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首页> 外文期刊>Hydrology and Earth System Sciences >Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi)
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Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi)

机译:印度大河流域(马哈纳迪)TRMM雨量估算的评估

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The paper examines the quality of satellite-based precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the subbasin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-runoff simulation. At sub-basin level (4000 to 16 000 km~2) the satellite-based areal precipitation estimates were found to be moderately correlated with the gauge-based counterparts (R~2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high-intensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate< 0.6 for ground-based intensities > 80mm day~(-1)). At the same time, the remotely sensed rainfall rates frequently exceed the gauge-based equivalents (false alarm ratios of 0.2-0.6). In addition, the real-time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall-runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash-Sutcliffe index of 0.76-0.88 at gauges not affected by reservoir operation). This compares to the values of 0.71-0.78 for the gaugeadjusted TRMM 3B42 data and 0.65-0.77 for the 3B42-RT real-time data. Whether the 3B42-RT data are useful in the context of operational runoff prediction in spite of the identified problems remains a question for further research.
机译:本文研究了下马哈纳迪河流域(印度东部)的卫星降水估计质量。被认为是3B42和3B42-RT(版本7 / 7A)的数据集通常由热带降雨测量任务(TRMM)根据被动微波和红外记录生成。尽管3B42-RT数据是实时分发的,但经过量规调整的3B42数据集的发布要延迟几个月。两种产品的质量分两步评估。首先,在次流域尺度上评估了遥感降水率与雨量计数据之间的对应关系。其次,通过在降雨径流模拟的背景下分析其性能来评估降雨估计的质量。在次流域水平(4000至16000 km〜2),基于卫星的面降水估计值与基于表距的对应值有中等相关性(3B42的R〜2为0.64-0.74,3B42-的R〜2为0.59-0.72 RT)。在高强度水平下,TRMM数据与地面观测值之间存在显着差异。 TRMM的估算通常不能反映出来自雨量计数据的降雨深度(地面强度> 80mm day〜(-1)时,命中率<0.6)。同时,遥感降雨率经常超过基于仪表的当量(误报率为0.2-0.6)。另外,发现实时产品3B42-RT具有空间上一致的负偏差。由于雨量计数据的区域化可能与许多错误相关,因此上述结果存在不确定性。因此,必须针对诸如流的独立信息进行验证。在本案例研究中,降雨径流模拟实验的结果与上述发现一致。如果将雨量计数据用作模型输入(在不受水库运行影响的水位计处,纳什-苏克利夫指数为0.76-0.88),则将获得最佳的观测流量与模拟流量之间的拟合。相比之下,经量规调整的TRMM 3B42数据的值为0.71-0.78,而3B42-RT实时数据的值为0.65-0.77。尽管发现了问题,但3B42-RT数据在运行径流预测中是否有用仍是有待进一步研究的问题。

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