CMORPH和TRMM 3B42降水估计产品的评估检验

文章利用2007-2010年中国2447个站点的逐小时降水观测数据对同期CMORPH和TRMM 3B42卫星降水估计产品进行了检验和评估。经过对比分析得出:CMORPH和TRMM 3B42卫星降水资料与地面台站资料的日平均降水量空间分布具有较好的相似性,3 h降水量的相关系数在大部分地区分别在0.5和0.4以上;偏差均在±0.25 mm之间,但CMORPH存在显著的南北差异;平均绝对误差、相对误差和均方根误差均存在明显的季节周期性变化;两种卫星资料能够较好反映我国大部分区域夏季降水日变化特征,但在部分地区存在大的偏差;CMORPH和TRMM 3B42总空演率分别为7.23%和2.63%,总漏演率分别为3.25%和5.50%。

怒江上游TRMM 3B42V7降水产品资料时空验证及降水特征分析

利用1998-2013年热带测雨卫星TRMM 3B42V7降水数据产品和18个气象站点观测数据对怒江上游进行了降雨时空分布特征的对比分析,研究了TRMM 3B42V7数据产品在该区域的精度。结果显示:研究区内TRMM 3B42V7数据和站点数据相关性月尺度最强(R>0.9),年尺度次之(R>0.5),日尺度较差(R<0.5);流域面雨量两组数据在月尺度上有极强的相关性(R≈0.98),时间序列拟合较好,但在降水量大的月份TRMM 3B42V7数据较站点观测数据略偏大;不同时间尺度下两组数据的空间分布特征总体具有较好的一致性,局部分布特征有差异;流域西北和东南局部区域TRMM降水分别有低估和高估趋势,其他大部区域相当。利用TRMM 3B42V7数据对流域降水进行季节占比分析,结果显示,流域降水季节分配不均匀,夏季(6-8月)降水占全年降水总量的比例较大,高达42%~72%;其他春(3-5月)、秋(9-11月)、冬(12月至次年2月)三季节降水整体较少,总占比为28%~58%。

基于TRMM 3B42数据的1998-2010年中国暴雨时空特征分析

基于TRMM 3B42数据,构建5个年尺度时间序列参数,借助GIS空间分析和数学方法,揭示和分析1998-2010年暴雨降水的格局与过程特征。研究表明:13年来,年暴雨降水总量与年降水总量均呈缓慢下降的趋势,且空间格局相似,年暴雨降水比例时间波动较显著;暴雨集中分布区年降水以及年暴雨降水的时间波动均比较明显,年暴雨频次的时间波动较小但空间差异显著;暴雨降水空间分布在东西方向的差异性明显强于南北方向;年暴雨降水呈现向东北方向偏移的趋势;5个变量的变化趋势均表现出较强的空间差异性,且大部分像元呈增加(或减少)但统计不显著的趋势。

贵州高原地带TRMM 3B42卫星降水数据的精度评价

在下垫面相对复杂,位于高原地带的贵州,利用19个气象站点实测数据分别从年、季度、月和天时间尺度对TRMM 3B42卫星降水数据进行精度检验,并讨论TRMM 3B42卫星对不同降水强度的探测能力,以此来分析其在贵州的适用性。结果表明,TRMM 3B42降水数据在年尺度上拟合优度较好(R=0.82)。研究区内19个站点年均相对误差为-2.39%,其中将近70%的站点数据表现TRMM 3B42降水量低于地面气象站点。月尺度上整体相关系数很好,R达到0.89。但是TRMM 3B42卫星数据对不同季节的探测能力存在差异,其中,冬季相关系数最低。在日尺度上TRMM 3B42降水数据与实际降水偏差大,对降水强度过大或过小的降水情况均不能准确地探测。对于单个站点而言,海拔较低的站点TRMM卫星探测出的降水与实测降水偏差小。

基于小波多分辨率分析的环渤海地区TRMM 3B42数据校正

利用环渤海地区1998-2014年55个气象站点的日降水资料,基于小波多分辨率分析方法对TRMM3B42卫星降水产品进行订正,并分析订正后3B42数据的降水估算精度.结果表明：订正后的3B42数据与站点降水数据之间的相关系数显著提高,MAE、RMSE则明显降低;订正后的3B42数据对日降水事件的探测成功率得到提高,错报率有所下降;小波多分辨率分析方法有效提高了3B42数据对各季节,特别是冬季日降水的估算精度;但,订正后的3B42数据对日降水量仍存在一定的高估现象.

