI re¯ects long-term tury. By employing a suite of climate model simulations, moisture, runoff, recharge, deep percolation, and evap- Hoerling and Kumar (2003) have recently linked the oration. The index is useful for drought analysis over Northern Hemisphere midlatitude droughts that oc- time spans of months or seasons. Also, it has proven curred from 1998 to 2002 in the United States, southern useful for drought reconstruction prior to the instru- Europe, and southwest Asia to common oceanic in¯u- mental record by using climate proxy data in the con- ences. Cold sea surface temperature (SST) in the eastern terminous United States (Cook et al. 1999), as well as tropical Paci®c and warm SSTs in the western tropical for summer drought reconstruction from the early eigh- Paci®c and Indian Oceans, a condition reminiscent of teenth century from tree rings in the southwestern Ca- the cold phase of ENSO, persisted throughout the pe- nadian Prairies (Sauchyn and Skinner 2001). There have riod. Their climate model experiments indicated that the been several drought indices developed (Heim 2002) climate anomalies forced by these oceanic regions con- that are related to different aspects of drought intensity, tributed in unison to large-scale midlatitude drying. duration, and persistence. This paper does not discuss Forced by anomalous rainfall in the tropical Paci®c, the the relative merits of each index, but only uses the PDSI resulting Rossby waves give rise to one of the principal because it is the most commonly cited index, and cur- modes of variability in the Northern Hemisphere cir- rently constitutes a component of the United States culationÐthe Paci®c±North American (PNA) telecon- Drought Monitor (Lawrimore et al. 2002). nection (Horel and Wallace 1981; Hoskins and Karoly Severe large spatial scale North American droughts 1981). The PNA has one of its strongest over the past century have had a tendency to be clustered centers of action over western Canada. It is, therefore, in successive years and are likely related to ocean±at- important to investigate and quantify the role of the mosphere variability on similar time scales (Hoerling interannual and interdecadal oceanic anomalies in the and Kumar 2003). The Dust Bowl drought of the 1930s initiation and maintenance of extended drought in Can- was a natural disaster that severely affected much of the ada. western United States and western Canada, occurring A strong relationship between seasonal Canadian in three waves: 1934, 1936, and 1939±40. Some regions temperature and precipitation, key factors in the for- of the High Plains (from Colorado and Kansas to south- mation of drought, and the ENSO cycle has already been ern and ) experienced drought established (Shabbar and Khandekar 1996; Shabbar et conditions for as many as eight consecutive years. Dur- al. 1997a). As well, Bonsal and Lawford (1999) have ing the 1950s, the southwestern United States and the related variations in the tropical Paci®c SSTs to regional Great Plains, and the adjacent Canadian Prairies, were Canadian Prairie dry spells. It is plausible that midlat- subjected to a 5-yr drought. In three of those years, itude decadal ocean±atmosphere variability could also drought conditions stretched from coast to coast. The play an important role in the establishment and persis- 1950s drought was characterized by both below-normal tence of extended dry spells in Canada. Mestas-NunÄez rainfall and higher-than-normal air temperatures. The 3- and En®eld (1999) de®ne the Atlantic multidecadal os- yr drought of the late 1980s (1987±89) resulted in tre- cillation (AMO) as the ®rst rotated empirical orthogonal mendous agricultural losses in western Canada. In ad- function (EOF) of the global SSTs from which intra- dition, approximately 7 million ha of Canadian forest seasonal ENSO and local trends have been removed. burned during the summer of 1989Ðthe most severe The AMO is a long-time-scale oceanic phenomena with forest ®re year since reliable records began in the early a 65±80 yr time scale and 0.4ЊC range. En®eld et al. 1950s (Skinner et al. 1999). This includes the most re- (2001) have found distinct associations between cold cent 2003 ®re season, when only approximately 1.6 mil- and warm phases of the AMO and the United States lion ha burned in . The drought of summer rainfall and river ¯ows. This Atlantic atmo- 2001±02 was particularly severe in western Canada. As sphere±ocean long-term variability may also provide ad- well, it had national extent during the summer of 2001, ditional information about summer moisture patterns in similar to large-scale drought patterns of the 1980s and Canada. 1950s. In Canada, the physical and economic impacts of A few recent studies have examined the associations drought are most evident during the warm season. Nu- among hydrologic drought and climatic conditions lead- merous studies have linked Canadian and United States ing to drought in the United States and the El NinÄo± precipitation and ENSO variability (e.g., Ropelewski Southern Oscillation (ENSO) phenomenon in the trop- and Halpert 1986). Few studies, however, have focussed ical Paci®c Ocean (i.e., Cole and Cook 1998; Nigam et on summer season moisture conditions and ocean±at- al. 1999; Trenberth and Barnstator 1992). The role of mosphere forcing mechanisms during the preceding ENSO in the initiation of North American drought is winter season. Evidence for the lagged relationship be- further supported in a study by Rajagopalan et al. tween the summer climate variability in Canada and (2000). Using partial correlation analysis and the sin- preceding winter tropical SSTs exist in observational gular value decomposition (SVD) technique, they iden- data. While examining seasonal temperature and pre- ti®ed the changing relationship between ENSO and the cipitation prediction skill, Shabbar and Barnston (1996)

