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。     

2001-2010年石羊河流域上游TRMM降水资料的降尺度研究

在地形比较复杂的石羊河流域上游,基于2001-2010年TRMM3B43降水数据和1 km空间分辨率DEM数据,采用回归方程+残差法的插值方法,对石羊河流域上游10年平均TRMM3B43和2001、2007年两个典型干、湿年份的TRMM3B43数据分别进行降尺度操作,将空间分辨率由原来的0.25°×0.25°提高为1 km×1 km。利用研究区34个雨量站的观测数据作为"真实值",对2001-2010年的TRMM3B43和降尺度结果进行精度检验,结果表明:TRMM3B43降水数据整体上具有一定的可信度,但比地面站点观测的降水量偏小;TRMM3B43经过降尺度之后,数据在空间分辨率和精度方面都有一定程度的提高,其中10年平均TRMM3B43降尺度结果的精度要高于2001年(干旱),而2001年的降尺度结果精度又高于2007年(湿润);就单个雨量站而言,位于西部高海拔区域的站点的降尺度结果精度较高,而位于东部低海拔区域的站点的降尺度结果精度较低。     

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。     

基于多种高分辨率卫星数据的TRMM降水数据降尺度研究——以内蒙古地区为例

利用内蒙古地区2001~2010年42个站点实测降水数据作为“真值”,采用LOO（Leave-One-Out）交叉验证、多元逐步回归等方法,构建TRMM（Tropical Rainfall Measuring Mission）降水数据与地形及气候等要素之间的多元回归关系,在此基础上,利用回归值+残差值的方法,获得空间分辨率为1 km×1 km的TRMM年降水数据,并对降尺度TRMM数据进行精度检验。研究表明：① TRMM数据可用于区域年降水量估计,且与实测年降水量呈显著线性关系;② 通过建立不同年份、不同空间分辨率TRMM数据与其它遥感数据的多元统计模型,研究发现在中尺度下TRMM与观测年降水数据拟合效果较好,且在空间分辨率为0.50°×0.50°时的拟合效果最好;③ 降尺度分析提高了TRMM数据对研究区降水时空特征的描述能力,确定性系数、标准误差和偏差均有明显改善,表明降尺度算法在将TRMM降水数据空间分辨率提高到1 km×1 km的同时,并能提高降水数据的精度。     

TRMM降水数据在中天山区域的精度评估分析

 遥感降水产品能反映降水的时空分布变化,对于资料稀缺的西北干旱区生态水文研究有重大意义。TRMM卫星降水资料在热带湿润地区有大量应用,但要将其用于我国西北干旱半干旱气候地区,还需对该数据产品在质量进行评估。选择干旱区内陆的新疆天山中部为研究区,并以周边15个台站的实测数据为依据对TRMM3B42降水数据质量进行评价。结果表明：（1）TRMM3B42数据对日降水事件的估计准确率较低,但是总体上暖季好于冷季,相对于较大的降水,对发生量小的降水估计更为准确;在暖季高估量小降水,低估量大降水,冷季则相反;（2）月降水情况来看,天山南坡两站与北坡的规律不符;对北坡山区降水估计的精度好于平原区,并且精度与海拔呈抛物线分布,降水越大的区域精度越高;偏差量的年内分布在各海拔区域之内一致性较好,但区域之间规律各有特点;（3）从年降水量来看,TRMM降水整体低于站点观测值,并且差量随着高程具有抛物线分布的特征。总之,该降水产品的质量总体上不高,但是其偏差在时间和空间上具有一定的规律性,该数据在干旱区的应用需要进一步校准处理。     

