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

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.

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Deciphering Organization of GOES–16 Green Cumulus, through the EOF Lens

10.5194/acp-2020-1242 ◽

2021 ◽

Author(s):

Tom Dror ◽

Mickaël D. Chekroun ◽

Orit Altaratz ◽

Ilan Koren

Keyword(s):

Gravity Waves ◽

Data Driven ◽

Time Variability ◽

Eof Analysis ◽

Spatial Properties ◽

Orthogonal Function ◽

Time Period ◽

Dominant Period ◽

Using Data ◽

Underlying Mechanisms

Abstract. A subset of continental shallow convective Cumulus (Cu) cloud fields were shown to have unique spatial properties and to form mostly over forests and vegetated areas, thus referred to as green Cu. 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 (GW), 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.

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EOF Analysis of Green Cumulus Mesoscale Organization

10.5194/egusphere-egu21-10884 ◽

2021 ◽

Author(s):

Tom Dror ◽

Mickael D. Chekroun ◽

Orit Altaratz ◽

Ilan Koren

Keyword(s):

Climate Model ◽

Time Variability ◽

Eof Analysis ◽

Convective Clouds ◽

Spatial Properties ◽

Orthogonal Function ◽

The Earth ◽

Dominant Period ◽

Using Data ◽

Underlying Mechanisms

<p>Warm convective clouds play a key role in the Earth&#8217;s radiative and water budgets. Nonetheless, they still comprise the largest source of uncertainty in climate model&#8217;s prediction of cloud feedback and climate sensitivity. The latter might be affected by the variety of patterns that warm convective clouds form on the mesoscale, an effect which is largely uninvestigated, and even more so over land. A large subset of continental shallow convective cumulus (Cu) fields was shown to have unique spatial properties and to form mostly over forests and vegetated areas thus referred to as green Cu. Green Cu fields form organized mesoscale patterns, yet the underlying mechanisms, as well as the time variability of these patterns, are still lacking understanding.&#160; In this work, we characterize the organization of green Cu in space and time, by using data-driven organization metrics, and by decomposing the high-resolution GOES&#8211;16 data using an Empirical Orthogonal Function (EOF) analysis. We extract and quantify modes of organization present in a green Cu field, during the course of a day. The EOF decomposition shows the field's key organization features such as cloud streets, and it also reveals hidden ones, as the propagation of gravity waves (GW), and the development of a highly ordered grid of clouds that extends over hundreds of kilometers, over a time span that scales as the field's lifetime. We then use cloud fields that were reconstructed from different subgroups of modes to quantify the cloud street's wavelength and aspect ratio, as well as the GW dominant period.</p>

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A cross-scale assessment of productivity-diversity relationships

10.1101/769232 ◽

2019 ◽

Author(s):

Dylan Craven ◽

Masha T. van der Sande ◽

Carsten Meyer ◽

Katharina Gerstner ◽

Joanne M. Bennett ◽

...

Keyword(s):

Structural Equation ◽

Net Primary Productivity ◽

Woody Species ◽

Time Period ◽

Forest Models ◽

Random Forest Models ◽

Spatial Grain ◽

Median Area ◽

Using Data ◽

Underlying Mechanisms

AbstractAimBiodiversity and ecosystem productivity vary across the globe and considerable effort has been made to describe their relationships. Biodiversity-ecosystem functioning research has traditionally focused on how experimentally controlled species richness affects net primary productivity (S→NPP) at small spatial grains. In contrast, the influence of productivity on richness (NPP→S) has been explored at many grains in naturally assembled communities. Mismatches in spatial scale between approaches have fostered debate about the strength and direction of biodiversity-productivity relationships. Here we examine the direction and strength of productivity’s influence on diversity (NPP→S) and of diversity’s influence on productivity (S→NPP), and how this varies across spatial grains.Locationcontiguous USATime period1999 - 2015Major taxa studiedwoody species (angiosperms and gymnosperms)MethodsUsing data from North American forests at grains from local (672 m2) to coarse spatial units (median area = 35,677 km2), we assess relationships between diversity and productivity using structural equation and random forest models, while accounting for variation in climate, environmental heterogeneity, management, and forest age.ResultsWe show that relationships between S and NPP strengthen with spatial grain. Within each grain, S→NPP and NPP→S have similar magnitudes, meaning that processes underlying S→NPP and NPP→S either operate simultaneously, or that one of them is real and the other is an artifact. At all spatial grains, S was one of the weakest predictors of forest productivity, which was largely driven by biomass, temperature, and forest management and age.Main conclusionsWe conclude that spatial grain mediates relationships between biodiversity and productivity in real-world ecosystems and that results supporting predictions from each approach (NPP→S and S→NPP) serve as an impetus for future studies testing underlying mechanisms. Productivity-diversity relationships emerge at multiple spatial grains, which should widen the focus of national and global policy and research to larger spatial grains.

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The Relationship between Equatorial Mixed Rossby–Gravity and Eastward Inertio-Gravity Waves. Part I

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-15-0230.1 ◽

2016 ◽

Vol 73 (5) ◽

pp. 2123-2145 ◽

Cited By ~ 25

Author(s):

George N. Kiladis ◽

Juliana Dias ◽

Maria Gehne

Keyword(s):

Spectral Analysis ◽

Gravity Waves ◽

Empirical Orthogonal Function ◽

Equatorial Waves ◽

Synoptic Scale ◽

Shallow Water Theory ◽

Orthogonal Function ◽

Convectively Coupled Equatorial Waves ◽

Beta Plane ◽

The Relationship

Abstract The relationship between n = 0 mixed Rossby–gravity waves (MRGs) and eastward inertio-gravity waves (EIGs) from Matsuno’s shallow-water theory on an equatorial beta plane is studied using statistics of satellite brightness temperature Tb and dynamical fields from ERA-Interim data. Unlike other observed convectively coupled equatorial waves, which have spectral signals well separated into eastward and westward modes, there is a continuum of MRG–EIG power standing above the background that peaks near wavenumber 0. This continuum is also present in the signals of dry stratospheric MRGs. While hundreds of papers have been written on MRGs, very little work on EIGs has appeared in the literature to date. The authors attribute this to the fact that EIG circulations are much weaker than those of MRGs for a given amount of divergence, making them more difficult to observe even though they strongly modulate convection. Empirical orthogonal function (EOF) and cross-spectral analysis of 2–6-day-filtered Tb isolate zonally standing modes of synoptic-scale convection originally identified by Wallace in 1971. These display antisymmetric Tb signals about the equator that propagate poleward with a period of around 4 days, along with westward-propagating MRG-like circulations that move through the Tb patterns. Further analysis here and in Part II shows that these signatures are not artifacts of the EOF approach but result from a mixture of MRG or EIG modes occurring either in isolation or at the same time.

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