Unauthenticated | Downloaded 09/25/21 04:31 PM UTC 2868 JOURNAL OF CLIMATE VOLUME 17 identi®ed the ENSO cycle, which manifests itself most forcefully in winter SSTs, as the main source of vari- ability in producing skillful forecasts for Canada from winter into early summer. As well, Rajagopalan et al. (2000) found a coupled pattern between summer drought over the continental United States and winter SST variability during the twentieth century. For these reasons, summer-season drought was analyzed in order to assess the utility of antecedent winter-season global SST anomalies for drought prediction. The PDSI is a soil moisture accounting algorithm based on the water balance and is derived from ongoing measurements of precipitation, air temperature, and lo- cal soil moisture. The index, in any given season, is a function of climatic and soil moisture conditions oc- curring in the current and preceding seasons, thus, mak- ing it a potentially useful measure to predict. Soil mois- ture is affected by precipitation, which, in turn, in¯u- ences current and future surface temperature, primarily through evaporation (Huang et al. 1996). The purpose of this study is to determine the spatial patterns and temporal variability of summer (June±Au- gust) moisture availability in Canada as determined by the PDSI from 1940 to 2002. Composite analysis and SVD of the joint structure between Canadian PDSI and global SSTs are used to quantify the impact of ENSO and other midlatitude ocean±atmosphere variability on extended dry spells. Additionally, structures in PDSI FIG. 1. (a) North America monthly PDSI site locations as calculated related to global warming, as manifested by long-term from Canadian historical database stations (red) and the United States Climate Division centroids (blue) monthly mean air temperature and changes in global SSTs, are also examined. It is hoped monthly total precipitation data. Data are gridded at approximate 250 that the coupled patterns obtained by identifying the km ϫ 250 km. (b) Summer (JJA) PDSI for 2001; with the exception source of global SST variability in the preceding winter of southern and parts of northwestern Ontario, most of months (December±February) will provide useful in- southern Canada experienced prolonged drought. sights toward developing a seasonal and possibly a mul- tiyear drought severity prediction scheme in Canada. The rest of the paper is organized as follows: the datasets balance. The computational procedure is described by are described in section 2. The SVD methodology and Palmer (1965) and Alley (1984). PDSI computation be- the teleconnection results are highlighted in section 3. gins with a climatic water balance, which is the same The paper closes with a summary and discussion in as that developed by Thornthwaite (1948). It requires section 4. temperature, precipitation, and soil water-holding ca- pacity as input parameters. The procedure for estimating potential evapotranspiration (PE) is based on tempera- 2. Data ture and the length of day, and a hierarchy for satisfying The Palmer Drought Severity Index has been com- water demands (e.g., ®rst satisfy PE, then recharge the puted for approximately 100 Canadian stations from the soil, and then allow for ). The Palmer homogenized Canadian historical air temperature and model divides the soil into two layers, assuming that 25 precipitation database of climate stations, having col- mm can be stored in the surface layer and that moisture located monthly mean air temperature and monthly total cannot be removed or recharged to the underlying layer precipitation records extending from 1940 or before to (75 mm) until the surface layer has been depleted or the end of 2002 (Fig. 1a). Monthly PDSI values for 344 saturated. There are three additional potential terms in contiguous United States Climate Divisions obtained the model of importance to soil moisture: potential re- from the National Climatic Data Center (NCDC) were charge (PR; the amount of moisture necessary to bring added to the Canadian data to provide more complete the soil to its water holding capacity), potential loss [PL; spatial coverage for analysis at the international border. the amount of moisture that can be withdrawn from the The PDSI has been a commonly used drought index soil for evapotranspiration (ET) during a zero-precipi- in North America and was developed to measure the tation period], and potential runoff (PRO; the soil water- intensity, duration, and spatial extent of drought. It is a holding capacity minus potential recharge). The model soil moisture accounting algorithm based on the water is initially calibrated to normal levels prior to calculating

