Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework

Abstract Cloud and precipitation systems are simulated with a multi‐scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar‐defined Precipitation Features (RPFs) product. A methodology, in close analogy to the TRMM RPFs...

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Autores principales:	Jiun‐Dar Chern, Wei‐Kuo Tao, Stephen E. Lang, Xiaowen Li, Toshihisa Matsui
Formato:	article
Lenguaje:	EN
Publicado:	American Geophysical Union (AGU) 2020
Materias:	Superparameterization multi‐scale modeling framework TRMM precipitation features two‐dimensionality cyclic boundary tropical precipitation Physical geography GB3-5030 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/eadc470c9f2e4c868163ed7722c75e80
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spelling	oai:doaj.org-article:eadc470c9f2e4c868163ed7722c75e802021-11-15T14:20:26ZEvaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework1942-246610.1029/2019MS002007https://doaj.org/article/eadc470c9f2e4c868163ed7722c75e802020-08-01T00:00:00Zhttps://doi.org/10.1029/2019MS002007https://doaj.org/toc/1942-2466Abstract Cloud and precipitation systems are simulated with a multi‐scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar‐defined Precipitation Features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to produce simulated precipitation features (PFs) from the output of the embedded two‐dimensional (2D) cloud‐resolving models (CRMs) within an MMF. Despite the limitations of 2D CRMs, the simulated population distribution, horizontal and vertical structure of PFs, and the geographical location and local rainfall contribution of mesoscale convective systems (MCSs) are in good agreement with the TRMM observations. However, some model discrepancies are found and can be identified and quantified within the PF distributions. Using model biases in relative population and rainfall contributions, PFs can be characterized into four size categories: small, medium to large, very large, and extremely large. Four different major mechanisms might account for the model biases in each different category: (1) the two‐dimensionality of the CRMs, (2) a positive convection‐wind‐evaporation feedback loop, (3) an artificial dynamic constraint in a bounded CRM domain with cyclic boundaries, and (4) the limited CRM domain size. The second and fourth mechanisms tend to contribute to the excessive tropical precipitation biases commonly found in most MMFs, whereas the other mechanisms reduce rainfall contributions from small and very large PFs. MMF sensitivity experiments with various CRM domain sizes and grid spacings showed that larger domains (higher resolutions) tend to shift PF populations toward larger (smaller) sizes.Jiun‐Dar ChernWei‐Kuo TaoStephen E. LangXiaowen LiToshihisa MatsuiAmerican Geophysical Union (AGU)articleSuperparameterizationmulti‐scale modeling frameworkTRMM precipitation featurestwo‐dimensionalitycyclic boundarytropical precipitationPhysical geographyGB3-5030OceanographyGC1-1581ENJournal of Advances in Modeling Earth Systems, Vol 12, Iss 8, Pp n/a-n/a (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Superparameterization multi‐scale modeling framework TRMM precipitation features two‐dimensionality cyclic boundary tropical precipitation Physical geography GB3-5030 Oceanography GC1-1581
spellingShingle	Superparameterization multi‐scale modeling framework TRMM precipitation features two‐dimensionality cyclic boundary tropical precipitation Physical geography GB3-5030 Oceanography GC1-1581 Jiun‐Dar Chern Wei‐Kuo Tao Stephen E. Lang Xiaowen Li Toshihisa Matsui Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework
description	Abstract Cloud and precipitation systems are simulated with a multi‐scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar‐defined Precipitation Features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to produce simulated precipitation features (PFs) from the output of the embedded two‐dimensional (2D) cloud‐resolving models (CRMs) within an MMF. Despite the limitations of 2D CRMs, the simulated population distribution, horizontal and vertical structure of PFs, and the geographical location and local rainfall contribution of mesoscale convective systems (MCSs) are in good agreement with the TRMM observations. However, some model discrepancies are found and can be identified and quantified within the PF distributions. Using model biases in relative population and rainfall contributions, PFs can be characterized into four size categories: small, medium to large, very large, and extremely large. Four different major mechanisms might account for the model biases in each different category: (1) the two‐dimensionality of the CRMs, (2) a positive convection‐wind‐evaporation feedback loop, (3) an artificial dynamic constraint in a bounded CRM domain with cyclic boundaries, and (4) the limited CRM domain size. The second and fourth mechanisms tend to contribute to the excessive tropical precipitation biases commonly found in most MMFs, whereas the other mechanisms reduce rainfall contributions from small and very large PFs. MMF sensitivity experiments with various CRM domain sizes and grid spacings showed that larger domains (higher resolutions) tend to shift PF populations toward larger (smaller) sizes.
format	article
author	Jiun‐Dar Chern Wei‐Kuo Tao Stephen E. Lang Xiaowen Li Toshihisa Matsui
author_facet	Jiun‐Dar Chern Wei‐Kuo Tao Stephen E. Lang Xiaowen Li Toshihisa Matsui
author_sort	Jiun‐Dar Chern
title	Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework
title_short	Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework
title_full	Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework
title_fullStr	Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework
title_full_unstemmed	Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework
title_sort	evaluating precipitation features and rainfall characteristics in a multi‐scale modeling framework
publisher	American Geophysical Union (AGU)
publishDate	2020
url	https://doaj.org/article/eadc470c9f2e4c868163ed7722c75e80
work_keys_str_mv	AT jiundarchern evaluatingprecipitationfeaturesandrainfallcharacteristicsinamultiscalemodelingframework AT weikuotao evaluatingprecipitationfeaturesandrainfallcharacteristicsinamultiscalemodelingframework AT stephenelang evaluatingprecipitationfeaturesandrainfallcharacteristicsinamultiscalemodelingframework AT xiaowenli evaluatingprecipitationfeaturesandrainfallcharacteristicsinamultiscalemodelingframework AT toshihisamatsui evaluatingprecipitationfeaturesandrainfallcharacteristicsinamultiscalemodelingframework
_version_	1718428409204310016

Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework

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