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.

Assessing the spatiotemporal distributions of evapotranspiration in the Three Gorges Reservoir Region of China using remote sensing data

Evapotranspiration(ET) is a critical component of the global hydrological cycle, and it has a large impact on water resource management as it affects the availability of freshwater resources. It is important to understand the hydrological cycle for the water resources planning and management. This study used Moderate Resolution Imaging Spectroradiometer(MODIS) satellite derived ET, and potential evapotranspiration(PET) and Tropical Rainfall Measuring Mission(TRMM) satellite derived precipitation datasets to assess the spatial and temporal distributions of ET, PET, and precipitation during the study period at Three Gorges Reservoir(TGR) region. Based on the topographic variations and land-use/land-cover distributions, the study region which includes five counties of Hubei Province and nineteen counties of Chongqing Municipality was divided into four study zones. The ET and precipitation data were evaluated using in situ observations. The ET, PET, and precipitation data were compared to analyze the spatial and long-term(2001-2016) temporal distributions of average annual ET, PET, and precipitation, and to understand the relationships between them in the study region. The results showed that each selected zone had highest ET at the counties with the Yangtze River passing through whereas lowest at the counties which were located away from the river. Results also showed increasing trends in ET and PET from south-west to north-east in the study region. Analysis showed TGR had a significant impact on spatial and temporal distributions of ET and PET in the study region. Therefore, this study helps to understand the impact of TGR on spatial and temporal distributions of ET and PET during and after the construction.

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.

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-gange stations.

Comparison of TMI and AMSR-E sea surface temperatures with Argo near-surface temperatures over the global oceans

Satellite-derived sea surface temperatures（SSTs） from the tropical rainfall measuring mission（TRMM）microwave imager（TMI） and the advanced microwave scanning radiometer for the earth observing system（AMSR-E） were compared with non-pumped near-surface temperatures（NSTs） obtained from Argo profiling floats over the global oceans. Factors that might cause temperature differences were examined, including wind speed, columnar water vapor, liquid cloud water, and geographic location. The results show that both TMI and AMSR-E SSTs are highly correlated with the Argo NSTs; however, at low wind speeds, they are on average warmer than the Argo NSTs. The TMI performs slightly better than the AMSR-E at low wind speeds, whereas the TMI SST retrievals might be poorly calibrated at high wind speeds. The temperature differences indicate a warm bias of the TMI/AMSR-E when columnar water vapor is low, which can indicate that neither TMI nor AMSR-E SSTs are well calibrated at high latitudes. The SST in the Kuroshio Extension region has higher variability than in the Kuroshio region. The variability of the temperature difference between the satellite-retrieved SSTs and the Argo NSTs is lower in the Kuroshio Extension during spring. At low wind speeds, neither TMI nor AMSR-E SSTs are well calibrated, although the TMI performs better than the AMSR-E.

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.

Evaluation of the WRF Weather Forecasts over the Southern Region of Brazil

The data assimilation technique, known as 3DVAR, of the WRF mesoscale modeling system has been used in order to perform the impact analysis of meteorological data assimilation in the weather forecasts over the Rio Grande do Sul State in Brazil. The consistency of the data assimilation has been analyzed by investigating and evaluating the model forecast results processed with and without data assimilations. Two different procedures of data assimilation have been conducted to perform the study. The forecasts of the accumulated rainfall model variable, spatially plotted over the model integration domains, have been compared and validated against the Tropical Rain Measuring Mission (TRMM) satellite based data, as well as with the Canguçu city meteorological radar reflectivity data. The comparison has been made considering the total amount of the accumulated rainfall predicted by the model against the automatic weather station data and most of the conducted processing presented compatible results. It has also been observed that, the inclusion of assimilated data enabled an improvement in the intensity as well as in the location of the main convective cell. The radar reflectivity field showed a significant performance in all processed experiments with data assimilation. However, for some regions, more significant obtained results have been shown to be the case in which the spectral radiances were assimilated, as compared with the case in which the spectral radiances were not included. The evaluation of the vertical atmospheric profiles of temperature and dew point temperature showed only a small impact of data assimilation. However, both simulations coherently presented the two vertical profiles, when compared with the observed profiles. In short, the study shows that, although the forecasts presented some inconsistencies in the evaluated results, the 3DVAR assimilation improves significantly the forecasting of the Weather WRF model.

Comprehensive applicability evaluation of four precipitation products at multiple spatiotemporal scales in Northwest China

Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in summer months.TRMM showed a relatively low correlation with station observations in winter months(correlation coefficients≤0.70).The capture performance analysis showed that ERA5,GPCC,and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased.ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased.GPCC had the lowest FAR values.TRMM was statistically ineffective for predicting the occurrence of daily precipitation events.The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.

