Evaluation of Tropical Rainfall Measuring Mission (TRMM) satellite precipitation products for drought monitoring over the middle and lower reaches of the Yangtze River Basin,China

Drought is one of the most frequent and widespread natural disasters and has tremendous agricultural, ecological, societal, and economic impacts. Among the many drought indices, the standardized precipitation index(SPI) based on monthly precipitation data is simple to calculate and has multiscale characteristics. To evaluate the applicability of high spatiotemporal resolution satellite precipitation products for drought monitoring, based on the Tropical Rainfall Measuring Mission(TRMM) products and station-based meteorological data, the SPI values at different time scales(1, 3, 6, and 12 months) were calculated for the period of 1998–2016 in the middle and lower reaches of the Yangtze River Basin(MLRYRB). The temporal correlations show that there is a high degree of consistency between calculations at the different time scales(1, 3, 6 and 12 months) based on the two data sources and that the amplitude of fluctuations decreases with increasing time scale. In addition, the Mann-Kendall(MK) test method was applied to analyze the trends from 1998 to 2016, and the results suggest that wetting trends clearly prevailed over drying trends. Moreover, a correlation analysis of the two data sources based on 60 meteorological stations was performed with the SPI values at different time scales. The correlation coefficients at the short time scales(1, 3, and 6 months) are all greater than 0.7, and the correlation coefficient at the long time scale(12 months) is greater than 0.5. In summary, the results demonstrate that the TRMM 3 B43 precipitation product provides a new data source that can be used for reliable drought monitoring in the MLRYRB.     

中国干旱灾害评估与空间特征分析(英文)

Based on the monthly precipitation data for the period 1960-2008 from 616 rainfall stations and the phenology data of main grain crops,the spatial characteristics of drought hazard in China were investigated at a 10 km×10 km grid-cell scale using a GIS-based drought hazard assessment model,which was constructed by using 3-month Standard Pre-cipitation Index (SPI).Drought-prone areas and heavy drought centers were also identified in this study.The spatial distribution of drought hazard in China shows apparent east-west dif-ference,with the eastern part of China being far more hazardous than the western part.High hazard areas are common in the eastern and central parts of Inner Mongolian Plateau,the central part of Northeast China Plain,the northern part of Heilongjiang,the southeastern part of Qinghai-Tibet Plateau,the central and southern parts of Loess Plateau,the southern part of North China Plain,the northern and southern parts of Yangtze River Plain,and Yun-nan-Guizhou Plateau.Furthermore,obvious differences in drought hazard were found both within and between different agricultural zonings.     

雅鲁藏布江流域降水中氧稳定同位素的时空变化

This paper reveals the temporal and spatial variations of stable isotope in precipita-tion of the Yarlung Zangbo River Basin based on the variations of δ18O in precipitation at four stations (Lhaze,Nugesha,Yangcun and Nuxia) in 2005. The results show that δ18O of pre-cipitation has distinct seasonal changes in the Yarlung Zangbo River Basin. The higher value of δ18O occurs in spring prior to monsoon precipitation,and the lower value occurs during monsoon precipitation. From the spatial variations,with the altitude-effect and rainout process during moisture transport along the Yarlung Zangbo River Valley,18O of precipitation is gradually depleted. Thus,δ18O of precipitation decreases gradually from the downstream to the upstream,and the lapse rate of δ18O in precipitation is approximately 0.34‰/100m and 0.7‰/100km for the two reasons. During monsoon precipitation,spatial variation of δ18O in precipitation is dominated by the amount effect in the large scale synoptic condition.     