TRMM卫星降水数据在川渝地区的适用性分析

在地形复杂的川渝地区,利用72个气象站点的实测降水数据对TRMM(Tropical Rainfall MeasurementMission)卫星降水数据的精度分别在年、季和月尺度上进行验证,并进一步分析了高程和坡度对月尺度验证结果的影响,同时借助主成分分析法,对比了高程与坡度对TRMM 3B43降水数据的影响程度.结果表明:TRMM3B43估算的年降水量在川渝地区平均偏高5.38％,其中西部高原区估算结果比中东部地区相对精确.TRMM3B43与气象站点的季尺度降水数据拟合优度较高,但各季拟合优度之间存在差异,其中春季降水的拟合优度高于其余季节.而TRMM 3B43的月数据与站点实测降水数据拟合优度R2=0.7615,相关系数R=0.87,表明两者之间相关性显著,数据精度较高;就单个站点而言,大部分站点相关系数较高,误差较小,但叙永站相关系数相对较低,小金、雅安、雷波、盐源以及攀枝花站点数据误差相对较大.高程对数据精度的影响较坡度大,且呈现三次非线性回归的变化特征,随着高程的升高,R呈现增大的变化趋势,|Bias(％)|则呈现出增大—减小—增大的变化趋势;坡度对降水数据精度的影响相对较小且变化规律也较复杂,整体上随坡度变化,TRMM 3B43数据精度受到明显的影响.     

基于TRMM 3B43产品的1998—2016年黄淮海平原降水时空特征研究

以黄淮海平原为研究区,基于59个气象站点的逐月降水数据,采用相关系数（R）、相对误差（BIAS）和均方根误差（RMSE）对TRMM 3B43降水产品的精度进行系统评估,揭示黄淮海平原降水的时空变化规律。研究表明：① TRMM 3B43产品对研究区内大部分气象站点存在轻微高估现象,总体上TRMM产品和站点数据在黄淮海平原的拟合效果较好,且月尺度的精度较年尺度高;② 1998—2016年黄淮海平原年降水和秋季降水增加明显,其余季节降水呈不同程度的减少趋势;③ 研究区降水在空间上呈从南到北递减的趋势,且南北降水差距较大。研究结果为卫星降水产品在中纬度地区水资源评估、农业生产和洪旱灾害等研究提供一定的参考。     

多源降水数据的小流域水文模拟效用评估

小流域是研究小微尺度水文水资源系统演变规律的理想对象，是用于计算河流产水产沙 的最小单元，是水文及水土流失研究与管理的最佳地域尺度。通过遥感技术，气候模式获得降水 数据，并驱动分布式水文模型，模拟和预测水文过程，是流域水文水资源研究的必然趋势。以 NO? AA-CPC-US 降水作为参照，在美国不同地区的 9 个小流域，评估卫星降水产品 PERSIANN，PERSI? ANN-CDR，TRMM-3B42V7，GPM-IMERG，雷达降水 StageIV 以及气候模式 ERA5 降水产品的精度， 并用这 7 种降水产品驱动 CREST 分布式水文模型，评估了 7 种降水产品的水文模拟效用。研究表 明：各降水产品与 NOAA-CPC-US 降水吻合程度从高到低，依次是 StageIV 雷达降水，PERSIANN- CDR 和 GPM-IMERG 次之，再次是 PERSIANN 和 ERA5，最后是 TRMM-3B42V7。各降水产品在美 国北部高纬度地区和西部山地等区域的小流域降水估算精度略低，在美国中部，南部，东部的小流 域有较好的降水精度。在水文模拟效用评估中，设定相同率定期，分别使用 7 种降水产品率定 CREST 模型参数，得到率定参数集后，在相同验证期对流域日径流过程进行模拟。结果表明：NO? AA-CPC-US 和 Stage IV 雷达降水在各小流域水文模拟中效果较好，在美国北部和西部地区，使用 PERSIANN，PERSIANN- CDR，GPM- IMERG，ERA5 降 水 进 行 水 文 模 拟 时 需 要 谨 慎 。 TRMM- 3B42V7 的小流域水文模拟效果不理想。     

基于TRMM数据的广西西江流域降水时空分布特征

以广西西江流域为研究对象,以TRMM数据为主要数据源,利用研究区15个气象站降水实测数据,使用相关系数、相对偏差和均方根误差对1998—2013年TRMM降水数据进行验证,并在此基础上对广西西江流域的降水时空分布特征进行分析,结果表明:1)TRMM 3B43降水数据与气象站点实测降水数据具有较好的一致性,年尺度和月尺度相关系数分别是0.79和0.92(α0.01),可以代表研究区实际降水情况;2)在降水时间分布上,1998—2013年间年降水量呈微弱的下降趋势,流域降水的季节分配不均匀,大部分降水集中在5至8月;3)在降水空间分布上,降水整体由东向西逐渐递减,春季(3—5月)的降水中心在流域东部,夏季(6—8月)移至西南部,秋季(9—11月)继续停留在西南部,冬季(12—2月)又移回东北部。     

