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.

A comparison of summer precipitation structures over the South China Sea and the East China Sea based on tropical rainfall measurement mission

The three-dimensional structures of summer precipitation over the South China Sea （SCS） and the East China Sea （ECS） are investigated based on tropical rainfall measurement mission （TRMM）. The primary results are as follows. First, both the convective and stratiform precipitation rates in the SCS are much higher than those of the ECS. The contribution of the convective cloud precipitation to the surface precipitation is primarily over the SCS and the ECS with a proportion of about 70%, but the contribution of convective cloud precipitation is slightly larger in the SCS than the ECS. The contribution of stratus precipitation is slightly larger in the ECS than that in the SCS. Second, the content of cloud particles and precipitation particles in the ECS in June was greater than that in the SCS, while in July and August, the content of cloud and precipitation particles in the ECS was less than that in the SCS. Third, the latent heat profile of the ECS is quite different from that of the SCS. In June, the peak values of evaporation and condensation latent heating rates in the ECS are greater than those in the SCS. In July and August, however, the peak values of evaporation and condensation latent heating rates in the ECS are about 0.05°/h less than those in the SCS.

A new procedure to estimate the rainfall erosivity factor based on Tropical Rainfall Measuring Mission(TRMM) data

Soil erosion by water is the most important land degradation problem worldwide.In this paper a new procedure was developed to estimate the rainfall-runoff erosivity factor(R)based on Tropical Rainfall Measuring Mission(TRMM)satellite-estimated precipitation data,which consists of 3-h rainfall intensity data.In this method,R was calculated as the product of the maximum 180-min rainfall intensity and the rainfall energy.This procedure was applied to the Daling River basin in Liaoning Province,China,R in terms of yearly,monthly and event-based rainfall in 2005 was computed separately using TRMM 3B42 data.The TRMM data showed a significant correlation with the interpolated rain-gauge data.Furthermore,because the TRMM data are based on rainfall intensity,they can represent the impact on erosion more accurately.It reflects both the spatial distribution and the intensity of rainfall.The procedure is a new approach to estimate the rainfall erosivity for soil water erosion modeling,especially in areas lacking rain-gauge stations.

Hydrological assessment of TRMM rainfall data over Yangtze River Basin

High-quality rainfall information is critical for accurate simulation of runoff and water cycle processes on the land surface. In situ monitoring of rainfall has a very limited utility at the regional and global scale because of the high temporal and spatial variability of rainfall. As a step toward overcoming this problem, microwave remote sensing observations can be used to retrieve the temporal and spatial rainfall coverage because of their global availability and frequency of measurement. This paper addresses the question of whether remote sensing rainfall estimates over a catchment can be used for water balance computations in the distributed hydrological model. The TRMM 3B42V6 rainfall product was introduced into the hydrological cycle simulation of the Yangtze River Basin in South China. A tool was developed to interpolate the rain gauge observations at the same temporal and spatial resolution as the TRMM data and then evaluate the precision of TRMM 3B42V6 data from 1998 to 2006. It shows that the TRMM 3B42V6 rainfall product was reliable and had good precision in application to the Yangtze River Basin. The TRMM 3B42V6 data slightly overestimated rainfall during the wet season and underestimated rainfall during the dry season in the Yangtze River Basin. Results suggest that the TRMM 3B42V6 rainfall product can be used as an alternative data source for large-scale distributed hydrological models.

Evaluation of Precipitation Datasets from TRMM Satellite and Down-scaled Reanalysis Products with Bias-correction in Middle Qilian Mountain,China

