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TRMM卫星降雨数据的精度及径流模拟评估
Evaluation of Accuracy and Streamflow Simulation of TRMM Satellite Precipitation Data
 [PDF]

王佳伶, 陈华, 许崇育, 李翔泉, 曾强
Journal of Water Resources Research (JWRR) , 2016, DOI: 10.12677/JWRR.2016.55050
Abstract:
卫星测雨的精度已成为人们关注的热点,并且在水文研究及应用上有很大的发展前景。本文选取湘江流域为研究区,以地面雨量站点数据为参照,评估了不同时空尺度下热带测雨观测计划(Tropical Rainfall Measuring Mission, TRMM)多卫星降雨分析新产品(TRMM 3B42 V7)的精度,同时分析了精度在不同时期、雨强及高程等因素下的影响规律,并驱动新安江模型展现了径流模拟效果。研究表明:TRMM降水数据与站点数据相关性较好,TRMM数据精度在月尺度明显优于日尺度,流域尺度优于栅格尺度,面雨量精度湿润季节高于干旱季节;雨量估计上TRMM相对站点在流域尺度下整体低估,栅格尺度下受高程影响,在高程较大区域TRMM数据倾向低估,反之倾向高估;各雨强级别下TRMM对小强度降雨稍低估而对强降雨和无雨高估;TRMM数据月径流模拟效果比日径流好,均在可接受范围,但对洪峰、洪量及峰现时间不如站点模拟精准。本研究为TRMM数据的精度订正提供相关思路,并分析其在径流模拟应用中的可行性。
The accuracy of satellite precipitation estimates has become a focus of attention, having a promising prospect in the hydrological researches and applications. In this study, the new precipitation product (3B42 V7) of Tropical Rainfall Measuring Mission (TRMM) was evaluated via comparison with the rain gauge precipitation data in Xiangjiang River Basin. The evaluations were conducted at different spatial and temporal scales. Simultaneously, the laws of data accuracy under different periods, rainfall intensity levels, and elevations were analyzed. These two precipitation data were then adopted to drive the Xinan-jiang Model to perform streamflow simulation. The results showed that TRMM satellite precipitation data had a good correlation with rain gauge precipitation data; it had better accuracy under monthly scale than daily scale and showed better performance at watershed scale than it did at grid scale. The area precipitation of TRMM data showed better accuracy in humid season than in arid season. From an overall estimate on the amount of precipitation, areal precipitation from TRMM data on watershed scale was underestimated in contrast with areal precipitation interpolated from rain gauge data. While at grid scale, TRMM data from higher elevations inclined toward underestimation, while the contrary inclined toward overestimation. The frequency statistical result of different rainfall intensity levels indicated that TRMM tended to underestimate the occurrence of light rainfall intensity but overestimate the occurrence of heavy rainfall intensity and no-rain events. The TRMM-driven streamflow simulation performed better at monthly scale relative to the daily scale, but all were within acceptable range. However, the effects of streamflow simulation driven by TRMM data were not as accurate as those driven by rain gauge data displayed in the aspects of flood peak, flood volume and flood duration. This study assesses the accuracy of the latest product TRMM 3B42 V7, revealing the influential factors regarding accuracy for future
Experiences in using the TRMM data to complement rain gauge data in the Ecuadorian coastal foothills
M. Arias-Hidalgo,B. Bhattacharya,A. E. Mynett,A. van Griensven
Hydrology and Earth System Sciences Discussions , 2012, DOI: 10.5194/hessd-9-12435-2012
Abstract: Nowadays, new technologies are being used to expand the coverage of conventional meteorological datasets. An example of these is the TRMM data as long as one considers the bias, the type of rainfall and the current coarse spatial resolution. Although in the Guayas River Basin (Ecuadorian lowlands) the radar-based precipitation does not match the magnitude of the ground-based rainfall, at least it records somewhat the spatial pattern. The bias remains more or less steady when the temporal resolution increases from yearly to seasonal and monthly data. By means of an empirical disaggregation method, synthetic daily rainfall time series were generated at the satellite measuring spots. These artificial series were incorporated into an existing hydrological model to complement the available raingauge data to assess the model performance. The results were quite comparable with those using only gauge information. Although the model outcomes did not improve remarkably, the contribution of this approach was based on the fact that given a known bias, the satellite data could still be corrected and may resemble the information provided by the raingauges. Therefore, TRMM may supply valuable information in areas scarcely gauged such as the Andean foothills in the Guayas River Basin.
Generic Method for Merging Satellite and Historical Ground Station Data to Design Rainfall Intensity Duration Frequency (IDF) Curves in Recordless Sub-Saharian Countries  [PDF]
Jorge E. Matos
Open Journal of Modern Hydrology (OJMH) , 2018, DOI: 10.4236/ojmh.2018.84008
Abstract: The availability of long-term rainfall records is essential to conduct a serious frequency analysis in order to estimate the effective precipitation depth. The development of the process of elaboration of IDF (Intensity-Duration-Frequency) curves for a given location requires very precise data, at least with daily frequency, obtained through the use of rainfall records. The present study presents a method used to merge historical precipitation data with the latest data collected by satellite in order to perform graphs with IDF curves in places where rainfall records are scarce. The homogeneity of the data used is analyzed in order to guarantee its statistical utility and the frequency analysis was performed with the statistical distributions of Extreme Values Type I (Gumbel), Gamma, Pearson Type III and finally with Log-Pearson Type III, in order to verify which one of them applies better to the sites chosen for this analysis: the cities of Benguela and Lobito in the south of Angola. Daily rainfall data from the TRMM mission and historical daily data were used to derive the relationships between the maximum daily precipitation and the sub-daily precipitation values. From the observed daily data, techniques of disaggregation of the collected data were used, in order to generate a synthetic precipitation sequence with the extreme values in periods of time inferior to the daily one, with statistical properties similar to the registered data. Then IDF equations are established, with which the occasional storm depth is calculated for various return periods and various durations and, after them, the IDF curves are drawn for these two geographic stations.
Developing Intensity-Duration-Frequency Curves in Scarce Data Region: An Approach using Regional Analysis and Satellite Data  [PDF]
Ayman G. Awadallah, Mohamed ElGamal, Ashraf ElMostafa, Hesham ElBadry
Engineering (ENG) , 2011, DOI: 10.4236/eng.2011.33025
Abstract: The availability of data is an important aspect in frequency analysis. This paper explores the joint use of lim- ited data from ground rainfall stations and TRMM data to develop Intensity Duration Frequency (IDF) curves, where very limited ground station rainfall records are available. Homogeneity of the means and variances are first checked for both types of data. The study zone is assumed to be belonging to the same region and checked using the Wiltshire test. An Index Flood procedure is adopted to generate the theoretical regional distribution equation. Rainfall depths at various return periods are calculated for all stations and plotted spatially. Regional patterns are identified and discussed. TRMM data are used to develop ratios between 24-hr rainfall depth and shorter duration depths. The regional patterns along with the developed ratios are used to develop regional IDF curves. The methodology is applied on a region in the North-West of Angola.
Study of 1998 Heavy Rainfall over the Yangtze River Basin Using TRMM Data
用TRMM资料研究1998年长江流域暴雨

