Deciphering organization of GOES-16 green cumulus through the empirical orthogonal function (EOF) lens

Tom Dror,Orit Altaratz,Mickaël D. Chekroun,Ilan Koren

doi:10.5194/acp-21-12261-2021

Abstract

Abstract. 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.

Highlights

The emergence of organized patterns in cloud fields is ubiquitous and observed throughout different cloud types around the world, across a wide range of scales
We proposed a new approach combining GOES-16 Advanced Baseline Imager (ABI)’s high-resolution corrected reflectance data, organization metrics, and an empirical orthogonal function (EOF) analysis to investigate and characterize the mesoscale patterns obtained by a vast shallow Cu field over continental US (CONUS), during 22 August 2018
By focusing on two subdomains, we show that gravity waves (GWs), that are orthogonal to the cloud streets, travel through the field and affect the organization by clustering the clouds, making them larger and fewer, and that the clouds’ organization deviates from randomness to a gridlike organization type (Fig. 3)

Summary

Introduction

The emergence of organized patterns in cloud fields is ubiquitous and observed throughout different cloud types around the world, across a wide range of scales. Shallow cumulus (Cu) clouds cover large areas over the oceans and continents (Norris, 1998; Bony et al, 2004) They reflect part of the incoming solar radiation but have minor influence on the outgoing longwave radiation (OLR) (Turner et al, 2007; Berg et al, 2011); they contribute to a net cooling effect on the planet (Boucher et al, 2013). Shallow Cu fields exhibit a variety of patterns such as cloud streets (Brown, 1980), clusters (Zhu et al, 1992; Heus and Seifert, 2013), skeletal networks, or mesoscale arcs (Stevens et al, 2019) Such organized patterns of a cloud field result often from the interaction between the internal nonlinear dynamics (self-organization) and the external forcings (Klitch et al, 1985). These properties determine the clouds’ locations and their size distribution within the field (Seifert and Heus, 2013), and they play a key role in determining the radiative effects (Tobin et al, 2012)

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Conclusion