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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

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Author(s):
Adams, David K. ; Barbosa, Henrique M. J. ; Patricia Gaitan De Los Rios, Karen
Total Authors: 3
Document type: Journal article
Source: MONTHLY WEATHER REVIEW; v. 145, n. 1, p. 279-288, JAN 2017.
Web of Science Citations: 3
Abstract

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)

FAPESP's process: 13/50510-5 - Brazil-USA collaborative research: modifications by anthropogenic pollution of the natural atmospheric chemistry and particle microphysics of the tropical rain forest during GoAmazon intensive operating periods
Grantee:Henrique de Melo Jorge Barbosa
Support type: Research Program on Global Climate Change - Regular Grants