Tropical cloud fractions from combined CALIPSO and CloudSat observations are classified based on a K-means cluster analysis. These satellite instruments together retrieve detailed vertical structure of clouds, allowing for an objective decomposition of tropical clouds into distinct regimes. The identified cloud regimes are overall robust except that an increasing number of redundant high-cloud clusters are produced as the specified number of clusters is increased. This redundancy arises because geometrically thin clouds with slightly different altitudes can be mathematically distant from one another in the clustering procedure despite their morphological similarity, suggesting that an excessive number of clusters only generate unrealistic subclasses of high clouds. Objective evaluation metrics indicates that the most appropriate number of clusters is four, where the clusters may be labeled as near clear-sky, low cloud, high cloud, and deep convective regimes. A five-cluster classification is also deemed as reasonable, where a fifth regime of congestus clouds joins the other four regimes practically equivalent to the four-cluster solution. This study suggests that determining the optimal clustering solutions requires a careful interpretation from meteorological perspectives beyond a mere statistical assessment of clustering performance.

A document by Hirohiko Masunaga. Click on the document to view its contents.

Convective Quasi-Equilibrium (CQE) is often adopted as a useful closure assumption to summarize the effects of unresolved convection on large-scale thermodynamics, while existing efforts to observationally validate CQE largely rely on specific spatial domains or sites rather than the source of CQE constraints—deep convection. This study employs a Lagrangian framework to investigate leading temperature perturbation patterns near deep convection, of which the centers are located by use of an ensemble of satellite measurements. Temperature perturbations near deep convection with high peak precipitation are rapidly adjusted towards the CQE structure within the two hours centered on peak precipitation. The top 1% precipitating deep convection constrains the neighboring free-tropospheric leading perturbations up to 8 degrees. Notable CQE validity beyond a 1-degree radius is observed when peak precipitation exceeds the 95th percentile. These findings suggest that only a small fraction of deep convection with extreme precipitation shapes tropical free-tropospheric temperature patterns dominantly.

The iris hypothesis suggests a cloud feedback mechanism that a reduction in the tropical anvil cloud fraction (CF) in a warmer climate may act to mitigate the warming by enhanced outgoing longwave radiation. Two different physical processes, one involving precipitation efficiency and the other focusing on upper-tropospheric stability, have been argued in the literature to be responsible for the iris effect. In this study, A-Train observations and reanalysis data are analyzed to assess these two processes. Major findings are as follows: (1) the anvil CF changes evidently with upper-tropospheric stability as expected from the stability iris theory, (2) precipitation efficiency is unlikely to have control on the anvil CF but is related to mid- and low-level CFs, and (3) the day and nighttime cloud radiative effects are expected to largely cancel out when integrated over a diurnal cycle, suggesting a neutral cloud feedback.