Editorial Type:
Article
Article Type:
Research Article

Impact of Gauge Representative Error on a Radar Rainfall Uncertainty Model

Qiang Dai Key Laboratory of Virtual Geographic Environment, Ministry of Education, and School of Geography Science, Nanjing Normal University, Nanjing, China, and Water and Environmental Management Research Centre, Department of Civil Engineering, University of Bristol, Bristol, United Kingdom, and Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China

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Qiqi Yang Key Laboratory of Virtual Geographic Environment, Ministry of Education, and School of Geography Science, Nanjing Normal University, Nanjing, China

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Jun Zhang Water and Environmental Management Research Centre, Department of Civil Engineering, University of Bristol, Bristol, United Kingdom

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Shuliang Zhang Key Laboratory of Virtual Geographic Environment, Ministry of Education, and School of Geography Science, Nanjing Normal University, Nanjing, China

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Print Publication:
01 Dec 2018
DOI:
https://doi.org/10.1175/JAMC-D-17-0272.1
Page(s):
2769–2787
Restricted access

Abstract

In modeling the radar rainfall uncertainty, rain gauge measurement is generally regarded as the areal “true” rainfall. However, the inconsistent scales between radar and gauge may introduce a new uncertainty (also known as gauge representative uncertainty), which is erroneously identified as radar rainfall uncertainty and therefore called pseudouncertainty. It is crucial to comprehend what percentage of the estimated radar rainfall uncertainty actually stems from such pseudouncertainty rather than radar rainfall itself. For this reason, based on a fully formulated radar rainfall uncertainty model, this study aims to explore how the gauge representative error affects the distribution, spatial dependence, and temporal dependence of hourly accumulated radar rainfall uncertainty, and consequently affects the produced radar rainfall uncertainty band. Three group scenarios that delineate various degrees of gauge representative errors were designed to configure and run the uncertainty model. In the setting of a long-term analysis (almost 7 years) of the Brue catchment in the United Kingdom, we found that the gauge representative error affected the simulation of the marginal distribution of radar rainfall error, and had a considerable effect on temporal dependence estimation of radar rainfall uncertainty. The spread of the rainfall uncertainty band decreased with the growth of the gauge density in a radar pixel. The scenario with the lowest representative error only had 78% uncertainty spread of the scenario that has the largest error. This indicated there was a large impact of the representative error on radar rainfall uncertainty models. It is hoped that more catchments with diverse climate and geographical conditions and more radar data with various spatial scales could be explored by the research community to further investigate this crucial issue.

© 2018 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: Shuliang Zhang, zhangshuliang@njnu.edu.cn

Abstract

In modeling the radar rainfall uncertainty, rain gauge measurement is generally regarded as the areal “true” rainfall. However, the inconsistent scales between radar and gauge may introduce a new uncertainty (also known as gauge representative uncertainty), which is erroneously identified as radar rainfall uncertainty and therefore called pseudouncertainty. It is crucial to comprehend what percentage of the estimated radar rainfall uncertainty actually stems from such pseudouncertainty rather than radar rainfall itself. For this reason, based on a fully formulated radar rainfall uncertainty model, this study aims to explore how the gauge representative error affects the distribution, spatial dependence, and temporal dependence of hourly accumulated radar rainfall uncertainty, and consequently affects the produced radar rainfall uncertainty band. Three group scenarios that delineate various degrees of gauge representative errors were designed to configure and run the uncertainty model. In the setting of a long-term analysis (almost 7 years) of the Brue catchment in the United Kingdom, we found that the gauge representative error affected the simulation of the marginal distribution of radar rainfall error, and had a considerable effect on temporal dependence estimation of radar rainfall uncertainty. The spread of the rainfall uncertainty band decreased with the growth of the gauge density in a radar pixel. The scenario with the lowest representative error only had 78% uncertainty spread of the scenario that has the largest error. This indicated there was a large impact of the representative error on radar rainfall uncertainty models. It is hoped that more catchments with diverse climate and geographical conditions and more radar data with various spatial scales could be explored by the research community to further investigate this crucial issue.

© 2018 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: Shuliang Zhang, zhangshuliang@njnu.edu.cn
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Journal of Applied Meteorology and Climatology

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