Unauthenticated | Downloaded 09/25/21 04:31 PM UTC 15 JULY 2004 SHABBAR AND SKINNER 2869 the monthly index. This involves simulating the water TABLE 1. Severity classes of PDSI. balance over a historical time series of climate data in PDSI Class order to derive several coef®cients and parameters that Ն4.00 Extremely wet are dependent on the area being analyzed. As a result, 3.00±3.99 Very wet PDSI values are normalized with respect to time and 2.00±2.99 Moderately wet location, and, thus, allow for comparison of the index 1.00±1.99 Slightly wet in time and space. 0.50±0.99 Incipient wet spell The PDSI has become the primary tool for describing Ϫ0.49±0.49 Near normal Ϫ0.50 to Ϫ0.99 Incipient drought and monitoring prevailing drought (Louie 1986). The Ϫ1.00 to Ϫ1.99 Mild drought PDSI model allows measurement of prolonged abnor- Ϫ2.00 to Ϫ2.99 Moderate drought mal dryness, or wetness, across a region and can be Ϫ3.00 to Ϫ3.99 Severe drought related directly to past weather conditions. Similar to ՅϪ4.00 Extreme drought the stream¯ow data, the PDSI re¯ects a relatively long- term memory that is modulated by seasonal in¯uences. Summer PDSI values re¯ect moisture inputs and bal- Gauge-speci®c wetting loss corrections were also ap- ances, not only during the current season but also over plied for each rainfall event. For snowfall, ruler mea- the previous several months, including winter snowfall surements were used throughout the time series to min- and storage. It is, thus, absolutely necessary to have imize potential discontinuities introduced by the adop- accurate winter precipitation (mainly snowfall) mea- tion of Nipher-shielded gauge measurements in surements for the soil moisture account. the mid-1960s. Density corrections based upon coin- cident ruler and Nipher measurements were mapped for Canada and applied to all ruler measurements. Where a. Canadian historical climate database and PDSI necessary, and where possible, records from neighbor- The homogenized Canadian historical air temperature ing stations were joined by employing a technique based and precipitation database is the result of several years on a simple ratio of observations. Overlapping periods of research at the Climate Research Branch of the Me- were used to minimize possible inhomogeneities. teorological Service of Canada. This database of ho- In the absence of detailed, site-speci®c soil type and mogenized and long-term temperature time series of soil moisture characteristics, all stations in the Canadian monthly maximum, minimum, and mean temperatures analysis were given the same 100-mm ®eld capacity at (Vincent 1998; Vincent and Gullett 1999) has been spe- the drought model initiation. Negative PDSI values in- ci®cally designed for climate change research. Missing dicate dry conditions and positive values indicate wet values were estimated using highly correlated neigh- conditions. PDSI values generally fall between Ϫ6 and boring stations. It was necessary in some cases to join ϩ6 (Table 1), although extreme values of Ϫ10 and ϩ10 short-term-station segments to create long-term series can occur. Values near zero represent near-normal con- and to test for ``relative homogeneity'' with respect to ditions. surrounding stations. The methodology involves the All North American data were gridded using the Krig- identi®cation of inhomogeneities in the temperature se- ing method (Isaaks and Srivastava 1989) at approxi- ries, which are often nonclimatic steps due to station mately 250 km2, and data representing grid squares alterations, including changes in site exposure, location, north of 40ЊN were further analyzed (Fig. 1a). The krig- instrumentation, observer, observing program, or a com- ing method was used because it is ¯exible in the degree bination of the above. Monthly adjustment factors were of smoothing, which allows for larger datasets over large derived from regression models, and adjustments were and spatially diverse areas. Averages were calculated applied to bring each homogeneous segment into agree- for the summer season. As an example, the PDSI ®eld ment with the most recent homogenous part of the series. for summer 2001 is shown in Fig. 1b. Whenever possible, the main causes of the identi®ed inhomogeneities were retrieved through historical evi- b. Global SST data dence, such as station maintenance reports. Similar to air temperature, long-term precipitation da- Extended reconstructed global sea surface tempera- tasets have also been prepared for climate change anal- ture (Smith and Reynolds 2003) anomalies are analyzed yses in Canada (Mekis and Hogg 1999). However, the for the 1940±2002 period, where the anomalies are cal- precipitation network density is insuf®cient to allow for culated relative to the 1960±90 base period. For the widespread use of surrounding station data to identify 1940±97 period, in situ observations from a new version and adjust inhomogeneities. Instead, the primary goal of the Comprehensive Ocean±Atmosphere Data Set has been to correct daily rain and snow measurements (COADS) release 2 (Woodruff et al. 1998) are used for all known inhomogeneities. Adjustments were ap- together with an eigenvector reconstruction (Smith et plied on the daily level for rain and snow separately. al. 1998). The reconstruction of the data involves a rig- For each rain gauge type, corrections to account for orous quality control procedure and a statistical analysis wind undercatch and evaporation were implemented. methodology, which is an improvement over their pre-

