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).

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Laura D Fowler, Mary C Barth, Kiran Alapaty
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引用次数: 5

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.

Abstract Image

Abstract Image

Abstract Image

基于跨尺度预测模式(MPAS-v5.2)的尺度感知深层对流对云、液、冰水路径和降水的影响。
利用均匀分辨率和变分辨率跨尺度预测模式(MPAS)模拟的云液态水路径(LWP)、冰水路径(IWP)和降水,与云和地球辐射能系统(CERES)以及热带降雨测量任务的数据进行了比较。我们将月平均模式诊断结果与卫星数据进行比较,重点关注热带太平洋的对流活动区,从信风边界层云发展的热带东太平洋盆地延伸到以深度对流上升气流为特征的西太平洋暖池,该暖池被扩展的对流层上层冰云覆盖。使用具有尺度感知的Grell-Freitas (GF)和多尺度kainfritsch (MSKF)对流方案与Thompson云微物理相结合,均匀分辨率实验在模拟和卫星反演的LWP、IWP和降水之间产生了很大的偏差。浅层对流处理的差异导致使用GF时LWP被严重高估,而使用MSKF与CERES数据相比,两者的一致性相对较好。在深对流区域,均匀分辨率和变分辨率实验用MSKF和GF都高估了IWP,导致大气顶部长波和短波辐射相对于卫星反演数据有很强的偏差。由于网格尺度的凝结和向上垂直运动的增加,西太平洋暖池的网格细化并没有导致LWP、IWP和降水的显著改善。结果强调了在进行网格细化全球模拟时,除了降水之外,评估云、其光学特性和大气顶部辐射预算的重要性。
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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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