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Title: Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions

Abstract

With the incorporation of the Plant-Craig stochastic deep convection scheme into the Zhang-McFarlane deterministic parameterization in the Community Atmospheric Model version 5 (CAM5), its impact on extreme precipitation at different resolutions (2°, 1°, and 0.5°) is investigated. CAM5 with the stochastic deep convection scheme (experiment (EXP)) simulates the precipitation extreme indices better than the standard version (control). At 2° and 1° resolutions, EXP increases high percentile (>99th) daily precipitation over the United States, Europe, and China, resulting in a better agreement with observations. However, at 0.5° resolution, due to enhanced grid-scale precipitation with increasing resolution, EXP overestimates extreme precipitation over southeastern U.S. and eastern Europe. The reduced biases in EXP at each resolution benefit from a broader probability distribution function of convective precipitation intensity simulated. Among EXP simulations at different resolutions, if the spatial averaging area over which input quantities used in convective closure are spatially averaged in the stochastic convection scheme is comparable, the modeled convective precipitation intensity decreases with increasing resolution, when gridded to the same resolution, while the total precipitation is not sensitive to model resolution, exhibiting some degree of scale-awareness. Sensitivity tests show that for the same resolution, increasing the size of spatial averaging area decreasesmore » convective precipitation but increases the grid-scale precipitation.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]
  1. Tsinghua Univ., Beijing (China)
  2. Tsinghua Univ., Beijing (China); Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography
Publication Date:
Research Org.:
Univ. of California, San Diego, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1537318
Grant/Contract Number:  
SC0016504
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 122; Journal Issue: 23; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Meteorology & Atmospheric Sciences

Citation Formats

Wang, Yong, Zhang, Guang J., and He, Yu‐Jun. Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions. United States: N. p., 2017. Web. doi:10.1002/2017jd026901.
Wang, Yong, Zhang, Guang J., & He, Yu‐Jun. Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions. United States. https://doi.org/10.1002/2017jd026901
Wang, Yong, Zhang, Guang J., and He, Yu‐Jun. 2017. "Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions". United States. https://doi.org/10.1002/2017jd026901. https://www.osti.gov/servlets/purl/1537318.
@article{osti_1537318,
title = {Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions},
author = {Wang, Yong and Zhang, Guang J. and He, Yu‐Jun},
abstractNote = {With the incorporation of the Plant-Craig stochastic deep convection scheme into the Zhang-McFarlane deterministic parameterization in the Community Atmospheric Model version 5 (CAM5), its impact on extreme precipitation at different resolutions (2°, 1°, and 0.5°) is investigated. CAM5 with the stochastic deep convection scheme (experiment (EXP)) simulates the precipitation extreme indices better than the standard version (control). At 2° and 1° resolutions, EXP increases high percentile (>99th) daily precipitation over the United States, Europe, and China, resulting in a better agreement with observations. However, at 0.5° resolution, due to enhanced grid-scale precipitation with increasing resolution, EXP overestimates extreme precipitation over southeastern U.S. and eastern Europe. The reduced biases in EXP at each resolution benefit from a broader probability distribution function of convective precipitation intensity simulated. Among EXP simulations at different resolutions, if the spatial averaging area over which input quantities used in convective closure are spatially averaged in the stochastic convection scheme is comparable, the modeled convective precipitation intensity decreases with increasing resolution, when gridded to the same resolution, while the total precipitation is not sensitive to model resolution, exhibiting some degree of scale-awareness. Sensitivity tests show that for the same resolution, increasing the size of spatial averaging area decreases convective precipitation but increases the grid-scale precipitation.},
doi = {10.1002/2017jd026901},
url = {https://www.osti.gov/biblio/1537318}, journal = {Journal of Geophysical Research: Atmospheres},
issn = {2169-897X},
number = 23,
volume = 122,
place = {United States},
year = {Wed Nov 22 00:00:00 EST 2017},
month = {Wed Nov 22 00:00:00 EST 2017}
}

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Cited by: 13 works
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Works referenced in this record:

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Works referencing / citing this record:

Convective response to large-scale forcing in the tropical western Pacific simulated by spCAM5 and CanAM4.3
journal, January 2019