Uncovering the Large-Scale Meteorology That Drives Continental, Shallow, Green Cumulus Through Supervised Classification

Abstract

One of the major sources of uncertainty in climate prediction results from the limitations in representing shallow cumulus (Cu) in models. Recently, a class of continental shallow convective Cu was shown to share distinct morphological properties and to emerge globally mostly over forests and vegetated areas, thus named greenCu. Using machine-learning supervised classification, we identify greenCu fields over three regions, from the tropics to mid- and higher-latitudes, and establish a novel satellite-based data set called greenCuDb, consisting of 1° × 1° sized, high-resolution MODIS images. Using greenCuDb in conjunction with ERA5 reanalysis data, we create greenCu composites for different regions and reveal that greenCu are driven by similar large-scale meteorological conditions, regardless of their geographical locations throughout the world's continents. These conditions include distinct profiles of temperature, humidity and large-scale vertical velocity. The boundary layer is anomalously warm and moderately humid, and is accompanied by a strong large-scale subsidence in the free troposphere.

Figure 1

Model predictions: boxplot of cloud fraction (CF) per class and region (Amazon, USA, and Eastern Europe). In each box, the circle marks the median, the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. The whiskers extend to the most extreme data points not considered outliers. Dashed horizontal lines indicate the mean 25th and 75th percentiles of greenCu CF used as lower and upper thresholds to filter the greenCu post‐processing. Bottom row shows, for each class, a representative 1° × 1° image.

Figure 2

The greenCu share similar organizational patterns.Examples of 1° × 1° greenCu fields over the (a) Amazon, (b) USA, and (c) Eastern Europe. Observed Nearest Neighbor Cumulative Density Function (NNCDF) against Poisson NNCDF, and a boxplot of I _org for the (d) Amazon, (e) USA, and (f) Eastern Europe.

Figure 3

Large‐scale meteorological conditions associated with the different classes (upper‐row), greenCu composites per region (middle‐row), and greenCu normalized anomalies from the June–July–August climatological mean (lower‐row) in the Amazon (black), USA (blue), and Eastern Europe (red). Mean vertical profiles of θ, q, RH, and ω (column‐wise, from left to right, respectively). The standard deviations are shown in Figure S4 in Supporting Information S1.