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Validating CHIRPS-based satellite precipitation estimates in Northeast Brazil

机译:验证巴西东北部基于CHIRPS的卫星降水估计

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Satellite-based rainfall is an alternative source of information for regions such as the Northeast Brazil (NEB) where there are large areas that do not have ground observation stations. In this study, the monthly rainfall derived from the satellite-based rainfall product, Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS v.2), is compared with observation from 21 ground stations in the NEB, for the period 1981-2013. Various metrics based on pairwise comparison were applied to evaluate its performance in estimating rainfall amount and rain detection capability. Results show that the CHIRPS data correlate well with observations for all stations (r = 0.94), but tend to overestimate low and underestimate high rainfall values (>100 mm/month). Although CHIRPS achieves better results during the wet season (March to May; bias = -4.60%), its ability for the rain detection is poor (probability = 0.44). The best global performance was noted in the Cerrado biome (r = 0.93; rain detection = 0.53), but fails to detect rain in other biomes (r = 0.92; rain detection = 0.16). The study concluded that the CHIRPS v.2 dataset can be a useful substitute for rain-gauge precipitation data outside the semiarid NEB. (C) 2016 Elsevier Ltd. All rights reserved.
机译:对于大部分地区没有地面观测站的地区,例如巴西东北部(NEB),基于卫星的降雨是替代信息来源。在这项研究中,将1981-2013年期间来自卫星降雨产品气候危险集团站内红外降水(CHIRPS v.2)的月降雨量与NEB 21个地面站的观测值进行了比较。应用基于成对比较的各种指标来评估其在估计雨量和降雨检测能力方面的性能。结果表明,CHIRPS数据与所有观测站的观测值均具有良好的相关性(r = 0.94),但往往高估了低降水量值(> 100 mm /月)。尽管CHIRPS在雨季(3月至5月;偏差= -4.60%)取得了较好的结果,但其雨水检测能力很差(概率= 0.44)。在Cerrado生物群落中,全球表现最佳(r = 0.93;降雨检测= 0.53),但在其他生物群落中未检测到降雨(r = 0.92;降雨检测= 0.16)。研究得出结论,CHIRPS v.2数据集可以替代半干旱NEB以外的雨量计降水数据。 (C)2016 Elsevier Ltd.保留所有权利。

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