J. Meteor. Res.  2014, Vol. 28 Issue (6): 1085-1098   PDF    
http://dx.doi.org/10.1007/s13351-014-4022-6
The Chinese Meteorological Society
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Article Information

JIANG Zhihong, SHEN Yuchen, MA Tingting, ZHAI Panmao, FANG Sida. 2014.
Changes of Precipitation Intensity Spectra in Different Regions of Mainland China During 1961-2006
J. Meteor. Res., 28(6): 1085-1098
http://dx.doi.org/10.1007/s13351-014-4022-6

Article History

Received November 21, 2013;
in final form May 4, 2014
Changes of Precipitation Intensity Spectra in Different Regions of Mainland China During 1961-2006
JIANG Zhihong1 , SHEN Yuchen1, MA Tingting1, ZHAI Panmao1,2, FANG Sida1,3    
1 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science & Technology, Nanjing 210044;
2 Chinese Academy of Meteorological Sciences, Beijing 100081;
3 Wuhan Regional Climate Center, Wuhan 430074
ABSTRACT:The spectral characteristics of precipitation intensity during warm and cold years are compared in six regions of China based on precipitation data at 404 meteorological stations during 1961-2006. In all of the studied regions except North China, with the increasing temperature, a decreasing trend is observed in light precipitation and the number of light precipitation days, while an increasing trend appears in heavy precipitation and the heavy precipitation days. Although changes in precipitation days in North China are similar to the changes in the other five regions, heavy precipitation decreases with the increasing temperature in this region. These results indicate that in most parts of China, the amount of precipitation and number of precipitation days have shifted towards heavy precipitation under the background of a warming climate; however, the responses of precipitation distributions to global warming differ from place to place. The number of light precipitation days decreases in the warm and humid regions of China (Jianghuai region, South China, and Southwest China), while the increasing amplitude of heavy precipitation and the number of heavy precipitation days are greater in the warm and humid regions of China than that in the northern regions (North China, Northwest China, and Northeast China). In addition, changes are much more obvious in winter than in summer, indicating that the changes in the precipitation frequency are more affected by the increasing temperature during winter than summer. The shape and scale parameters of the Γ distribution of daily precipitation at most stations of China have increased under the background of global warming. The scale parameter changes are smaller than the shape parameter changes in all regions except Northwest China. This suggests that daily precipitation shifts toward heavy precipitation in China under the warming climate. The number of extreme precipitation events increases slightly, indicating that changes in the Γ distribution fitting parameters reflect changes in the regional precipitation distribution structure.
Keywordsprecipitation intensity distribution     different regions     Γ distribution    
1. Introduction

Changes in amount, frequency, and intensity ofprecipitation under the background of global warminghave caused widespread concern. Many studies indicated that the frequency and intensity of heavy precipitation events have increased in the past 30 years(Groisman et al., 1999; Alpert et al., 2002; Haylock and Goodess, 2004; Donat et al., 2013 ), and so is the dryspells with higher frequency and intensity, and longerduration, especially in the tropical and subtropical regions(Easterling et al., 2000; Groisman and Knight, 2008 ). Changes of precipitation intensity, frequency, and amount in China are also investigated by many researchers(Gong and Wang, 1999; Zhai et al., 1999, 2005 , 2007; Yan and Yang, 2000; Ma et al., 2003 , 2005; Dai et al., 2004; Jiang et al., 2007; Qian et al., 2007; Wang and Zhai, 2008 ). Their studies indicatean increasing trend in extreme precipitation and a decreasing trend in light precipitation in most regionsof China, and changes of precipitation intensity varyamong different regions.

Recently, Wu and Fu(2013) investigated thechanges of precipitation spectrum on different spatialscales and found a quasi-linear relationship betweenglobal temperature and precipitation. Wu and Fu(2013) also indicated that different precipitation intensities respond differently to temperature increase although all regions show a spectral shift from light precipitation to heavy precipitation. Overall, the precipitation spectral changes in different regions of Chinaunder the increasing temperature are similar to theobserved global changes. However, non-homogeneousl and surface coverage and topography can change thelocal energy, momentum, and water flux, as well as thewater vapor transport among regions. Thus, regionalprecipitation changes are associated with great uncertainty. Clearly, further research about the changes inthe distribution of precipitation intensity and its regional differences is required to determine the responseof China's precipitation to increasing temperature.

