Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile (datasets)

This file contains the dataset (both raw observed precipitation data and figures obtained as output of the analysis) accompanying the manuscript 'hess-2016-453' submitted to the HESS journal (http://www.hydrology-and-earth-system-sciences.net/).

Title: "Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile"

Abstract

Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access (e.g., high elevation zones). Recently, satellite-based rainfall estimates (SRE) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods. 

This study attempts to exhaustively evaluate -for the first time- the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-adj, MSWEPv1.1 and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE. The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, several categorical indices were used to assess the ability of each SRE to correctly identify different precipitation intensities.

Results revealed that most SRE products performed better for the humid South (36.4-43.7ºS) and Central Chile (32.18-36.4ºS), in particular at low- and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (MAM-JJA) compared to summer (DJF) and autumn (SON). In addition, all SREs were able to correctly identify the occurrence of no rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all time scales, which can be clearly attributed to its bias-correction procedure using 213 stations from Chile. Good results were also obtained by CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR and PERSIANN-CCS-adj were not able to represent observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resources assessments. We finally conclude that despite improvements of most SRE products, a site-specific calibration is still needed before any use in catchment-scale hydrological studies.

本文件包含随投稿至《水文与地球系统科学》（Hydrology and Earth System Sciences，简称HESS）期刊、手稿编号为hess-2016-453的研究一同发布的数据集，涵盖原始观测降水数据与分析输出所得图表，该期刊官网为http://www.hydrology-and-earth-system-sciences.net/。

标题：“智利复杂地形与气候梯度下卫星降水估计产品的时空评估”

摘要
当前，对流域降水输入的真实时空变异性进行精准表征仍存在极大局限。此外，空间插值得到的流域降水数据往往伴随较大不确定性，在发展中国家及难以抵达的区域（如高海拔地区）尤为突出。

近年来，卫星降水估计产品（Satellite-based Rainfall Estimates，简称SRE）为诸多水文应用场景提供了前所未有的机遇，覆盖从水资源建模到干旱、洪水等极端事件监测的广泛领域。

本研究首次针对智利复杂地形与多样气候梯度区域，对7款主流卫星降水估计产品进行全面适用性评估，涉及产品包括TMPA 3B42v7、CHIRPSv2、CMORPH、PERSIANN-CDR、PERSIANN-CCS-adj、MSWEPv1.1及PGFv3。研究采用日、月、季、年不同时间尺度，对366个观测站（涵盖海平面至安第斯高原4600米海拔区域）测得的降水时间序列，与各卫星降水估计产品对应网格单元的数据开展点-像元对比分析。本研究采用修正的克林-古普塔效率（Kling-Gupta Efficiency）指标，识别各卫星降水估计产品的系统性误差来源；同时引入多分类指标，评估各产品对不同降水强度的正确识别能力。

结果显示，相较于干旱的北部与极南部区域，多数卫星降水估计产品在湿润的智利南部（36.4°S~43.7°S）及中部（32.18°S~36.4°S）表现更优，尤其在低海拔与中海拔区域（0~1000米海拔）。从季节维度来看，所有产品在湿季（MAM-JJA）的表现均优于夏季（DJF）与秋季（SON）。此外，所有卫星降水估计产品均可正确识别无降水事件，但在降雨日的降水强度分类任务中表现不佳。

整体而言，PGFv3在全区域与全时间尺度下均表现最优，这可归因于其采用智利境内213个观测站数据进行偏差校正的处理流程。CHIRPSv2、TMPA 3B42v7与MSWEPv1.1同样表现优异，而CMORPH、PERSIANN-CDR及PERSIANN-CCS-adj则无法准确还原实测降水数据。尽管PGFv3（当前数据更新至2010年）可用于智利的历史水文分析与模型率定，但CHIRPS与TMPA 3B42v7（正过渡至IMERG产品）凭借其高空间分辨率、低延迟性与长时序数据记录，在气象研究与水资源评估领域展现出良好的应用潜力。

本研究最终得出结论：尽管多数卫星降水估计产品已有所改进，但在应用于流域尺度水文研究之前，仍需针对具体站点开展率定校准。