ABSTRACT

The actual accuracy of satellite rainfall products is often unknown due to the limitation of raingauge networks. We evaluated the effect of gauge representativeness error on evaluation of rainfall estimates from the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) rainfall product. The reference data were collected using an experimental raingauge network within a small watershed of 1690 ha, which is comparable to the CHIRPS resolution. The study applied a total bias approach, decomposed into hit, missed and false biases, and an error-variance separation method to evaluate gauge representativeness error at the scale of CHIRPS pixel size, as well as modeled the spatial correlation field of daily rainfall with a three-parametric exponential model. The results indicate that the gauge representativeness error is still too large to ignore in evaluating satellite rainfall. However, it is significantly affected by sample size and caution should be exercised when the rainfall data has a small sample size.

摘要

由于雨量计网络的限制，卫星降雨产品的实际精度往往是未知的。我们评估了仪表代表性误差对 CHIRPS（气候灾害组红外降水站数据）降雨产品评估降雨量估计的影响。参考数据是在 1690 公顷的小流域内使用实验性雨量器网络收集的，这与 CHIRPS 分辨率相当。该研究采用总偏差方法，分解为命中偏差、遗漏偏差和错误偏差，以及误差方差分离方法，以评估 CHIRPS 像素大小尺度下的雨量计代表性误差，并模拟了每日降雨量的空间相关场三参数指数模型。结果表明，在评估卫星降雨时，雨量器的代表性误差仍然太大，不容忽视。然而，它受样本量的影响很大，当降雨数据的样本量较小时应谨慎行事。