Statistically, climatic variables can be regardedas r and om variables, and changes in the precipitation intensity spectrum can be reflected by changesin the probability distribution pattern. The Γ distribution is one of the most commonlYused models todescribe the probability distribution of precipitation(Yao and Ding, 1990; Wilks, 1995 ). The probability density function depends on the shape(α) and scale(β)parameters of the Γ distribution function.Studying changes in the Γ distribution function parameters can improve our underst and ing of changes inthe distribution of precipitation intensity and providea basis for estimating future changes in the precipitation intensity spectra with global warming. Therefore, we use the complete daily precipitation data at404 meteorological stations 1)to study the spectralstructure of precipitation intensity in six different regions of China(Northwest China, Northeast China, North China, South China, Southwest China, and theJianghuai region), 2)to compare the spatiotemporaldifferences of precipitation intensity between differentregions under a colder and warmer climate, and to re-flect possible changes of the spectral structure of precipitation under global warming. In addition, the ¡distribution is used to fit the daily precipitation distribution, to investigate the connection between changesin precipitation intensity spectra and changes in probability distribution function parameters, and eventually to improve our overall underst and ing of precipitation changes in various regions of China under thechanging climate.2. Data and methods2.1 Data

The observation data used in the present studywere obtained from the Information MeteorologicalCenter, China Meteorological Administration. Dailyprecipitation data(1961-2006)cover 404 meteorological stations in six regions of China, including Northwest China(north of 36°N, west of 110°E), NortheastChina(42°-52° N, 115°-135°E), North China(35°-42°N, 110° -120°E), the Jianghuai region(28°-34°N, east of 110° E), South China(Fujian, Guangdong, Guangxi, and Hainan), and Southwest China(southof 29°N, 97° -104°E). The distribution of 404 stationsis shown in Fig. 1. Table 1 contains the basic information for each study region, including the averageannual precipitation and number of days of precipitation.

Fig. 1. Distribution of the meteorological stations in six regions of China.
Table 1. Basic information for the meteorological stations in each region

The global temperature data include the meanglobal temperature anomaly data(1961-2006)thatare provided by NOAA(http://www.ncdc.noaa.gov/oa/ncdc.html).2.2 Methods2.2.1 Determining daily precipitation level thr esholds

To account for the regional differences and nonuniform precipitation, the multi-year precipitationdata from each station that are greater than or equalto 0.1 mm are sorted in ascending order. In addition, precipitation intensity of each percentile is determinedbYusing the threshold method proposed by Bonsal et al.(2001) . In the present paper, daily precipitationintensities are divided into 12 levels, i.e., 0-10%, 10%-20%, : : :, 90%-95%, 95%-99%, and 99%-100%. Precipitation intensity below 10% is defined as extremelylight precipitation, and precipitation intensity above95% is defined as extremely heavy precipitation.2.2.2 Calculating the contribution r ates of differentprecipitation intensities

To compare the precipitation spectra of variousregions, we calculate the percentage of the number ofdifferent precipitation intensity days relative to the total number of precipitation days; this percentage isknown as the contribution rate of the number of daysfor a specific precipitation intensity. The percentageof the total amount of precipitation at the specific precipitation intensity relative to the total amount of precipitation is referred to as the contribution rate of thatspecific precipitation intensity.

When calculating the contribution rates of thenumber of different precipitation intensity days and the rates of precipitation intensity for each region, thearithmetic means of the contribution rates of each siteare used. The differences between the precipitationcontribution rates of different stations are reflected bythe value that is twice the st and ard deviation of thestations in each region.2.2.3 Selecting c old and warm years and verifying theprecipitation variation

Liu et al.(2009) showed that changes in the spectral structure of regional precipitation intensity are closely related to the global mean temperature. Therefore, to investigate the impacts of global warming onthe spectral structure of the regional precipitation intensity distribution, five of the coldest and warmestyears from 1961-2006 were selected according to themean global temperature anomaly sequence for thecomposite analysis. The five coldest years are 1964, 1976, 1974, 1965, and 1971, and the five warmest yearsare 2005, 1998, 2003, 2002, and 2006. The warmestyears occurred after the 1990s, and the coldest yearsoccurred during the 1960s and 1970s.

