atmosphere

Article Spatiotemporal Variations of Precipitation in China Using Surface Gauge Observations from 1961 to 2016

Yunfei Su 1, Chuanfeng Zhao 1,2,*, Yuan Wang 2 and Zhanshan Ma 1,3

1 State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; [email protected] (Y.S.); [email protected] (Z.M.) 2 Division of Geology and Planetary Science, California Institute of Technology, Pasadena, CA 91125, USA; [email protected] 3 Numerical Weather Prediction Center of China Meteorological Administration, Beijing 100081, China * Correspondence: [email protected]; Tel.: +86-010-5880-2171



Received: 16 February 2020; Accepted: 18 March 2020; Published: 20 March 2020


Abstract: Long-term precipitation trend is a good indicator of climate and hydrological change. The data from 635 ground stations are used to quantify the temporal trends of precipitation with different intensity in China from 1961 to 2016. These sites are roughly uniformly distributed in the east or west regions of China, while fewer sites exist in the western region. The result shows that precipitation with a rate of <10 mm/day dominates in China, with a fraction of >70%. With a 95% confidence level, there is no significant temporal change of annually averaged precipitation in the whole of China. Seasonally, there are no significant temporal changes except for a robust decreasing trend in autumn. Spatially, significant differences in the temporal trends of precipitation are found among various regions. The increasing trend is the largest in Northwest China, and the decreasing trend is the largest in North China. The annually averaged number of precipitation days shows a decreasing trend in all regions except for Northwest China. Regarding precipitation type, the number of light precipitation days shows a robust decreasing trend for almost all regions, while other types show no significant change. Considering the high frequency, the temporal trends of light precipitation could highly explain the temporal variation of the total precipitation amount in China.

Keywords: precipitation amount; precipitation days; temporal variation; light precipitation; heavy precipitation; China

1. Introduction Precipitation is a critical component in the hydrologic cycle and ecology system on both global and regional scales [1–5]. It also plays an essential role in the energy transport by storing or releasing latent heat in the climate system [6,7]. Therefore, characterizing the spatial distribution and temporal trends of precipitation is crucial both for improving the physical understanding of regional climate dynamics and for evaluating weather and climate models. Ultimately, it can help manage water for agriculture and deal with flood crisis, especially for a country with frequent drought and flooding such as China. Various factors could affect the temporal and spatial patterns of precipitation on regional and global scales, including the natural variabilities, such as El-Nino/Southern Oscillation [8], the soil moisture [9], the surface temperature [2,10,11], and the aerosols [12–18]. As indicated by [2], when climate changes, there are changes in precipitation in the intensity, frequency, and duration. In China, whether precipitation trends are driven by greenhouse gases or anthropogenic aerosols has been under debate for a while. Qian et al. [19] analyzed the surface precipitation data and suggested that increasing

Atmosphere 2020, 11, 303; doi:10.3390/atmos11030303 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, 303 2 of 17 aerosols could result in a decreasing trend of light and middle precipitation by serving as cloud condensation nuclei (CCN). Such a hypothesis about the microphysical aerosol effect on precipitation in China was corroborated by the climatic simulations using a state-of-the-art global climate model [20]. Thus, it is important to examine the precipitation variation from an observational perspective. Long-term precipitation datasets have been obtained from different sources. The rain gauge measurements, ground and satellite remote sensing observations, and model outputs have generally been used for the analysis of precipitation [7,21–24]. As indicated by [23], there are non-negligible random errors and biases in the satellite precipitation retrievals because of the indirect nature of the relationship between the observation signal and the precipitation, the inadequate sampling, and algorithm imperfections. By contrast, rain gauges give relatively accurate point measurements, while suffering from sample volume, particularly over ocean and mountain regions. Using the rain gauge observations, several studies have been carried out to obtain the precipitation characteristics in China [25–30], particularly regarding the extreme precipitation events. Liu et al. [26] described the spatial and temporal variation of precipitation observed daily at 272 weather stations operated by the China Meteorological Administration (CMA) from 1960 to 2000. They found that precipitation in China increased by 2% over that period, while the frequency of precipitation events decreased by 10%. Zhang et al. [29] examined the spatial and temporal variation of precipitation over China using 160 stations from 1951 to 2005. It showed that precipitation in China is uneven in space and time, and its complex temporal structure and spatial variations are different in each season. Chen et al. [31] carried out spatial interpolation to daily precipitation in China to get gridded precipitation from 1951 to 2005. Miao et al. [27] investigated the temporospatial features of hourly precipitation during the warm season over mainland China from 1991 to 2012 and revealed the basic information about the variation of the frequency, intensity, and total amount of precipitation. Zhou and Wang [30] showed the sensitivity of precipitation to long-term warming and found a high sensitivity for the weak precipitation days. While these studies provide basic information about the characteristics of precipitation over China, the change in the number of precipitation days has rarely been investigated. Moreover, the characteristics of precipitation found by previous studies are not always consistent. Furthermore, the station sites that are used are limited and uneven in either East China or West China, and the study period is also limited without accounting for the precipitation after 2010 for most studies. Here, we choose the ground rain gauge stations with the longer precipitation records and roughly uniform spatial distribution to carry out a comprehensive analysis about the temporal trends of relative changes of both precipitation amount and precipitation days over different regions during a long time period from 1961 to 2016. The number of rain gauge network stations adopted in this study reaches 635, which is more than most of the previous studies and with a more uniform spatial distribution. The temporal variation of annually and seasonally averaged precipitation for precipitation amount and for precipitation days with different rain intensity over five classified regions will be analyzed. This can provide more information about the statistical characteristics of different types of precipitation in China, which can help understand the change of atmospheric processes. The paper is organized as follows. Section2 describes the data and methods. Section3 shows the data analysis and results. And Section4 provides the summary and discussion.

2. Data and Method

2.1. Weather Station and Data Daily precipitation data were obtained from 2472 stations from the Chinese National Meteorological Center from January 1961 to February 2016 [32]. Considering that the number of observational stations in service has changed with time and there are partial stations with many missing data, we have made two criteria to select the data and observation stations. First, when there are continuously missing data for more than one year from 1961 to 2016 at a station, the observations from that station will not be used. Second, we divide the whole region in China into 1 1 grids and only adopt the station ◦ × ◦ Atmosphere 2020, 11, 303 3 of 17 Atmosphere 2020, 11, x FOR PEER REVIEW 3 of 16 onlywith adopt the least the missing station datawith tothe use least in every missing grid. data With to theseuse in two every criteria, grid. we With roughly these maketwo criteria, the stations we roughlyused in thismake study the stations uniformly used distributed in this study in space uniformly in eastern distributed or western in space China. in By eastern applying or western the two China.criteria, By we applying finally obtained the two 635criteria, stations we finally in this study,obtained which 635 arestations shown in inthis Figure study,1. Consideringwhich are shown what inwe Figure use is daily1. Considering precipitation what data, we we use will is not daily interpolate precipitation the precipitation data, we will data not for theinterpolate time or grids the precipitationwith missing data data. for the time or grids with missing data.

FigureFigure 1. SpatialSpatial distribution distribution of 635of 635 ground ground weather weather stations stations used in thisused study in this and regionstudy classification.and region classification.Five regions haveFive beenregions classified, have been which classified, are Northwest which are China Northwest (NW), Tibetan China Plateau(NW), Tibetan (TP), Northeast Plateau (TP),China Northeast (NE), North China China (NE), (N), North and China South (N), China and (S). So Theuth China colors (S). represent The colors the groundrepresent altitude the ground above altitudesea level. above sea level.