Unauthenticated | Downloaded 09/25/21 04:31 PM UTC 2870 JOURNAL OF CLIMATE VOLUME 17 vious version (Smith et al. 1996). Data from 1998 to 2002 are based on in situ observations and satellite es- timates, which are combined using the optimum inter- polation method as described by Reynolds et al. (2002). At high latitudes, an improved sea ±to-SST conver- sion algorithm is used. The joined SST data are then analyzed at 2Њ resolution. The anomaly reconstruction is performed separately for the low- and high-frequency components, and the sum of these components constitute the total SST anomaly. Smith and Reynolds (2003) show that the resulting SSTs are capable of resolving domi- nant modes of climate variability. In order to extract dominant modes of SST variability, EOFs of the cross- FIG. 2. National summary of Canadian summer (JJA) PDSI, 1940± covariance matrix are carried out on the winter averages. 2002. The line indicates the Canada-wide mean PDSI and the bars represent the spatial variability (standard deviation). 3. Methods and results Summary statistics of the Canadian summer PDSI tends to be the same if the correlation between the am- data were extracted to enable ranking of national mois- plitude time series of the given mode is high and sig- ture conditions, and also to determine the years of ex- ni®cant. In this study, we will focus on the heteroge- treme moisture conditions and relate them to current neous correlation patterns between the PDSI and global global SSTs anomaly patterns. Large-scale relationships SSTs. The SVD method is similar to canonical corre- between winter patterns of global SSTs and the follow- lation analysis (CCA) where two sets of orthogonal time ing summer drought patterns in Canada are analyzed series are produced, along with their corresponding spa- for the 63-yr period of 1940±2002 by SVD analysis tial patterns. CCA aims to maximize correlation between (also known as maximum covariance analysis in the variables, while SVD aims to maximize covariance be- climate literature; von Storch and Zwiers 1999). tween variables. Barnston and Smith (1996) provide an The SVD method aims to relate the two ®elds by in-depth analysis of CCA and its relation with SVD. decomposing their covariance matrix into singular val- ues and two sets of paired-orthogonal vectorsÐone for a. Extreme moisture conditions each ®eld. The covariance between the expansion co- ef®cients of the leading pattern in each ®eld is maxi- The time series of average summer PDSI for Canada mized. The singular values give the magnitude of the is shown in Fig. 2. Also shown is the standard deviation squared covariance fraction (SCF) as accounted for by of summer PDSI. Conditions were generally dry during the various singular values (Bretherton et al. 1992; Wal- the 1940s and 1950s, wet during the 1960s to the mid- lace et al. 1992). The square of any singular value be- 1990s, and dry again since that time. The driest years tween two ®elds for a given mode is indicative of the occurred in the 1940s and since 1995. Although there fraction of the total squared covariance accounted for is a tendency toward drier conditions since the 1970s, by that mode. The between the two two of the wettest years on record are 1992 and 1996. ®elds is discerned by the spatial patterns of the hetero- This highlights the existence of strong interannual var- geneous correlation, which is de®ned as the serial cor- iability in the last 13 yr compared to the previous years. relation between the expansion coef®cients of one ®eld There is no evidence of changes in the spatial variability and the grid point anomaly values of the other ®eld (standard deviation) of PDSI over the period of record. r[PDSIk(t), SSTi(t)] and r[SSTk(t), PDSIi(t)], where k Figures 3a and 3b show the composite PDSI patterns and i refer to the mode and grid number, respectively. for the ®ve driest and the ®ve wettest Canadian summers The heterogeneous correlation patterns for the nth mode since 1950, as derived from Fig. 2. The dry composite in the SVD expansion indicate how well the pattern of identi®es generally dry conditions across Canada with anomalies in the PDSI (SST) ®eld can be speci®ed on extremely dry conditions in the central areas of the three the basis of the nth expansion coef®cient of the SST Prairie provinces. The wet composite identi®es extreme- (PDSI) ®eld. In the spatial domain, the loading maps ly wet conditions in most regions of Canada, although for a given ®eld are mutually orthogonal. Heterogeneous there are areas in southern British Columbia and on the correlation patterns for the ®rst three modes in the direct Paci®c coast that show somewhat drier conditions. The SVD expansion are analyzed for statistical evidence of extremes of moisture have a strong tendency to be clus- teleconnections between the two ®elds. The homoge- tered over a span of successive years, for example, neous correlation pattern indicates that the spatial pat- 1972±75 (wet), and 1987±89 and 1998±2002 (both dry), tern of the variations are associated with the time series which is suggestive of larger-scale forcings on similar of the mode in the same ®eld. The structure of both temporal scales (Zhang et al. 1997; Nigam et al. 1999; heterogeneous and homogeneous correlation patterns Rajagopalan et al. 2000).

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FIG. 4. (a) Global winter (DJF) SST anomaly composite for the FIG. 3. (a) Composite Canada PDSI map for the ®ve driest summers ®ve driest Canadian summers (JJA). (b) Same as (a), but for the ®ve (JJA) 1940±2002. The ®ve driest summers in descending order are wettest Canadian summers (JJA). Thick-black dashed line delineates 2002, 1941, 1998, 1961, and 1940. (b) Composite Canada PDSI map regions where the values are signi®cant at the 5% level. for the ®ve wettest summers (JJA) 1940±2002. The ®ve wettest sum- mers in ascending order are 1992, 1996, 1947, 1974, and 1972. terns in determining seasonal extreme moisture condi- Composites of previous winter SST anomaly patterns tions over Canada. In this study, these teleconnections are shown in Figs. 4a and 4b, corresponding to Canadian are explored using the SVD analysis. summers as identi®ed in Figs. 3a and 3b, respectively. Dry conditions in Canada coincide with warmer-than- b. SVD analysis of Canadian drought data and normal SSTs in the equatorial eastern Paci®c, along the global SST data North American west coast, and in the North Atlantic. Previous winter SST anomalies along the equatorial Pa- Prior to the SVD analysis, the dimensionality of ci®c are warmer than normal, indicative of the warm drought and SST datasets was reduced by the EOF anal- phase of ENSO. The warm SST anomalies in the North ysis. The ®rst 10 EOF modes of the summer drought Atlantic resemble the AMO pattern. Dashed lines de- and winter SST were chosen as input into the SVD lineate regions where the composite values are statis- procedure. These 10 EOFs capture just over 70% of the tically signi®cant at the 5% level. Wet summer condi- total variance in their respective datasets. Most of the tions in Canada coincide with colder-than-normal SSTs variance, however, is concentrated in the ®rst three in the previous winter, in the central equatorial Paci®c, EOFs, with 41.2% of the total variability for summer and along the North American west coast, indicative of drought and 43.7% of the total variability for winter the cold phase of ENSO. Present also in the North Pa- SST. ci®c is the SST pattern resembling the North Paci®c The SVD analysis is used to identify and compare mode as identi®ed by Deser and Blackmon (1995), or the coupled modes of variability in the PDSI and SST the ENSO-like interdecadal variability mode (Zhang et anomaly data. A similar technique has been used by al. 1997). Previous winter global SST anomaly patterns Wallace et al. (1992) and Iwasaka and Wallace (1995) are distinctly different prior to Canadian summers with to identify large-scale relationships between SST and extreme wet or dry conditions. Regions with values sta- 500-hPa height anomalies and heat ¯ux and atmospheric tistically different from zero at the 5% level are shown circulation, respectively. A mathematical description of by dashed lines. These SST composites suggest the in- SVD analysis can be found in Iwasaka and Wallace ¯uences of large-scale global ocean teleconnection pat- (1995). SVD methodology always gives a mathematical

