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Using Radar Observations to Evaluate 3D Radar Echo Structure Simulated by a Global Model.

Authors :
Jingyu Wang
Jiwen Fan
Houze Jr., Robert A.
Brodzik, Stella R.
Kai Zhang
Zhang, Guang J.
Ma, Po-Lun
Source :
Geoscientific Model Development Discussions. 5/25/2020, p1-23. 23p.
Publication Year :
2020

Abstract

The Energy Exascale Earth System Model (E3SM) developed by the Department of Energy has a goal of addressing challenges in understanding the global water cycle. Success depends on correct simulation of cloud and precipitation elements. However, lack of appropriate evaluation metrics has hindered the accurate representation of these elements in general circulation models. We derive metrics from the three-dimensional data of the ground-based Next generation radar (NEXRAD) network over the U.S. to evaluate both horizontal and vertical structures of precipitation elements. We coarsened the resolution of the radar observations to be consistent with the model resolution and improved the coupling of the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) and E3SM Atmospheric Model Version 1 (EAMv1) to obtain the best possible model output for comparison with the observations. Three warm seasons (2014-2016) of EAMv1 simulations of 3D radar reflectivity features at an hourly scale are evaluated. A general agreement in domain-mean radar reflectivity intensity is found between EAMv1 and NEXRAD below 4 km altitude; however, the model underestimates reflectivity over the central United States, which suggests that the model does not capture the mesoscale convective systems that produce much of precipitation in that region. The shape of the model estimated histogram of subgrid scale reflectivity is improved by correcting the microphysical assumptions in COSP. The model severely underestimates radar reflectivity at upper levels - the simulated echo top height is about 4 km lower than in observations - and this result is not changed by tuning any single physics parameter. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19919611
Database :
Academic Search Index
Journal :
Geoscientific Model Development Discussions
Publication Type :
Academic Journal
Accession number :
143395417
Full Text :
https://doi.org/10.5194/gmd-2020-98