2.2.2.2. Precipitation Precipitation Type Type and and Region Region Classification Classification TheThe daily daily precipitation precipitation data data at at all all stations stations could could be be classified classified into into six six types types according according to to the the precipitation intensity (P), which are no (P < 0.1 mm/day), light (0.1 mm/day P 1 mm/day), small precipitation intensity (P), which are no (P < 0.1 mm/day), light (0.1 mm/day ≤ P ≤≤1 mm/day), small (1 mm/day < P 10 mm/day), middle (10 mm/day < P 25 mm/day), heavy (25 mm/day < P 50 (1 mm/day < P ≤≤ 10 mm/day), middle (10 mm/day < P ≤≤ 25 mm/day), heavy (25 mm/day < P ≤≤ 50 mm/day),mm/day), and and severe (P >> 50 mmmm/day)/day) precipitations.precipitations. Note Note that that trace trace precipitation precipitation with with P lessP less than than 0.1 0.1mm mm/day/day and and fogs fogs have have been been defined defined as noas precipitation.no precipitation. The The last last four four types types of precipitations of precipitations are alsoare alsocalled called as e ffasective effective precipitation precipitation [33]. [33]. WeWe classify classify the the China China mainland mainland into into five five regions regions based based on on their their different different climate climate characteristics, characteristics, whichwhich are are Northwest Northwest China China (NW), (NW), Tibetan Tibetan Plateau Plateau (TP), (TP), Northeast Northeast China China (NE), (NE), North North China China (N), and (N), Southand South China China (S), as (S), indicated as indicated in Figure in Figure 1. The1. The NW NW belongs belongs to an to anarid arid and and semi-arid semi-arid region region with with a continentala continental temperature temperature monsoon monsoon clim climate.ate. It generally It generally has a has relatively a relatively large large area areaof dry of surface dry surface and smalland small amount amount of precipitation. of precipitation. The TP The belongs TP belongs to a plateau to a plateaumountain mountain region with region a mountain with a mountain climate. Itclimate. is generally It is generallywith strong with solar strong radiation, solar radiation, low temperatures, low temperatures, and large and diurnal large diurnalvariation variation of air temperature,of air temperature, along with along significant with significant uneven uneven spatial distribution spatial distribution of precipitation. of precipitation. The NE Theand NEN both and belongN both to belong the mid-latitude to the mid-latitude monsoon monsoon climate, climate, with withhigh high temperatures temperatures and and a large a large amount amount of of precipitationsprecipitations in in summer, summer, and and low low temperatures temperatures an andd a a small small amount amount of of precipitation precipitation in in winter. winter. The The annualannual precipitation precipitation amounts amounts in in NE NE and and N N are are both both about about 300–1000 300–1000 mm. mm. However, However, compared compared to to N, N, thethe temperature temperature over over NE NE is is lower lower with with a a larger larger se seasonalasonal variation. variation. The The S S belongs belongs to to a a subtropical subtropical monsoonmonsoon climate, climate, with with high high temperatures, temperatures, a a large large amount amount of of precipitations, precipitations, and and relatively relatively weak weak seasonalseasonal variations ofof atmosphericatmospheric status. status. A A similar simila regionr region classification classification has has been been adopted adopted in our in earlyour earlystudy study [34]. [34]. We will We analyzewill analyze the temporal the temporal trend tren of precipitationd of precipitation in each in region,each region, along along with thewith whole the wholeof China. of China.

2.3. Statistical Analysis Method A linear fitting regression analysis for the temporal trend of both time averaged precipitation amount and precipitation day number is adopted in our analysis, which is described as

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2.3. Statistical Analysis Method A linear fitting regression analysis for the temporal trend of both time averaged precipitation amount and precipitation day number is adopted in our analysis, which is described as

y = at + b (1) where y is the seasonally or yearly averaged precipitation amount or precipitation day number (precipitation days), and t is the time in unit of year, a is the regression coefficient, which denotes the linear trend, b is another regression coefficient, which represents the intercept of linear fitting. The statistical t-test method is used to examine whether the temporal trends of precipitation amount and precipitation days reach statistical significance at a confidence level of 95%. Considering the significant differences in precipitation amount and precipitation days among different regions, it is not meaningful to compare the temporal trend of precipitation among the different regions in absolute values. Instead, we focus on the temporal trend of relative changes of precipitation amount and the number of precipitation days for each region or station in units of %/10 years, which are defined as the ratio of temporal trends in absolute values to the averages of precipitation amount and precipitation days between 1961 and 2016.

3. Observation-Based Analysis and Results

3.1. Temporal Trends of Precipitation Amount We first analyze the temporal trends of precipitation amount at every station and region in China. Figure2 shows the temporal trends of relative changes in annual precipitation amount for all stations examined from 1961 to 2016. The blue solid circles indicate increasing precipitation amount, red open circles denote decreasing precipitation amount, and the large, middle, and small circles represent the stations with increasing (blue) or decreasing (red) precipitation amount > 10%/10 years, 10%/10 years–5%/10 years, and < 5%/10 years, respectively. For all significant temporal changes of precipitation amount with a confidence level of 95%, the stations have been indicated with an extra black ‘O’. Roughly, there are similar numbers for stations with increasing and decreasing trends of precipitation amount, which are 305 and 330 stations, respectively. However, for the stations with significant decadal trends of precipitation amount, the station number (55) with increasing trends is clearly larger than that (26) with decreasing trends. Figure2 also shows a clear spatial pattern regarding the temporal trends of precipitation amount. Particularly, there is a clear increasing trend of precipitation amount in the NW region, and a clear decreasing trend of precipitation amount in the boundary regions between TP and S, N. Figure3 further shows the temporal trends of annually averaged precipitation amount over the five regions we classified in Figure1. The temporal trends of seasonally averaged precipitation amount over the five regions have also been examined in this study. Table1 lists the values of temporal trends of both annually and seasonally averaged precipitation amount over the five regions. The bold values shown in Table1 indicate that they pass the significance test at a confidence level of 95%. Roughly, there are significant increases in precipitation amount in the summer of NW and S regions in the winter of NE and NW regions and in the spring of NE and TP; there are significant decreases in precipitation amount in the summer of TP and autumn of the whole country. Annually averaged, there is a weak (not significant) decreasing trend of precipitation amount in the whole of China, which is 0.11%/10 − years. By contrast, there is a strong decreasing trend of seasonally averaged precipitation amount in autumn ( 2.6%/10 years), which could contribute a lot to the weak decreasing trend of the annually − averaged precipitation amount in China. Consistent with the decreasing trend in China, there are decreasing trends of precipitation amount in N, NE, and TP, with values of 1.7, 0.3, and 0.88 %/10 − − − years, respectively. Differently, there is a weak increasing trend in S with a value of 0.32%/10 years, but a strong increasing trend in NW with a value of 4.4%/10 years. Note that a previous study [26] found Atmosphere 2020, 11, x FOR PEER REVIEW 4 of 16

+= baty (1)

where y is the seasonally or yearly averaged precipitation amount or precipitation day number (precipitation days), and t is the time in unit of year, a is the regression coefficient, which denotes the linear trend, b is another regression coefficient, which represents the intercept of linear fitting. The statistical t-test method is used to examine whether the temporal trends of precipitation amount and precipitation days reach statistical significance at a confidence level of 95%. Considering the significant differences in precipitation amount and precipitation days among different regions, it is not meaningful to compare the temporal trend of precipitation among the different regions in absolute values. Instead, we focus on the temporal trend of relative changes of precipitation amount and the number of precipitation days for each region or station in units of %/10 years, which are defined as the ratio of temporal trends in absolute values to the averages of precipitation amount and precipitation days between 1961 and 2016.

3. Observation-Based Analysis and Results

3.1. Temporal Trends of Precipitation Amount We first analyze the temporal trends of precipitation amount at every station and region in China. Figure 2 shows the temporal trends of relative changes in annual precipitation amount for all stations examined from 1961 to 2016. The blue solid circles indicate increasing precipitation amount, Atmospherered2020 open, 11, 303circles denote decreasing precipitation amount, and the large, middle, and small circles 5 of 17 represent the stations with increasing (blue) or decreasing (red) precipitation amount > 10%/10 years, 10%/10 years–5%/10 years, and < 5%/10 years, respectively. For all significant temporal changes of that precipitationprecipitation in amount China increasedwith a confidence by 2% level from of 1960 95% to, the 2000 stations with have an increasing been indicated rate with of ~0.5% an extra/10 years, differentblack from ‘Ο the’. Roughly, weak decreasing there are similar trend numbers ( 0.11% for/10 statio years)ns foundwith increasing in this study. and decreasing The diff erencetrends of could be − partly relatedprecipita totion the amount, different which study are periods 305 and and 330 observationstations, respectively. stations However, used. Another for the studystations [ 29with] showed Atmosphereunclear temporalsignificant 2020, 11, x decadal variationFOR PEER trends REVIEW of precipitation of precipitation amount amount, overthe station the whole number of (55) China with from increasing 1951 trends to 2005, is while5 of 16 they alsoclearly showed larger the than decreasing that (26) trendswith decreasing of precipitation trends. amountFigure 2 inalso N shows and NE a clear and spatial increasing pattern trends of amount regardingover the thefive temporal regions trends have ofalso precipitation been exam amouinednt. in Particularly, this study. there Table is a 1 clear lists increasing the values of precipitationtrend amount in NW. temporal trends of both annually and seasonally averaged precipitation amount over the five regions. The bold values shown in Table 1 indicate that they pass the significance test at a confidence level of 95%. Roughly, there are significant increases in precipitation amount in the summer of NW and S regions in the winter of NE and NW regions and in the spring of NE and TP; there are significant decreases in precipitation amount in the summer of TP and autumn of the whole country. Annually averaged, there is a weak (not significant) decreasing trend of precipitation amount in the whole of China, which is −0.11%/10 years. By contrast, there is a strong decreasing trend of seasonally averaged precipitation amount in autumn (−2.6%/10 years), which could contribute a lot to the weak decreasing trend of the annually averaged precipitation amount in China. Consistent with the decreasing trend in China, there are decreasing trends of precipitation amount in N, NE, and TP, with values of −1.7, −0.3, and −0.88 %/10 years, respectively. Differently, there is a weak increasing trend in S with a value of 0.32%/10 years, but a strong increasing trend in NW with a value of 4.4%/10 years. Note that a previous study [26] found that precipitation in China increased by 2% from 1960 to 2000 with an increasing rate of ~0.5%/10 years, different from the weak decreasing trend (−0.11%/10 years) found in this study. The difference could be partly related to the different study periods and observation stationsFigure used. 2.FigureThe Another decadal2. The decadal study trend trend [29] of the of showed the relative relative changeunclear change ofof temporal annually averaged averagedvariation precipitation precipitation of precipitation for all for examined all examinedamount over 635 ground stations from 1961 to 2016. the whole635 ground of China stations from from 1951 1961 to to2005, 2016. while they also showed the decreasing trends of precipitation amount in NFigure and NE 3 further and increasingshows the temporal trends trendsof precipitation of annually averagedamount precipitationin NW. amount over the five regions we classified in Figure 1. The temporal trends of seasonally averaged precipitation