1956-2000年云南红河流域径流的时空分布

This paper studies the variation of runoff of Red River Basin and discusses the influence of＂corridor-barrier＂functions of valleys and mountains on variation of runoff by using GIS and statistic methods based on the monthly precipitation,temperature and evaporation data from 1960 to 2000 at 32 meteorological stations in Red River Basin,and the annual runoff data of Yuanjiang River,Lixian River and Panlong River from 1956 to 2000.The results show out：（1）Under the effect of＂corridor-barrier＂functions of valleys and mountains in Red River Basin,the patterns of annual precipitation and runoff depth distribution in spatial change a NW-SE direction,which is similar with the trend of the Red River valley and Ailao mountains.（2）In the long temporal scale averaged over years,the most obvious effects of the＂corridor-barrier＂functions is on runoff variation,and the second is on the precipitation, but not obvious on the temperature.（3）Under the superposed effect of climate changes and the＂corridor-barrier＂functions of valleys and mountains in Red River Basin,the difference of runoff variation is obvious in the east-west direction：the runoff variation of Yuanjiang River along the Red River Fault present an ascending trend,but the Lixian River on the west side of the Fault and the Panlong River on the east present a descending trend;the annual runoff in Yuanjiang River and Panlong River had a quasi-5a periods,and Panlong River had a quasi-8a periods;the runoff variation are quite inconsistent in different periods among the three river basins.     

Temporal and spatial variations of δ^18O in precipitation of the Yarlung Zangbo River Basin

This paper reveals the temporal and spatial variations of stable isotope in precipitation of the Yarlung Zangbo River Basin based on the variations of δ^18O in precipitation at four stations （Lhaze, Nugesha, Yangcun and Nuxia） in 2005. The results show that δ^18O of precipitation has distinct seasonal changes in the Yarlung Zangbo River Basin. The higher value of δ^18O occurs in spring prior to monsoon precipitation, and the lower value occurs during monsoon precipitation. From the spatial variations, with the altitude-effect and rainout process during moisture transport along the Yarlung Zangbo River Valley, δ^18O of precipitation is gradually depleted. Thus, δ^18O of precipitation decreases gradually from the downstream to the upstream, and the lapse rate of δ^18O in precipitation is approximately 0.34‰/100m and 0.7%J‰/100km for the two reasons. During monsoon precipitation, spatial variation of δ^18O in precipitation is dominated by the amount effect in the large scale synoptic condition.     

2000–2011年三江源区植被覆盖时空变化特征(英文)

The Three-River Headwaters Region(TRHR), which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological security of China. Because of climate changes and human activities, ecological degradation occurred in this region. Therefore, "The nature reserve of Three-River Source Regions" was established, and "The project of ecological protection and construction for the Three-River Headwaters Nature Reserve" was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following:(1) In the past 12 years(2000–2011), the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend.(2) Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure.(3) The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south.(4) The reverse characteristics of vegetation coverage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin.(5) The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature.(6) The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project.     

Impacts of climate change and LULC change on runoff in the Jinsha River Basin

The climate change and Land Use/Land Cover(LULC) change both have an important impact on the rainfall-runoff processes. How to quantitatively distinguish and predict the impacts of the above two factors has been a hot spot and frontier issue in the field of hydrology and water resources. In this research, the SWAT(Soil and Water Assessment Tool) model was established for the Jinsha River Basin, and the method of scenarios simulation was used to study the runoff response to climate change and LULC change. Furthermore, the climate variables exported from 7 typical General Circulation Models(GCMs) under RCP4.5 and RCP8.5 emission scenarios were bias corrected and input into the SWAT model to predict runoff in 2017–2050. Results showed that:(1) During the past 57 years, the annual average precipitation and temperature in the Jinsha River Basin both increased significantly while the rising trend of runoff was far from obvious.(2) Compared with the significant increase of temperature in the Jinsha River Basin, the LULC change was very small.(3) During the historical period, the LULC change had little effect on the hydrological processes in the basin, and climate change was one of the main factors affecting runoff.(4) In the context of global climate change, the precipitation, temperature and runoff in the Jinsha River Basin will rise in 2017–2050 compared with the historical period. This study provides significant references to the planning and management of large-scale hydroelectric bases at the source of the Yangtze River.     

