A Spatiotemporal Water Vapor-Deep Convection Correlation Metric Derived from the Amazon Dense GNSS Meteorological Network

Autor(es)

Adams, David K. ; Barbosa, Henrique M. J. ; Patricia Gaitan De Los Rios, Karen

• Tipo de documento: Artigo Científico
• Fonte: MONTHLY WEATHER REVIEW; v. 145, n. 1, p. 279-288, JAN 2017.
• Citações Web of Science: 3

Resumo

Deep atmospheric convection, which covers a large range of spatial scales during its evolution, continues to be a challenge for models to replicate, particularly over land in the tropics. Specifically, the shallow-to-deep convective transition and organization on the mesoscale are often not properly represented in coarse-resolution models. High-resolution models offer insights on physical mechanisms responsible for the shallow-to-deep transition. Model verification, however, at both coarse and high resolution requires validation and, hence, observational metrics, which are lacking in the tropics. Here a straightforward metric derived from the Amazon Dense GNSS Meteorological Network (similar to 100 km x 100 km) is presented based on a spatial correlation decay time scale during convective evolution on the mesoscale. For the shallow-to-deep transition, the correlation decay time scale is shown to be around 3.5 h. This novel result provides a much needed metric from the deep tropics for numerical models to replicate. (AU)

• Processo FAPESP: 13/50510-5 - Pesquisa colaborativa Brasil-EUA: modificações causadas pela poluição antrópica na química da atmosfera e na microfísica de partículas da floresta tropical durante as campanhas intensivas do GoAmazon
• Beneficiário: Henrique de Melo Jorge Barbosa
• Linha de fomento: Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - Regular