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Abstract. Global climate models (GCMs) have advanced in many ways ascomputing power has allowed more complexity and finer resolutions. As GCMsreach storm-resolving scales, they need to be able to produce realisticprecipitation intensity, duration, and frequency at fine scales withconsideration of scale-aware parameterization. This study uses astate-of-the-art storm-resolving GCM with a nonhydrostatic dynamical core – theModel for Prediction Across Scales (MPAS), incorporated in the atmosphericcomponent (Community Atmosphere Model, CAM) of the open-source CommunityEarth System Model (CESM), within the System for Integrated Modeling of theAtmosphere (SIMA) framework (referred to as SIMA-MPAS). At uniform coarse (here, at 120 km) gridresolution, the SIMA-MPAS configuration is comparable to the standardhydrostatic CESM (with a finite-volume (FV) dynamical core) with reasonableenergy and mass conservation on climatological timescales. With thecomparable energy and mass balance performance between CAM-FV (workhorse dynamical core) and SIMA-MPAS (newly developed dynamical core), it gives confidence inSIMA-MPAS's applications at a finer resolution. To evaluate this, we focuson how the SIMA-MPAS model performs when reaching a storm-resolving scale at3 km. To do this efficiently, we compose a case study using a SIMA-MPASvariable-resolution configuration with a refined mesh of 3 km covering thewestern USA and 60 km over the rest of the globe. We evaluated the modelperformance using satellite and station-based gridded observations withcomparison to a traditional regional climate model (WRF, the WeatherResearch and Forecasting model). Our results show realistic representationsof precipitation over the refined complex terrains temporally and spatially.Along with much improved near-surface temperature, realistic topography, andland–air interactions, we also demonstrate significantly enhanced snowpackdistributions. This work illustrates that the global SIMA-MPAS atstorm-resolving resolution can produce much more realistic regional climatevariability, fine-scale features, and extremes to advance both climate andweather studies. This next-generation storm-resolving model could ultimatelybridge large-scale forcing constraints and better inform climate impactsand weather predictions across scales.
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Examining Tropical Convection Features at Storm‐Resolving Scales Over the Maritime Continent Region
Abstract Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better‐informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open‐source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. We focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional‐refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm‐resolving model in precipitation predictions across scales.
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- PAR ID:
- 10616545
- Publisher / Repository:
- American Geophysical Union
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 129
- Issue:
- 20
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Journal Article:
- https://doi.org/10.1029/2024JD040976