祁连山TRMM降水数据降尺度不同方法比较研究

降水数据对研究山区陆面过程、水文模型、生态模型至关重要,而山区地形复杂降水数据获取困难,且TRMM (Tropical Rainfall Measuring Mission)降水数据空间分辨率难以进行小尺度区域降水研究。本文以祁连山为研究区,应用2005—2016年的TRMM降水数据,从不同时间尺度对TRMM降水数据在祁连山的适用性进行分析,利用多元逐步回归模型、地理加权回归模型、随机森林模型三种降尺度方法,分别建立了降水与高程、植被指数、纬度、经度、坡度、坡向的关系,获得1 km高分辨率的TRMM降尺度数据,并通过对比三种模型的降尺度结果来选取适用于祁连山的降尺度方法。结果表明:(1)TRMM降水数据适用于祁连山。TRMM降水数据和实测数据在不同时间尺度上具有显著的相关性,年、季、月相关系数分别为0.88、0.92、0.88。(2)三种降尺度模型都能有效地获得1 km高分辨率的TRMM降尺度数据,其中随机森林模型更适用于获取祁连山TRMM降尺度降水数据。(3)相比于原始TRMM降水数据,随机森林模型降尺度结果整体偏小,同时具有更高的空间分辨率和更小的偏差。本研究可以为进一步获取西部山地高空间分辨降水数据和开展水文研究提供参考与借鉴。     

中国西北干旱区TRMM遥感降水探测能力初步评价

西北干旱区雨量站点稀少且分布不均,为水文过程研究带来一定困难。TRMM遥感降水数据覆盖范围广、时空分辨率高,是很有潜力的降水替代品,但其在西北干旱区应用的可靠性需要评价。对TRMM网格降水量与地面实测降水量在日尺度和月尺度上进行比较,通过FBI（frequency bias index）、POD（probability of detection）、FAR（false alarm ratio）、偏差和相关系数等指标分析TRMM对降水的探测能力。结果表明：TRMM对降水的探测能力因区域、海拔和冷暖季而异,月时间尺度上TRMM对降水事件的发生频率和降水量的估计比日时间尺度更为准确,但二者探测能力都非常有限;76个格点中,日降水的[FBI]值都远离最优值1,POD值和FAR值则分别在0.72以下和0.37以上,离最优值较远,相关系数几乎都在0.4以下,只有14个格点的偏差在±10%之间,其余格点最大偏差高达389%。最多有9个格点的月降水[FBI]值达最优,14个格点的POD值达最优,24个格点的FAR值达最优,67个格点的相关系数在0.4以上,14个格点的偏差在±10%之间,只有极少数格点的全部指标都在可接受范围之内,多数站点是某些指标达最优值,而某些指标在可接受范围之外。总体来讲,TRMM遥感降水数据在西北干旱区难以直接应用,需要进一步纠正处理。     

Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China

The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission (TRMM) data with rain gauge data and further to use this TRMM data to drive a Distributed Time-Variant Gain Model (DTVGM) to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year (2001-2010) daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R² varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years (2001-2007) of data on daily hydrological processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamflow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.     

Spatio-temporal accuracy evaluation of MSWEP daily precipitation over the Huaihe River Basin,China: A comparison study with representative satellite- and reanalysis-based products

Multi-source weighted-ensemble precipitation (MSWEP) is one of the most popular merged global precipitation products with long-term spanning and high spatial resolution. While various studies have acknowledged its ability to accurately estimate precipitation in terms of temporal dynamics, its performance regarding spatial pattern and extreme rainfall is overlooked. To fill this knowledge gap, the daily precipitation of two versions of MSWEP (MSWEP V2.1 & V2.2) are compared with that of three representative satellite- and reanalysis-based products, namely the Tropical Rainfall Measuring Mission (TRMM 3B42 V7), the climate prediction center morphing technique satellite-gauge merged product (CMORPH BLD), and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5). The comparison is made according to the dense daily rainfall observations from 539 rain gauges over the Huaihe River Basin in China during 2006-2015. The results show that MSWEP V2.1, MSWEP V2.2 and CMORPH BLD have better performance on temporal accuracy of precipitation estimation, followed by ERA5 and TRMM 3B42 V7. MSWEPs yield the most even spatial distribution across the basin since it takes full advantage of the multi datasets. As the weighted-ensemble method is independently carried out on each grid in MSWEPs, the spatial distribution of local precipitation is changed by different source data, which results in that MSWEPs perform worse than CMORPH BLD in terms of the representation of precipitation spatial pattern. In addition, the capability of MSWEPs to describe the spatial structure in the rainy season is lower than that in the dry season. Strong precipitation (≥100 mm/d) events are better represented in TRMM 3B42 V7 products than in MSWEPs. Finally, based on the comparison results, we suggest to improve the merging algorithm of MSWEP by considering the precipitation spatial self-correlation and adjusting the merging weights based on the performance of the source datasets under different precipitation intensities.     