Unauthenticated | Downloaded 09/25/21 04:31 PM UTC 2872 JOURNAL OF CLIMATE VOLUME 17 solution, and it is recognized that there is a chance that mining the underlying oceanic variability on an inter- the resulting pair of coupled patterns may be nothing annual time scale has been shown in a number of studies more than a mathematical artifact (Cherry 1997; New- (e.g., Czaja and Marshall 2001; Hurrell 1996). While man and Sardeshmukh 1995). The geophysical inter- examining variability of the 500-hPa geopotential pretation of the coupled patterns, however, can be aided heights in the western Atlantic, Shabbar et al. (1997b) by comparison of the results from the principal com- found a similar change in their Baf®n±west Atlantic ponents analysis (PCA), where the time expansion of circulation index in the early 1970s. summer PDSI EOFs are correlated with the winter Figure 6b exhibits the spatial pattern associated with anomaly ®eld of the SSTs and vice versa. S 2(SST) (16.3% of the total variance). It identi®es strong loadings in the tropical Paci®c Ocean, with a weaker center in the North Paci®c. Zhang et al. (1997) c. SVD pattern of Canadian summer drought found a similar mode while examining wintertime var- Figure 5a shows that the spatial pattern associated iability in the high-pass (interannual) ®ltered SSTs. De- with S1(PDSI), explaining 12.7% of the total variance ser and Blackmon (1995) also report an interannual of Canadian PDSI, has a northwest±southeast dipole in ENSO pattern as their leading mode of Paci®c basin western and central Canada, with opposing extreme con- SSTs, with a similar structure as the one shown in Fig. ditions over the southern Prairie provinces and north- 6b. The accompanying time series shows extremes in western Canada. There is a third, albeit weaker, center ENSO years. Warm El NinÄo (positive) and cold La NinÄa located over the lower Great Lakes. The time series for (negative) ENSO events are also identi®ed. The time

S1(PDSI) shows both interannual and decadal variability series exhibits interannual variability with a long-term with a positive trend. change toward higher values in 1976±77. The relative Figure 5b shows the spatial pattern associated with warmth of the tropical Paci®c since 1976, as noted by

S 2(PDSI) (12.0% of the total variance), identifying a Trenberth and Hurrell (1994) and Lau and Nath (1994), gradient to more severe conditions in western and cen- is re¯ected in the S 2(SST) time series. tral Canada, centered on the southern Prairie provinces. The spatial pattern associated with S3(SST) (12.5% The time series for S 2(PDSI) shows a decreasing trend of the total variance) is shown in Fig. 6c. The extra- until the mid-1970s, followed by an abrupt increase to- tropical SST ¯uctuations in the central North Paci®c, ward higher values starting in 1976±77. It will be shown resembling the coupled ocean±atmosphere mode known that this mode of the PDSI has its origin in the ENSO as the Paci®c decadal oscillation (PDO; Mantua et al. phenomenon. 1997), are prominent in this mode. This mode also in- Figure 5c shows that the spatial pattern associated cludes a component of the interannual variability as re- with S3(PDSI) (8.8% of the total variance) has strong ¯ected by a broader and weaker center in the eastern positive loadings in western and northwestern Canada tropical Paci®c. Compared to S 2 (Fig. 6b), the tropical and negative loadings in northeastern Canada. Addi- loadings in S3 (Fig. 6c) are located considerably further tionally, there is a weak positive center over the south- west, just east of the international date line. Deser and eastern portions of the Prairie provinces. The time series Blackmon (1995) identify this pattern in the Paci®c ba- for S3(PDSI) shows little evidence of trend but consid- sin SSTs as their second EOF. This pattern also bears a erable interannual variability prior to 1960 and after striking resemblance to the low-pass (interdecadal) ®l- 1990 with extreme conditions in the early 1990s. tered SSTs in the Paci®c basin as identi®ed by Zhang et al. (1997). The time series associated with this mode also identi®es some warm (negative) and cold (positive) d. SVD pattern of global SST years of the ENSO phenomenon. Additionally, a change

The spatial pattern associated with S1(SST), explain- point in the time series is also evident corresponding to ing 10.6% of the total variance of global winter SST the 1976±77 regime change. This shift is re¯ective of variability, is shown in Fig. 6a. It identi®es the warming the climate shift in the mean sea level pressure in the trend signal in the SSTs with strong positive loadings North Paci®c as identi®ed by Trenberth and Paolino throughout the southern oceans. A similar SST loading (1981). pattern has been reported by Smith and Reynolds The two series S 2(SST) and S3(SST) are correlated (2003). In their second rotated EOFs of the global SSTs, with one another at a modest level (r ϭϪ0.56, where they obtained a similar SST pattern, and identi®ed it as r denotes the correlation coef®cient). The differences in the trend mode. The AMO pattern with negative load- the North Paci®c features between these two patterns ings in the North Atlantic is also clearly evident. The have profound implications on the PDSI pattern in west- accompanying time series shows considerable interan- ern Canada. Whereas the strong positive loadings in the nual variability with a strong positive trend, as well as North Paci®c have a northeast±southwest orientation at an apparent shift toward higher values circa the early 30ЊNinS3, the concomitant negative and weaker load- 1970s. This sharp change in the time coef®cient is likely ing center is located north of 30ЊNinS 2. These changes associated with the variability of the AMO. The role of in the SSTs are associated with rather distinct midtro- the atmosphere in the North Atlantic sector in deter- pospheric circulation patterns. The difference in the

