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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)
Citation:
Alapaty, K., L. Fowler, AND M. Barth. 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). Geoscientific Model Development . Copernicus Publications, Katlenburg-Lindau, Germany, 13(6):2851–2877, (2020). https://doi.org/10.5194/gmd-13-2851-2020
Impact/Purpose:
Environmental pollution modeling needs meteorological inputs to drive pollutant fate and transport. Accurate specification of atmospheric state is critical to increase the fidelity of pollutant transport. Using the next generation modeling system, two different atmospheric cloud physical and dynamical formulations were tested & compared with satellite measurements. One of the cloud schemes is developed internally within in the EPA and is adopted by the National Center for Atmospheric Research (NCAR) and implemented by them. Results indicate the EPA cloud scheme is works well and at times fares better than the other cloud scheme in simulating atmospheric parameters when compared to satellite measurements. This research, funded by NCAR will be useful to the ongoing next generation modeling research in our Division (AESM). Further tests are warranted to extend the analysis and evaluation of the performance of the two cloud schemes using other measurements.
Description:
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 Multi-scale 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.
URLs/Downloads:
DOI: 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)
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