The Radiative, Cloud, and Thermodynamic Properties of the Major Tropical Western Pacific Cloud Regimes

Abstract

This study investigates the radiative, cloud, and thermodynamic characteristics of the atmosphere separated into objectively defined cloud regimes in the tropical western Pacific (TWP). A cluster analysis is applied to 2 yr of daytime-only data from the International Satellite Cloud Climatology Project (ISCCP) to identify four major cloud regimes in the TWP region. A variety of data collected at the Department of Energy's Atmospheric Radiation Measurement Program (ARM) site on Manus Island is then used to identify the main characteristics of the regimes. Those include surface and top-of-the-atmosphere radiative fluxes and cloud properties derived from a suite of ground-based active remote sensors, as well as the temperature and water vapor distribution measured from radiosondes.The major cloud regimes identified in the TWP area are two suppressed regimes-one dominated by the occurrence of mostly shallow clouds, the other by thin cirrus-as well as two convectively active regimesone exhibiting a large coverage of optically thin cirrus clouds, the other characterized by a large coverage with optically thick clouds. All four of these TWP cloud regimes are shown to exist with varying frequency of occurrence at the ARM site at Manus. It is further shown that the detailed data available at that site can be used to characterize the radiative, cloud, and thermodynamic properties of each of the regimes, demonstrating the potential of the regime separation to facilitate the extrapolation of observations at one location to larger scales. A variety of other potential applications of the regime separation are discussed.

Major Characteristics of Southern Ocean Cloud Regimes and Their Effects on the Energy Budget

“…A clustering algorithm was used to identify common modes of cloudiness, or cloud regimes. This is a straightforward extension of the methods developed for the tropics by Jakob and Tselioudis (2003) and Rossow et al (2005). The clustering was applied to the ISCCP data for several reasons: 1) the ISCCP data are available for a 25-yr period whereas CloudSat-CALIPSO data are only available for the few years since launch, 2) the ISCCP data cover a wider horizontal area, and with greater frequency, than is available from CloudSat-CALIPSO, and 3) the cloud structures observed from an ISCCP perspective are more directly comparable to those produced by models on the scale of a GCM grid box.…”

“…An ISCCP-style joint histogram (e.g., Jakob and Tselioudis 2003;Rossow and Schiffer 1991;Tselioudis et al 2000) showing the frequency of occurrence (FOCC) of clouds as a function of both cloud-top pressure and visible optical depth for the SHB during 1983-2008 is given in Fig. 1.…”

“…After the assignment of all data points to one of the n clusters, new cluster centroids are calculated by averaging all cluster members. The process then iterates, starting with this new set of clusters, and continues until the difference between clusters from one iteration to the next becomes vanishingly small (Jakob and Tselioudis 2003). Using a mix of objective and subjective criteria (Rossow et al 2005), the optimal number of clusters (regimes) representing SHB cloudiness is found to be n 5 8.…”

“…Our technique varies chiefly in that we use all 42 ISCCP cloud classes (e.g., Jakob and Tselioudis 2003;Jakob et al 2005;Rossow et al 2005) and focus exclusively on the Southern Hemisphere. Their differences are not expected to result in significantly different clusters, as suggested by GN10.…”

Cluster analysis of midlatitude oceanic cloud regimes: mean properties and temperature sensitivity

“…Dividing the atmosphere into a series of distinct meteorological regimes, each with different cloud properties, is an effective method for understanding the connections between the dynamics and thermodynamics of the atmosphere and the clouds they produce (Jakob, 2003). More recent investigations have used clustering algorithms to more objectively identify cloud regimes without direct reference to meteorological parameters (e.g., Jakob and Tselioudis, 2003;Gordon et al, 2005;Jakob et al, 2005;Rossow et al, 2005). Williams and Tselioudis (2007) examined differences between simulated cloud properties in control runs and 2×CO 2 experiments through the use of a clustering algorithm.…”