Volume 128, Issue 12 e2023JD038553
Research Article

Effects of Lower Troposphere Vertical Mixing on Simulated Clouds and Precipitation Over the Amazon During the Wet Season

Xiao-Ming Hu

Corresponding Author

Xiao-Ming Hu

Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, OK, USA

School of Meteorology, University of Oklahoma, Norman, OK, USA

Correspondence to:

X.-M. Hu, M. Xue and H. M. Novoa,

[email protected];

[email protected];

[email protected]

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Yongjie Huang

Yongjie Huang

Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, OK, USA

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Ming Xue

Corresponding Author

Ming Xue

Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, OK, USA

School of Meteorology, University of Oklahoma, Norman, OK, USA

Correspondence to:

X.-M. Hu, M. Xue and H. M. Novoa,

[email protected];

[email protected];

[email protected]

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Elinor Martin

Elinor Martin

School of Meteorology, University of Oklahoma, Norman, OK, USA

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Yang Hong

Yang Hong

School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK, USA

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Mengye Chen

Mengye Chen

School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK, USA

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Hector Mayol Novoa

Corresponding Author

Hector Mayol Novoa

Universidad Nacional de San Agustín de Arequipa, Arequipa, Peru

Correspondence to:

X.-M. Hu, M. Xue and H. M. Novoa,

[email protected];

[email protected];

[email protected]

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Renee McPherson

Renee McPherson

Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK, USA

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Andres Perez

Andres Perez

Universidad Nacional de San Agustín de Arequipa, Arequipa, Peru

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Isaac Yanqui Morales

Isaac Yanqui Morales

Universidad Nacional de San Agustín de Arequipa, Arequipa, Peru

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Auria Julieta Flores Luna

Auria Julieta Flores Luna

Universidad Nacional de San Agustín de Arequipa, Arequipa, Peru

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First published: 18 June 2023
Citations: 1

Abstract

Planetary boundary layer (PBL) schemes parameterize unresolved turbulent mixing within the PBL and free troposphere (FT). Previous studies reported that precipitation simulation over the Amazon in South America is quite sensitive to PBL schemes and the exact relationship between the turbulent mixing and precipitation processes is, however, not disentangled. In this study, regional climate simulations over the Amazon in January–February 2019 are examined at process level to understand the precipitation sensitivity to PBL scheme. The focus is on two PBL schemes, the Yonsei University (YSU) scheme, and the asymmetric convective model v2 (ACM2) scheme, which show the largest difference in the simulated precipitation. During daytime, while the FT clouds simulated by YSU dissipate, clouds simulated by ACM2 maintain because of enhanced moisture supply due to the enhanced vertical moisture relay transport process: (a) vertical mixing within PBL transports surface moisture to the PBL top, and (b) FT mixing feeds the moisture into the FT cloud deck. Due to the thick cloud deck over Amazon simulated by ACM2, surface radiative heating is reduced and consequently the convective available potential energy is reduced. As a result, precipitation is weaker from ACM2. Two key parameters dictating the vertical mixing are identified, p, an exponent determining boundary layer mixing and λ, a scale dictating FT mixing. Sensitivity simulations with altered p, λ, and other treatments within YSU and ACM2 confirm the precipitation sensitivity. The FT mixing in the presence of clouds appears most critical to explain the sensitivity between YSU and ACM2.

Key Points

  • Disentangle turbulence/cloud/precipitation processes over Amazon and reveal root cause for sensitivity to planetary boundary layer (PBL) schemes using the Weather Research and Forecasting model

  • Free troposphere (FT) mixing becomes prominent in the presence of clouds, which in turn supports maintenance of the FT clouds that would otherwise dissipate

  • Stronger vertical moisture relay transport in asymmetric convective model v2 (ACM2) PBL scheme supports thicker FT clouds, leading to reduced heating and precipitation

Plain Language Summary

Predictions of weather and climate in terms of clouds and precipitation over the Amazon in South America are quite uncertain. This uncertainty has been largely attributed to errors in the planetary boundary layer (PBL) scheme, which represents turbulent mixing. A lack of understanding of the relationship between turbulence, clouds, and precipitation processes prevents us from improving PBL representation in models to achieve better weather and climate simulations. This study disentangles the turbulence/clouds/precipitation relationship, and identifies the root cause of model errors in PBL schemes using regional climate simulations over the Amazon. Two PBL schemes, the Yonsei University (YSU) scheme, and the asymmetric convective model v2 (ACM2) scheme, are examined, which show the largest difference in the simulated precipitation. The main difference between the two PBL schemes is the dissipation (YSU) or maintenance (ACM2) of clouds during daytime above the boundary layer, which modulates surface heating and consequently precipitation. The maintenance of a thick cloud deck over the Amazon in ACM2, is caused by enhanced vertical transport of moisture from the surface to above the boundary layer. Such an improved understanding of the turbulence/clouds/precipitation relationship allow us to propose potential solutions to improve PBL schemes in weather and climate models.

Data Availability Statement

The ERA5 reanalysis data (Hersbach et al., 2020) are available at https://doi.org/10.5065/BH6N-5N20. GPM IMERG Final Precipitation data set is from Huffman et al. (2019). CMORPH data set (Joyce et al., 2004) is available at https://ftp.cpc.ncep.noaa.gov/precip/CMORPH_V1.0/CRT/8km-30min (last access: 12 November 2020). Figures in this manuscript are produced using the NCAR Command Language (Version 6.6.2) [Software] (2019). Model data produced from this study have been archived at CAPS website https://caps.ou.edu/micronet/Regionalclimate.html and the Luster NSF projects data server at the San Diego Super computer Center,/expanse/luster/projects/uok114/xhu2.