Climate Analysis
One of the problems that makes climate research both interesting and challenging is the blending of physical processes whose evolution in time can be predicted well into the future with others that cannot. Comparisons of observations about the Earth's climate with models of how the climate is evolving must take into account this inherent lack of predictability, sometimes referred to as climate noise. Much of climate data analysis involves the separation of climate signal from the noise. Branch scientists carry out climate diagnostic studies using a mix of historical climate data, remote sensing data, and outputs from general circulation models. Methods have been developed to filter out climate noise from signal using optimal weighting of observations and using simplified models of the coupled climate system, to compare climate change predictions with observed changes.

Information pertaining to the global thermal state is being extracted from satellite radiometer observations made by the TIROS Microwave Sounding Unit (MSU) in the 50-54GHz region to estimate the long-term tropospheric temperature trend. Branch Scientists use analyzed data from the Comprehensive Ocean-Atmosphere Data Sed (COADS) and model- assimilated data to study the variability of the global hydrologic cycle including changes in the distribution of water vapor, precipitation, evaporation, and moisture transport in relation to naturally occuring climate fluctuations such as the EL Nino Sothern Oscillation (ENSO), the quasi-biennial oscillation, and low-frequency oscillations in the tropical atmosphere and oceans.

Using long-term satellite observations of outgoing longwave radiation and global wind analysis from the European Center for Medium-Range Weather Forecasts and the National Meteorological Center, dominant modes of atmospheric circulation and tropical heating patterns on a wide range of time scales have been identified. These studies will improve understanding of the mechanisms of tropical-extratropical interaction and provide assessments of the role of the tropics in determining short-term climate predictability in the extratropics.

Contact: Kyu-Myong Kim



Hsu, N. C., S.-C. Tsay, M.-J. Jeong, and Q. Ji, 2008: Deep Blue Characterization of Dust and Pollution Aerosols During the UAE2 Experiment. Geophys. Res. Lett.. (Submitted)

Freeborn, P. H., M. J. Wooster, W. M. Hao, C. A. Ryan, B. L. Nordgren, S. P. Baker, and C. Ichoku, 2008: Relationships between energy release, fuel mass loss, and trace gas and aerosol emissions during laboratory biomass fires. J. Geophys. Res., 113, D01301, doi:10.1029/2007JD008679. [Full Text (PDF)]

Jordan, N., C. Ichoku, and R. Hoff, 2008: Estimating Smoke Emissions Over The U.S. Southern Great Plains Using MODIS Fire Radiative Power and Aerosol Observations. Atmos. Env., 42, 2007–2022.. [Full Text (PDF)]

Ichoku, C., J. V. Martins, Y. J. Kaufman, M. J. Wooster, P. H. Freeborn, W. M. Hao, S. Baker, C. A. Ryan, and B. L. Nordgren, 2008: Laboratory investigation of fire radiative energy and smoke aerosol emissions. J. Geophys. Res., 113, D14S09, doi:10.1029/2007JD009659.. [Full Text (PDF)]

Ichoku, C., L. Giglio, M. J. Wooster, and L. A. Remer, 2008: Global characterization of biomass-burning patterns using satellite measurements of Fire Radiative Energy. Remote Sens. Environ., 112, 2950-2962, 2008.. [Full Text (PDF)]

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Updated:
January 14, 2009 in Publications
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