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

Abstract

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.

Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM

“…The E3SM Atmosphere Model version 1 (EAMv1) was developed from the NCAR Community Atmosphere Model version 5.3 (CAM5.3; Neale et al., 2012) with significant changes in many aspects including coding, performance, resolution, physics parameterizations, testing, and development procedures (Rasch et al., 2019). The overall performance of EAMv1 in simulating aerosols, clouds, convection, precipitation, as well as other technical details in model tuning and numerical choices can be seen in many preceding studies (e.g., Lin et al., 2019; Qian et al., 2018; Xie et al., 2018; Wang et al., 2020; Wang et al., 2021; Zhang et al., 2018; Zhang et al., 2019). The RRM framework has been implemented in EAMv1 with 0.25° over CONUS, where the topography is re‐configured and a new tensor hyperviscosity formulation (Guba et al., 2014) is applied to eliminate numerical noise and oscillations (Tang et al., 2019).…”