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Cloud fraction and cloud radiative forcing at the surface

PI: Baike Xi
Institution: University of North Dakota
Clouds have been classified as the highest priority by the U.S. Climate Change Research Initiative (USCCRI, 2001) because they are one of the largest sources of uncertainty in predicting any potential future climate change (Wielicki et al. 1995; Houghton et al. 2001). Clouds are also the dominant modulators of radiation both at the surface and top of atmosphere (TOA), and their impact on the Earth’s radiation budget mainly depends on the bulk properties of clouds such as cloud amount, height, and microphsycal/optical features (Wielicki et al. 1998; Curry et al. 2000; Houghton et al. 2001). Characterizing cloud radiative effects on the surface is a critical component for understanding the current climate and an important step towards simulating potential climate change. Cloud radiative forcing (CRF) is a simple but effective means of studying cloud-radiation interactions and diagnosing problems in general circulation models (GCM) because the CRF represents the bulk effects of clouds on the surface radiation budget.

We are developing a climatology of mid-latitude continental cloud properties and their impact on the surface radiation budget using data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility (SCF; 36.6oN, 97.5oW; see (Ackerman and Stokes 2003) from January 1997 to December 2002. We calculate the cloud fractions of total, and single-layer low, middle, and high clouds, and their corresponding CRFs. We rely entirely on both radar and lidar/ceilometer measurements to identify clear sky, total cloud cover, and single-layer low, middle, and high clouds first, then we average clear-sky net (down-up) SW and LW fluxes during a certain time period (a month or season), finally we calculate the seasonal and monthly mean SW, LW, and net CRF for each category.

Now, we propose to compare our surface observations with CMIP's up-to-date monthly average outputs. We want to test whether the shortwave and long wave fluxes at the surface under different conditions between the observational and model results will be consistent. If they are consistent to each other, we may use the model outputs at TOA to calculate the atmosphere absorption. If they are not consistent to each other, what is the reason to cause the discrepancy?

The parameters will be:
(1)Clear-sky downwelling shortwave flux at the earth’s surface
The radiative transfer model can accurately calculate the atmospheric absorption of solar radiation, therefore, the difference between the observational downwelling shortwave flux with the calculated clear-sky downwelling flux is expected to be small;

(2)All-sky shortwave downwelling flux at the earth’s surface
The cloud absorption to solar radiation is one of the biggest uncertainties in the GCMs. We try to find a way to calculate the cloud absorption by using model's TOA downwelling flux and the observed downwelling flux at the surface. Therefore, the comparisons between the model fluxes and the observational ones may help us to understand the cloud absorption to the solar radiation;

(3)Cloud fraction
We compare this parameter to see whether the model gives the right order of the magnitude with the observed cloud amount in the same time period.

(4)Cloud radiative forcing
Finally, we want to compare the overall energy budget on the earth surface, and to see whether observed could effect on the surface is consistent to that of model output.

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    Lawrence Livermore National Laboratory  |  Physical & Life Sciences Directorate