The impact of an observationally based surface emissivity dataset on the simulation of Microwave Sounding Unit Temperatures
Justin J. Hnilo, LLNL, Livermore, CA; and L. Litten, B. D. Santer, and J. R. Christy
Relatively few studies have attempted to simulate synthetic MSU temperatures with use of a radiation model. Most employ the simpler and computationally less-expensive method of applying a static, global-mean weighting function to three-dimensional profiles of atmospheric temperature. Both approaches require a number of key assumptions. One of the major assumptions relates to surface emissivity. To date, two different strategies have been used for prescribing surface emissivity values. The first assumes a fixed global surface emissivity, while the second specifies separate (time-invariant) emissivity values for land and ocean.
In this research, we introduce space- and time-dependence to the specified emissivity fields, using recent observationally-based estimates of surface emissivity changes over 1988 to 2000. We use a radiative transfer code to explore the impact of this more complex treatment of surface emissivity. This sensitivity analysis is performed with monthly-mean fields of surface temperature, atmospheric temperature, and moisture taken from multiple reanalyses. Our goal is to quantify the possible impact of emissivity changes on global-scale estimates of tropospheric temperature trends (e.g., trends estimated from MSU channel 2 and MSU 2LT), and to document the sensitivity of synthetic MSU temperatures to a variety of input data and processing choices.
This work is supported under the auspices of the Office of Science, U.S. Department of Energy at the University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48
Poster Session 1, Observed climate change
Monday, 30 January 2006, 2:30 PM-4:00 PM, Exhibit Hall A2
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