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FIG. 5. (a) The ®rst SVD pattern (S1) of PDSI and standardized amplitude based on data for 63 summer (JJA) seasons 1940±2002. (b)

Same as (a) except for the second SVD pattern (S2) of PDSI. (c) Same as (a) except for the third SVD pattern (S3) of PDSI.

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FIG. 6. (a) The ®rst SVD pattern (S1) of SST and standardized amplitude based on data for 63 winter (DJF) seasons 1940±2002. (b) Same

as (a) except for the second SVD pattern (S2) of SST. (c) Same as (a) except for the third SVD pattern (S3)ofSST. composites of 500-hPa geopotential heights between the lands. These circulation changes have strong impacts positive and negative phases of S3 has a very strong on the temperature and moisture regimes over the west anomaly center in the central North Paci®c (not shown). coastal areas of Canada. The stronger S3(SST) in the The same composite difference for S 2 shows a weaker central North Paci®c leads to higher PDSI over British North Paci®c center northward over the Aleutian Is- Columbia and the southern Yukon (cf. Figs. 5b and 5c).

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TABLE 2. Summary statistics of SVD analysis for Canadian variations of the mode in the two ®elds. It is a measure drought (PDSI) data and global SST anomaly data, 1940±2002. of the similarity between the time variations of the pat- Mode Correlation Variance (%) Variance (%) terns of the two ®elds, or how strongly the two ®elds (k) SCF (%) coef®cient (Drought) (SST) NCF (%) are related to each other. The values remain near 0.5 1 32.43 0.59 12.72 10.59 6.84 (signi®cant at the 5% level) for the ®rst ®ve modes. The 2 27.99 0.46 11.96 16.25 6.36 third statistic, the normalized root-mean-squared co- 3 20.14 0.51 8.79 12.51 5.39 variance (NCFk), is the ratio of the squared singular 4 7.69 0.50 8.66 5.17 3.33 value of the mode to the greatest possible total squared 5 6.24 0.57 6.12 4.59 3.00 covariance of the matrix. It is a measure of the absolute importance of the SVD mode in the relationship between the two ®elds. Nearly 19% of NCF is concentrated in The mathematics of SVD separates the Paci®c Ocean the ®rst three modes of the SVD expansion. In the ®rst processes of ENSO and the interdecadal PDO as two three modes, the values are about equally distributed separate modes. Together, these processes account for and drop off in higher modes, again emphasizing the nearly 50% of the squared covariance fraction, thus, importance of these modes in relation to higher modes. making ENSO and the ENSO-like interdecadal vari- While examining relationships between surface heat ¯ux ability in the Paci®c basin the most signi®cant factors over the North Paci®c and 500-hPa geopotential heights in explaining the summer moisture variability over Can- and SSTs, Iwasaka and Wallace (1995) found that the ada. signi®cant NCFs were in the range of 8%±14%. In order to discern geophysical relevancy of the SVD- The robustness of these results is established by the coupled patterns, Cherry (1997) suggests a comparison Monte Carlo technique, as suggested by Barnett and of the SVD results with those from the PCA analysis. Preisendorfer (1987). Test results on 1000 Monte Carlo When the leading three principal components (PCs) of SVD expansions, in which the time coef®cient of the summer PDSI are correlated with the previous winter PDSI series is randomly shuf¯ed, show that the rk and global SST anomalies, the salient features of Fig. 6, NCFk statistics in all three modes of the PDSI and global namely the ENSO-related SST pattern in the Paci®c SST anomaly data are statistically signi®cant at the 5% basin, the warming of the southern oceans and the mul- level. The (rk) 5% signi®cance level for r1 ϭ 0.45, tidecadal AMO dipole in the Atlantic basin, are all re- r2 ϭ 0.38, and r3 ϭ 0.33. The NCFk 5% signi®cance covered (not shown). To highlight the separability of S 2 level for NCF1 ϭ 4.66, NCF2 ϭ 3.40, and NCF3 ϭ 2.66 and S3 modes, the correlation between the Paci®c basin (see Table 2 for comparison with the actual values). SSTs and the individual PCs of the PDSI was calculated. The heterogeneous correlation patterns show how the The results show the interannual ENSO and the inter- two ®elds are related to one another and how much of decadal PDO variability as two separate entities (not the amplitude of the variations is explained by the SVD shown). This comparison lends credence to the dynam- mode. Figure 7 shows the heterogeneous correlation pat- ical signi®cance of the SVD-coupled patterns found in terns for each of the ®rst three modes in the SVD ex- this study. The statistical signi®cance of the coupled pansion for winter global SST anomaly data and for the patterns will be shown below. following Canadian summer drought (PDSI) data from 1940 to 2002. Each map represents the correlation be- e. Teleconnection between Canadian drought and tween the expansion coef®cients of one ®eld and the global SST patterns grid point anomaly values of the other ®eld. The het- erogeneous pattern for the ®rst SVD mode (Fig. 7a) has Table 2 provides the three main summary statistics two prominent features. The primary characteristic is of the SVD analysis. These statistics provide a measure the warming of the southern oceans as indicated by the of the strength of the relationship between the two ®elds. positive loadings, mainly south of the equator. Secondly, The ®rst statistic, the squared covariance fraction the North Atlantic center of action is indicative of cool-

