Horizontal and Vertical Scaling of Cloud Geometry Inferred from CloudSat Data

Abstract

A method is described to characterize the scale dependence of cloud chord length using cloud-type classification reported with the 94-GHz CloudSat radar. The cloud length along the CloudSat track is quantified using horizontal and vertical structures of cloud classification separately for each cloud type and for all clouds independent of cloud type. While the individual cloud types do not follow a clear power-law behavior as a function of horizontal or vertical scale, a robust power-law scaling of cloud chord length is observed when cloud type is not considered. The exponent of horizontal length is approximated by β ≈ 1.66 ± 0.00 across two orders of magnitude (~10–1000 km). The exponent of vertical thickness is approximated by β ≈ 2.23 ± 0.03 in excess of one order of magnitude (~1–14 km). These exponents are in agreement with previous studies using numerical models, satellites, dropsondes, and in situ aircraft observations. These differences in horizontal and vertical cloud scaling are consistent with scaling of temperature and horizontal wind in the horizontal dimension and with scaling of buoyancy flux in the vertical dimension. The observed scale dependence should serve as a guide to test and evaluate scale-cognizant climate and weather numerical prediction models.

Footprint-scale cloud type mixtures and their impacts on Atmospheric Infrared Sounder cloud property retrievals

“…values reported in Table 1. Note that these values are similar to but not exactly the same as those calculated in Guillaume et al (2018), for which cloud length was derived from a 2-D curtain of cloud features. The main characteristic shared by all cloud types in Fig.…”

“…The cloud chord length was obtained at the cloud top (see Fig. 5) unlike that obtained in Guillaume et al (2018). frequency decrease for larger scales.…”

“…The reasons for the maximum number of observed cloud scenes (210) at a particular horizontal scale (105 km) are not immediately clear. The scale preference depends on the physical characteristics of cloud regimes and the degree to which cloud types are mixed together by region and furthermore depend on cloud length distributions (Guillaume et al, 2018). A simple model is described below that is able to approximate the results of Fig.…”

“…The preponderance of undetermined phase for Ac may indicate frequent supercooled liquid cloud tops (Zhang et al, 2010). Ham et al (2013) showed that Ac are typically 2-3 km lower in altitude than As, and this probably explains some of the difference in liquid and ice phase, as lower clouds are usually warmer. The Ns cloud scene histogram is dominated by ice detection with occasional liquid and undetermined cloud tops.…”

Reconstruction of Cloud Vertical Structure With a Generative Adversarial Network

“…Guillaume et al (2018) have shown that the distribution of horizontal cloud chord length evaluated from CloudSat data was heavily skewed toward short scales, so that clouds at the CloudSat horizontal resolution of 1.1 km are vastly more frequent than clouds at scales of about 2,000 km, which are very rare. From these data, we extracted nonoverlapping rectangular patches of radar reflectivity, 64 × 64 radar bins in size.…”