In this paper, the F-test is used to examine thesignificance of the differences of contribution rates ofthe precipitation(the number of precipitation days)for different precipitation intensities between warm and cold years(Wei, 2007 ).2.2.4 Fitting of the Γ distribution and estimating therelate d parameters

The probability density function of the Γ distribution is determined as:

The distribution function is defined as:
where α is shape parameter, and β is scale parameter.Note that α > 0 and β > 0 always hold. The smallerα is, the more skewed the Γ distribution is, and thesmaller the average daily precipitation intensity willbe. Given is constant, thevalue of β depends on the mean square error of thesequence. Smaller values of β correspond to less dispersed Γ distributions(Yao and Ding, 1990; Zhang and Ding, 1991 ).

The robust L-estimator(Yao and Ding, 1990; Cai et al., 2007 )is used to estimate the Γ distribution parameters, and the Kolmogorov-Smirnov(K-S)test isused to examine the fitness of the Γ distribution.3. Comparison of precipitation spectral characteristics between cold and warm years indifferent regions3.1 Precipitation sp e ctr al char acteristics

The total annual precipitation, annual numberof precipitation days, average daily precipitation intensity, and percentiles of differences between warm and cold years relative to the climatology in different regions of China are shown in Fig. 2. In North and Southwest China, the total annual precipitationis lower during warm years than cold years. However, in the Jianghuai region and South China, the total annual precipitation is greater during warm years thancold years. Both of these differences are significantat the 95% confidence level. Furthermore, the annual numbers of precipitation days in North China, theJianghuai region, South China, and Southwest Chinaare greater during cold years than warm years. Besides, the relative differences of the annual numbersof precipitation days in these regions are greater than14%(Fig. 2d). All six regions have greater averagedaily precipitation intensities during warm years. Thedifference is greater than 11% between cold and warmyears in the Jianghuai region, North China, SouthChina, and Southwest China(at a 95% confidencelevel). Thus, the precipitation in various regions ofChina is characterized by decreasing average precipitation days and increasing precipitation intensity, withincreasing temperature. In addition, except NorthChina and Southwest China, there is an increasingtrend of the average annual precipitation in Northwest China, Northeast China, the Jianghuai region, and South China.

Fig. 2. Basic characteristics of precipitation for the six regions of China during typical warm and cold years.(a)Totalannual precipitation, (b)annual number of precipitation days, (c)average daily precipitation, and (d)relative differenceof the amounts of precipitation between cold and warm years. The relative difference is the percentage of the differencebetween cold and warm years relative to the annual average, and the shaded areas indicate a 95% confidence level.
3.2 Contribution r ates of precipitation days and amount at different intensity levels3.2.1 Precipitation days

To investigate the changes in precipitation in different regions at different intensity levels under globalwarming, Fig. 3 shows a comparison of the contribution rates of precipitation days in various regionsof China between the typical warm and cold years.In North China, Northwest China, Southwest China, Northeast China, the Jianghuai region, and SouthChina, the contribution rates of light precipitationdays are smaller during warm years than cold years.However, the contribution rates of heavy precipitationdays are greater during warm years than cold years, with the different turning threshold generally occurring at an intensity of 20%-30%. The number of lightprecipitation days at the intensity less than 20%-30%significantly decreases during warm years. For precipitation with intensity greater than 20%-30%, the number of precipitation days during warm years increaseswith increasing precipitation intensity. In general, thedifferences in the amount of precipitation between cold and warm years are greatest when the precipitationintensity levels are greater than 80%(the corresponding daily precipitation is listed in Table 1). These dataindicate that with the increasing temperature, the frequency distribution of daily precipitation shifts toward heavy precipitation in various regions of China.

