CHIRPS 估算约旦瓦拉盆地极端降水量的性能

Safaa AL Shamayleh, M. Tan, N. Samat, Michel Rahbeh, Fei Zhang
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摘要

对开放源降水数据进行评估对于为特定研究或业务应用选择最合适的产品至关重要。本研究旨在评估空间分辨率为 0.05°的气候灾害小组红外降水与站点数据(CHIRPS)的能力,采用点到像素比较法估算约旦瓦拉盆地从 1987 年到 2017 年的月降水量和年降水量。本研究采用了气候变化检测和指数专家组(ETCCDI)推荐的 11 个降水极端指数。研究结果表明,在月降水量估算中,CHIRPS 与站点的相关性适中,皮尔逊相关系数在 0.50 至 0.73 之间。然而,除 PRCPTOT、R10mm 和 R20mm 外,CHIRPS 与大多数极端指数的相关性较低。特别是在极端年份,CHIRPS 高估了低降水量,低估了高降水量。此外,CHIRPS 低估了连续干旱日、连续湿润日、R10mm、R20mm 和 R30mm 的计算结果,而高估了 R95p、R99p 和 Rx1day 的计算结果。趋势分析和威尔科克斯文本显示,CHIRPS 和测站之间缺乏相似性,这表明在对该地区进行极端分析之前需要进行偏差校正。
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Performance of CHIRPS for estimating precipitation extremes in the Wala Basin, Jordan
The evaluation of open-source precipitation data is crucial to enable the selection of the most appropriate product for a specific research or operational application. This study aims to evaluate the capability of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) with a spatial resolution of 0.05° for estimating monthly and annual precipitation in the Wala basin, Jordan, from 1987 to 2017 using a point-to-pixel comparison approach. Eleven precipitation extreme indices, recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), were used in this study. The findings show that CHIRPS correlated moderately with stations in monthly precipitation estimation, with the Pearson correlation coefficient values ranging from 0.50 to 0.73. However, CHIRPS had low correlations with stations in most of the extreme indices, except PRCPTOT, R10mm, and R20mm. The CHIRPS, particularly in the extreme years, overestimated low precipitation amounts and underestimated high ones. Moreover, CHIRPS underestimated the calculation of consecutive dry days, consecutive wet days, R10mm, R20mm, and R30mm, while an overestimation was found for the R95p, R99p, and Rx1day. The trend analysis and Wilcox text showed a lack of resemblance between the CHIRPS and gauges, showing a bias correction is needed before applying an extreme analysis in this region.
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