Deciphering organization of GOES-16 green cumulus through the empirical orthogonal function (EOF) lens
| Autor: | Mickaël D. Chekroun, Orit Altaratz, Tom Dror, Ilan Koren |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences Spacetime Meteorology business.industry Physics QC1-999 Mesoscale meteorology Empirical orthogonal functions Cloud computing 15. Life on land Grid 01 natural sciences Field (geography) 010305 fluids & plasmas Wavelength Chemistry 0103 physical sciences Spatial ecology business QD1-999 Geology 0105 earth and related environmental sciences |
| Zdroj: | Atmospheric Chemistry and Physics, Vol 21, Pp 12261-12272 (2021) Atmospheric Chemistry and Physics |
| ISSN: | 1680-7324 1680-7316 |
| Popis: | A subset of continental shallow convective cumulus (Cu) cloud fields has been shown to have distinct spatial properties and to form mostly over forests and vegetated areas, thus referred to as “green Cu” (Dror et al., 2020). Green Cu fields are known to form organized mesoscale patterns, yet the underlying mechanisms, as well as the time variability of these patterns, are still lacking understanding. Here, we characterize the organization of green Cu in space and time, by using data-driven organization metrics and by applying an empirical orthogonal function (EOF) analysis to a high-resolution GOES-16 dataset. We extract, quantify, and reveal modes of organization present in a green Cu field, during the course of a day. The EOF decomposition is able to show the field's key organization features such as cloud streets, and it also delineates the less visible ones, as the propagation of gravity waves (GWs) and the emergence of a highly organized grid on a spatial scale of hundreds of kilometers, over a time period that scales with the field's lifetime. Using cloud fields that were reconstructed from different subgroups of modes, we quantify the cloud street's wavelength and aspect ratio, as well as the GW-dominant period. |
| Databáze: | OpenAIRE |
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