Accurate estimates of precipitation are fundamental for hydrometeorological and ecohydrological studies,but are more difficult in high mountainous areas because of the high elevation and complex terrain.This study compares and evaluates two kinds of precipitation datasets,the reanalysis product downscaled by the Weather Research and Forecasting(WRF)output,and the satellite product,the Tropical Rainfall Measuring Mission(TRMM)Multisatellite Precipitation Analysis(TMPA)product,as well as their bias-corrected datasets in the Middle Qilian Mountain in Northwest China.Results show that the WRF output with finer resolution perfonns well in both estimating precipitation and hydrological simulation,while the TMPA product is unreliable in high mountainous areas.Moreover,bias-corrected WRF output also performs better than bias-corrected TMPA product.Combined with the previous studies,atmospheric reanalysis datasets are more suitable than the satellite products in high mountainous areas.Climate is more important than altitude for the\falseAlarms'events of the TRMM product.Designed to focus on the tropical areas,the TMPA product mistakes certain meteorological situations for precipitation in subhumid and semiarid areas,thus causing significant"falseAlarms"events and leading to significant overestimations and unreliable performance.Simple linear bias correction method,only removing systematical errors,can significantly improves the accuracy of both the WRF output and the TMPA product in arid high mountainous areas with data scarcity.Evaluated by hydrological simulations,the bias-corrected WRF output is more reliable than the gauge dataset.Thus,data merging of the WRF output and gauge observations would provide more reliable precipitation estimations in arid high mountainous areas.

Evaluating a satellite-based sea surface temperature by shipboard survey in the Northwest Indian Ocean

A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature（SST）, and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager（TMI）, and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis（OSTIA）. The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile,the relative humidity shows the high correlation with the SST error for the OSTIA product.

Historical Satellite Data Analysis to Enhance Climate Change Adaption and Hydrologic Models in Egypt

Egypt suffers from the impacts of climate change. Adaption plans should solve the shortage in water resources and increase the use of renewable energy. Detailed data on rainfall as non conventional water and detailed data on potential renewable energy are important. The added value of this research is to investigate the suitability of satellite data locally in North Sinai in Egypt. The Tropical Rainfall Measuring Mission (TRMM) satellites and available data from ground rain gauges are studied at North Sinai of Egypt. Local multiplication factors and correlation equations on a monthly basis were developed based on short term historical data. General equation based on short term data was developed to enhance TRMM data for the rainy season to minimize spatial and temporal errors. This equation would be very useful, especially in the ungauged areas in North Sinai to adjust TRMM rainfall data. TRMM data are spatially distributed, so it enhances the hydrology models for runoff estimation. This runoff could be used as non conventional water resource. The runoff was estimated in the RasSudr area in the 2010 storm to be 3.6 (m3/s). The hydropower of this runoff was estimated and ranged from 15,135 to 57,352 (kWh). The solar energy is studied from (NASA) satellite data. The monthly averaged solar energy was estimated to get possible generated power from the solar panel at locations of rainfall ground stations. The generated solar energy would supply self-sufficient energy for ground stations measuring instruments rather than batteries. The results show that a small solar panel project of 200 (m2) could safe electric network power by generating about 20,385 (kWh/year). The results of this study could help in enhancing adapting plans for climate change and runoff estimation model that needs grid data, especially in the area lacking ground data.

基于TRMM卫星雷达降雨的流域陆面水文过程

利用热带降雨观测计划（TRMM）卫星雷达降雨数据驱动分布式陆面水文模型，研究流域尺度陆面水文过程，评估该数据在水文模拟与预报等研究领域的性能。通过与实测雨量资料比较，验证TRMM卫星雷达降雨数据的质量。分别将TRMM卫星雷达降雨与观测降雨作为耦合模型的气象输人，模拟和研究淮河流域1998～2003年的陆面水文过程时空变化。结果表明，TRMM卫星雷达降雨数据能够很好地描述降雨的时空分布，利用TRMM降雨模拟的结果与利用观测降雨模拟的结果精度相当；模拟流量与实测资料基本吻合。卫星雷达降雨数据在陆面水文过程研究中具有广泛的应用前景。

TRMM卫星降水数据在洣水流域径流模拟中的应用

采用地面雨量站点观测降水作为基准数据,评估热带降雨观测计划(TRMM)最新一代卫星降水产品3B42V7的精度;利用站点和卫星两种降水数据驱动栅格新安江模型,采用SCEM-UA算法考虑模型参数不确定性,进行流量过程模拟,评估TRMM 3B42V7在流域水文模拟和预报中的应用能力。数据精度评估显示:在平均意义上,TRMM 3B42V7日降水精度较高,较站点观测低估了6.68%;但在绝对值意义上,TRMM 3B42V7日降水精度较低,绝对偏差达到57.76%;TRMM 3B42V7经过了地面月降水量偏差校准,其精度在月尺度上有较大提高。径流模拟结果表明:TRMM 3B42V7模拟的日径流过程精度较低,有部分洪峰没有捕捉到,但仍能表征径流的日变化特征;月尺度上模拟径流与实测径流吻合较好,能表征径流的季节性和年内变化特征;计算的日尺度和月尺度95%置信区间包含大部分实测流量过程。