Fig. 3. Comparison of the contribution rates of precipitation days at different precipitation intensity levels betweenfive typical warm years(black solid line) and five typical cold years(gray dashed line)for the six regions during 1961-2006. The x-axis represents the percentiles of the precipitation levels, and the y-axis represents the contribution ratesof precipitation days. The * symbol indicates the value at the 95% confidence level. The dots represent the averagecontribution rates of various stations in the region at this level, and the vertical line represents the inter-station at twicethe st and ard deviation.

Regardless of the precipitation intensity(bothlight and heavy), the differences in contribution ratefor precipitation days between the cold and warmyears are greater in the Jianghuai region, SouthwestChina, and South China than in other regions. Inaddition, the difference between the number of precipitation days of precipitation intensity less than 10% and greater than 80% between cold and warm years has a confidence level that is greater than 95% inthe Jianghuai region, Southwest China, and SouthChina. This phenomenon is especially obvious in theJianghuai region(which has the greatest difference).In the Jianghuai region, the number of extremelylight precipitation days decreases by 62% during warmyears(Fig. 4a), while the number of extremely heavyprecipitation days(with intensity greater than 95%)increases by 40% during warm years(Fig. 4a). Thesechanges indicate that with increasing temperature, thereduced number of light precipitation days and increased number of heavy precipitation days are significant in the Jianghuai region, Southwest China, and South China. The vertical line in Fig. 3 representstwice the st and ard deviation of the contribution ratesof precipitation at various stations in the region. Asmaller st and ard deviation indicates a less dispersedcontribution rate of precipitation among stations inthe specific regions. Figure 3 indicates that the st and ard deviation of the contribution rates of extremelylight precipitation days is greater than that of heavyprecipitation days in all the six regions. These results indicate that the regional uncertainty of the contribution rates of extremely light precipitation daysis greater than that of heavy precipitation days. Inaddition, the differences in the contribution rates ofextremely light precipitation days between cold and warm years in the Jianghuai region and SouthwestChina are significantly greater than those in other regions. This finding indicates that the regional differences between warm and cold years are significant.

Fig. 4. Comparison of the contribution rate of(a)extreme light precipitation days to total precipitation days, and (b)heavy precipitation days to total precipitation days, during warm and cold years for the six regions of China.

Figure 4 shows a comparison between the relativechanges(in percentage)in the contribution rates of extremely light precipitation days and extremely heavyprecipitation days between cold and warm years during summer and winter in the six regions. The relativechanges between the cold and warm years in winterare significantly greater than that in summer in theJianghuai region, South China, and Southwest China.In the Jianghuai region, the number of extremelylight precipitation days in winter during cold years isless than in warm years by nearly 100%(the difference is approximately thrice greater than the differencein summer). In Northeast China, Northwest China, and North China, these differences are slightly greaterin summer than in winter(not significant). F or extremely heavy precipitation, the differences betweencold and warm years are greater in winter than insummer in Northeast China, the Jianghuai region, South China, and Southwest China. Especially, inthe Jianghuai region and South China, the number ofextremely heavy precipitation days in winter duringwarm years increases by 60% and 55%, respectively .In Northwest China, the difference is slightly greaterin summer than in winter(not significant). In NorthChina, extreme heavy precipitation days in winter increase by nearly 50% in warm years compared to coldyears, but an opposite trend is observed in summer, with a decreased number of heavy precipitation daysduring warm years compared to cold years. The comparison between winter and summer indicates that thedifferences between cold and warm years for light and heavy precipitation are more significant in winter thansummer for most regions, especially the Jianghuai region, South China, and Southwest China. These results suggest that the characteristics of decreased lightprecipitation days and increased heavy precipitationdays are more significant in winter in China under awarming background(i.e., the changes in the spectralstructure of precipitation in winter are primarily affected by the increasing global temperature whereassummer precipitation may be affected by additionalfactors)(Huang et al., 2008; Zhou et al., 2010 ).