TRMM 3B42降水产品在洮河中上游的精度评估分析

基于洮河中上游2006-2016年气象站实测降水数据,在不同时间尺度上评估了TRMM 3B42 V7卫星产品在该区域的精度。结果表明:(1)研究区超过60%的降雨事件能被TRMM卫星探测到,综合评价指标ETS平均达到0. 31,体现了TRMM卫星在洮河中上游具备较好的降雨事件探测能力;TRMM产品在中雨和暴雨的尺度上探测能力表现最好。(2)TRMM数据和实测数据在日尺度的相关系数平均为0. 64,在降水量对比中,两者相差较小,精度较好;月尺度的精度比日尺度高,相关系数平均为0. 94;在月份差异上,温暖湿润的季节效果优于寒冷干燥的季节。(3)在年均和夏秋季节降水空间分布上,TRMM数据与站点实测降水的对应较好,两者均表现出洮河中上游降水西南多、东北少的趋势,且TRMM轻微高估了实测降水。以上结果表明了TRMM 3B42 V7降水产品在洮河中上游精度较高,对站点稀缺区具有重要的应用价值。

Observed Diurnal Cycle of Summer Precipitation over South Asia and East Asia Based on CMORPH and TRMM Satellite Data

The characteristics of the summer precipitation diurnal cycle over South Asia and East Asia during 2001–13 are investigated based on the high spatiotemporal resolution estimates of the CPC(Climate Prediction Center) Morphing(CMORPH) technique. The results show that summer precipitation over South Asia and East Asia possesses a remarkable diurnal cycle, with obvious regional differences. Over the coastal areas, plateau, and high mountains, summer precipitation peaks in the late afternoon; while over low altitude areas, such as valleys, basins, and inshore seas, it peaks during midnight to early morning. In addition to these general features consistent with previous studies, the high resolution CMORPH technique can depict finer regional details, such as the less coherent phase pattern over a few regions. Besides, through comparative analysis of the diurnal cycle strength and precipitation fields, the authors find that for humid areas the summer precipitation diurnal cycle is especially significant over Southeast China, the Sichuan Basin, Hainan Province, Taiwan Province, the Philippines, and Indonesia. And it is relatively weak over the south of Northeast China, central East China, Yunnan Province, the central Indian Peninsula, and most oceanic areas. Comparisons between two satellite datasets—those of the CMORPH and Tropical Rainfall Measuring Mission(TRMM) 3B42 products—are also presented. For summer precipitation and the main diurnal cycle features, the results from both products agree over most regions, except a few areas, e.g., the Tibetan Plateau.

CMADS、ITPCAS和TRMM 3B42 3套降水数据集在玉龙喀什河流域的适用性评价

我国西北地区地形复杂、环境恶劣、气象观测水平有限,在海拔较高的山区缺乏长期观测资料。再分析气象数据集(产品)基于气象卫星、数值模拟等技术,结合站点实测资料制作而成,具有时空分辨率高、可靠性好等优点,越来越多地被应用于大气水文相关的研究工作中。选择西北典型的高寒山区流域为研究对象,首先分析3套具有代表性的再分析气象数据产品(CMADS、ITPCAS和TRMM 3B42)降水资料在研究区年际和年内的分布情况,然后利用3套降水资料驱动SWAT水文模型,将模型模拟的结果与水文站实测径流资料进行比较,并进行参数率定和敏感性分析,从而分析3套数据集在研究区对降水的模拟效果。最终获得以下结论:3套降水资料在流域内的降水量分布情况存在较大差异,CMADS和ITPCAS数据集在降水总量上大于TRMM 3B42数据集,且CMADS数据集的年际降水和年内降水分布与冰川分布较为一致;3套再分析数据产品中,CMADS数据集驱动水文模型的模拟效果最好,逐日、月的NSE系数达到0.53、0.71,ITPCAS和TRMM 3B42数据集的NSE系数较低,径流模拟效果较差。

Spatial and temporal distribution of precipitation based on corrected TRMM data around the Hexi Corridor,China

