Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
复制标题
DOI：
10.5194/gmd-15-8135-2022
复制
发表时间：
2022-11
影响因子：
5.1
通讯作者：
Xingying Huang;A. Gettelman;W. Skamarock;P. Lauritzen;Miles Curry;A. Herrington;John T. Truesdale;M. Duda
中科院分区：
文献类型：
--
作者：
Xingying Huang;A. Gettelman;W. Skamarock;P. Lauritzen;Miles Curry;A. Herrington;John T. Truesdale;M. Duda
抽象。全球气候模型（GCM）在许多方面都取得了进展，因为计算能力允许更复杂和更精细的分辨率。由于GCM达到风暴分辨率尺度，他们需要能够产生现实的降水强度，持续时间和频率在细尺度考虑尺度感知参数化。本研究使用了一个国家的最先进的风暴解决GCM与非流体静力学动力学的核心-跨尺度预测模型（MPAS），纳入大气组件（社区大气模型，CAM）的开源社区地球系统模型（CESM），在大气综合建模系统（SIMA）框架内（简称为SIMA-MPAS）。在统一的粗网格分辨率（这里，在120公里），SIMA-MPAS配置是可比的标准流体静力CESM（有限体积（FV）动力核心）与合理的能量和质量守恒的气候时间尺度。CAM-FV（workhorse dynamic core）和SIMA-MPAS（new-developed dynamic core）在能量和质量平衡方面的性能相当，这为SIMA-MPAS在更高分辨率下的应用提供了信心。为了评估这一点，我们专注于如何SIMA-MPAS模型执行时，达到风暴分辨率的规模在3公里。为了有效地做到这一点，我们组成了一个案例研究，使用SIMA-MPAS可变分辨率配置与细化网格3公里，覆盖美国西部和60公里以上的地球仪的其余部分。我们使用卫星和基于站的网格观测与传统的区域气候模型（WRF，天气研究和预报模型）相比，评估了模型的性能。我们的研究结果显示了在时间和空间上精确的复杂地形的降水的现实表示。沿着更好的近地表温度，逼真的地形，和陆-气相互作用，我们还展示了显着增强积雪分布。这项工作表明，在风暴分辨率的全球SIMA-MPAS可以产生更真实的区域气候变率，精细尺度特征和极端，以推进气候和天气研究。这种下一代风暴解析模型最终可以弥合大规模强迫约束，并更好地为气候影响和跨尺度天气预测提供信息。
Abstract. Global climate models (GCMs) have advanced in many ways as computing power has allowed more complexity and finer resolutions. As GCMs reach storm-resolving scales, they need to be able to produce realistic precipitation intensity, duration, and frequency at fine scales with consideration of scale-aware parameterization. This study uses a state-of-the-art storm-resolving GCM with a nonhydrostatic dynamical core – the Model for Prediction Across Scales (MPAS), incorporated in the atmospheric component (Community Atmosphere Model, CAM) of the open-source Community Earth System Model (CESM), within the System for Integrated Modeling of the Atmosphere (SIMA) framework (referred to as SIMA-MPAS). At uniform coarse (here, at 120 km) grid resolution, the SIMA-MPAS configuration is comparable to the standard hydrostatic CESM (with a finite-volume (FV) dynamical core) with reasonable energy and mass conservation on climatological timescales. With the comparable energy and mass balance performance between CAM-FV (workhorse dynamical core) and SIMA-MPAS (newly developed dynamical core), it gives confidence in SIMA-MPAS's applications at a finer resolution. To evaluate this, we focus on how the SIMA-MPAS model performs when reaching a storm-resolving scale at 3 km. To do this efficiently, we compose a case study using a SIMA-MPAS variable-resolution configuration with a refined mesh of 3 km covering the western USA and 60 km over the rest of the globe. We evaluated the model performance using satellite and station-based gridded observations with comparison to a traditional regional climate model (WRF, the Weather Research and Forecasting model). Our results show realistic representations of precipitation over the refined complex terrains temporally and spatially. Along with much improved near-surface temperature, realistic topography, and land–air interactions, we also demonstrate significantly enhanced snowpack distributions. This work illustrates that the global SIMA-MPAS at storm-resolving resolution can produce much more realistic regional climate variability, fine-scale features, and extremes to advance both climate and weather studies. This next-generation storm-resolving model could ultimately bridge large-scale forcing constraints and better inform climate impacts and weather predictions across scales.