In summary, in the context of global warming, the phenomena of decreasing light precipitation days and increasing heavy precipitation days occur in various regions of China. The threshold for these changesis generally observed when the precipitation intensity is in the 20th-30th percentile. The magnitudeof the daily precipitation frequency distribution shifttoward heavy precipitation varies from region to region. The characteristic of fewer light precipitationdays and more heavy precipitation days is particularlysignificant in the Jianghuai region, Southwest China, and South China. In most regions, this response is significantly greater in winter than in summer, which indicates that changes in the spectral structure of winterprecipitation are primarily affected by the increasingtemperature.3.2.2 Precipitation amount at different intensitylevels

Figure 5 shows a comparison of the contributionrates of different precipitation intensities in various regions between typical cold and warm years. Here, thedifferences in the precipitation contribution rates between cold and warm years in various regions of Chinaare obvious in the different contribution rates of heavyprecipitation. Except in North China, the contribution rates of heavy precipitation with intensity above90%(corresponding daily precipitation is listed in Table 1)are greater in warm years than cold years inNorthwest China, Northeast China, the Jianghuai region, Southwest China, and South China. The contribution rates of precipitation from moderate intensityto the intensity that is less than 80%-90% level areslightly less during warm years than cold years(Table 1). In North China, the contribution rates of precipitation with an intensity of less than 60%-70%(seeTable 1 for daily precipitation)or greater than 90%are less during warm years than cold years. However, the contribution rates of precipitation at otherintensities are slightly greater in warm years than coldyears. The differences in the precipitation contribution rates between cold and warm years are small forlight precipitation; however, the differences graduallyincrease with increasing precipitation intensity. Theregions with large differences between cold and warmyears include the Jianghuai region, South China, and Southwest China, indicating that there is an increasedcontribution of heavy precipitation to the total precipitation with the increasing temperature in these regions. In addition, the comparisons in Fig. 3 also showthat the difference in the contribution rates for precipitation days between cold and warm years is greaterthan the contribution rate of the precipitation amount.

Fig. 5. Comparison of the contribution rates of various precipitation levels in different regions from 1961 to 2006.The black solid line represents warm years, and the gray dotted line represents cold years. The x-axis represents thepercentile of precipitation levels, and the y-axis represents the contribution rate of the precipitation amount. The dotsrepresent the average contribution rates of various stations in the region at this level, and the vertical line represents theinter-station at twice the st and ard deviation. In order to clearly illustrate the turning point of different precipitationintensities between cold and warm years and heavy precipitation contribution, the non-equidistant coordinate axis isapplied in Fig. 5.

In summary, except in North China, the precipitation characteristics in the Jianghuai region, Northwest China, Northeast China, Southwest China, and South China show an increasing number of heavy precipitation days(with increasing heavy precipitation) and a decreasing number of light precipitation days(with decreasing light precipitation). The increasingamplitude of heavy precipitation days and heavy precipitation is positively correlated with the precipitation intensity(i.e., greater increase amplitude withgreater intensity). However, the turning thresholdsbetween cold and warm years for the number of precipitation days and the amount of precipitation areslightly different in different regions. The turningthreshold for the difference of precipitation days between cold and warm years generally occurs at theprecipitation intensity of 20%-30%, whereas it is 80%-90% for precipitation amounts. The difference is significantly greater for precipitation days than for theprecipitation amount. In North China, the precipitation characteristics are similar to the other regionsregarding precipitation days. However, when the precipitation intensity is less than 60%-70% or greaterthan 90%, the differences between cold and warm yearsare smaller during warm years than cold years, whileat other precipitation intensities, these differences aregreater in warm years than cold years. These resultsindicate that the responses of precipitation distribution spectra to global warming are different in different regions. With increasing temperature, the characteristics of a decreasing number of light precipitation days, an increasing number of heavy precipitation days, and increasing heavy precipitation are allmore significant in the warm and humid regions(theJianghuai region, South China, and Southwest China)than in the cold and arid(semi-arid)regions(NorthChina, Northwest China, and Northeast China). Inaddition, the changes in light precipitation and extreme precipitation are both more significant in winterthan summer, indicating that global warming has anincreasing effect on changes in the spectral structureof precipitation in winter than in summer. With theincreasing temperature, the distribution of the numberof precipitation days and precipitation amount displaycharacteristics of shifting to heavy precipitation, whichresults in an increasing number of heavy precipitationdays and heavy precipitation amount, and decreasingnumber of light precipitation days and light precipitation amount."