(SCFk), where k is the mode number, provides the per- ing. In their rotated EOF analysis, Smith and Reynolds centage of the total squared covariance between the two (2003) have also identi®ed this mode as the trend mode. ®elds explained by the SVD mode, and is proportional In the next section, the North Atlantic feature will be to the square of its singular value. This is a measure of related to the in¯uences of the AMO. The accompanying the relative importance of the SVD mode in the rela- PDSI pattern shows a de®cit in the PDSI in an area tionship between the two ®elds. It is clear from Table stretching from the southern Canadian prairies to central 2 that the squared covariance is concentrated in the ®rst Quebec. While examining the summer precipitation three modes (approximately 80% of the squared co- trend during the second half of the twentieth century, variance). Thereafter, the squared covariance statistic Zhang et al. (2000) also found a tendency toward drying drops off sharply, thus, signifying the importance of the throughout the same region. In the following section, it ®rst three modes in determining PDSI variability. The will be shown that the centers over northwestern Canada second statistic is the correlation coef®cient (rk) be- and over the lower Great Lakes and the St. Lawrence tween the two time series that represent the temporal valley are more closely related to the variability in the

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FIG. 7. (a) Heterogeneous correlation patterns for the ®rst mode in the direct SVD expansion. The temporal correlation coef®cient between the corresponding expansion coef®cients r(PDSIk SSTk), where k refers to the mode number, and the SCF (%) are shown. (b) Same as (a), but for the second mode. (c) Same as (a), but for the third mode.

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AMO. Statistics calculated in Table 2 mark this mode as the most important singular mode in the relationship between the two ®elds. The heterogeneous pattern for the second SVD mode (Fig. 7b) has its origin mainly in the interannual ENSO mode as identi®ed by Zhang et al. (1997) and Deser and Blackmon (1995). This mode shows that the warm phase of ENSO leads to a de®cit in summer PDSI over western and central Canada. The center is particularly strong over southwestern British Columbia and over the central Prairie provinces. The heterogeneous pattern for the third SVD mode (Fig. 7c) mainly reveals the ENSO-like interdecadal var- iability in the North Paci®c, with an indication of a weaker and more diffuse ENSO variability in the equa- torial Paci®c. As noted earlier, the structure of this mode relates more to the interdecadal variability in the central North Paci®c (see Fig. 6c), where the center is stronger and shifted southwestward, compared to the center shown in Fig. 7b. The resulting atmospheric circulation from this pattern is conducive to producing a stronger center of circulation over the North American west coast, which leads to an excessive moisture regime over western Canada. In this con®guration, the subtropical jet stream brings moisture-bearing storms to the west coast of Canada. This mode shows that the negative phase of the PDO, along with the cold phase of the interannual ENSO, leads to higher PDSI values in sum- FIG. 8. Heterogeneous correlation patterns for the ®rst mode in the mer over western Canada and over the southeastern ar- direct SVD expansion using Atlantic SSTs. The temporal correlation eas of the Prairie provinces. coef®cient between the corresponding expansion coef®cients r(PDSIk, SSTk), where k refers to the mode number, and the SCF (%) are shown. 4. Summary and discussion Recently, Hoerling and Kumar (2003) have linked the mer drought PDSI data from 1940 to 2002. The het- droughts that occurred from 1998 to 2002 in certain erogeneous patterns for this SVD mode retain the fea- areas of the midlatitudes to common global oceanic in- tures identi®ed in the global SST analysis in Fig. 7a. ¯uences. In particular, observation and modeling results The primary feature of the SST pattern is the strong relate the cold ENSO-like conditions to drought in the center of negative loadings in the North Atlantic. This southwestern United States, Europe, and southwest pattern is similar to the AMO pattern of variability ob- Asia. A long-time-scale oceanic phenomenon referred tained by Mestas-NunÄez and En®eld (1999). The com- to as the AMO, the ®rst rotated EOF of Atlantic SSTs, plementary drought map exhibits strong positive centers has been found with a 65±80-yr time scale (En®eld et over northwestern Canada and over the lower Great al. 2001). The signal is most intense in the North At- Lakes and the St. Lawrence valley, and a weak negative lantic, but is global in scope, with a positively correlated center over the extreme southeastern Prairies. This pat- co-oscillation in the North Paci®c. An AMO warm tern is very similar to the drought pattern shown in Fig. phase occurred from 1940 to 1960 with less-than-normal 7a. Thus, the ®rst SVD mode (Fig. 5a) and the hetero- rainfall in the continental United States, and a cool phase geneous correlation (Fig. 7a) of the Canadian PDSI are occurred from 1970 to 1990 with greater-than-normal re¯ective of both the warming trend in the global south- rainfall in the continental United States. In this study, ern oceans and the in¯uences of the AMO variability. coupled modes between the winter global SSTs and the The percentage of SCF, as explained by the ®rst mode following summer PDSI are documented for Canada. It between the winter Atlantic SSTs and the following is found that the interannual and interdecadal variability summer PDSI, is over 56%. The correlation coef®cient in the Paci®c basin, as well as the multidecadal vari- between their expansion coef®cients is 0.63, and over ability (AMO), play a prominent role in affecting sum- 10% of the NCF, is concentrated in the ®rst mode of mer drought conditions. the SVD expansion. All three statistics are signi®cant Figure 8 shows the heterogeneous correlation patterns at the 5% level, indicating the presence of a strong cou- for the ®rst mode in the SVD expansion for winter At- pled mode. lantic SST anomaly data and following Canadian sum- Figure 9a provides further corroborating evidence