Figure 3. TheThe temporal temporal trend trend of of annually annually averaged averaged prec precipitationipitation amount amount for for the the whole whole area area over the 55 classified classified regions of of ( a)) Northeast Northeast China China (NE), (NE), ( (bb)) Northwest Northwest China China (NW), (NW), ( (cc)) South South China China (S), (S), ( (dd)) North China China (N), (N), and and ( (ee)) Tibetan Tibetan Plateau Plateau (TP). (TP). The The dashed dashed line line represents represents the the linear linear temporal temporal trend. trend. Unit mm/d mm/d demotes millimeter per day.

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Table 1. Temporal trends of annually and seasonally averaged precipitation amount for the station Table 1. Temporal trends of annually and seasonally averaged precipitation amount for the station observations (bold values indicate that they pass the significance test with a 95% confidence level) observations (bold values indicate that they pass the significance test with a 95% confidence level) (unit: (unit: %/10 years). %/10 years). CHINA S N NE NW TP CHINA S N NE NW TP ANNUAL −0.11 1.0 −1.5 0.8 5.2 −0.7 ANNUAL 0.11 1.0 1.5 0.8 5.2 0.7 MAM −0.26− −1.6 −−0.4 5.4 3.0 − 3.4 MAM 0.26 1.6 0.4 5.4 3.0 3.4 − − − JJAJJA 0.390.39 2.42.4 −2.12.1 −1.61.6 3.93.9 1.6−1.6 − − − SONSON −2.62.6 −3.33.3 −2.42.4 −1.71.7 3.93.9 2.1−2.1 − − − − − DJFDJF 3.93.9 4.1 4.1 2.1 2.1 9.79.7 13.813.8 1.8−1.8 −

TheThe temporal temporal trends trends of of relative relative changes changes in in the the seasonally seasonally averaged averaged precipitation precipitation amount amount show show didifferentfferent spatial spatial distributions distributions from from that that of of the the annually annually averaged averaged precipitation precipitation amount, amount, which which are are shownshown in in Figure Figure4. The4. The circles circles and and colors colors shown shown in Figure in Figure4 have 4 have the same the same meanings meanings as those as those shown shown in Figurein Figure2. In spring,2. In thespring, precipitation the precipitation amounts showamount clears show increasing clear trendsincreasing in Northeast, trends in Northwest, Northeast, andNorthwest, Tibetan Plateau and Tibetan regions, Plateau with a lotregions, of stations with passinga lot of thestations significance passing test the at significance a 95% confidence test at level.a 95% Byconfidence contrast, thelevel. precipitation By contrast, amount the precipitation in South China amount shows in aSouth decreasing China trend,shows while a decreasing with limited trend, stationswhile passingwith limited the significance stations passing test at a the 95% significance confidence level.test at In a summer, 95% confidence in addition level. to the In Northwestsummer, in region,addition there to isthe also Northwest an increasing region, trend there of precipitationis also an increasing amount trend in South of precipitation China, particularly amount for in those South coastalChina, stations particularly that pass for thethose 95% coastal confidence stations significance that pass test. the By95% contrast, confidence the decreasing significance trends test. of By precipitationcontrast, the amounts decreasing can trends be found of precipitation in most stations amounts over Northeast, can be found North in most China, stations and Tibetan over Northeast, Plateau regions.North China, In autumn, and exceptTibetan for Plateau the increasing regions. trendsIn autumn, of the precipitationexcept for the amount increasing in the trends Northwest of the region,precipitation the seasonally amount averaged in the Northwest precipitation region, amount the seasonally shows clear averaged decreasing precipitation trends for mostamount stations shows inclear other decreasing regions. In trends winter, for except most forstations the south in other region regions. of the In Tibetan winter, Plateau except andfor the some south coastal region sites of inthe theTibetan North ChinaPlateau region, and some there coastal are very sites clear in increasing the North trends China of region, the precipitation there are very amount clear with increasing many stationstrends passingof the precipitation the 95% confidence amount significancewith many stations test. passing the 95% confidence significance test.

FigureFigure 4. 4.The The decadal decadal trends trends of of relative relative changes changes ofof seasonallyseasonally averaged precipitation amount amount (unit: (unit: % % /10/10 years) in ((a)) springspring (MAM),(MAM), ((bb)) summersummer (JJA),(JJA), ( c(c)) autumn autumn (SON), (SON), and and ( d()d winter) winter (DJF) (DJF) at at 635 635 groundground stations. stations.

InIn summary, summary, there there are are significant significant increasing increasing trends trends of of annually annually and and seasonally seasonally averaged averaged precipitationprecipitation amounts amounts for for most most stations stations in in the the Northwest Northwest China China region. region. For For the the South South China China region, region, there are decreasing trends in both spring and autumn, and increasing trends in both summer and

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Atmosphere 2020, 11, x FOR PEER REVIEW 7 of 16 there are decreasing trends in both spring and autumn, and increasing trends in both summer and winterwinter for for most most stations, stations, causing causing a a weak weak increasing increasing trend trend of of annually annually averaged averaged precipitation precipitation amount. amount. ForFor the the Northeast Northeast China China region, region, there there are are increasing increasing trends trends in in both both spring spring and and winter, winter, but but decreasing decreasing trendstrends in in summer summer and and autumn autumn for most for most stations, stations, causing causing a weak a decreasing weak decreasing trend of annuallytrend of averaged annually precipitationaveraged precipitation amount. For amount. the North For Chinathe North region, Chin therea region, are decreasing there are trendsdecreasing for most trends stations for most in summer,stations andin summer, no clear and trends no inclear other trends seasons. in other Correspondingly, seasons. Correspondingly, the annual averaged the annual precipitation averaged amountprecipitation has shown amount a weak has decreasingshown a weak trend decreasing in North China. trend Forin North the Tibetan China. Plateau For the region, Tibetan except Plateau for theregion, increasing except trend for inthe spring, increasing there aretrend decreasing in spring trends, there in are other decreasing seasons, particularly trends in other for the seasons, South regionparticularly of Tibetan for plateau,the South causing region a of decreasing Tibetan plateau, trend of causing annually a averageddecreasing precipitation trend of annually amount. averaged While notprecipitation certain, the amount. temporal While variation not ofcertain, precipitation the temporal over the variation TP is likely of precipitation influenced by over its topography,the TP is likely as showninfluenced in Figure by 1its, along topography, with the as large-scale shown in circulation, Figure 1, along which with is beyond the large-scale the scope ofcirculation, the current which study. is beyond the scope of the current study. 3.2. Temporal Trends of Precipitation Days 3.2. Temporal Trends of Precipitation Days In addition to the precipitation amount, we also analyzed the temporal trends of precipitation days atIn every addition station to the and precipitation region. Figure amount,5 shows we the also temporal analyzed trends the temporal of relative trends changes of precipitation in annual precipitationdays at every days station for all and 635 region. stations Figure from 5 1961 shows to 2016. the temporal The circles trends have of the relative same meanings changes in as annual those shownprecipitation in Figure days2 except for all that 635 they stations are for from precipitation 1961 to 2016. days The instead circles of have precipitation the same amount. meanings It showsas those ashown very di inff erentFigure spatial 2 except pattern that they as that are shownfor precipitation for precipitation days instead amount. of precipitation For most stations amount. in It China, shows therea very are different clear decreasing spatial pattern trends as in that precipitation shown for daysprecipitation except for amount. the Northwest For most region, stations for in which China, therethere are are clear clear increasing decreasing trends trends in in precipitation precipitation days days except except for for a few the stations.Northwest Also region, different for which from thethere results are clear of precipitation increasing amount,trends in theprecipitation changes in days precipitation except for days a few are stations. significant Also for different many more from stations.the results Table of2 precipitation lists the temporal amount, trends the of changes relative in changes precipitation of precipitation days are dayssignificant in China, for alongmany with more thosestations. in the Table five 2 regions lists the classified temporal in trends Figure of1. relati Thereve are changes significant of precipitation decreasing trendsdays in in China, China along for thewith precipitation those in the days, five whichregions is classified2.9%/10 in years, Figure1.5% 1. There/10 years, are significant2.1%/10 years,decreasing5.9% trends/10 years, in China and − − − − for2.8 the %/10 precipitation years for yearly days, average, which is spring, −2.9%/10 summer, years, − autumn,1.5%/10 andyears, winter, −2.1%/10 respectively. years, −5.9%/10 In contrast, years, − Liuand et − al.2.8 [26 %/10] showed years a for decreasing yearly average, trend of precipitationspring, summer, frequency autumn, from and 1960 winter, to 2000 respectively. with a rate ofIn contrast,2.5%/10 years,Liu et whichal. [26] isshowed roughly a decreasing consistent withtrend our of precipitation finding of 2.9%frequency/10 years. from Regionally, 1960 to 2000 there with − − area rate also of significant −2.5%/10 years, decreasing which trends is roughly of annual consistent precipitation with our daysfinding in S,of N,−2.9%/10 NE, and years. TP, whichRegionally, are there3.5%/ 10are years, also significant3.9%/10 years, decreasing1.6% /trends10 years of andannual3.8% precipitation/10 years, respectively. days in S, N, Di NE,fferently, and TP, there which is a − − − − significantare −3.5%/10 increasing years, − trend3.9%/10 of annualyears, − precipitation1.6%/10 years days and in−3.8%/10 the NW years, region, respectively. which is 1.7% Differently,/10 years. there The reasonsis a significant that the increasing precipitation trend days of have annual these precipitation temporal and days spatial in the variations NW region, are which not clear is 1.7%/10 and need years. to beThe further reasons explored that the in precipitation future studies. days have these temporal and spatial variations are not clear and need to be further explored in future studies.