According to the Clausius-Clapeyron equation, the saturated vapor pressure increases at a rate of7% K-1 with increasing air temperature. Temperature rising directly increases the vapor content in theatmosphere, which increases the precipitation intensity(Trenberth, 1998 ). Therefore, it is reasonablethat with the increasing temperature, both the number of heavy precipitation days and heavy precipitation amount increase in most regions, which is alsoconsistent with previous research(Zhai et al., 2007; Zhu et al., 2009 ). A recent publication by Yu and Jian(2012) demonstrates that the relationship between extreme precipitation and temperature exhibits signifi-cant regional differences. With an increasing temperature in North China, the changes of extreme precipitation do not show a significant trend, which is related to the decreasing water vapor transport. In thesouth regions, however, the ample water vapor limitsthe changes in relative humidity, which increases theextreme precipitation. In addition to being affectedby air temperature, the decrease in light precipitationis also related to human activities, such as the aerosolemissions and the underlying surface changes. Recentstudies(Rosenfeld et al., 2008; Qian et al., 2009; Wu and Fu, 2013 )indicate that an increased amount ofatmospheric aerosols significantly increases the clouddroplet concentration in the atmosphere and decreasesthe radius of the cloud droplets. These changes inhibit precipitation, which might reduce the light precipitation and eventually convert light precipitation toheavy precipitation.4. Comparison of the daily precipitation Γ distribution in different regions between cold and warm years

From a statistical perspective, the changes in thecontribution rates of precipitation at different intensity levels reflect the changes in the probability density distribution function of precipitation. Therefore, we use the Γ distribution function to fit the distribution of daily precipitation and analyze the parametersof the distribution function to determine the statistical significance of changes in the contribution rates of different precipitation intensity levels.

The Γ distribution fitting is performed on thedaily precipitation data from 404 representative observ ation stations in China, and the goodness of fitis verified bYusing the K-S method. The daily precipitation distribution of all the stations fits the twoparameter Γ distribution. According to the definitionof the Γ distribution, changes in the shape parameter ff and scale parameter β influence the shape of the probability distribution function. When β is a constant and α increases, the skewness of the Γ distributioncurve decreases, indicating increasing daily precipitation. When α is a constant and β increases, the dispersion of the Γ distribution curve increases, indicating that extreme precipitation events tend to increase.Therefore, changes in the Γ distribution parameters indifferent climatic contexts can reflect changes in thespectral structure of the precipitation intensity .

The daily precipitation data are fitted with the Γ distribution function in the six regions of China for thefive warm and five cold years, respectively. The fit Γ distribution parameter of daily precipitation is set as ƒw(α, β)in the warm years, and ƒc(α, β)in the coldyears. In addition, the fit Γ distribution parameter ofdaily precipitation in the past 46 years is set as ƒs(α, β).

The change rate of the Γ distribution parametersis defined as 4.1 Changes in the shap e parameter

Figure 6 shows the distribution of the change ratesfor the shape parameter α of the daily precipitation Γ distribution in the six regions of China in the cold and warm years. Other than a few stations in Northeast China, Northwest China, and Southwest China, the value of α is greater in the warm years than coldyears for most of the stations. Among these regions, the Jianghuai region shows the greatest change in ffwith an average regional change of more than 20%.In the northeast and northwest regions, the changesin α are relatively small and generally less than 10%.In North China, South China, and Southwest China, the value of α increases by approximately 15%. Theseresults indicate that with the increasing temperature, the skewness of the daily precipitation Γ distributiondecreases for most of the stations in the six regions ofChina. In addition, the daily precipitation Γ distribution in various regions of China shifts towards heavyprecipitation and average daily precipitation intensitytrends to increase. In the Jianghuai region and SouthChina, the value of α significantly increases, meaningthat the shift of daily precipitation towards heavy precipitation is more significant, and the increases in theaverage daily precipitation intensity is greater. Theseresults are consistent with the analyses in previous sections.

