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Evaluation of extreme rainfall indices from CHIRPS precipitation estimates over the Brazilian Amazonia
Atmospheric Research ( IF 4.5 ) Pub Date : 2020-07-01 , DOI: 10.1016/j.atmosres.2020.104879
Rosane Barbosa Lopes Cavalcante , Douglas Batista da Silva Ferreira , Paulo Rógenes Monteiro Pontes , Renata Gonçalves Tedeschi , Cláudia Priscila Wanzeler da Costa , Everaldo Barreiros de Souza

Abstract Since several datasets are available with marked differences, the assessment of precipitation data is a key aspect to support the choice of the most adequate precipitation product for a certain research or operational application. In the present study, we evaluated the use of the daily rainfall dataset from CHIRPS with spatial resolution of 0.05° for different purposes in the states of the Brazilian Legal Amazon. We compared monthly rainfall, annual rainfall indices and their trends calculated using CHIRPS data and rain gauge observations with a point-to-pixel analysis. The use of daily CHIRPS data provided mean monthly rainfall similar to that obtained using data from the rain gauge stations, but CHIRPS data tend to underestimate the values for the rainiest months. The correlation was usually lower in the western Amazon, especially during its rainy season. The same underestimation was observed for extreme rainfall indices. CHIRPS product produces more similar results to rain gauge data for the indices PRCPTOT, nP, and R95pad, while strong underestimate the most extreme rainfall indices (R50mm, Rx1day, Rx5days). For the 45 stations and 15 rainfall indices analysed, 63 significant trends were detected using rain gauge data, of which only 13 were detected using CHIRPS product. Therefore, the use of CHIRPS data does not well represent the trends in rainfall indices.

中文翻译:

根据 CHIRPS 降水估计对巴西亚马逊河流域的极端降雨指数进行评估

摘要 由于有几个数据集存在显着差异,因此降水数据的评估是支持为特定研究或业务应用选择最合适的降水产品的关键方面。在本研究中,我们评估了来自 CHIRPS 的日降雨数据集的使用,其空间分辨率为 0.05°,用于巴西合法亚马逊州的不同目的。我们通过点到像素分析比较了使用 CHIRPS 数据和雨量计观测计算的月降雨量、年降雨量指数及其趋势。使用每日 CHIRPS 数据提供的平均月降雨量与使用雨量站数据获得的相似,但 CHIRPS 数据往往低估了降雨最多月份的值。亚马逊西部的相关性通常较低,尤其是在它的雨季。对于极端降雨指数也观察到同样的低估。CHIRPS 产品对指数 PRCPTOT、nP 和 R95pad 的雨量计数据产生更相似的结果,而强烈低估了最极端的降雨指数(R50mm、Rx1day、Rx5days)。在分析的 45 个站点和 15 个降雨指数中,使用雨量计数据检测到 63 个显着趋势,其中只有 13 个使用 CHIRPS 产品检测到。因此,使用 CHIRPS 数据并不能很好地代表降雨指数的趋势。在分析的 45 个站点和 15 个降雨指数中,使用雨量计数据检测到 63 个显着趋势,其中只有 13 个使用 CHIRPS 产品检测到。因此,使用 CHIRPS 数据并不能很好地代表降雨指数的趋势。在分析的 45 个站点和 15 个降雨指数中,使用雨量计数据检测到 63 个显着趋势,其中只有 13 个使用 CHIRPS 产品检测到。因此,使用 CHIRPS 数据并不能很好地代表降雨指数的趋势。
更新日期:2020-07-01
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