Accurate rainfall distribution is difficult to acquire based on limited meteorological stations, especially in remote areas like high mountains and deserts. The Hexi Corridor and its adjacent regions （including the Qilian Mountains and the Alxa Plateau） are typical districts where there are only 30 available rain gauges. Tropical Rainfall Measuring Mission （TRMM） data provide a possible solution. After precision analysis of monthly 0.25 degree resolution TRMM 3B43 data from 1998 to 2012, we find that the correlations between TRMM 3B43 estimates and rain gauge precipitation are significant overall and in each station around the Hexi Corridor; however, the biases of annual precipitation differ in different stations and are seriously overestimated in most of the sites. Thus, Inverse Distance Weighting （IDW） interpolation method was used to rectify TRMM data based on the difference between TRMM 3B43 estimates and rain gauge observations. The results show that rectified TRMM data present more details than rain gauges in remote areas where there are few stations, alt- hough they show high coherence of distribution. Precipitation decreases from southeast to northwest on an annual and seasonal scale. There are three rainfall centers （〉500 mm） including Menyuan, Qilian and Toson Lake, and two low rain- fall centers （〈50 mm） including Dunhuang and Ejin Banner. Meanwhile, precipitation in most of the study area presents an increasing trend; especially in northern Qilian Mountains （〉5 mm/a）, Badain Jaran Desert （〉2 mm/a）, Toson Lake （〉20 mm/a） and Qingtu Lake （〉20 ram/a） which shows a significant increasing trend, while precipitation in Hala Lake （〈-2 mm/a） and Tengger Desert （〈-3 mm/a） demonstrates a decreasing trend.

TRMM 3B42降水产品在秦巴山区的适用性研究

利用1999~2016年秦巴山区范围内的81个气象站实测逐日降水资料,对TRMM 3B42卫星降水数据在秦巴山区的适用性进行了评估。结果表明:TRMM 3B42数据在月、季、年尺度上具有较高的精度,3~11月精度较高,1月略低,四季中冬季精度较低。TRMM所反映的降水变化过程与实测降水过程基本一致,但在降水量上存在一定差异,TRMM有略微高估降水的特征。按不同雨量等级对比,发现卫星资料对中雨及以上级别的降水具有较高的精度,无雨及小雨精度略低,原因是TRMM对0.1~0.9mm微量降水的探测能力较弱。无雨、小雨、暴雨日TRMM估计与站点实测具有相反的年际变化趋势,中雨、大雨日具有相同的年际变化趋势。研究结果对秦巴山区资料缺乏地区的气象过程研究具有重要的应用价值。

2000—2013年5—10月TRMM测雨产品3B42RT在浙江地区的评估检验

利用2000—2013年5—10月浙江省70个常规站逐小时降水观测资料来检验同期TRMM卫星3B42RT降水产品,尤其针对台风降水进行了评估。对比分析得出,2000—2013年5—10月3B42RT资料与台站观测资料在3 h、6 h、12 h和24 h 4个时间尺度上降水总量接近,两组数据呈显著正相关,相关系数随时间尺度的增大而加强,相关系数大值区位于浙江西部地区;无论是5—10月还是台风降水期间,3B42RT测雨资料的日变化特征与台站观测资料均较为一致,3B42RT能够准确抓到峰值出现的时间;台风期间3B42RT数据表征的全省降水普遍偏低,但与台站观测数据的相关性明显好于5—10月全时段,且相关系数大值区位于浙江东部沿海地区,台风前后时刻的3B42RT逐3 h降水量差值序列与台站观测降水量差值序列呈显著正相关,两组资料表征的降水量变化随时间的演变趋势较为一致。另外,选取2004年0414号台风"云娜"进行相关分析和基于目标诊断技术检验,发现3B42RT资料对降水的结构预报和实况相似度较高。

TRMM3B42在湖南省各流域2013年夏季降雨的时空分布及精度验证

根据湖南省流域的分布,将湖南省分为湘江流域、资江流域、沅江流域及澧水流域,将2013年5月至8月的TRMM3B42 V6逐三小时降雨数据与站点数据在这四个流域进行不同时间尺度上的对比分析,旨在验证TRMM3B42 V6能否准确反映这四个流域的降雨时空分布。结果发现三小时时间尺度上,3B42 V6数据高估了湘江、澧水流域的降雨量,低估了沅江、资江流域的降雨量。每日时间尺度上,3B42 V6探测到的降雨情形与三小时类似。在每月时间尺度上,3B42 V6能够探测到最大降雨的分布地区。当时间尺度是三小时和每日的时候,降雨多集中在25mm以下,3B42 V6对于大降雨的探测和降雨空间分布上存在着一定的不足。在湘江、资江流域随着时间尺度地增加,3B42 V6与站点的相关系数也在增加,其余两个流域的相关性变化则各自不同。

TRMM 3B42V7数据在岷江上游的季节尺度精度评估研究

降水作为全球水循环的关键过程,精确测量降水量在实际生产生活中有着重要的作用。因此,本文将以岷江上游为研究区域,选择其周围邻近12个站点,通过计算TRMM 3B42 V7数据与地面站点实际观测数据的均方根误差,相关系数,平均绝对误差、ETS、HKS、探测率和和空报率评分等指标,对TRMM 3B42 V7该降水产品的精度做出评价,研究结果表明:卫星反演降水结果在夏季的正确率较高,但除了冬季,在春、秋、夏季节都存在一定的高估现象。

Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China

Three high-resolution satellite precipitation products, the Tropical Rainfall Measuring Mission （TRMM） standard precipitation products 3B42V6 and 3B42RT and the Climate Precipitation Center＇s （CPC） morphing technique precipitation product （CMORPH）, were evaluated against surface rain gauge observations from the Laohahe Basin in northern China. Widely used statistical validation indices and categorical statistics were adopted. The evaluations were performed at multiple time scales, ranging from daily to yearly, for the years from 2003 to 2008. The results show that all three satellite precipitation products perform very well in detecting the occurrence of precipitation events, but there are some different biases in the amount of precipitation. 3B42V6, which has a bias of 21%, fits best with the surface rain gauge observations at both daily and monthly scales, while the biases of 3B42RT and CMORPH, with values of 81% and 67%, respectively, are much higher than a normal receivable threshold. The quality of the satellite precipitation products also shows monthly and yearly variation： 3B42RT has a large positive bias in the cold season from September to April, while CMORPH has a large positive bias in the warm season from May to August, and they all attained their best values in 2006 （with 10%, 50%, and -5% biases for 3B42V6, 3B42RT, and CMORPH, respectively）. Our evaluation shows that, for the Laohahe Basin, 3B42V6 has the best correspondence with the surface observations, and CMORPH performs much better than 3B42RT. The large errors of 3B42RT and CMORPH remind us of the need for new improvements to satellite precipitation retrieval algorithms or feasible bias adjusting methods.

Spatial Downscaling of the Tropical Rainfall Measuring Mission Precipitation Using Geographically Weighted Regression Kriging over the Lancang River Basin, China

Satellite-based precipitation products have been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these products has limited their application in localized regions and watersheds.This study investigated a spatial downscaling approach, Geographically Weighted Regression Kriging(GWRK), to downscale the Tropical Rainfall Measuring Mission(TRMM) 3 B43 Version 7 over the Lancang River Basin(LRB) for 2001–2015. Downscaling was performed based on the relationships between the TRMM precipitation and the Normalized Difference Vegetation Index(NDVI), the Land Surface Temperature(LST), and the Digital Elevation Model(DEM). Geographical ratio analysis(GRA) was used to calibrate the annual downscaled precipitation data, and the monthly fractions derived from the original TRMM data were used to disaggregate annual downscaled and calibrated precipitation to monthly precipitation at 1 km resolution. The final downscaled precipitation datasets were validated against station-based observed precipitation in 2001–2015. Results showed that: 1) The TRMM 3 B43 precipitation was highly accurate with slight overestimation at the basin scale(i.e., CC(correlation coefficient) = 0.91, Bias = 13.3%). Spatially, the accuracies of the upstream and downstream regions were higher than that of the midstream region. 2) The annual downscaled TRMM precipitation data at 1 km spatial resolution obtained by GWRK effectively captured the high spatial variability of precipitation over the LRB. 3) The annual downscaled TRMM precipitation with GRA calibration gave better accuracy compared with the original TRMM dataset. 4) The final downscaled and calibrated precipitation had significantly improved spatial resolution, and agreed well with data from the validated rain gauge stations, i.e., CC = 0.75, RMSE(root mean square error) = 182 mm, MAE(mean absolute error) = 142 mm, and Bias = 0.78%for annual precipitation and CC = 0.95, RMSE = 25 mm, MAE = 16 mm, and Bias = 0.67% for monthly precipitation.

Evaluation of TRMM 3B42 Precipitation Product Using Rain Gauge Data in Meichuan Watershed, Poyang Lake Basin, China

This study evaluated Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） product i.e. TRMM 3B42 data, using data from 52 rain gauge stations around the Meichuan watershed, which is a representative watershed of Poyang Lake basin in China. Both the latest Version 7 （V7） and previous Version 6 （V6） of TRMM 3B42 data were compared and evaluated for a 9-year period covering 2001-2005 and 2007-2010. The evaluations were conducted at different spatial （grid and watershed） and temporal （daily, monthly and annual） scales. For evaluation at grid scale, the Thiessen polygon method was used to transform pointed-based rain gauge data to areal precipitation at the same grid scale （0.25°） as TRMM 3B42 data. The results showed that there was little difference in performances of V6 and V7 TRMM 3B42 products. Overall, both V6 and V7 products slightly overestimated precipitation with a bias of 0.04. At daily scale, both V6 and V7 data were considered to be unreliable with large relative RMSE （135%-199%） at the two spatial scales, and they were deficient in capturing large storms. These results suggest that local calibration with rain gauge data should be conducted before V6 and V7 TRMM 3B42 data are used at daily scale. At monthly and annual scales, V6 and V7 TRMM 3B42 data match the rain gauge data well （R2=0.91-0.99, relative RMSE = 4%-23%） at both grid and watershed scale and thus have good potential for hydrological applications.