FigureFigure 5. 5.The The decadal decadal trend trend of of the the relative relative change change of of annual annual precipitation precipitation days days at at 635 635 stations. stations.

Figure 6 further shows the spatial distribution of temporal trends of relative changes in seasonally averaged precipitation days in China. Note that the temporal trends of relative changes in

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Atmosphere 2020, 11, x FOR PEER REVIEW 8 of 16 Table 2. Decadal trend of annual and seasonal averaged precipitation days in China and its five seasonallyclassified averaged regions (bold precipitation values indicate days that in China, the changes along passed with thethose 95% in significance the five classified test) (unit: regions % /10 have alsoyears). been listed in Table 2. Different temporal trends of precipitation days can be clearly seen over different regions and seasons in Figure 6. The total precipitation day number shows clear decreasing CHINA S N NE NW TP trends in autumn for all regions, which are −7.7, −6.3, −3.3, −0.2, and −6.0 %/10 years in S, N, NE, NW, ANNUAL 2.9 3.5 3.9 1.6 1.7 3.8 and TP regions, respectively.− For other− seasons,− the temporal− changes of total precipitation− day MAM 1.5 3.0 2.8 2.2 1.0 0.3 − − − − number demonstrateJJA different2.1 performance0.83 among4.0 the five4.1 regions.0.68 Roughly, there2.1 are clear − − − − − decreasesSON in total precipitation5.9 days in7.7 spring of S6.3 region, in -3.3summer of N,0.2 NE, and 6.0TP regions, in − − − − − winter of DJFS and TP regions.2.8 In contrast,3.4 there are 1.2clear increases 2.2 of total 7.1precipitation12.3 days only in − − − − winter of the NW region. One interesting result is found for the temporal trends of relative changes of seasonallyFigure6 further averaged shows precipitation the spatial distributiondays in NW: of there temporal are a trendslarge number of relative of stations changes with in seasonally significant averagedincreasing precipitation trends of total days precipitation in China. Note days that in thespring temporal and winter, trends along of relative with changesa considerable in seasonally number averagedof stations precipitation with significant days in China,decreasing along trends with thoseof precipitation in the five classified days in regionssummer have and also autumn, been listedparticularly in Table in2. autumn. Di fferent temporal trends of precipitation days can be clearly seen over different regions and seasons in Figure6. The total precipitation day number shows clear decreasing trends in autumnTable for all2. Decadal regions, trend which of areannual7.7, and 6.3,seasonal3.3, averaged0.2, and precipitation6.0 %/10 yearsdays in in China S, N, and NE, its NW, five and classified regions (bold values indicate− − that the− changes− passed− the 95% significance test) (unit: % /10 TP regions, respectively. For other seasons, the temporal changes of total precipitation day number years). demonstrate different performance among the five regions. Roughly, there are clear decreases in total precipitation days inCHINA spring of S region,S in summerN of N, NE, andNE TP regions,NW in winter ofTP S and TP regions.ANNUAL In contrast, there−2.9 are clear increases−3.5 of total− precipitation3.9 − days1.6 only in winter1.7 of the NW−3.8 region. One interestingMAM result is−1.5 found for the−3.0 temporal trends−2.8 of relative2.2 changes of1.0 seasonally − averaged0.3 precipitationJJA days in NW:−2.1 there are a− large0.83 number of−4.0 stations with−4.1 significant increasing0.68 trends−2.1 of total precipitationSON days in spring−5.9 and winter,−7.7 along with− a6.3 considerable -3.3 number of stations−0.2 with significant−6.0 decreasingDJF trends of precipitation−2.8 days−3.4 in summer− and1.2 autumn,2.2 particularly in7.1 autumn. −12.3

FigureFigure 6. 6.The The decadal decadal trend trend of of the the relative relative change change of seasonallyof seasonally averaged averaged precipitation precipitation days days (unit: (unit: %/10 % years)/ 10 years) in (a) spring,in (a) spring, (b) summer, (b) summer, (c) autumn, (c) autumn, and (d and) winter (d) winter at 635 groundat 635 ground stations. stations.

FigureFigure6 shows 6 shows the similarthe similar spatial spatial distribution distribution in temporal in trendstemporal of relative trends changes of relative of precipitation changes of daysprecipitation as that in decadaldays as trendsthat in of decadal relative trends changes of of relative precipitation changes amount of precipitation shown in Figure amount4 except shown for in theFigure winter 4 seasonexcept (DJF).for the This winter implies season that (DJF). the temporal This implies variation that in the the temporal relative changes variation of precipitationin the relative dayschanges could ofplay precipitation an important days contributingcould play an role important to the temporalcontributing change role ofto precipitationthe temporal change amount. of precipitation amount. Actually, Miao et al. [27] have also shown that the changes in the precipitation amount resulted mainly from changes in frequency rather than changes in intensity in China.

Atmosphere 2020, 11, 303 9 of 17

AtmosphereActually, 2020 Miao, 11, et x FOR al. [ 27PEER] have REVIEW also shown that the changes in the precipitation amount resulted mainly9 of 16 from changes in frequency rather than changes in intensity in China. ConsideringConsidering the the impacts impacts of of precipitation precipitation on on loca locall environment environment (ecology, (ecology, plants, plants, agriculture, agriculture, and and soso on) on) and and water water management management depend depend on on both both the the precipitation precipitation amount amount and and precipitation precipitation days days in a in seasona season or ora year, a year, the the precipitation precipitation day day information information shown shown in in Figure Figure 66 along along with with the the precipitation precipitation amountamount information information shown shown in inFigure Figure 4 4could could help help a lot a lot for for the the water water management. management. For example, For example, the increasethe increase of precipitation of precipitation day dayand andamount amount in Northwest in Northwest China China implies implies the thepotential potential reduction reduction of irrigationof irrigation needed needed in this in this area, area, and and the the decreasing decreasing precipitation precipitation day day and and increasing increasing precipitation precipitation amountamount in in South South China China in in summer summer and and winter winter impl implyy the the increase increase of of heavy heavy precipitation precipitation and and more more storagestorage capability capability for for dams dams in in this this region region is is demanded. demanded.