1975-2016年天山中段阿克苏河流域冰川变化分析（英文）

In this study, we analyzed glacier changes in the Aksu River Basin during the period 1975–2016, based on Landsat MSS/TM/ETM+/OLI imagery analysis and the Chinese Glacier Inventory(CGI). The results showed that the total number, area, and volume of the studied glaciers in the Aksu River Basin decreased by 202(7.65%), 965.7 km~2(25.88%), and 74.85–78.52 km~3(23.72%–24.3%), respectively. The rate of glacier retreat in the basin was slower in the north, northwest and west, but reached the highest in the east(measuring 0.86% yr~(-1)). Furthermore, there were significant regional differences in the distribution and change of glaciers, the Kumalak River Basin had the largest glacier number and area, about 63.15% and 76.47% of the studied basin, and the rate of glacier retreat in the Kumalak River Basin was 0.65% yr~(-1), it was higher than the Toxkan River Basin which reached 0.57% yr~(-1). We found the shrinkage rate of glacier for different periods in the past 41 years, during 1975–1990 the glaciers showed the greatest retreat, while the rate of glacier area retreat slowed down significantly from 1990 to 2000. In recent 16 years since 2000, the rate of glacier retreat in the Toxkan River Basin was higher compared with 1990–2000. The RGI50~(-1)3.04920 glacier of Kumalak River Basin had been in a state of retreat since 1990. Over the past 41 years, the temperature and precipitation in the Aksu River Basin increased obviously, and the warming temperatures were clearly the main reason for glacier retreat in the region, while the increased precipitation in the mountain area may have a direct relation with the retreating rate of glaciers.     

三江源区径流演变及其对气候变化的响应(英文)

Runoff at the three time scales(non-flooding season,flooding season and annual period) was simulated and tested from 1958 to 2005 at Tangnaihai(Yellow River Source Region:YeSR),Zhimenda(Yangtze River Source Region:YaSR) and Changdu(Lancang River Source Region:LcSR) by hydrological modeling,trend detection and comparative analysis.Also,future runoff variations from 2010 to 2039 at the three outlets were analyzed in A1B and B1 scenarios of CSIRO and NCAR climate model and the impact of climate change was tested.The results showed that the annual and non-flooding season runoff decreased significantly in YeSR,which decreased the water discharge to the midstream and downstream of the Yellow River,and intensified the water shortage in the Yellow River Basin,but the other two regions were not statistically significant in the last 48 years.Compared with the runoff in baseline(1990s),the runoff in YeSR would decrease in the following 30 years(2010-2039),especially in the non-flooding season.Thus the water shortage in the midstream and downstream of the Yellow River Basin would be serious continuously.The runoff in YaSR would increase,especially in the flooding season,thus the flood control situation would be severe.The runoff in LcSR would also be greater than the current runoff,and the annual and flooding season runoff would not change significantly,while the runoff variation in the non-flooding season is uncertain.It would increase significantly in the B1 scenario of CSIRO model but decrease significantly in B1 scenario of NCAR model.Furthermore,the most sensitive region to climate change is YaSR,followed by YeSR and LcSR.     

Spatiotemporal changes in vegetation coverage and its driving factors in the Three-River Headwaters Region during 2000–2011简

The Three-River Headwaters Region （TRHR）, which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological secu- rity of China. Because of climate changes and human activities, ecological degradation oc- curred in this region. Therefore, ＂The nature reserve of Three-River Sou,＇ce Regions＂ was established, and ＂The project of ecological protection and construction for the Three-River Headwaters Nature Reserve＂ was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following： （1） In the past 12 years （2000-2011）, the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend. （2） Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure. （3） The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south. （4） The reverse characteristics of vegetation cov- erage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin. （5） The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature. （6） The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project.     