TRMM多卫星测雨数据在赣江上游径流模拟中的应用

选取赣江上游峡山站以上集水区域为研究区域,以雨量站观测数据为基准数据,评估热带降雨观测计划TRMM-3B42V6降水数据的精度,并采用上述2种降水数据驱动栅格型新安江模型,模拟赣江峡山站日流量和月流量过程.结果表明,尽管TRMM日降水数据较雨量站数据存在较大偏差,但采用TRMM降水数据模拟的日流量能基本再现峡山站的日流量过程;TRMM月降水数据精度较高,能够较为精确地模拟峡山站的月流量过程.因此TRMM月降水数据可应用于赣江流域的降雨-径流过程模拟,在无资料地区的水文预报、水资源估算、水资源评价与规划等相关研究领域具有广阔的应用前景.

中国大陆流域分区TRMM降水质量评价

根据中国境内2 257个气象站点1998—2013年逐日降水资料,结合流域分区,采用探测准确性、相关系数以及相对误差等指标,对热带降水测量(TRMM)降水精度和一致性进行系统评价。结果表明:1 TRMM日降水准确性从东南沿海向西北内陆递减;2气象站点年均降水日数显著大于TRMM年均降水日数;3西北片区以外气象站点降水量和TRMM降水量在月尺度和年尺度上均具有较好的相关关系;4各流域年均TRMM面降水量均高于气象站点面降水量,且TRMM面降水量相对误差雨季较小,枯季较大;5各流域TRMM面降水量与气象站点面降水量演变趋势基本一致,南方各流域年降水量均呈减少趋势,北方各流域年降水量均呈增加趋势,全国尺度上年降水量呈微弱的减少趋势。

赣江流域TRMM遥感降水对地面站点观测的可替代性

多卫星遥感降水产品为无/缺资料地区的水文过程模拟提供了新的数据来源。结合地面高密度雨量站网,在中国典型暴雨区赣江流域定量评估两种TRMM降水产品(3B42V7和3B42RTV7)的精度,并通过耦合分布式水文模型CREST,探讨了水文模拟中TRMM卫星降水产品对地面观测降水的可替代性。研究表明:3B42和3B42RT与地面观测流域平均月降水相关系数达到0.9以上,偏差在5%以内,日尺度上相关性略差,偏差略有增加。同时设计2种水文模拟对比试验:情景I为静态参数,使用地面雨量站降水率定模型参数,采用卫星降雨验证模型;情景II为动态参数,采用卫星数据重新率定模型参数,再利用卫星降雨验证模型。对比结果表明:情景II中完全使用TRMM降水后模型效果明显改善,证明TRMM卫星数据在赣江流域具有替代地面站点观测的潜力,但需要重新根据卫星降雨率定模型。

TRMM3B43降水产品在西藏地区的精度检验和应用

以西藏地区38个国家基准站和基本站的实测降水资料,利用双线性插值、相关系数、散点斜率和相对误差等指标,对热带降水测量卫星(TRMM)的3B43降水产品的精度进行检验和分析。结果表明:月尺度上,整体而言TRMM3B43降水产品与实测降水量具有较好的一致性,其中西藏西部和东部喜马拉雅山脉东段北麓地区相关性相对较差,平均相对误差较大。年尺度上TRMM3B43降水产品的相关性不如月尺度好,平均相对误差随统计数值的增大而减小。在应用TRMM3B43降水产品进行流域面雨量估算时,采用气象站点实测降水资料校准TRMM3B43降水产品的T-G联合法,对TRMM3B43降水产品进行订正。