3.3.3.3. Temporal Temporal Trends Trends of of Precipitation Precipitation Days Days with with Different Different Intensity Intensity SectionSection 2 has classifiedclassified thethe precipitation precipitation into into six si typesx types based based on on the the precipitation precipitation intensity. intensity. We hereWe hereexamine examine the precipitationthe precipitation days days for these for these six di sixfferent different types types of precipitation. of precipitation. Figure Figure7 shows 7 theshows relative the relativefrequency frequency for six di forfferent six different types of precipitationtypes of precipitation in the classified in the fiveclassified regions. five For regions. all of these For all five of regions, these fivethe regions, precipitation the precipitation with P < 10 mmwith/day P < dominates,10 mm/day with dominates, a fraction with of overa fraction 70%. Actually,of over 70%. around Actually, 50% of aroundthe precipitation 50% of the events precipitation are with Pevents< 2 mm are/day. with By P contrast,< 2 mm/day. the heavy By contrast, precipitation the heavy with Pprecipitation> 25 mm/day withhas veryP > 25 low mm/day occurrence has very frequencies, low occurrence which are frequenc generallyies, lesswhich than are 10%. generally The extreme less than precipitation 10%. The extremeevents mainlyprecipitation occur inevents the South mainly China occur region, in the withSouth a frequencyChina region, close with to 10%. a frequency For other close regions, to 10%. the Forextreme other precipitation regions, the events extreme have precipitation much less occurrence events have frequencies, much less particularly occurrence in thefrequencies, Northwest particularlyregion (<1%). in Ningthe Northwest and Qian [34region] have (<1%). also indicated Ning and that Qian the precipitation[34] have also amount indicated associated that withthe precipitationweak and middle amount precipitation associated with events weak are and more middle than 60% precipitation of the total events precipitation are more amountthan 60% for of most the totalregions precipitation in China amount by the annual for most average. regions Thus, in China the by temporal the annual trends average. of total Thus, precipitation the temporal amount trends for ofweak total and precipitation middle precipitation amount for events weak shouldand middle play moreprecipitation important events roles should rather than play that more for important heavy and rolessevere rather precipitation than that eventsfor heavy for mostand severe regions. precipit Of course,ation forevents the for South most China regions. region Of withcourse, a relatively for the Southhigh frequencyChina region of heavy with a precipitation, relatively high the frequency temporal trendsof heavy of heavyprecipitation, precipitation the temporal events should trends also of heavyplay anprecipitation important role.events should also play an important role.

FigureFigure 7. 7. TheThe relativerelative frequencyfrequency of of precipitation precipitation days days for diforfferent different types types of precipitation of precipitation in the classified in the classifiedfive regions five ofregions Northeast of Northeast China (NE), China Northwest (NE), Northwest China (NW), China South (NW), China South (S), China North (S), China North (N), China and (N),Tibetan and Tibetan Plateau Plateau (TI). (TI).

FigureFigure 88 shows shows the the temporal temporal trends trends of ofrelative relative changes changes of precipitation of precipitation occurrence occurrence frequency frequency for differentfor different types types of precipitation of precipitation over over the thefive five clas classifiedsified regions regions along along with with the the whole whole China China region. region. AveragedAveraged for for all all 635 635 stations stations in in China, China, there there ar aree significant significant temporal temporal decreases decreases of of precipitation precipitation occurrenceoccurrence for for both both weak weak and and middle middle precipitation precipitation events, events, among among which which the decreasing the decreasing trend trendof light of precipitationlight precipitation is the ismost the mostsignificant, significant, which which is 5. is4%/10 5.4% /years.10 years. In Incontrast, contrast, the the heavy heavy precipitation precipitation occurrenceoccurrence frequency frequency has has an an increasing increasing trend, trend, consis consistenttent with with the the findings findings by by Ning Ning and and Qian Qian [35]. [35 ]. Differently,Differently, the the increasing increasing trend trend we we found found here here do doeses not not pass pass the the 95% 95% confidence confidence significance significance test.

AtmosphereAtmosphere2020 2020, 11,, 11 303, x FOR PEER REVIEW 1010 of 17of 16

FigureFigure 8. The8. The decadal decadal trend trend of relative of relative changes changes of precipitation of precipitation occurrence occurrence frequency frequency for diff erentfor different types oftypes precipitation of precipitation over (a) over the whole (a) the China whole region, China along region, with along the with five classifiedthe five classified regions ofregions (b) South of (b) ChinaSouth (S), China (c) North (S), ( Chinac) North (N), China (d) Tibetan (N), ( Plateaud) Tibetan (TP), Plateau (e) Northeast (TP), (e China) Northeast (NE), andChina (f) (NE), Northwest and (f) ChinaNorthwest (NW). China (NW).

ForFor all all the the five five classified classified regions, regions, we we can can see see that that the the sunny sunny days days have have significant significant increasing increasing trendstrends in in the the occurrence occurrence frequency, frequency, indicating indicating that that the the precipitation precipitation days days have have significant significant decreases decreases countrywide.countrywide. For For South South China China region, region, the the precipitation precipitation occurrence occurrence frequencies frequencies for for di differentfferent types types of of precipitationprecipitation show show the the same same temporal temporal trends trends as as that that for for the the whole whole China China region: region: there there are are significant significant decreasingdecreasing trends trends for for light, light, small, small, and and middle middle precipitation, precipitation, and and the the annual annual heavy heavy precipitation precipitation days days increaseincrease with with time, time, causing causing the the total total precipitation precipitation amount amount to to increase increase slightly. slightly. Note Note that that the the light light precipitationprecipitation days days decrease decrease at at a higha high rate rate of of 8% 8%/1/10 years0 years in in South South China. China. For For the the North North China China region, region, therethere are are significant significant decreasing decreasing trends trends of of precipitation precipitation days days for for both both light light and and small small precipitation. precipitation. WhileWhile not not significant, significant, there there are are also also decreasing decreasing trends trends of of precipitation precipitation days days for for middle middle and and heavy heavy precipitationprecipitation in in North North China, China, which which could could be be as as large large as as 2.0% 2.0%/10/10 years, years, causing causing the the total total precipitation precipitation amountamount in Northin North China China to decrease. to decrease. For theFor Northeastthe Northe Chinaast China region, region, only light only precipitation light precipitation days have days a clearhave decreasinga clear decreasing trend, andtrend, there and are there no clearare no temporal clear temporal trends fortrends other for types other of types precipitation. of precipitation. The occurrenceThe occurrence frequencies frequencies of middle of middle and heavy and precipitation heavy precipitation have slightly have decreasingslightly decreasing trends with trends values with lessvalues than 1%less/10 than years. 1%/10 As ayears. result, As the a totalresult, precipitation the total precipitation amount has amount a slightly has decreasing a slightly trend decreasing from 1961trend to 2016from in 1961 the Northeastto 2016 in China the Northeast region. For China the Tibetan region. Plateau For the region, Tibetan there Plateau are decreasing region, there trends are fordecreasing the occurrence trends frequencies for the occurrence of all types frequencies of precipitation, of all types but only of precipitation, those with P but< 5 only mm/ daythose pass with the P < significance5 mm/day testpass with the significance a 95% confidence test with level. a 95% Over confid the Tibetanence level. Plateau Over region,the Tibetan the decreasing Plateau region, trends the ofdecreasing precipitation trends occurrence of precipitation frequency occurrence are about freq 9%uency/10 years are forabout light 9%/10 precipitation, years for light 1%/10 precipitation, years for middle1%/10 precipitation, years for middle and < precipitation,1%/10 years for and heavy <1%/10 precipitation. years for heavy For the precipitation. Northwest China For the region, Northwest there areChina increasing region, trends there for are the increasing occurrence trends frequencies for the occurrence of all types frequencies of precipitation, of all particularly types of precipitation, for those withparticularly P > 1 mm for/day. those The with increasing P > 1 mm/day. trend of The precipitation increasing occurrencetrend of precipitation frequency occurrence is even larger frequency than 10%is /10even years larger for heavythan precipitation.10%/10 years Allfor ofheavy these makeprecipitation. the yearly All total of precipitationthese make the amount yearly in thetotal Northwestprecipitation China amount region in increase the Northwest with time China from regi 1961on to increase 2016. with time from 1961 to 2016.