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.     

基于GWR模型的陕西秦巴山区TRMM降水数据降尺度研究

应用TRMM降水数据,进行国内典型区域降尺度相关研究,可弥补应用气象站点数据研究带来的局限。以陕西秦巴山区为研究区,基于TRMM降水数据和NDVI数据,应用GWR模型和比例指数,获得GWR年、月降尺度数据并进行检验,最后分析地形对降尺度结果的影响。结果表明：获得的1 km分辨率的GWR降尺度降水数据,具有较强的细节表现能力;降尺度数据与实测降水数据年尺度上相关系数为0.88,月为0.93,相关性较好;与TRMM原始数据对比,降尺度结果降水值略小,整体低估降水;区内秦岭山地GWR降尺度结果精度变化幅度最小,相似地形条件下,海拔越高,GWR降尺度结果表现越好;采用GWR模型进行秦巴山区TRMM降水数据的降尺度研究,具有较强的适用性。     

An assessment of three satellite-based precipitation data sets as applied to the Thailand region

The study examines three satellite-based data sets to estimate long-term precipitation for the Thailand region: the Tropical Rainfall Mapping Mission (TRMM) 3B43, the Climate Prediction Centre morphing technique (CMORPH), and a locally developed regression model using the geostationary meteorological satellite (GMS) covering the Thailand region. Data for the first two sets were available at a spatial resolution of 0.25° × 0.25°, while the local regression model used data from the GMS at a resolution of 5 km × 5 km. The statistical regression model was developed by relating long-term monthly average precipitation from 27 rain gauge stations with concurrent satellite data in the visible and thermal infrared bands. The model was then tested against independent data from 27 rain gauge stations. Satellite/rain gauge ratios were estimated, and a smooth spline surface was used to correct the error from the model. Data from the three approaches were compared with a rain gauge network. The TRMM relation performed better than CMORPH, and the performance for GMS was comparable to TRMM with root mean square different and mean bias difference of 33.6 and 4.2%, respectively. The locally developed regression model was used to produce monthly and yearly total rainfall maps from the GMS data for the entire country.     

塔里木河流域TRMM降水数据精度评估

利用塔里木河流域24个气象站降水数据,分析了2000-2013年TRMM多卫星降水数据(TRMM 3B43 v7)在塔里木河流域的适用性。检验结果表明:全年来看,TRMM数据对研究区所有站点的年均降水量拟合较好(R²=0.8846),流域内24个站点平均年降水量相对偏差为19.02%,其中60%的站点表现为TRMM年降水量高于地面实测年降水量;月降水方面,除个别站点(于田、且末、乌恰)较差外,大部分站点的拟合度都较好;就季节而言:春季拟合效果最好,夏、秋季的TRMM数据存在低估问题,而冬季则偏高估;流域降水量由东南向西北递增,并在西北部边缘地区增加较显著,形成一个相对丰水带;而向沙漠腹地方向延伸的降水量则呈减少趋势。同时流域最大降水区域在一年中变化存在一定的规律。     

TMPA降水数据在澜沧江流域干旱监测中的评估(英文)

Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis (TMPA; 3B43 V.6) product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index (SPI), at the grid point (0.25°×0.25°) and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. (1) At the grid point spatial scale, in comparison with the monitoring results between rain gauges (SPI1g) and TMPA grid (SPI1s), both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index (CSI) are distributed in the middle stream of the Lancang River Basin. (2) The same as SPI1s, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. (3) At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. (4) At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate (underestimate) the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.