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The Precipitation Characteristics of ISCCP Tropical Weather States

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  • 1 GESTAR, University Space Research Association, Columbia, and Earth Sciences Division, NASA GSFC, Greenbelt, Maryland, and Seoul National University, Seoul, South Korea
  • 2 Earth Sciences Division, NASA GSFC, Greenbelt, Maryland
  • 3 Science Systems and Applications Inc., Lanham, and Earth Sciences Division, NASA GSFC, Greenbelt, Maryland
  • 4 Cooperative Remote Sensing Science and Technology Institute, City College of New York, New York, New York
  • 5 Seoul National University, Seoul, South Korea
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Abstract

The authors examine the daytime precipitation characteristics of the International Satellite Cloud Climatology Project (ISCCP) weather states in the extended tropics (35°S–35°N) for a 10-yr period. The main precipitation dataset used is the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis operational product 3B42 dataset, but Global Precipitation Climatology Project daily data are also used for comparison. It is found that the most convectively active ISCCP weather state (WS1), despite an occurrence frequency below 10%, is the most dominant state with regard to surface precipitation, producing both the largest mean precipitation rates when present and the largest percent contribution to the total precipitation of the tropics; yet, even this weather state appears to not precipitate about half the time, although this may be to some extent an artifact of detection and spatiotemporal matching limitations of the precipitation dataset. WS1 exhibits a modest annual cycle of the domain-average precipitation rate, but notable seasonal shifts in its geographic distribution. The precipitation rates of the other weather states appear to be stronger when occurring before or after WS1. The precipitation rates of the various weather states are different between ocean and land, with WS1 producing higher daytime rates on average over ocean than land, likely because of the larger size and more persistent nature of oceanic WS1s. The results of this study, in addition to advancing the understanding of tropical hydrology, can serve as higher-order diagnostics for evaluating the realism of tropical precipitation distributions in large-scale models.

Current affiliation: Earth Sciences Division, NASA GSFC, Greenbelt, Maryland.

Corresponding author address: Lazaros Oreopoulos, NASA GSFC, Code 613, Greenbelt, MD 20771. E-mail: lazaros.oreopoulos@nasa.gov

Abstract

The authors examine the daytime precipitation characteristics of the International Satellite Cloud Climatology Project (ISCCP) weather states in the extended tropics (35°S–35°N) for a 10-yr period. The main precipitation dataset used is the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis operational product 3B42 dataset, but Global Precipitation Climatology Project daily data are also used for comparison. It is found that the most convectively active ISCCP weather state (WS1), despite an occurrence frequency below 10%, is the most dominant state with regard to surface precipitation, producing both the largest mean precipitation rates when present and the largest percent contribution to the total precipitation of the tropics; yet, even this weather state appears to not precipitate about half the time, although this may be to some extent an artifact of detection and spatiotemporal matching limitations of the precipitation dataset. WS1 exhibits a modest annual cycle of the domain-average precipitation rate, but notable seasonal shifts in its geographic distribution. The precipitation rates of the other weather states appear to be stronger when occurring before or after WS1. The precipitation rates of the various weather states are different between ocean and land, with WS1 producing higher daytime rates on average over ocean than land, likely because of the larger size and more persistent nature of oceanic WS1s. The results of this study, in addition to advancing the understanding of tropical hydrology, can serve as higher-order diagnostics for evaluating the realism of tropical precipitation distributions in large-scale models.

Current affiliation: Earth Sciences Division, NASA GSFC, Greenbelt, Maryland.

Corresponding author address: Lazaros Oreopoulos, NASA GSFC, Code 613, Greenbelt, MD 20771. E-mail: lazaros.oreopoulos@nasa.gov
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