Cheng Minghu,He Huizhong,Mao Dongyan,Qi Yanjun,Cui Zhehu,Zhou Fengxian,
Cheng Minghu
,He Huizhong,Mao Dongyan,Qi Yanjun,Cui Zhehu,Zhou Fengxian

大气科学进展 , 2001,
Abstract: TRMM (Tropical Rainfall Measuring Mission) data have been made available to the public users since June 1998. In this paper, some preliminary research is reported for the case study of heavy rainfall over the Yangtze River Basin using TRMM data at 2140 UTC 20 July 1998. TRMM derived precipitation products are also compared with rain gauge observation, ground radar data and numerical model simulation results.It is shown that TRMM data can be easily used to monitor the heavy rainfall and have many applications.
Dry/Wet Conditions Monitoring Based on TRMM Rainfall Data and Its Reliability Validation over Poyang Lake Basin, China  [PDF]
Xianghu Li,Qi Zhang,Xuchun Ye
Water , 2013, DOI: 10.3390/w5041848
Abstract: Local dry/wet conditions are of great concern in regional water resource and floods/droughts disaster risk management. Satellite-based precipitation products have greatly improved their accuracy and applicability and are expected to offer an alternative to ground rain gauges data. This paper investigated the capability of Tropical Rainfall Measuring Mission (TRMM) rainfall data for monitoring the temporal and spatial variation of dry/wet conditions in Poyang Lake basin during 1998–2010, and validated its reliability with rain gauges data from 14 national meteorological stations in the basin. The results show that: (1) the daily TRMM rainfall data does not describe the occurrence and contribution rates of precipitation accurately, but monthly TRMM data have a good linear relationship with rain gauges rainfall data; (2) both the Z index and Standardized Precipitation Index (SPI) based on monthly TRMM rainfall data oscillate around zero and show a consistent interannual variability as compared with rain gauges data; (3) the spatial pattern of moisture status, either in dry months or wet months, based on both the Z index and SPI using TRMM data, agree with the observed rainfall. In conclusion, the monthly TRMM rainfall data can be used for monitoring the variation and spatial distribution of dry/wet conditions in Poyang Lake basin.
Probing on suitability of TRMM data to explain spatio-temporal pattern of severe storms in tropic region
A. Akbari,F. Othman,A. Abu Samah
Hydrology and Earth System Sciences Discussions , 2011, DOI: 10.5194/hessd-8-9435-2011
Abstract: Spatial and temporal pattern of rainfall play an important role in runoff generation. Raingauge density influences the accuracy of spatial pattern and time interval influence the accuracy of temporal pattern of storms. Usually due to practical and financial limitation the perfect distribution is not achievable. Several sources of data are used to define the behavior of rainfall over a watershed. Raingauges station, radar operation and satellite sensor are the main source of rainfall estimation over the space and time. Recording raingauges are the most common source of rainfall data in many countries. However raingauge network has not adequate coverage in many watersheds spatially in developing countries. Therefore other global source of rainfall data may be useful for hydrological analysis such as flood modeling. This research assessed the ability of TRMM rainfall estimates for explain the Spatio-temporal pattern of severe storm over Klang watershed which is a hydrologically well instrumented watershed. It was experienced that TRMM rainfall estimates are 35% less than actual data for the investigated events. Due to coarse temporal resolution of TRMM (3 h) compare to gauge rainfall (15 min), significant uncertainty influences identifying the start and end of storm event and consequently their resultant time to peak of flood hydrograph which is extremely important in flood forecasting systems. Due to coarse pixel size of TRMM data, watershed scale is important issue.