Atmosphere 2020, 11, 303 11 of 17

In every region, the temporal trends of relative changes of precipitation days also vary with season for all types of precipitation. Figures S1–S5 (only available online in the Supplementary Materials) show the temporal trends of occurrence frequencies of different types of precipitation for spring, summer, autumn, and winter in S, N, NE, TP, and NW regions, respectively. We first examine the South China region. There are clear decreasing trends of precipitation days for light, small, and middle precipitation in spring and autumn. In summer, there are decreasing trends for light precipitation in summer and winter, but also a clear increasing trend for heavy precipitation in summer. Shortly, in South China, heavy precipitation increases in summer, and light precipitation decreases in all seasons. Second, we examine the North China region. There are clear decreasing trends of precipitation days for all types of precipitation in summer and autumn, with the light and small precipitation types passing the 95% confidence significance test. A significant decreasing trend in the occurrence frequency is also found for light precipitation in spring. There are no significant temporal trends in the occurrence days for other types of precipitation or for the winter season. Shortly, significant decreasing trends of precipitation days are found in spring, summer, and autumn for light precipitation, and in summer for small precipitation. Third, we examine the Northeast China region. There are significant decreasing trends of precipitation days for light precipitation in summer and autumn and for small precipitation in summer; however, there are significant increasing trends for small precipitation in spring and winter. Fourth, we examine the Tibetan Plateau region. Significant decreasing trends of precipitation days can be found for light precipitation in all seasons, for small precipitation in summer and autumn, and for middle precipitation in summer. By contrast, significant increasing trends of precipitation days are only found in spring for small, middle, and heavy precipitation. Fifth, the temporal trends of precipitation occurrence days in Northwest China are examined. There are slightly decreasing trends of precipitation days for light precipitation and clear increasing trends for other types of precipitation for almost all seasons, while only part of these trends pass the 95% confidence significance test. Shortly, significant increasing trends of precipitation days are found for small and middle precipitation in summer, autumn, and winter, for heavy precipitation in summer and winter, and for light precipitation in winter in Northwest China. In contrast, there are no significant decreasing trends for all types of precipitation in the four seasons. In summary, there are significantly increasing trends of the sunny days, and significant decreasing trends of occurrence frequency for light precipitation for most regions and most seasons. While multiple reasons could exist, one likely explanation is the increasing aerosol pollution in China, which enhances CCN concentration, reduces cloud droplet mean radius, and suppresses drizzle formation [20]. This mechanism works particularly for light precipitation. For precipitation occurrence days other than light precipitation, there are different temporal trends in different regions and seasons, which indicates that the temporal trends of precipitation occurrence days should be highly related to the location, season, and precipitation type.

3.4. Spatial Pattern for Temporal Trends of Light and Heavy Precipitation Occurrence Days We have shown robust findings about the decreasing trends of light precipitation days over most regions and in most seasons and increasing trends of heavy precipitation days for all cases when the temporal changes are significant. We next examine the spatial patterns about the temporal trends of both light and heavy precipitation occurrence days using the measurements at all 635 stations. Figure9 shows the spatial distributions about the temporal trends of light precipitation occurrence days. The circles have the same meanings as those shown in Figure3, except that they are for light precipitation occurrence days. For most stations in China, except that in the Northwest region, there are significant decreasing trends of light precipitation occurrence days with a 95% confidence level. The decreasing trends are particularly large in South China, North China and Tibetan Plateau regions, with a lot of stations having decreasing trends larger than 10%/10 years. By contrast, the decreasing trends are much smaller in the Northeast China region. Atmosphere 2020, 11, x FOR PEER REVIEW 12 of 16

than those with decreasing trends for the heavy precipitation occurrence days. At a confidence level of 95%, there are only partial stations with significant temporal changes in the heavy precipitation occurrence days. Different from the regional average values shown in Figures S1–S4, significant decreasing trends of heavy precipitation days also exist in some stations. The increasing trends of heavyAtmosphere precipitation2020, 11, 303 occurrence days mainly occur at stations in South China and Northwest12 of China, 17 and the decreasing trends of heavy precipitation mainly occur at partial stations in Northeast China.

Atmosphere 2020, 11, x FOR PEER REVIEW 12 of 16 than those with decreasing trends for the heavy precipitation occurrence days. At a confidence level of 95%, there are only partial stations with significant temporal changes in the heavy precipitation occurrence days. Different from the regional average values shown in Figures S1–S4, significant decreasing trends of heavy precipitation days also exist in some stations. The increasing trends of heavy precipitation occurrence days mainly occur at stations in South China and Northwest China, and the decreasing trends of heavy precipitation mainly occur at partial stations in Northeast China.

FigureFigure 9. The 9. The spatial spatial distributions distributions about about the temporaltemporal trends trends of of light light precipitation precipitation occurrence occurrence days days at at 635635 ground ground stations stations in in China. China.

Figure 10 shows the spatial distributions about the temporal trends of heavy precipitation occurrence days. Compared to that shown in Figure9 for light precipitation, the spatial pattern for heavy precipitation is much more complex. Roughly, there are more stations with increasing trends than those with decreasing trends for the heavy precipitation occurrence days. At a confidence level of 95%, there are only partial stations with significant temporal changes in the heavy precipitation occurrence days. Different from the regional average values shown in Figures S1–S4, significant

decreasing trends of heavy precipitation days also exist in some stations. The increasing trends of heavyFigure precipitation 9. The spatial occurrence distributions days about mainly the temporal occur at stationstrends of in light South precipitation China and occurrence Northwest days China, at and635 the ground decreasing stations trends in China. of heavy precipitation mainly occur at partial stations in Northeast China.

Figure 10. The spatial distributions about the temporal trends of heavy precipitation occurrence days at 635 ground stations in China.

Different spatial patterns have been found among the four seasons for both light and heavy precipitation. Figure 11 shows the spatial distributions about the temporal trends of light precipitation occurrence days in four seasons. In general, Figure 11 shows the similar results regarding the temporal trends of relative changes of the light precipitation days for the five regions using station observations as shown in Figures S1-S4 using the region-average data, while a few

unique stations often exist with different temporal changes from most stations in that region. Figure Figure 10. The spatial distributions about the temporal trends of heavy precipitation occurrence days 11 alsoFigure suggests 10. The that spatial there distributions are more aboutstations the withtemporal significant trends of increasing heavy precipitation trends of occurrence light precipitation days at 635 ground stations in China. occurrenceat 635 ground days instations the Northwest in China. region for all seasons, and in the Northeast region in spring and winter; and there are more stations with significant decreasing trends of light precipitation Different spatial patterns have been found among the four seasons for both light and heavy precipitation. Figure 11 shows the spatial distributions about the temporal trends of light precipitation occurrence days in four seasons. In general, Figure 11 shows the similar results regarding the temporal trends of relative changes of the light precipitation days for the five regions using station observations as shown in Figures S1-S4 using the region-average data, while a few unique stations often exist with different temporal changes from most stations in that region. Figure 11 also suggests that there are more stations with significant increasing trends of light precipitation occurrence days in the Northwest region for all seasons, and in the Northeast region in spring and winter; and there are more stations with significant decreasing trends of light precipitation

Atmosphere 2020, 11, 303 13 of 17

Different spatial patterns have been found among the four seasons for both light and heavy precipitation. Figure 11 shows the spatial distributions about the temporal trends of light precipitation occurrence days in four seasons. In general, Figure 11 shows the similar results regarding the temporal trends of relative changes of the light precipitation days for the five regions using station observations as shown in Figures S1–S4 using the region-average data, while a few unique stations often exist with different temporal changes from most stations in that region. Figure 11 also suggests that there are moreAtmosphere stations 2020 with, 11, x significant FOR PEER REVIEW increasing trends of light precipitation occurrence days in the Northwest13 of 16 region for all seasons, and in the Northeast region in spring and winter; and there are more stations withoccurrence significant days decreasing in North trends China, of South light precipitation China, Tibe occurrencetan Plateau days regions in North for all China, seasons, South and China, in the TibetanNortheast Plateau region regions in summer for all seasons,and autumn. and in the Northeast region in summer and autumn.

Figure 11. The spatial distributions about the temporal trends of light precipitation occurrence days Figure 11. The spatial distributions about the temporal trends of light precipitation occurrence days (unit: %/10 years) in (a) spring, (b) summer, (c) autumn, and (d) winter at 635 stations. (unit: % / 10 years) in (a) spring, (b) summer, (c) autumn, and (d) winter at 635 stations. Figure 12 further shows the spatial distributions of the temporal trends of heavy precipitation occurrenceFigure days 12 atfurther all stations shows inthe four spatial seasons. distributions In general, of therethe temporal are more trends stations of withheavy significantly precipitation increasingoccurrence trends days of at heavy all stations precipitation in four daysseasons. for almostIn general, all regions there are in fourmore seasons, stations except with significantly for North Chinaincreasing in summer trends and of heavy Northeast precipitation China in days summer for al andmost autumn. all regions Particularly, in four seasons, there are except clearly for more North stationsChina within summer significant and Northeast increasing China trends in of summer heavy precipitationand autumn. daysParticularly, for South there China are inclearly summer more andstations winter. with significant increasing trends of heavy precipitation days for South China in summer and winter.