Evaluation of Latest TMPA and CMORPH Precipitation Products with Independent Rain Gauge Observation Networks over High-latitude and Low-latitude Basins in China

The Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） and National Oceanic and Atmospheric Administration （NOAA） Climate Prediction Center （CPC） morphing technique （CMORPH） are two important multi-satellite precipitation products in TRMM-era and perform important functions in GPM-era. Both TMPA and CMORPH systems simultaneously upgraded their retrieval algorithms and released their latest version of precipitation data in 2013. In this study, the latest TMPA and CMORPH products （i.e., Version-7 real-time TMPA （T-rt） and gauge-adjusted TMPA （T-adj）, and Version- 1.0 real-time CMORPH （C-rt） and Version-l.0 gauge-adjusted CMORPH （C-adj）） are evaluated and intercompared by using independent rain gauge observations for a 12-year （2000--2011） period over two typical basins in China with different geographical and climate conditions. Results indicate that all TMPA and CMORPH products tend to overestimate precipitation for the high-latitude semiarid Laoha River Basin and underestimate it for the low-latitude humid Mishui Basin. Overall, the satellite precipitation products exhibit superior performance over Mishui Basin than that over Laoha River Basin. The C-adj presents the best performance over the high-latitude Laoha River Basin, whereas T-adj showed the best performance over the low-latitude Mishui Basin. The two gauge-adjusted products demonstrate potential in water resource management. However, the accuracy of two real-time satellite precipitation products demonstrates large variability in the two validation basins. The C-rt reaches a similar accuracy level with the gauge-adjusted satellite precipitation products in the high-latitude Laoha River Basin, and T-rt performs well in the low-latitude Mishui Basin. The study also reveals that all satellite precipitation products obviously overestimate light rain amounts and events over Laoha River Basin, whereas they underestimate the amount and events over Mishui Basin. The findings of the precision characteristics associated with the latest TMPA and CMORPH precipitation products at different basins will offer satellite pre- cipitation users an enhanced understanding of the applicability of the latest TMPA and CMORPH for water resource management, hydrologic process simulation, and hydrometeorological disaster prediction in other similar regions in China. The findings will also be useful for IMERG algorithm development and update in GPM-era.

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.

Significant impacts of the TRMM satellite orbit boost on climatological records of tropical precipitation

With the unprecedented spaceborne precipitation radar(PR),the Tropical Rainfall Measuring Mission(TRMM) satellite has collected high-quality precipitation measurements for over ten years.The TRMM/PR data are nowadays extensively exploited in numerous meteorological and hydrological fields.Yet an artificial orbit boost of the TRMM satellite in August 2001 modulated the observation parameters,which inevitably affects climatological applications of the PR data and needs to be clarified.This study investigates the orbit boost effects of the TRMM satellite on the PR-derived precipitation characteristics.Both the potential impacts on precipitation frequency(PF) and precipitation intensity(PI) are carefully analyzed.The results show that the total PF decreases by 8.3% and PI increases by 4.0% over the tropics after the orbit boost.Such changes significantly exceed the natural variabilities and imply the strong effects of orbit boost on precipitation characteristics.The impacts on stratiform precipitation and convective precipitation are inconsistent,which is attributed to their distinct precipitation features.Further analysis reveal that the increased PI of stratiform precipitation is mainly due to the decreased frequencies of light precipitation,while the semi-constant PI of convective precipitation is caused by the concurrently decreased frequencies of light and heavy precipitation.A modification is applied to the post-boost PR precipitation data to retrieve the actual trends of tropical precipitation characteristics.It is found that the PI of total-precipitation approximately keeps invariable from 1998 to 2005.The total PF has no obvious trend over tropical oceans but decreases considerably over tropical lands.

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。

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。

利用热带降雨测量卫星的微波成像仪观测资料反演陆地降水

利用热带降雨测量卫星的微波成像仪资料，结合淮河流域试验加密观测期的阜阳地面天 气雷达雨量资料，建立了以散射指数和极化订正温度为主要参数的降水反演算法。对文 中所做反演试验与日本ＮＡＳＤＡ用微波成像仪和星载测雨雷达反演的雨强进行了比较。结果表明 ，文中所用的方法在反演陆地下垫面的降雨强度的分布和降雨区域的确定是比较成功的。

0302号(鲸鱼)台风降水和水粒子空间分布的三维结构特征

由于缺乏关于台风结构信息的高分辨率资料,即探测台风云系内部结构特征的技术限制,造成了进一步理解台风的动力传送特征的困难。作者用热带测雨卫星(TRMM,Tropical Rainfall Measuring Mission)的测雨雷达(PR,Precipitation Radar)和TRMM微波图像仪(TMI,TRMM Microwave Imager)资料详细研究了“鲸鱼”台风(0302号)于2003年4月16日1105 UTC的降水和降水云系中各种水粒子的三维结构特征。通过分析发现该时刻:(1)台风降水中大部分区域为层性降水(占总降水面积的85.5%),对流性降水占总降水面积的13.1%,但对流性降水的贡献却达到41.8%,所以,虽然对流性降水所占面积比例很少,但是它对总降水量的贡献却很大。(2)60%降水主要集中在距离台风中心100 km以内的区域,约占总降水量的60%。(3)各种水粒子含量随着与台风中心距离的增加而减少。降水云系中水粒子最大含量出现高度与水粒子的种类和与台风中心的距离有关。最后,分析了台风降水和降水云系中三维分布的成因。

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。

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.