TRMM测雨产品3B42与台站资料在中国区域的对比分析

本文利用2004—2008年6—8月中国673个气象站逐6小时降水资料检验同期TRMM测雨产品3B42的精度。经检验得出:卫星资料日平均降水和降水频率空间分布与台站资料非常类似,相关系数分别能达到0.79和0.84,降水频率与台站资料相比偏大;从日降水相关空间分布看,卫星资料在东部地区相关性较高,日降水相关系数都在0.6～0.9之间;从日降水和逐6小时降水平均绝对误差空间分布看,卫星资料在华南地区误差最大,长江流域次之;从中国8个区域逐6小时降水总量日变化看,卫星资料与台站资料有很好的一致性,但在华南地区20时降水量偏小;按不同雨量等级对比,发现卫星资料绝对误差相对百分率空间分布有如下特点:小雨全国普遍数值偏高,中雨东部部分地区偏大,大雨和暴雨整体上数值小于1;全国平均漏演率和空演率分别为10%和14%。

基于TRMM卫星降水的太行山区降水时空分布格局

基于TRMM 3B42V7数据,综合采用多元线性回归、偏最小二乘回归和地理加权回归3种方法,建立了太行山区卫星降水产品的降尺度校正模型,将遥感降水信息从0. 25°×0. 25°降尺度到0. 05°×0. 05°。在结果评估和优选的基础上,分析了"像元—集水区—全区"年、月降水的多时空尺度干湿季节分布和垂向分布特征,并从机理方面论证了研究的合理性。结果表明:①地理加权回归校正效果最优,可明显降低校正降水与实测降水系列的均方根误差和平均相对偏差且提高决定系数;偏最小二乘回归可降低两项误差,但对决定系数无提升;多元线性回归最差,各项指标均无改善。②处于夏季风迎风侧的东坡和南坡降水量普遍高于500 mm,背风侧的西坡和北坡降水量较低,最大年降水量位于东南坡海拔1 300～1 500 m的地带。③研究区7—9月降水量占全年的58. 7%,干湿季节降水量之比为1∶18,各集水区的变化范围为1∶13～1∶25。④季风风向影响降水中心的移动路径,各月降水量沿高程变化梯度区间为-5. 2～6. 7 mm/hm,且迎风坡降水的垂向分布更复杂。

基于TRMM降水数据的山区降水垂直分布特征

选择天山和祁连山区为典型区,利用台站降水数据验证以上两区多卫星降水数据（TRMM）精度的基础上,借助TRMM数据分析了所选山区年降水梯度效应,并探讨了天山及祁连山最大降水高度带。结果表明,多卫星降水数据在天山和祁连山区精度较高,天山及祁连山年降水量都明显受到海拔影响,降水随海拔升高而增加,但天山降水与海拔正相关关系最好,南、北和西坡相关系数分别为0.90、0.81和0.58,多年平均降水直减率分别为11.0mm/100 m、6.3 mm/100 m、7.4 mm/100 m,最大降水高度带则分别位于海拔2 200-3 500 m和3 200-3 700 m和3 000m左右;祁连山东、中、西段降水随海拔有增加趋势,但降水梯度效应在祁连山东段明显高于祁连山中西段地区,梯度效应由东向西呈现递减趋势,其最大降水带主要分布在东段4 000-4 500 m的高山带。

TRMM-3B43降水产品在新疆地区的适用性研究

为研究热带降雨测量计划卫星(tropical rainfall measuring mission,TRMM)-3 B43(简称"TRMM")降水产品在新疆地区的适用性,利用1998—2013年TRMM月降水量产品与新疆地区105个国家气象站点的降水观测结果,通过统计分析分别在年、季和月尺度上进行验证。结果表明:TRMM估算的年降水量与新疆地区实测降水具有很高的一致性(平均偏高5.29%);与气象站点实测的季尺度降水数据决策系数较高,相关系数均在0.7以上;与气象站点实测的月降水数据的相关系数为0.75,表明两者之间相关性较显著,数据精度较高。就单个气象站点而言,大部分TRMM降水数据与气象站点实测降水数据相关系数较高,误差在30%以内,整体相关系数达到0.81,说明TRMM降水数据与气象台站点实测降水数据的一致性较好;但TRMM降水产品在时间和空间上具有一定的偏差,使用中需要进一步订正。

