Deep Convective Cloud Systems Research Articles

A new satellite deep convective ice index for tropical climate monitoring: Possible implications for existing oceanic precipitation data sets

The tropical atmosphere is continually overturning, with deep moist convective cloud systems exporting energy from the subcloud layer and depositing it in the upper troposphere. A new satellite index of this deep convective activity is based upon measurements of large ice particles in the upper portions of tropical convective complexes. This 20‐year record reveals a strong signal of the El Niño Southern Oscillation (ENSO), with 10 to 15% upward (downward) swings in the deep convective index during El Niño (La Niña). Warming of tropical sea surface temperatures (SST), whether from anthropogenically‐produced greenhouse gases or natural climate variability, is expected to be associated with more convective overturning of the atmosphere. While other tropical precipitation climatologies vary dramatically in their support of this relationship, the present deep convective ice (DCI) index shows a strong correlation between interannual variations of tropical convection and SST.

Spatial characteristics of the tropical cloud systems: comparison between model simulation and satellite observations

A Lagrangian cloud classification algorithm is applied to the cloud fields in the tropical Pacificsimulated by a high-resolution regional atmospheric model. The purpose of this work is toassess the model’s ability to reproduce the observed spatial characteristics of the tropical cloudsystems. The cloud systems are broadly grouped into three categories: deep clouds, mid-levelclouds and low clouds. The deep clouds are further divided into mesoscale convective systemsand non-mesoscale convective systems. It is shown that the model is able to simulate the totalcloud cover for each category reasonably well. However, when the cloud cover is broken downinto contributions from cloud systems of different sizes, it is shown that the simulated cloudsize distribution is biased toward large cloud systems, with contribution from relatively smallcloud systems significantly under-represented in the model for both deep and mid-level clouds. The number distribution and area contribution to the cloud cover from mesoscale convectivesystems are very well simulated compared to the satellite observations, so are low clouds aswell. The dependence of the cloud physical properties on cloud scale is examined. It is foundthat cloud liquid water path, rainfall, and ocean surface sensible and latent heat fluxes have aclear dependence on cloud types and scale. This is of particular interest to studies of the cloudeffects on surface energy budget and hydrological cycle. The diurnal variation of the cloudpopulation and area is also examined. The model exhibits a varying degree of success in simulatingthe diurnal variation of the cloud number and area. The observed early morning maximumcloud cover in deep convective cloud systems is qualitatively simulated. However, the afternoonsecondary maximum is missing in the model simulation. The diurnal variation of the tropospherictemperature is well reproduced by the model while simulation of the diurnal variationof the moisture field is poor. The implication of this comparison between model simulation andobservations on cloud parameterization is discussed.

Life Cycle Variations of Mesoscale Convective Systems over the Americas

Abstract Using GOES-7 ISCCP-B3 satellite data for 1987–88, the authors studied the evolution of the morphological and radiative properties of clouds over the life cycles of deep convective systems (CS) over the Americas at both tropical and middle latitudes. A deep convective cloud system is identified by adjacent satellite image pixels with infrared brightness temperatures, TIR < 245 K (−28°C), that at some time contain embedded convective clusters that are defined by pixel values of TIR < 218 K (−55°C). The first part of the analysis computes parameters for each convective system that describe the system areal size, number of convective clusters, fractional convective area, average and maximum size of the convective clusters, shape eccentricity and orientation, mean TIR, variance of TIR, TIR gradient, and the mean, variance, and gradient of collocated visible reflectances (when available). The second part of the analysis searches a 5° × 5° region centered on each convective system, but in the subsequent...

Dehydration of the upper troposphere and lower stratosphere by subvisible cirrus clouds near the tropical tropopause

The extreme dryness of the lower stratosphere is believed to be caused by freeze‐drying of air as it enters the stratosphere through the cold tropical tropopause. Previous investigations have been focused on dehydration occurring at the tops of deep convective cloud systems. However, recent observations of a ubiquitous stratiform cirrus cloud layer near the tropical tropopause suggest the possibility of dehydration as air is slowly lifted by large‐scale motions. In this study, we have evaluated this possibility using a detailed ice cloud model. Simulations of ice cloud formation in the temperature minima of gravity waves (wave periods of 1–2 hours) indicate that large numbers of ice crystals will likely form due to the low temperatures and rapid cooling. As a result, the crystals do not grow larger than about 10 µm, fallspeeds are no greater than a few cm‐s−1, and little or no precipitation or dehydration occurs. However, ice clouds formed by large‐scale vertical motions (with lifetimes of a day or more) should have fewer crystals and more time for crystal sedimentation to occur, resulting in water vapor depletions as large as 1 ppmv near the tropopause. We suggest that gradual lifting near the tropical tropopause, accompanied by formation of thin cirrus, may account for the dehydration.

A Satellite-derived Climatology of the ITCZ

This paper presents fundamental climatological characteristics of the intertropical convergence zone (ITCZ) in a simple concise manner using the highly reflective cloud (HRC) dataset. This satellite-derived dataset uses both visible and infrared observations to measure the frequency of occurrence of large-scale convective systems over the global tropics at a 1 deg spatial resolution. These dataset characteristics make the HRC particularly well suited for climatological analysis of the ITCZ because the dataset is based on estimates of organized deep convective cloud systems rather than observations of clouds as a whole, and it provides the spatial resolution needed to identify these large-scale convective structures. Furthermore, the dataset covers a time period extending nearly two decades, which provides for a fairly robust climatology and the opportunity to examine seasonal and interannual variability of both the convection and the latitude of the ITCZ.