Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States?
Abstract Mesoscale convective systems (MCSs) are a major source of precipitation in many regions of the world. Traditional global climate models (GCMs) do not have adequate parameterizations to represent MCSs. In contrast, the Multiscalex Modeling Framework (MMF), which explicitly resolves convectio...
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doaj-d18ad369550648738f8ec297ec6043cf2020-11-24T21:43:28ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662019-12-0111124669468610.1029/2019MS001849Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States?Guangxing Lin0Jiwen Fan1Zhe Feng2William I. Gustafson Jr3Po‐Lun Ma4Kai Zhang5Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USAAtmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USAAtmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USAAtmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USAAtmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USAAtmospheric Sciences and Global Change Division Pacific Northwest National Laboratory Richland WA USAAbstract Mesoscale convective systems (MCSs) are a major source of precipitation in many regions of the world. Traditional global climate models (GCMs) do not have adequate parameterizations to represent MCSs. In contrast, the Multiscalex Modeling Framework (MMF), which explicitly resolves convection within the cloud‐resolving model embedded in each GCM column, has been shown to be a promising tool for simulating MCSs, particularly over the Tropics. In this work, we use ground‐based radar‐observed precipitation, North American Regional Reanalysis data, and a high‐resolution Weather Research and Forecasting simulation to evaluate in detail the MCS‐associated precipitation over the central United States predicted by a prototype MMF simulation that has a 2° host‐GCM grid. We show that the prototype MMF with nudged winds fails to capture the convective initiation in three out of four major MCS events during May 201x1 and underpredicts the precipitation rates for the remaining event, because the model cannot resolve the mesoscale drylines/fronts that are important drivers for initiating convection over the Southern Great Plains region. By reducing the host‐GCM grid spacing to 0.25° in the MMF and nudging the winds, the simulation is able to better capture the mesoscale dynamics, which drastically improves the model performance. We also show that the MMF model performs better than the traditional GCM in capturing the precipitation intensity. Our results suggest that increasing resolution plays a dominant role in improving the simulation of precipitation in the MMF, and the cloud‐resolving model embedded in each GCM column further helps to boost precipitation rate.https://doi.org/10.1029/2019MS001849 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Guangxing Lin Jiwen Fan Zhe Feng William I. Gustafson Jr Po‐Lun Ma Kai Zhang |
spellingShingle |
Guangxing Lin Jiwen Fan Zhe Feng William I. Gustafson Jr Po‐Lun Ma Kai Zhang Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States? Journal of Advances in Modeling Earth Systems |
author_facet |
Guangxing Lin Jiwen Fan Zhe Feng William I. Gustafson Jr Po‐Lun Ma Kai Zhang |
author_sort |
Guangxing Lin |
title |
Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States? |
title_short |
Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States? |
title_full |
Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States? |
title_fullStr |
Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States? |
title_full_unstemmed |
Can the Multiscale Modeling Framework (MMF) Simulate the MCS‐Associated Precipitation Over the Central United States? |
title_sort |
can the multiscale modeling framework (mmf) simulate the mcs‐associated precipitation over the central united states? |
publisher |
American Geophysical Union (AGU) |
series |
Journal of Advances in Modeling Earth Systems |
issn |
1942-2466 |
publishDate |
2019-12-01 |
description |
Abstract Mesoscale convective systems (MCSs) are a major source of precipitation in many regions of the world. Traditional global climate models (GCMs) do not have adequate parameterizations to represent MCSs. In contrast, the Multiscalex Modeling Framework (MMF), which explicitly resolves convection within the cloud‐resolving model embedded in each GCM column, has been shown to be a promising tool for simulating MCSs, particularly over the Tropics. In this work, we use ground‐based radar‐observed precipitation, North American Regional Reanalysis data, and a high‐resolution Weather Research and Forecasting simulation to evaluate in detail the MCS‐associated precipitation over the central United States predicted by a prototype MMF simulation that has a 2° host‐GCM grid. We show that the prototype MMF with nudged winds fails to capture the convective initiation in three out of four major MCS events during May 201x1 and underpredicts the precipitation rates for the remaining event, because the model cannot resolve the mesoscale drylines/fronts that are important drivers for initiating convection over the Southern Great Plains region. By reducing the host‐GCM grid spacing to 0.25° in the MMF and nudging the winds, the simulation is able to better capture the mesoscale dynamics, which drastically improves the model performance. We also show that the MMF model performs better than the traditional GCM in capturing the precipitation intensity. Our results suggest that increasing resolution plays a dominant role in improving the simulation of precipitation in the MMF, and the cloud‐resolving model embedded in each GCM column further helps to boost precipitation rate. |
url |
https://doi.org/10.1029/2019MS001849 |
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