Impact of scale-aware deep convection on the cloud liquid and ice water paths and precipitation using the Model for Prediction Across Scales (MPAS-v5.2).

Laura D Fowler,Mary C Barth,Kiran Alapaty

doi:10.5194/gmd-13-2851-2020

Abstract

The cloud liquid water path (LWP), ice water path (IWP), and precipitation simulated with uniform- and variable-resolution numerical experiments using the Model for Prediction Across Scales (MPAS) are compared against Clouds and the Earth’s Radiant Energy System (CERES) and Tropical Rainfall Measuring Mission data. Our comparison between monthly-mean model diagnostics and satellite data focuses on the convective activity regions of the tropical Pacific Ocean, extending from the Tropical Eastern Pacific Basin where trade wind boundary layer clouds develop to the Western Pacific Warm Pool characterized by deep convective updrafts capped with extended upper-tropospheric ice clouds. Using the scale-aware Grell–Freitas (GF) and Multiscale Kain–Fritsch (MSKF) convection schemes in conjunction with the Thompson cloud microphysics, uniform-resolution experiments produce large biases between simulated and satellite-retrieved LWP, IWP, and precipitation. Differences in the treatment of shallow convection lead the LWP to be strongly overestimated when using GF, while being in relatively good agreement when using MSKF compared to CERES data. Over areas of deep convection, uniform- and variable-resolution experiments overestimate the IWP with both MSKF and GF, leading to strong biases in the top-of-the-atmosphere longwave and shortwave radiation relative to satellite-retrieved data. Mesh refinement over the Western Pacific Warm Pool does not lead to significant improvement in the LWP, IWP, and precipitation due to increased grid-scale condensation and upward vertical motions. Results underscore the importance of evaluating clouds, their optical properties, and the top-of-the-atmosphere radiation budget in addition to precipitation when performing mesh refinement global simulations.

Highlights

Comparing simulated against observed global cloud liquid and ice water paths (LWP and IWP) remains challenging because of uncertainties in parameterizing moist processes and cloudiness in global climate and numerical weather prediction (NWP) models and errors in retrieving the liquid water path (LWP) and IWP from satellite measurements
Cloud simulations from general circulation models (GCMs) involved in Phase 3 and 5 of the Coupled Model Intercomparison Project (CMIP3; CMIP5; Meehl et al, 2007; Taylor et al, 2012) display a strong disparity in the simulated LWP (Jiang et al, 2012; Li et al, 2018) and IWP (Li et al, 2012), producing annual mean LWP and IWP overestimated by factors of 2 to 10 compared to satellite data
We suggest that uncertainties in parameterizing moist convection and impact on grid-scale clouds may explain a major part of the differences in the LWP and IWP simulated between the CMIP3 and CMIP5 GCMs

Summary

Introduction

Comparing simulated against observed global cloud liquid and ice water paths (LWP and IWP) remains challenging because of uncertainties in parameterizing moist processes and cloudiness in global climate and numerical weather prediction (NWP) models and errors in retrieving the LWP and IWP from satellite measurements. Defining the LWP and IWP varies between models, depending on the complexity of the parameterization of cloud microphysics processes and prognostic versus diagnostic treatment of falling hydrometeors. While comparing simulated and observed LWP and IWP may not be as straightforward as comparing the top-of-the-atmosphere (TOA) radiation budget (Dolinar et al, 2015; Stanfield et al, 2015), it offers a different way to directly diagnose biases in simulated total cloud liquid and ice water mass as a first step to help correct deficiencies in parameterizing global-scale moist processes and precipitation

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