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Comparison of Traditional Method and Triple Collocation Analysis for Evaluation of Multiple Gridded Precipitation Products across Germany

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  • 1 a Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
  • | 2 b Chair of Hydrology and River Basin Management, Technical University of Munich, Munich, Germany
  • | 3 c State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing, China
  • | 4 d Center for Eco-Environmental Research, Nanjing Hydraulic Research Institute, Nanjing, China
  • | 5 e Key Laboratory of Geographic Information Science (Ministry of Education of China), East China Normal University, Shanghai, China
  • | 6 f Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts
  • | 7 g Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing, China
  • | 8 h Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
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Abstract

Evaluating the accuracy of precipitation products is essential for many applications. The traditional method for evaluation is to calculate error metrics of products with gauge measurements that are considered as ground truth. The multiplicative triple collocation (MTC) method has been demonstrated powerful in error quantification of precipitation products when ground truth is not known. This study applied MTC to evaluate five precipitation products in Germany: two raw satellite-based products (CMORPH and PERSIANN), one reanalysis product (ERA-Interim), one soil moisture–based product (SM2RAIN-ASCAT), and one gauge-based product (REGNIE). Evaluation was performed at the 0.5° daily spatial–temporal scales. MTC involves a log transformation of data, necessitating dealing with zero values in daily precipitation. Effects of 12 different strategies for dealing with zero values on MTC results were investigated. Seven different triplet combinations were tested to evaluate the stability of MTC. Results showed that different strategies for replacing zero values had considerable effects on MTC-derived error metrics, particularly for root-mean-square error (RMSE). MTC with different triplet combinations generated different error metrics for individual products. The MTC-derived correlation coefficient (CC) was more reliable than RMSE. It is more appropriate to use MTC to compare the relative accuracy of different precipitation products. Based on CC with unknown truth, MTC with different triplet combinations produced the same ranking of products as the traditional method. A comparison of results from MTC and the classic TC with additive error model showed the potential limitation of MTC in arid areas or dry time periods with a large ratio of zero daily precipitation.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Hongkai Gao, hkgao@geo.ecnu.edu.cn

Abstract

Evaluating the accuracy of precipitation products is essential for many applications. The traditional method for evaluation is to calculate error metrics of products with gauge measurements that are considered as ground truth. The multiplicative triple collocation (MTC) method has been demonstrated powerful in error quantification of precipitation products when ground truth is not known. This study applied MTC to evaluate five precipitation products in Germany: two raw satellite-based products (CMORPH and PERSIANN), one reanalysis product (ERA-Interim), one soil moisture–based product (SM2RAIN-ASCAT), and one gauge-based product (REGNIE). Evaluation was performed at the 0.5° daily spatial–temporal scales. MTC involves a log transformation of data, necessitating dealing with zero values in daily precipitation. Effects of 12 different strategies for dealing with zero values on MTC results were investigated. Seven different triplet combinations were tested to evaluate the stability of MTC. Results showed that different strategies for replacing zero values had considerable effects on MTC-derived error metrics, particularly for root-mean-square error (RMSE). MTC with different triplet combinations generated different error metrics for individual products. The MTC-derived correlation coefficient (CC) was more reliable than RMSE. It is more appropriate to use MTC to compare the relative accuracy of different precipitation products. Based on CC with unknown truth, MTC with different triplet combinations produced the same ranking of products as the traditional method. A comparison of results from MTC and the classic TC with additive error model showed the potential limitation of MTC in arid areas or dry time periods with a large ratio of zero daily precipitation.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Hongkai Gao, hkgao@geo.ecnu.edu.cn
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