松花江流域季节性气象干旱特征及风险区划研究

利用松花江流域67个代表性气象站1960~2009年气象观测资料,采用标准化降水指数（SPI）为评价指标,计算松花江流域50 a中各季干旱指数,在此基础上分析了流域季节性气象干旱演变特征及规律,研究发现,松花江流域气象干旱呈现出明显的空间分带性和季节分带性。从地域变化来看,流域干旱区主要分布在东北、西南部;从季度变化来看,春旱和夏旱是流域气象干旱的主要类型,夏季干旱最严重,春季次之。建立评价指标体系实现了基于GIS技术的气象干旱风险区划,针对不同风险区提出相应的抗旱措施,为流域有效应对干旱灾害提供依据。     

2007-2016年四川省土壤干旱时空动态分析

四川作为农业大省,旱灾是导致农业减产最主要的因素。通过遥感和GIS手段进行四川省土壤干旱程度的时空分析,提高干旱的空间可视化程度,加强干旱监测的时效性尤为重要。本研究基于四川省2007—2016年逐季度的MODIS数据和1961—2011年40个气象站的月降水资料,采用温度植被干旱指数(TVDI)计算得到四川省干旱等级分布情况,辅以标准化降雨指数(SPI)进行相关性分析,并通过线性回归、反距离权重空间插值、GIS空间分析模型重建等方法,分析近十年来四川省地区以季度为时间尺度的土壤干旱时空变化特征,制作各时相土壤干旱分布图展示其微变化。结果表明:(1)在月时间尺度上,SPI-1与TVDI呈中等至强负相关关系,即TVDI值越小,SPI值越大,干旱程度越轻;验证结果表明TVDI都能够较好地对四川省的干旱空间分布状况进行反映。(2)四川省各区域、各季节干旱分布不均:空间上,干旱频发的区域集中在四川盆地及攀西南部区域。时间上,在春季,四川盆地区域的土壤干旱程度大致呈现加剧—持续—减缓的趋势;夏季,四川盆地的干旱变化趋势是加剧—减缓—加剧;秋季,四川盆地的干旱变化趋势是加剧—减缓—持续减缓;冬季,全川干旱程度变化不明显。本文的研究结果对四川省开展农业防灾减灾,引导农业灌溉具有指导意义。     

基于SPI指数的甘肃省河东地区干旱时空特征分析

干旱是西北地区主要的自然灾害之一。本文以甘肃省河东地区作为研究区,基于该地区38个气象站1971-2010年逐月降水数据计算标准化降水指数（SPI指数）,分析了不同时间尺度SPI指数的时间序列特征,探讨了SPI₃和SPI₁₂的年代际距平和倾向率的时空变化,以及特旱、重旱和中旱的发生频次。结果表明：（1）随着时间尺度的增加,SPI指数随机性在减弱,持续性在加强。干旱出现较多的时期为1991-2005年,出现较少的时期为1974-1982年。（2）20世纪80年代以前河东地区偏湿,90年代以后河东地区有偏干的趋势。河东地区行政区划分为7个部分,70-80年代,除甘南地区外,其余地区的SPI₃倾向率均显著增加;80-90年代,河东地区SPI₃倾向率持续减少,减少最明显的为定西地区;90年代到21世纪初,河东地区SPI₃倾向率又有增加趋势。对于SPI₁₂来说,自20世纪70年代到2010年,除甘南、陇南和天水地区的SPI₁₂倾向率为先减少后增加以外,其余地区均呈现先增加,后减小,然后再增加的趋势。（3）3个月时间尺度干旱的分布范围广,发生频次高,主要发生于河东地区的北部。12个月时间尺度的特旱主要发生在河东地区的北部,重旱和中旱主要发生在河东地区的东部。     

