Sensitivity of the Shallow-to-Deep Convective Transition to Moisture and Wind Shear in the Amazon

dc.contributor.authorViscardi, Leandro Alex Moreira
dc.contributor.authorTorri, Giuseppe
dc.contributor.authorAdams, David Kenton
dc.contributor.authorBarbosa, H. M. J.
dc.date.accessioned2024-11-14T15:19:02Z
dc.date.available2024-11-14T15:19:02Z
dc.date.issued2025-04-17
dc.description.abstractDeep convection is the primary influence on weather and climate in tropical regions. However, understanding and simulating the shallow-to-deep (STD) convective transition has long been challenging. Here, we conduct high-resolution numerical simulations to assess the environmental controls on the evolution of isolated convection in the Amazon during the wet season. The large-scale forcing derived through a constrained variational analysis approach for the GoAmazon2014/5 Experiment is used in the simulations. Through sensitivity experiments, we examine the relative importance of moisture and wind shear in controlling the shallow-to-deep convective transition for isolated convective events. Convection exhibits the greatest sensitivity to humidity within the lowest 1.5 km, where a 4 mm reduction in column water vapor nearly suppresses ice water formation on deep convective days. In contrast, a reduction in column water vapor in the free troposphere by a factor of two or more is necessary to produce a comparable impact on convection. Increasing low-level wind speed from 6 to 9 m s⁻¹ enhances afternoon deep convection, raising the cloud ice mixing ratio by approximately 25%. Conversely, upper-level wind shear reveals the weakest correlation with daytime convection in our simulations. Our results help characterize the role of moisture and wind shear on the STD transition and our understanding of the underlying mechanisms.
dc.description.sponsorshipThe authors express their gratitude to Marat Khairoutdinov for providing access to the SAM code and for offering valuable assistance with the Land Surface Model. The technical support and advanced computing resources from University of Hawai‘i Information Technology Services – Cyberinfrastructure, funded in part by the National Science Foundation CC∗awards # 2201428 and # 2232862 are gratefully acknowledged. We also acknowledge the data from the Atmospheric Radiation Measurement (ARM) Program sponsored by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division. L.A.M.V. acknowledges the Brazilian National Council for Scientific and Technological Development (CNPq) graduate fellowship (grant number 148652/2019-0). Additionally, gratitude is extended to the Coordination for the Improvement of Higher Education Personnel (CAPES) fellowship (grant number 88887.571091/2020-00). H.M.J.B acknowledges support from the –19– manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES) U.S. Department of Energy, Office of Science, Biological and Environmental Research program under Award Number DE-SC-0023058.
dc.description.urihttps://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024MS004238
dc.format.extent13 pages
dc.genrejournal articles
dc.identifierdoi:10.13016/m2qdao-zbl4
dc.identifier.citationViscardi, Leandro Alex Moreira, Giuseppe Torri, David K. Adams, and Henrique de Melo Jorge Barbosa. “Sensitivity of the Shallow-To-Deep Convective Transition to Moisture and Wind Shear in the Amazon.” Journal of Advances in Modeling Earth Systems 17, no. 4 (2025): e2024MS004238. https://doi.org/10.1029/2024MS004238.
dc.identifier.urihttps://doi.org/10.1029/2024MS004238
dc.identifier.urihttp://hdl.handle.net/11603/36984
dc.language.isoen_US
dc.publisherAGU
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Physics Department
dc.relation.ispartofUMBC Faculty Collection
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleSensitivity of the Shallow-to-Deep Convective Transition to Moisture and Wind Shear in the Amazon
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-4027-1855

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