4. Conclusions Using the meteorological observations at the selected 635 stations from 1961 to 2016, this study reveals the temporal trends of annually and seasonally averaged precipitation amounts and precipitation occurrence frequencies with different rainfall intensities. While the temporal trends of precipitation amount and precipitation occurrence frequency with different rainfall intensities vary substantially with regions and seasons, several robust findings about their statistical characteristics have been found. The annual averaged precipitation amount shows a weak and insignificant decreasing trend in the whole of China. The precipitation with a rate less than 10 mm/day dominates in China, with a total precipitation fraction of over 70%. In Northwest China, the total precipitation amount shows a clear increasing trend for both annually and seasonally averaged values. By contrast, there are significant decreasing trends of annually averaged precipitation amounts in the boundary regions between the Tibetan Plateau and North China, South China. Seasonally, we can find significant decreasing trends in annually averaged precipitation amounts in autumn. There are significant increases in sunny days for all regions except the Northwest in China. Except for Northwest China, light precipitation days in general show a robust decreasing trend in China. The decreasing trends are particularly large in South China, North China and Tibetan Plateau regions, with a lot of stations having a decreasing trend larger than 10%/10 years. Considering the high frequency of light and small precipitation (>70%), the decadal trends of precipitation days could

Atmosphere 2020, 11, x FOR PEER REVIEW 14 of 16

highly explain the temporal variation of precipitation amount in China, which is consistent with the Atmosphereprevious2020 findings, 11, 303 [27]. 14 of 17

FigureFigure 12. 12.The The spatial spatial distributions distributions about about the the temporal temporal trends trends of of heavy heavy precipitation precipitation occurrence occurrence days days (unit:(unit: % /%10 / years)10 years) in (ina) spring,(a) spring, (b) ( summer,b) summer, (c) autumn,(c) autumn, and and (d) winter(d) winter at 635 at 635 stations. stations. 4. Conclusions The temporal trends of heavy precipitation days are much more complex. Generally speaking, thereUsing are themore meteorological stations with observations increasing at trends the selected than 635those stations with fromdecreasing 1961 to trends 2016, this forstudy heavy revealsprecipitation the temporal occurrence trends ofdays. annually At a and confidence seasonally level averaged of 95%, precipitation there are amountsonly limited and precipitationstations with occurrencesignificant frequencies temporal changes with di ffoferent heavy rainfall precipitatio intensities.n occurrence While the days. temporal The increasing trends of trends precipitation of heavy amountprecipitation and precipitation occurrence occurrencedays mainly frequency occur at stat withions di ffinerent South rainfall China intensitiesand Northwest vary substantiallyChina, and the withdecreasing regions andtrends seasons, of heavy several precipitation robust findings mainly about occur their at partial statistical stations characteristics in Northeast have China. been found. ThePrecipitation annual averaged amount precipitation and occurrence amount days shows in diffe a weakrent seasons and insignificant over the fi decreasingve classified trend regions in thehave whole also of been China. analyzed, The precipitation which exhibits with a different rate less thantemporal 10 mm variation/day dominates patterns. in For China, example, with a for total the precipitationNorthwest China fraction region, of over in 70%.addition In Northwest to the increasing China, trends the total of precipitationprecipitation amountamount showsin foura seasons clear increasingfor most trendstations, for bothsignificant annually increasing and seasonally trends averagedof precipitation values. days By contrast, are also therefound are for significant small and decreasingmiddle precipitation trends of annually in summer, averaged autumn, precipitation and winter, amounts for heavy in theprecipitation boundary in regions summer between and winter, the Tibetanand for Plateau light precipitation and North China, in winter. South Correspondingly China. Seasonally,, significant we can find increasing significant trends decreasing in the trends annually in annuallyaveraged averaged precipitation precipitation amount amounts have been in autumn. found in the Northwest China region. Except for the NorthwestThere are China significant region, increases there are in sunnysignificantly days for incr alleasing regions trends except of the the Northwest sunny days, in China.and significant Except fordecreasing Northwest trends China, of light occurrence precipitation frequency days in for general light precipitation show a robust for decreasing almost all trend seasons in China. over Themost decreasingregions. Future trends studies are particularly will be co largenducted in South to understand China, North the Chinahistorical and trends Tibetan of Plateau precipitation regions, in withChina a lotas introduced of stations having in this astudy, decreasing by analyzing trend larger multiple than 10%observed/10 years. meteorological Considering factors the high and frequency performing of lightmodel and sensitivity small precipitation analyses (using>70%), regional/global the decadal trends climate of precipitationsimulations. days could highly explain the temporalSupplementary variation Materials: of precipitation The following amount are in available China, online which at is www.mdpi.com/xxx/s1, consistent with the previous Figure findingsS1: The decadal [27]. trendThe of temporalthe relative trends change of of heavy precipitation precipitation occurrence days frequency are much for more different complex. types Generallyof precipitation speaking, in four thereseasons are moreover South stations China with (S) increasing region, where trends P represents than those precipitation with decreasing rate. Figure trends S2: for The heavy decadal precipitation trend of the occurrencerelative change days. of At precipitation a confidence occurrence level of frequency 95%, there for are di onlyfferent limited types of stations precipitation with significantin four seasons temporal over the changesNorth China of heavy (N) precipitationregion, where P occurrence represents days.precipitation The increasing rate. Figure trends S3: The of heavydecadal precipitation trend of the relative occurrence change daysof precipitation mainly occur occurrence at stations frequency in South for China different and Northwesttypes of precipitation China, and in the four decreasing seasons over trends the of Northeast heavy precipitationChina (NE) region, mainly where occur P atrepresents partial stations precipitation in Northeast rate. Figure China. S4: The decadal trend of the relative change of precipitation occurrence frequency for different types of precipitation in four seasons over the Tibetan Plateau Precipitation amount and occurrence days in different seasons over the five classified regions (TP) region, where P represents precipitation rate. Figure S5: The decadal trend of the relative change of have also been analyzed, which exhibits different temporal variation patterns. For example, for the Northwest China region, in addition to the increasing trends of precipitation amount in four seasons for most stations, significant increasing trends of precipitation days are also found for small and middle Atmosphere 2020, 11, 303 15 of 17 precipitation in summer, autumn, and winter, for heavy precipitation in summer and winter, and for light precipitation in winter. Correspondingly, significant increasing trends in the annually averaged precipitation amount have been found in the Northwest China region. Except for the Northwest China region, there are significantly increasing trends of the sunny days, and significant decreasing trends of occurrence frequency for light precipitation for almost all seasons over most regions. Future studies will be conducted to understand the historical trends of precipitation in China as introduced in this study, by analyzing multiple observed meteorological factors and performing model sensitivity analyses using regional/global climate simulations.

Supplementary Materials: The following are available online at http://www.mdpi.com/2073-4433/11/3/303/s1, Figure S1: The decadal trend of the relative change of precipitation occurrence frequency for different types of precipitation in four seasons over South China (S) region, where P represents precipitation rate. Figure S2: The decadal trend of the relative change of precipitation occurrence frequency for different types of precipitation in four seasons over the North China (N) region, where P represents precipitation rate. Figure S3: The decadal trend of the relative change of precipitation occurrence frequency for different types of precipitation in four seasons over the Northeast China (NE) region, where P represents precipitation rate. Figure S4: The decadal trend of the relative change of precipitation occurrence frequency for different types of precipitation in four seasons over the Tibetan Plateau (TP) region, where P represents precipitation rate. Figure S5: The decadal trend of the relative change of precipitation occurrence frequency for different types of precipitation in four seasons over the Northwest China (NW) region. Author Contributions: Conceptualization, Y.S. and C.Z.; methodology, Y.S.; software, Y.S.; validation, Y.S., C.Z.; formal analysis, Y.S., Z.M.; investigation, Y.S., C.Z.; resources, Z.M.; data curation, Z.M.; writing—original draft preparation, Y.S.; writing—review and editing, C.Z., Y.W.; visualization, Y.S.; supervision, C.Z.; funding acquisition, C.Z. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the National Natural Science Foundation of China, grant number 41925022, 91837204, and 41575143; the National Key R&D Program on Monitoring, Early Warning and Prevention of Major Natural Disasters, grant number 2017YFC1501403; and the State Key Laboratory of Earth Surface Processes and Resources Ecology. Acknowledgments: We acknowledge the data support from the Chinese Meteorology Administration. Data used in this study are available online from http://data.cma.cn/data/cdcdetail/dataCode/SURF_CLI_CHN_MUL_DAY_ V3.0.html. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Adler, R.F.; Huffman, G.J.; Chang, A.; Ferraro, R.; Xie, P.; Janowiak, J.; Rudolf, B.; Schneider, U.; Curtis, S.; Bolvin, D.; et al. The version 2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeorol. 2003, 4, 1147–1167. [CrossRef] 2. Trenberth, K.E.; Dai, A.; Rasmussen, R.M.; Parsons, D.B. The changing character of precipitation. Bull. Amer. Meteor. Soc. 2003, 84, 1205–1217. [CrossRef] 3. Jamieson, M.A.; Trowbridge, A.M.; Raffa, K.F.; Lindrot, R.L. Consequences of climate warming and altered precipitation patterns for plant-insect and multitrophic interactions. Plant Physiol. 2012, 160, 1719–1727. [CrossRef] 4. Schneider, U.; Finger, P.; Meyer-Christoffer, A.; Rustemeier, E.; Ziese, M.; Becker, A. Evaluating the Hydrological Cycle over Land Using the Newly-Corrected Precipitation Climatology from the Global Precipitation Climatology Centre (GPCC). Atmosphere 2017, 8, 52. [CrossRef] 5. Siepielski, A.M.; Morrissey, M.B.; Buoro, M.; Carlson, S.M.; Caruso, C.M.; Clegg, S.M.; Coulson, T.; DiBattista, J.; Gotanda, K.M.; Francis, C.D.; et al. Precipitation drives global variation in natural selection. Science 2017, 355, 959–962. [CrossRef] 6. Muller, C.J.; O’Gorman, P.A. An energetic perspective on the regional response of precipitation to climate change. Nat. Clim. Chang. 2011, 1, 266–271. [CrossRef] 7. Zhao, C.; Garrett, T.J. Ground-based remote sensing of precipitation in the Arctic. J. Geophys. Res. 2008, 113, D14204. [CrossRef] 8. Ropelewski, C.F.; Halpert, M.S. Global and regional scale precipitation patterns associated with the El Niño/Southern Oscillation. Mon. Weather Rev. 2013, 115, 985–996. [CrossRef] Atmosphere 2020, 11, 303 16 of 17