基于Meta-Gaussian模型的中国农业干旱预测研究

在全球气候变化背景下,干旱愈加频发,有效且可靠的农业干旱预测对于保障粮食安全和水资源安全具有重要意义。以标准化降水指数（SPI）和联合标准化土壤湿度指数（JSSI）分别表征气象干旱和农业干旱,以前期的气象干旱和农业干旱指数作为预测因子,在1~3个月预见期下基于Meta-Gaussian（MG）模型对中国1961—2015年6—8月的农业干旱进行预测,并采用Brier Skill Score（BSS）和纳什效率系数（NSE）评价MG模型的预测性能。结果表明：① 将1个月、3个月、6个月、9个月和12个月时间尺度的标准化土壤湿度指数（SSI）结合起来得到的JSSI能够对中国农业干旱的综合状况进行客观评价。② 以中国2010年和2014年遭受严重的干旱事件为例,预见期为1~3个月时,除新疆南部、青海西部以及内蒙古西部等沙漠地区外,MG模型对6—8月农业干旱预测结果的分布范围与实际干旱的分布区域较吻合,预见期越短,吻合越好。③ 预见期为1个月时,6—8月BSS ≥ 0.5的面积比例分别为0.714、0.642和0.640,NSE ≥ 0.5的面积比例分别为0.903、0.829和0.837,表明MG模型能够对中国大部分区域的农业干旱作出可靠的预测。本文结果可为中国农业干旱的监测、预警及干旱决策提供科学指导。     

MODIS干旱指数对华北干旱的敏感性分析

针对近年来干旱发生频繁的华北地区,通过利用2000-2009年MODIS数据和气象观测站降水资料,建立草地和农田距平植被指数(AVI)与不同时间尺度标准化降水指数(SPI)之间的相关统计模型,比较AVI和距平水分指数(AWI)对干旱响应的敏感性。结果表明：(1)植被生长季AVI与不同时间尺度SPI的相关关系不同。草地AVI与1个月尺度的SPI(即1-SPI)相关系数较低,而与3-SPI相关最显著;而农田区AVI与SPI的相关性较低,总体上农田AVI与3-SPI的相关性较高;(2) AWI与AVI类似,也对SPI存在时滞响应,均与3-SPI有着极显著的相关关系,并且在干旱发生较严重的6~8月份AWI与3-SPI的相关性好于AVI与3-SPI的相关性;(3)运用AWI反演的华北地区2009年夏季干旱分布图较好地反映了旱情的时空分布,与相关气象资料结果相符合。     

基于Copula函数的中国东部季风区干旱风险研究

利用1961~2016年的中国地面降水月值0.5°×0.5°格网数据集计算了中国东部季风区不同时间尺度的标准化降水指数,并结合游程理论识别气象干旱事件。常规的单变量和基于Copula函数的双变量频率分析分别用来描述干旱事件的干旱历时和干旱烈度。结果表明：① 3个月时间尺度和6个月时间尺度的干旱特征空间格局非常相似,但与12个月时间尺度的干旱特征空间格局差异较大;② 各时间尺度的干旱历时和干旱烈度均呈正相关,即具有较长干旱历时的地区往往也是干旱烈度较大的区域;③ 西南区、长江下游地区、黄淮海区北部和南部、内蒙古东部和黑龙江省东部干旱风险较高,而长白山地区、松嫩平原和珠江流域干旱风险较低。研究结果可为中国东部季风区的干旱区划及旱灾风险评估提供科学依据。     

澜沧江径流量变化与云南降水量场变化的相关性特征

为了考查气候变化对澜沧江-湄公河流域水文水生态环境变化影响的基本事实,文章以云南境内澜沧江的逐月径流量观测数据和云南的同期月降水量场观测数据为基础,应用相关系数的分析方法,研究了云南境内澜沧江径流量变化与云南降水量场变化的相关性特征。结论为:澜沧江的跨境径流量变化与云南的降水量场变化之间存在有十分显著的相关关系,澜沧江的跨境径流量变化主要是由于云南降水量场的变化造成的。总体来说,云南降水量场变化对澜沧江跨境径流量变化的影响在4个季节内都是显著的,其中显著性最好的是3~5月的春季,其次分别是6~8月的夏季和9~11月的秋季,较差的是12~2月的冬季。     