Fig. 6. Spatial distribution of the change rates of the shape parameter α in the typical warm and cold years.
4.2 Changes in the sc ale parameter

The change rates of the scale parameter β for thecold and warm years in relation to the daily precipitation Γ distribution of various stations in the six regions of China are shown in Fig. 7. F or most stations, β is greater in warm years than cold years. However, relatively concentrated areas with decreasing β values occur in central North China, eastern Jianghuairegion, eastern Northwest China, and northern Southwest China. In terms of regional averages, the valueof β increases in all regions except for North China.The value of β increases the most in Northwest ChinabYup to approximately 15%. In Northeast China, theJianghuai region, South China, and Southwest China, the amplitude of β changes by approximately 5%. InNorth China, the change rate of β decreases by approximately -4.3%, which may be related to decadaldecreased changes in regional precipitation.

Fig. 7. As in Fig. 6, but for the scale parameter β

Compared with changes in α, changes in β aresmaller in all of the regions except Northwest China, which suggests that the increase of α for the daily precipitation Γ distribution plays an important role and dispersion increases slightly with global warming. Inaddition, these results indicate that the daily precipitation in various regions of China shifts towards heavyprecipitation and the number of extreme precipitationevents increases slightly with increasing temperature.These results are consistent with the above analyses.In Northwest China, changes in β are greater thanchanges in α, suggesting that the occurrence of extreme precipitation events increases in this region with global warming. In North China, the β value decreases slightly and dispersion decreases. In contrast, the value of α increases significantly, suggesting thatunder the warming, this region has an increasing precipitation intensity and decreasing number of extremeprecipitation events.5. Conclusions and discussion

The characteristics of the precipitation intensityspectrum in six regions of China(Northwest China, Northeast China, North China, the Jianghuai region, Southwest China, and South China)are analyzed based on the daily precipitation data from 404 meteorological stations in China from 1961 to 2006. Responses of the spectral structure of precipitation toglobal warming are investigated for different regionsin China. By fitting the daily precipitation distribution with the Γ function, changes in the shape(α) and scale(β)parameters of the Γ distribution functions ofdifferent regions during the cold and warm years arediscussed, and the following results are obtained.

(1)Under a warming background, the characteristics of precipitation in five regions(Northwest China, Northeast China, the Jianghuai region, SouthwestChina, and South China)show an increasing numberof heavy precipitation days as well as heavy precipitation amount, and decreasing number of light precipitation days as well as light precipitation amount.However, the turning threshold is slightly differentfor the changes in the number of precipitation days and precipitation amount. The turning threshold forthe difference of precipitation days between the cold and warm years generally occurs at precipitation intensities of 20%-30%, whereas for the total amountof precipitation, it occurs at precipitation intensitiesof 80%-90%. These results suggest that with the increasing temperature, the precipitation distributionshifts towards heavy precipitation for the number ofprecipitation days and precipitation amount. Thecharacteristics of the difference of heavy precipitation days in North China are similar to that in theother five regions; however, the contribution rate ofheavy precipitation with intensities of more than 90%is smaller in warm years than cold years.

(2)The responses of precipitation intensity spectrum to global warming differ from place to place.The characteristics of fewer light precipitation days, more heavy precipitation days, and more heavy precipitation are much more significant in the warm and humid areas(the Jianghuai region, South China, and Southwest China)than cold and arid(semi-arid)regions(North China, Northwest China, and NortheastChina). In addition, changes in light precipitation and extreme precipitation are significantly greater inwinter than summer.

(3)The results of the statistical analysis suggest that the daily precipitation of various stationsfit the two-parameter Γ distribution in NorthwestChina, Northeast China, the Jianghuai region, Southwest China, and South China. Under global warming, there are differences in the change rates of α and &bate;in the Γ distribution for different regions. However, the shape parameter α shows a significant increase, and scale parameter β shows a slight increase. Theseresults indicate that with the increasing temperature, in the Γ distribution, there is a shift of daily precipitation toward heavy precipitation and increaseddispersion in various regions of China.

In the present study, changes in the distributionstructure of the precipitation frequency in various regions of China are analyzed bYusing observ ationaldata and statistical modelling. Because there aredifferences in the factors(moreover, the factors alsodiffer from region to region)that affect changes in theprecipitation spectrum, additional model validation and theoretical explanations are required.

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