TRMM月降水产品在西北内陆河流域的适应性定量分析

利用1998-2008年56个气象台站降水资料,结合TRMM月降水产品,通过对TRMM3B43降水数据在不同气候区、不同时空尺度的精度对比分析,探讨了卫星遥感反演降水产品在中国西北内陆河流域的适应性.结果表明:TRMM探测的月降水数据与实测月降水数据在整体上具有较好的一致性和线性相关性,相关系数为0.76,效率系数为0.58,其探测的降水量比观测值略大;TRMM在高原气候区月降水量的探测效果要优于在西风带区的;TRMM数据所反映的降水量的年内变化过程和实测降水量结果基本一致,但在具体的量上有一定的差异,表现为对降水相对集中的5-9月低估实测降水量,而在降水较少的10月-次年4月高估实测降水量,反映了TRMM对较大强度降水量的探测能力不足.流域多年平均降水量呈现南、北部大,中部小的格局,降水量的高值中心主要出现在高山地区,高达300 mm;而受西风环流影响的塔里木盆地东南面的且末-若羌一带、吐鲁番盆地和受高原区影响的柴达木盆地为极端干旱少雨区,降水量均不足100 mm.

TRMM数据在中国降雨侵蚀力计算中的应用

长时间序列降雨过程资料的获取一直是降雨侵蚀力计算中的一个难题。尝试利用地面实测站点数据分别对TRMM（Tropical Rainfall Measuring Mission）卫星的3B43和3B42数据进行回归建模和订正,并采用订正后的3 h平均降雨强度代替30 min最大降雨强度,同时基于TRMM数据的EI180的降雨侵蚀力算法,计算出了全国南北纬50°范围（TRMM覆盖区）内2013年月、季和年降雨侵蚀力;最后分别计算了省域和区域尺度下的降雨侵蚀力对全国尺度下的结果进行对比验证。结果表明：（1）TRMM降水数据比地面站点观测的降水量略大,但与实测站点数据具有很好的线性回归关系,其季尺度决定系数R2均较高,由此也说明了TRMM数据可以很好地反映全国范围内降雨的季节性变化。（2）利用订正后的TRMM3B42数据计算出研究区内的年均降雨侵蚀力为536.02 MJ·mm·hm-2·h-1·a-1,其降雨侵蚀主要集中在5-8月份。（3）2013年全国降雨侵蚀变化趋势由东南向西北方向逐渐降低,且沿海省份较内陆省份降雨侵蚀较高。（4）通过对年降雨侵蚀力结果与实测站点降雨量以及订正的TRMM降水数据分析表明,降雨侵蚀力与降水之间存在着紧密的二次非线性关系。（5）通过尺度验证,其中省域尺度验证误差为8.34%,区域尺度误差仅为0.24%,由此说明了TRMM数据在不同尺度下均具有良好的适应性,同时也验证了方法在不同尺度下的有效性。该方法为有效解决土壤侵蚀中降雨强度计算资料缺乏的瓶颈,同时也为降雨侵蚀力的计算提供了一条有效的途径。

基于TRMM卫星资料的渤海降水遥感估算研究

降水是全球能量平衡和水分循环中的关键要素,但海洋区域实时、准确的降水观测资料难以获取,因此,遥感卫星资料在海洋降水及全球能量和水分循环研究领域具有十分重要的应用前景。本文基于1998-2012年6个气象站点（岛屿或海岸带）的实测降水资料,评估TRMM（Tropical Rainfall Meas-uring Mission）V7版本3B42、3B43两个降水产品对渤海降水量的估算精度,在此基础上,分析并揭示渤海区域年、季和月降水量的时空特征。结果表明：在日尺度,3B42产品对渤海降水量的估算效果总体较差,而在月、年尺度,3B42、3B43产品与实测降水量比较接近,而且,3B43产品的估算精度稍高；总体上, TRMM表现出低估降水的特点,且当实测月降水量大于300 mm时,这种特征尤为显著；1998-2012年,渤海年降水量表现出明显的年际丰枯变化特征,多年均值为631.6 mm；夏季降水量占年降水总量的62.0%,7月是降水量最丰富的月份；空间上,渤海中南部降水量相对较高,而近岸区域降水量相对较低；受大气环流等因素的影响,夏季降水量重心向西北方向偏移,冬季则向东南方向偏移。