基于改进型TVDI在干旱区旱情监测中的应用研究

干旱是全球范围内影响最为广泛的自然灾害之一，其所导致的土壤沙漠化、荒漠化和盐碱化给生态环境造成不可逆的危害。通过对MODIS数据进行投影转换、去云等预处理的基础上，利用地形校正对TVDI模型进行改进，构建了改进型的温度植被干旱指数（mTVDI）用于新疆干旱区旱情监测。利用土壤实测数据对mTVDI及传统的TVDI模型进行对比验证。研究结果表明：（1） 利用EVI与校正后的LST构建的mTVDI_E对干旱区旱情的敏感度最高，与实测土壤水分数据的相关性R²为0.74。（2） 从空间上看，新疆2015年旱情分布以塔里木盆地和准噶尔盆地为两个干旱中心，旱情状况由严重逐步向周围山区递减至湿润状态。从时间上看，新疆6月、7月和8月旱情最为严重。（3） 研究利用TRMM降水数据对基于mTVDI_E反演的新疆旱情时空分布特征进行对比分析，结果表明二者所表现出的旱情时空分布较为一致，不同时间段内的降水量与mTVDIE之间具有一定的相关性，且均通过了P<0.01显著性检验。综上，基于TVDI所提出的mTVDI_E 能够有效开展新疆干旱区旱情监测，且精度较高，从而为今后定量化开展大区域尺度旱情监测研究提供参考。     

不同源降水数据在天山南坡阿克苏河流域适用性分析

降水是水热循环以及气候变化研究的重要环节,降水资料的准确与否直接影响流域尺度的水文过程研究。本文基于2000-2015年天山南坡阿克苏河流域气象站点观测降水数据,对比分析了Tropical Rainfall Measuring Mission（TRMM）降水数据集和Global Land Data Assimilation System（GLDAS）两种具有代表性的降水格网数据集在阿克苏河流域的适用性。结果表明：TRMM3B43数据在阿克苏河流域的整体表现优于GLDAS-2数据。两种数据的精度在月尺度上表现最优,相关系数分别为0.938和0.901,通过了0.01的显著性检验;在季节尺度,TRMM3B43数据各季节与站点插值的拟合度要优于GLDAS-2数据,但二者均呈现出高估冷季降水而低估暖季降水的趋势;在年尺度上,两种数据表现较差。在空间分布上,两种数据类型均能够反映出阿克苏河流域降水自西北向东南递减的空间分布趋势。并且两种数据在平原区的表现均优于山区,低估高海拔地区降水而高估低海拔地区的降水。     

基于机器学习模型的海河北系干旱预测研究

提高干旱预测精度能为流域干旱应对及风险防范提供可靠数据支撑,构建比选合适的干旱模型是当前研究的热点。研究以4个时间尺度（3、6、9、12月）标准化降水指数（SPI）为表征指标,利用小波神经网络（WNN）、支持向量回归（SVR）、随机森林（RF）三种机器学习算法分别构建了海河北系干旱预测模型,利用Kendall、K-S、MAE三种检验方法判定模型表现及其稳定性。研究表明：（1） WNN、SVR模型呈现结果在不同时间尺度SPI存在差异,WNN最适合12个月尺度SPI干旱预测;SVR最适合6个月尺度SPI干旱预测。（2） 对3、12个月尺度SPI,RF预测性能最优（Kendall>0.898,MAE<0.05）;对6、9个月尺度SPI,SVR预测性能最优（Kendall>0.95,MAE<0.04）。（3） 模型预测性能稳定性存在区别,RF预测稳定性最高,其次为SVR。（4） 构建的三种模型表现异同主要是因为SVR转为凸优化问题解决了WNN易陷入局部最优解的不足,从而提高了模型预测性能,RF集成多样化回归树,降低了弱学习器的负面影响,提高了模型预测准确率及稳定性,同时,RF处理包含噪声的降水数据的能力更强。