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FIG. 9. (a) Winter (DJF) AMO and winter S1 (SST) Atlantic, 1940± 2002. (b) Correlation pattern between the winter (DJF) AMO and the following summer (JJA) PDSI. (c) Difference ®eld between the pos- itive and negative PDSI composites taken from the standardized am-

plitude for S1 (SST). Regions of Canada with signi®cant correlation and differences at the 5% level are shown by dashed lines.

concerning the AMO structure inherent in the Atlantic relation drought pattern for the ®rst mode in the direct sector S1 (Fig. 8). Plotted on this chart are the AMO SVD expansion SSTs (Fig. 7a). Further evidence of this index and the time coef®cient of the Atlantic S1 pattern. relationship is provided in Fig. 9c, which shows the The two time series track each other fairly well with a difference ®eld between the positive and negative com- correlation of 0.57, which is signi®cant at the 5% level. posites taken from the standardized amplitude for S1 The AMO warm phase from the 1950s to early 1960s (SST) Atlantic (Fig. 8). The emerging pattern strongly is associated with dry conditions (see Fig. 2), while the resembles that shown in Figs. 7a and 9b. Regions of cool phase from the 1960s to the 1990s is related to Canada possessing statistically signi®cant values at the wet conditions (see Fig. 2). Finally, the return to a warm 5% level are outlined by dashed lines. AMO phase in the late 1990s is linked with drier con- In summary, this study has determined the spatial ditions. En®eld et al. (2001) also found a negative cor- patterns of summer moisture availability in Canada as relation between the AMO time series and the Climate represented by the PDSI, and identi®ed the source of Division rainfall over the northeastern United States. variability in global SSTs in the preceding winter The negative correlations over the lower Great Lakes months. Large-scale relationships between summer and the St. Lawrence valley with the AMO index (Fig. PDSI patterns in Canada and previous winter global SST 8) could be regarded as the northward extension of their patterns are then analyzed using SVD analysis. The re- results. sulting coupled patterns provide insight into the tele- Figure 9b shows the correlation pattern between the connection patterns between Canadian drought and winter AMO index and following summer PDSI at each global SSTs. Canadian grid location. The effect of AMO is seen most The leading three SVD modes of Canadian summer clearly in the three Prairie provinces, along the west drought and global SST explain over 80% of the squared coast, and the lower Great Lakes region of southern covariance fraction between the two ®elds. The ®rst ®eld Ontario and central Quebec, with the most robust impact is a mixture of global SST trend and variability in the evident over the northern Prairie provinces. Signi®cant Atlantic Ocean. This mode accounts for approximately negative correlation seen along the west coast of Canada one-third of the squared covariance. It identi®es a mul- likely re¯ects the positively correlated co-oscillation in tidecadal scale variation strongly related to summer North Paci®c with the AMO, as suggested by En®eld drought conditions in southeastern and northwestern et al. (2001). The correlation pattern in eastern Canada Canada, as well as a trend component related to southern is quite similar to that found in the heterogeneous cor- global ocean variability throughout central Canada. The

Unauthenticated | Downloaded 09/25/21 04:31 PM UTC 15 JULY 2004 SHABBAR AND SKINNER 2879 time series of the winter AMO is correlated with the schemes for the occurrence of drought in Canada. This following summer PDSI grid, and the resulting pattern predictability may be further enhanced by the inclusion reproduces the heterogeneous correlation pattern for the of direct measurements of snow cover as well as re- ®rst mode in the direct SVD expansion. gional information, such as soil type and characteristics The second and third ®elds are related to Paci®c and vegetation, that provide additional information in- Ocean processes and the interrelationship between dependent of large-scale SSTs. ENSO and the PDO. Together these two modes explain over 48% of the squared covariance, thus, marking in- Acknowledgments. The reconstructed global SSTs terannual ENSO phenomenon and ENSO-related inter- were kindly provided by Tom Smith of the National decadal (PDO) variability as the most signi®cant pro- Climatic Data Center of NOAA. Constructive comments cesses in drought variability. Whereas Hoerling and Ku- from two anonymous reviewers and the editor are great- mar (2003) link the cold ENSO-like conditions to recent ly appreciated. droughts in the midlatitude regions of the Northern Hemisphere, the results of this study show that the warm phase of ENSO leads to droughts in the grain-growing REFERENCES areas of Canada. Speci®cally, the warm phase of ENSO leads to a de®cit in summer PDSI over the western two- Alley, W. H., 1984: The Palmer Drought Severity Index: Limitations thirds of Canada. Conversely, the cold phase produces and assumptions. J. Climate Appl. Meteor., 23, 1100±1109. Barnett, T. P., and R. 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