Satellite-based precipitation estimates using a dense rain gauge network over the Southwestern Brazilian Amazon: Implication for identifying trends in dry season rainfall
Satellite-based precipitation estimates using a dense rain gauge network over the Southwestern Brazilian Amazon: Implication for identifying trends in dry season rainfall
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DOI：
10.1016/j.atmosres.2021.105741
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发表时间：
2021-10
影响因子：
5.5
通讯作者：
Ye Mu;T. Biggs;S. Shen
中科院分区：
文献类型：
--
作者：
Ye Mu;T. Biggs;S. Shen
精确的时间和空间分辨率的长期降雨量估计对水文气象学和气候学研究至关重要，但在偏远地区往往得不到这种数据。我们评估了三种基于卫星的降水产品的准确性，这些产品拥有从1981年到2019年在巴西亚马逊隆多尼亚州的数据：(A)仅卫星数据，使用气候危害组织的红外降水(CHIRP)产品，(B)稀疏测量数据(CHIRPS)的CHIRP，以及(C)利用密集雨量站网(N=0.73)的数据校准的CHIRPS(DnCHIRPS)。我们在月和季时间尺度上使用额外的验证仪(N=2.55)对降雨产品进行了评估，并比较了它们的干旱事件和时间趋势。Chirp(10.0 mm/月平均误差(ME)，23.6%偏差(PB))和Chirps(−0.08ME，7.4%PB)都低估了雨季的月高降雨量，高估了枯水季的月低降雨量。与Chirp和Chirp相比，dnCHIRPS对月降雨量(−0.01ME，1.1%PB)的误差较小，在旱季dnCHIRPS与其他两个数据的百分比差异最大。DnCHIRPS捕捉到了该州农业地区旱季降雨量减少的趋势，这一趋势被其他两种产品忽略了。我们的结论是，高密度的雨量计对于记录亚马逊盆地这一重要农业区旱季和干旱期间的降雨空间格局和趋势至关重要。
Accurate long-term estimates of rainfall at fine spatial and temporal resolution are vital for hydrometeorology and climatology studies, but such data are often unavailable in remote regions. We assessed the accuracy of three satellite-based precipitation products that have data from 1981 to 2019 over the state of Rondônia in the Brazilian Amazon: (a) satellite-only, using the Climate Hazards Group Infrared Precipitation (CHIRP) product, (b) CHIRP with sparse gauge data (CHIRPS), and (c) CHIRPS calibrated with data from a dense rain gauge network (N= 73) (dnCHIRPS). We evaluated the rainfall products using additional validation gauges (N= 55) at the monthly and seasonal time scales and compared their drought events and temporal trends. Both CHIRP (10.0 mm/month mean error (ME), 23.6% percent bias (PB)) and CHIRPS (−0.08ME, 7.4% PB) underestimate high monthly rainfall in the wet season and overestimate low monthly rainfall during the dry season. dnCHIRPS had a lower error in monthly rainfall (−0.01ME, 1.1%PB) compared with CHIRP and CHIRPS, with the largest percentage difference between dnCHIRPS and the other two datasets in the dry season. dnCHIRPS captured decreasing trends in dry season rainfall over agricultural parts of the state, trends that were missed by the other two products. We conclude that a high density of rain gauges is essential for documenting the spatial pattern and trends in rainfall during the dry season and droughts in this important agricultural region of the Amazon basin.