Global Cloud Climatology from Surface Observations: Analyses and Decadal Update

University Of Washington, Seattle WA

Investigators

Abstract

This project will update and analyze surface synoptic observations from weather stations on land and ships in the ocean to determine the global distribution of the various cloud types and their seasonal and diurnal variations, as well as a study of how clouds have changed in the past half-century. Fourteen years of land data (1997-2010) will be added to the cloud-observations database and to the cloud-averages database created by the previous grants funded by National Science Foundation (NSF) and National Oceanic and Atmospheric Administration (NOAA). The analyses of interannual variations and trends will also be updated to include these 14 years. The resulting database will cover 55 years for the ocean and 40 years for land. The updated database will enable a number of climatic investigations. Clouds generally cause cooling in daytime but warming at night, so the radiative effects of clouds depend on their diurnal cycles. The databases will be analyzed for diurnal cycles of individual cloud types worldwide. Trends in the cloud types will be analyzed for day and night separately and compared, in order to investigate possible changes in the cloud radiative forcing over the past several decades. In past decades the total cloud cover has shown a slight increase over the ocean and slight decrease over the continents. Whether these trends continue into the more recent years will be investigated, as well as whether interannual variations also show the same anticorrelation. There have been modeling and remote-sensing studies of the relation of cloud height to surface temperature, which will be investigated on interannual time scales using the reports of base height in the surface-based cloud observations. The broader impacts of this work are in the area of climate research. The databases resulting from this project will be distributed widely for use by the scientific community, with potential applications in climate modeling, cloud process studies, evaluation of satellite observations of clouds, and in detection and attribution of climate change.