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A Spatiotemporal Water Vapor-Deep Convection Correlation Metric Derived from the Amazon Dense GNSS Meteorological Network
- Source :
- Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual), Universidade de São Paulo (USP), instacron:USP
- Publication Year :
- 2017
-
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 (~100 km × 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.
- Subjects :
- Convection
Atmospheric Science
Spatial correlation
010504 meteorology & atmospheric sciences
Meteorology
Scale (ratio)
AQUECIMENTO GLOBAL
Mesoscale meteorology
010502 geochemistry & geophysics
01 natural sciences
Atmospheric convection
GNSS applications
Metric (mathematics)
Environmental science
Physics::Atmospheric and Oceanic Physics
Water vapor
0105 earth and related environmental sciences
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual), Universidade de São Paulo (USP), instacron:USP
- Accession number :
- edsair.doi.dedup.....cf6336f613e26cf44dc4eafe9e1c8968