Zhijun Huang, Hua Wu, Guojun Gu, Xiaomeng Li, Nergui Nanding, Robert F. Adler, K. Yilmaz, Lorenzo Alfieri, Sirong Chen
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The gauge-corrected IMERG Final Run precipitation estimates and corresponding hydrological simulation are used as the references. Results showed that the hit bias is the dominant error source of IMERG-E, while the false precipitation is more noticeable in GEOS-FP. In terms of hydrological performance, GEOS-FP driven model (DRIVE-FP) performance is close to IMERG-E driven model (DRIVE-E) performance on Day 1, indicating that GEOS-FP could nicely fill the gap of nowcasting caused by the IMERG-E time latency. For longer lead time forecasts, the bias tends to diminish in most regions likely because the under-/over-estimation in IMERG-E is generally offset by the distinct types of misestimation in GEOS-FP. The skillful initial hydrological conditions present outperformed forecasts in most region, except for tropical areas where the accuracy of GEOS-FP prevails. 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引用次数: 0
摘要
众所周知,降水数据是水文模拟的关键驱动因素。因此,可靠的定量降水估计和预报对于准确的水文预报至关重要。基于卫星的GPM早期综合多卫星检索(imerge)降水估算和来自美国宇航局戈达德地球观测系统(GEOS-FP)的预报降水在全球洪水临近预报和预报中显示出价值。然而,很少有研究全面评估它们的水文性能,更不用说探索它们结合的潜在价值。因此,本研究对它们在实时水文监测和使用DRIVE模型进行1-5天预报中的效用进行了准全球评估。以经量规校正的IMERG Final Run降水估算值和相应的水文模拟为参考。结果表明,命中偏差是imerge的主要误差来源,而假降水在GEOS-FP中更为明显。在水文性能方面,GEOS-FP驱动模型(DRIVE-FP)在第1天的性能接近imerge驱动模型(DRIVE-E)的性能,表明GEOS-FP可以很好地填补imerge时间延迟造成的临近预报的空白。对于较长的提前期预测,偏差在大多数地区趋于减少,这可能是因为imerge中的过低/过高估计通常被GEOS-FP中不同类型的错误估计所抵消。在大多数地区,熟练的初始水文条件都优于预报,但在热带地区,GEOS-FP的准确性普遍较高。总的来说,本研究为imerge和GEOS-FP降水在水文预报和预报背景下的联合使用提供了有价值的观点。
Paired satellite and NWP precipitation for global flood forecasting
Precipitation data is known to be the key driver of hydrological simulations. Hence, reliable quantitative precipitation estimates and forecasts are vital for accurate hydrological forecasting. Satellite-based precipitation estimates from Integrated Multi-satellite Retrievals for GPM Early Run (IMERG-E) and forecasted precipitation from NASA’s Goddard Earth Observing System (GEOS-FP) have shown values in global flood nowcasting and forecasting. However, few studies have comprehensively evaluated their hydrological performance, let alone exploring the potential value of combining them. Therefore, this study undertakes a quasi-global evaluation of their utility in real-time hydrological monitoring and 1-5-day forecasting with the DRIVE model. The gauge-corrected IMERG Final Run precipitation estimates and corresponding hydrological simulation are used as the references. Results showed that the hit bias is the dominant error source of IMERG-E, while the false precipitation is more noticeable in GEOS-FP. In terms of hydrological performance, GEOS-FP driven model (DRIVE-FP) performance is close to IMERG-E driven model (DRIVE-E) performance on Day 1, indicating that GEOS-FP could nicely fill the gap of nowcasting caused by the IMERG-E time latency. For longer lead time forecasts, the bias tends to diminish in most regions likely because the under-/over-estimation in IMERG-E is generally offset by the distinct types of misestimation in GEOS-FP. The skillful initial hydrological conditions present outperformed forecasts in most region, except for tropical areas where the accuracy of GEOS-FP prevails. Overall, this study provides a valuable view of the combined use of IMERG-E and GEOS-FP precipitation in the context of hydrological nowcasts and forecasts.
期刊介绍:
The Journal of Hydrometeorology (JHM) (ISSN: 1525-755X; eISSN: 1525-7541) publishes research on modeling, observing, and forecasting processes related to fluxes and storage of water and energy, including interactions with the boundary layer and lower atmosphere, and processes related to precipitation, radiation, and other meteorological inputs.