The Utilization of Satellite Data Tropical Rainfall Measuring Mission (TRMM) For Mapping Zone Agroclimate Oldeman In South Kalimantan
Riza Arian Noor, Muhammad Ruslan, Gusti Rusmayadi, Badaruddin
EnviroScienteae , 2016, DOI: -
Abstract: The irregularity of observation sites distribution and network density, lack data availability and discontinuity are the obstacles to analyzing and producing the information of agroclimate zone in South Kalimantan. TRMM satellite needs to be researched to overcome the limitations of surface observation data. This study intended to validate TRMM 3B43 satellite data with surface rainfall, to produce Oldeman agroclimate zone based on TRMM satellite data and to analyze the agroclimate zone for agricultural resources management. Data validation is done using the statistical method by analyzing the correlation value (r) and RMSE (Root Mean Square Error). The agroclimate zone is classified based on Oldeman climate classification type. The calculation results are mapped spatially using Arc GIS 10.2 software. The validation result of the TRMM satellite and surface rainfall data shows a high correlation value for the monthly average. The value of correlation coefficient is 0,97 and 25 mm for RMSE value. Oldeman agroclimate zone based on TRMM satellite data in south Kalimantan is divided into five climate zones, such as B1, B2, C1, C2, and D1.
Application of TRMM/PR Data for Numerical Simulations with Mesoscale Model MM5
TRMM/PR资料在中尺度模式MM5中的应用(英)

XU Zhifang,GE Wenzhong,DANG Renqing,Toshio IGUCHI,Takao TAKADA,
XU Zhifang
,GE Wenzhong,DANG Renqing,Toshio IGUCHI,Takao TAKADA

大气科学进展 , 2003,
Abstract: Numerical simulations of two heavy rainfall cases in the Changjiang-Huaihe River basin are performed with TRMM/PR (precipitation radar) data incorporated into the PSU/NCAR meso scale model MM5.The mixing ratio of rainwater qr is obtained from the R-qr relation (R is the rainfall rate), and the mixing ratio of water vapor qv in the model is replaced by q'v=qv+qr. Then, TRMM/PR data are used to modify humidity analysis obtained from conventional radiosonde data, and sensitivity experiments (STE) are performed and compared to control experiments (CTL). Results show that both the heavy rainfall distribution and its maximum amounts from STE are improved compared with those from CTL.
Using MODIS Images and TRMM Data to Correlate Rainfall Peaks and Water Discharges from the Lebanese Coastal Rivers  [PDF]
Amin SHABAN, Crodula ROBINSON, Farouk EL-BAZ
Journal of Water Resource and Protection (JWARP) , 2009, DOI: 10.4236/jwarp.2009.14028
Abstract: Water flows from rivers into the sea (plumes) is a common phenomenon in many coastal zones. The hydro-logic behavior of plumes differs from one river to another depending on rainfall rate and intensity, as well as it is influenced by the hydrologic characteristics of river basin. In order to investigate the precipitation re-gime in a drainage basin versus the flow into the sea, sequential data must be available. Remotely sensed data can fulfill this scope, thus it can provide climatic and hydrologic data. The scope of this study is to monitor the behavior of water input in the catchments versus the output from rivers in the Lebanese coastal zone using remote sensing data. For this purpose, TRMM (Tropical Rainfall Mapping Mission) data and MODIS satellite images were used. Hence, rainfall data from TRMM was compared with the areal extent of water plumes from rivers. This enables establishing interpolation between water input/output for each river basin. In addition, the lag time and residence time of plumes into the sea can be measured and compared between the issuing rivers. The extracted data from remote sensing was compared with terrain measures and shows its reliability and accordance. The used approach proved to be creditable, non-invasive and cost effec-tive and can be applied to other costal river basins.
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