9. Koster, R.D.; Dirmeyer, P.A.; Guo, Z.; Bonan, G.; Chan, E.; Cox, P.; Gordon, C.T.; Kanae, S.; Kowalczyk, E.; Lawrence, D.; et al. Regions of strong coupling between soil moisture and precipitation. Science 2004, 305, 1138–1140. [CrossRef] 10. Allan, R.P.; Soden, B.J. Atmospheric warming and the amplification of precipitation extremes. Science 2008, 321, 1481–1484. [CrossRef] 11. Gong, D.; Wang, S. Severe summer rainfall in China associated with the enhanced global warming. Clim. Res. 2000, 16, 51–59. [CrossRef] 12. Garrett, T.J.; Zhao, C.; Dong, X.; Mace, G.G.; Hobbs, P.V. Effects of varying aerosol regimes on low-level Arctic stratus. Geophys. Res. Lett. 2004, 31, L17105. [CrossRef] 13. Gong, D.Y.; Ho, C.-H.; Chen, D.L.; Qian, Y.; Choi, Y.-S.; Kim, J. Weekly cycle of aerosolmeteorology interaction over China. J. Geophys. Res. 2007, 112.[CrossRef] 14. Rosenfeld, D. Suppression of rain and snow by urban and industrial air pollution. Science 2000, 287, 1793–1796. [CrossRef][PubMed] 15. Kaufman, Y.J.; Tanré, D.; Boucher, O. A satellite view of aerosols in the climate system. Nature 2002, 419, 215–223. [CrossRef] 16. Wang, Y.; Wan, Q.; Meng, W.; Liao, F.; Tan, H.; Zhang, R. Long-term impacts of aerosols on precipitation and lightning over the Pearl River Delta megacity area in China. Atmo. Chem. Phys. 2011, 11, 12421–12436. [CrossRef] 17. Zhao, C.; Klein, S.A.; Xie, S.; Liu, X.; Boyle, J.S.; Zhang, Y. Aerosol First Indirect effects on non-precipitating low-level liquid cloud properties as simulated by CAM5 at ARM sites. Geophys. Res. Lett. 2012, 39, L08806. [CrossRef] 18. Li, J.; Lv, Q.; Zhang, M.; Wang, T.; Kawamoto, K.; Chen, S.; Zhang, B. Effects of atmospheric dynamics and aerosols on the fraction of supercooled water clouds. Atmos. Chem. Phys. 2017, 17, 1847–1863. [CrossRef] 19. Qian, Y.; Gong, D.; Fan, J.; Leung, L.R.; Bennartz, R.; Chen, D.; Wang, W. Heavy pollution suppresses light rain in China: Observations and modeling. J. Geophys. Res. 2009, 114, D00K02. [CrossRef] 20. Wang, Y.; Ma, P.-L.; Jiang, J.; Su, H.; Rasch, P. Towards Reconciling the Influence of Atmospheric Aerosols and Greenhouse Gases on Light Precipitation Changes in Eastern China. J. Geophys. Res. Atmos. 2016, 121, 5878–5887. [CrossRef] 21. Kucera, P.A.; Ebert, E.E.; Turk, F.J.; Levizzani, V.; Kirschbaum, D.; Tapiador, F.J.; Loem, A.; Borsche, M. Precipitation from space: Advancing Earth System Science. Bull. Am. Meteorol. Soc. 2013, 94, 365–375. [CrossRef] 22. Tapiador, F.J.; Turk, F.J.; Petersen, W.; Hou, A.Y.; García-Ortega, E.; Machado, L.A.; Angelis, C.F.; Salio, P.; Kidd, C.; Huffman, G.J.; et al. Global precipitation measurement: Methods, datasets and applications. Atmos. Res. 2012, 104–105, 70–97. [CrossRef] 23. Xie, P.P.; Arkin, P.A. Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model output. Bull. Am. Meteorol. Soc. 1997, 78, 2539–2558. [CrossRef] 24. Zhao, C.; Lin, Y.; Wu, F.; Wang, Y.; Li, Z.; Rosenfeld, D.; Wang, Y. Enlarging Rainfall Area of Tropical Cyclones by Atmospheric Aerosols. Geophys. Res. Lett. 2018, 45.[CrossRef] 25. Chou, C.; Lan, C. Changes in the annual range of precipitation under global warming. J. Clim. 2012, 25, 222–235. [CrossRef] 26. Liu, B.; Xu, M.; Henderson, M.; Qi, Y. Observed trends of precipitation amount, frequency, and intensity in China, 1960–2000. J. Geophys. Res. 2005, 110, D08103. [CrossRef] 27. Miao, C.; Sun, Q.; Borthwick, A.G.L.; Duan, Q. Linkage between hourly precipitation events and atmospheric temperature changes over China during the warm season. Sci. Rep. 2016, 6.[CrossRef][PubMed] 28. Tan, L.; An, Z.; Huh, C.A.; Cai, Y.; Shen, C.C.; Shiau, L.J.; Yan, L.; Cheng, H.; Edwards, R.L. Cyclic precipitation variation on the western Loess Plateau of China during the past four centuries. Sci. Rep. 2014, 4, 6381. [CrossRef][PubMed] 29. Zhang, Q.; Xu, C.Y.; Zhang, Z.; Chen, Y.D.; Liu, C.L. Spatial and temporal variability of precipitation over China, 1951-2005. Theor. Appl. Climatol. 2009, 95, 53–68. [CrossRef] 30. Zhou, C.; Wang, K. Quantifying the Sensitivity of Precipitation to the Long-Term Warming Trend and Interannual–Decadal Variation of Surface Air Temperature over China. J. Clim. 2017, 30, 3687–3703. [CrossRef] Atmosphere 2020, 11, 303 17 of 17

31. Chen, D.; Ou, T.; Gong, L.; Xu, C.Y.; Li, W.; Ho, C.H.; Qian, W. Spatial interpolation of daily precipitation in China: 1951–2005. Adv. Atmos. Sci. 2010, 27, 1221–1232. [CrossRef] 32. The Data Center of Chinese Meteorological Agency. Available online: http://data.cma.cn/data/cdcdetail/ dataCode/SURF_CLI_CHN_MUL_DAY_V3.0.html (accessed on 12 March 2017). 33. Fu, J.; Qian, W.; Lin, X.; Chen, D. Trends in Graded Precipitation in China from 1961 to 2000. Adv. Atmos. Sci. 2008, 25, 267–278. [CrossRef] 34. Zhao, C.; Chen, Y.; Li, J.; Letu, H.; Su, Y.; Chen, T.; Wu, X. 15-year statistical analysis of cloud characteristics over China using Terra and Aqua MODIS observations. Int. J. Climatol. 2019, 38, 2612–2629. [CrossRef] 35. Ning, L.; Qian, Y. Analyses on Trends of Annual and Seasonal Four Kinds of Daily Precipitation in China. Plateau Meteorol. 2008, 27, 1010–1020. (In Chinese)

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