TRMM卫星降水反演数据在珠江流域的适用性研究——以东江和北江为例

为评估最新一代TRMM 3B42-V7卫星降水反演数据产品在珠江流域的精度和适用性,选取位于珠江流域下游的东江和北江流域为研究区域,基于地面雨量站点数据评估了该产品的精度和适用性,并结合可变下渗容量(Variable Infiltration Capacity,VIC)水文模型进行了水文模拟验证。对比分析结果表明,在网格尺度上,大多数网格日尺度相关系数达到0.60以上,月尺度相关系数达到0.90以上,3B42-V7产品表现出较好的精度,在区域尺度上精度得到了进一步提高;水文模拟验证分两种情景下进行,情景Ⅰ的结果表明,当水文模型由地面雨量站点数据率定时,3B42-V7产品数据的水文模拟效果不佳,个别区间内存在对洪峰流量明显的低估;情景Ⅱ的结果表明,由3B42-V7产品数据重新率定水文模型时径流模拟效果有了较大改善,说明该产品可在一定程度上作为资料缺乏地区的降水数据来源。

基于TRMM卫星产品的长江流域降水精度评估

卫星降水产品在降水空间格局分析中扮演着重要角色。为分析卫星降水产品在长江流域的应用精度,利用2003~2010年长江流域175个雨量站实测降水资料检验了同期TRMM(Tropical Rainfall Measurement Mission)降水产品3B42 RTV7及V7的精度。结果显示:(1)长江流域年平均降水总量从东南向西北呈现明显的梯度变化,年降水量从2 000 mm/a减少到400 mm/a,降水空间差异极大,时间分布也不均。(2)RTV7和V7降水产品能够捕捉到长江流域降水空间分布格局,尤其是V7在长江流域有较高的精度,对59.85%流域面积的估算偏差在-10%~10%之间;实时产品RTV7在长江上游存在明显的高估现象,偏差大于50%的流域面积高达33.51%。(3)长江中下游RTV7和V7日降水数据与对应的实测数据相关系数都大于长江上游地区,偏差更小。(4)RTV7和V7降水产品在丰水期的估算精度整体优于枯水期。

湘江流域TRMM降水数据精度检验

数据精度检验是卫星遥感降水数据应用中的关键问题之一。目前对TRMM数据精度检验多以偏差和相关性分析等方法为主,对不同雨量等级的估计检验比较缺乏。针对湘江流域,引入模糊综合评分方法以解决不同雨量等级降水估计的检验,同时利用泰森多边形法、模糊综合评分方法、相关系数法和散点斜率法,以研究区内14个气象站点实测降水数据为"真值",对TRMM 3B42降水数据在日、月尺度分别进行了定性和定量精度检验。结果表明:研究区TRMM 3B42降水数据在月、日尺度上相关系数分别达到了0.93、0.48,前者偏差值Bias比后者低84%,精度更优;在不同降水量级的预测中,精度由好到差依次为小雨、暴雨、大雨、中雨,其中小雨预报精度最好,达到良好水平,其他雨量级预报精度为中等水平。

TRMM降水数据在沙溪流域的精度验证

以闽江沙溪流域2008—2012年水文站及雨量站的实测降水资料为基准数据,利用探测率、击中率、Heidke技巧评分指数、模糊评分、统计参数、降水重心等指标,对热带降水测量卫星(TRMM)的3B42V6和3B42V7两种降水产品进行精度检验和分析。结果表明:日尺度上,TRMM数据在多数情况下能比较准确预报降水是否发生,两种TRMM降水数据的探测率Pd、集中率FH、Heidke技巧评分指数的平均值都超过0.55,3B42V7的漏报率和空报率比3B42V6均有所降低;两种TRMM降水数据在不同降水量级的预测中精度由好到差依次为小雨、暴雨、大雨、中雨,其中小雨预报精度最好,达到良好水平以上,3B42V7的效果更好一点;两种TRMM数据与实测数据的一致性都比较好,其中3B42V6的数据均方根误差、偏差、相关系数都更小;月尺度上,3B42V6降水数据呈现旱季偏差大、雨季偏差小的特征,而3B42V7数据在全年的偏差都较小;年尺度上,两种TRMM数据的降水重心位置与实测数据的降水重心位置十分接近,纬度方向的变迁路径一致,TRMM数据的空间分布与实测数据比较吻合。