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Robert Hallberg and Anand K. Inamdar


The correlation between observed values of atmospheric greenhouse trapping and sea surface temperature is found to vary seasonally. Atmospheric greenhouse trapping is defined here as the difference between infrared emissions from the earth's surface and infrared emissions from the top of the atmosphere through cloudless skies. Infrared surface emissions are calculated from known sea surface temperatures, and emissions from the top of the atmosphere are taken from direct satellite measurements. Atmospheric greenhouse trapping at the same sea surface temperature is greater in the winter than in the summer over temperate oceans. In subtropical latitudes, the opposite is true. At surface temperatures above approximately 298 K, atmospheric greenhouse trapping is found to increase even more rapidly from regions of lower sea surface temperature to regions of higher surface temperature than infrared surface emissions. The causes for this “super” greenhouse effect are explored, and four processes are found to contribute. Water vapor continuum absorption and thermodynamically controlled increases in water vapor concentration at constant relative humility with increasing atmospheric temperature are found to make significant contributions, but do not explain the entire super greenhouse effect. To explain the observations of atmospheric greenhouse trapping, the atmosphere, and in particular the upper and middle troposphere, must be increasingly moist over the warmest sea surface temperatures, while the atmospheric temperature profile becomes increasingly unstable. Regions with these high sea surface temperatures are also increasingly subject to deep convection, which suggests that convection moistens the upper and middle troposphere in regions of convective activity relative to nonconvective regions, resulting in the super greenhouse effect. Dynamic processes, along with local thermodynamic process. are required to explain the observed super greenhouse effect.

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Anand K. Inamdar and Kenneth R. Knapp


The International Satellite Cloud Climatology Project (ISCCP) B1 data, which were recently rescued at the National Oceanic and Atmospheric Administration’s National Climatic Data Center (NOAA/NCDC), are a resource for the study of the earth’s climate. The ISCCP B1 data represent geostationary satellite imagery for all channels, including the infrared (IR), visible, and IR water vapor sensors. These are global 3-hourly snapshots from satellites around the world, covering the time period from 1979 to present at approximately 10-km spatial resolution. ISCCP B1 data will be used in the reprocessing of the cloud products, resulting in a higher-resolution ISCCP cloud climatology, surface radiation budget (SRB), etc. To realize the promise of a higher-resolution cloud climatology from the B1 data, an independent assessment of the calibration of the visible band was performed. The present study aims to accomplish this by cross-calibrating with the intercalibrated Advanced Very High Resolution Radiometer (AVHRR) reflectance data from the AVHRR Pathfinder Atmospheres–Extended (PATMOS-x) dataset. Since the reflectance calibration approach followed in the PATMOS-x dataset is radiometrically tied to the absolute calibration of the National Aeronautics and Space Administration’s (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) imager instrument, the present intercalibration scheme yields calibration coefficients consistent with MODIS. Results from this study show that the two independent sets (this study and the ISCCP) of results agree to within their mutual uncertainties. An independent approach to calibration based on multiyear observations over spatially and temporally invariant desert sites has also been used for validation. Results reveal that for most of the geostationary satellites, the mean difference with ISCCP calibration is less than 3% with the random errors under 2%. Another result is that this extends the intercalibrated record to beyond what ISCCP provides (prior to 1983 and beyond 2009).

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Kenneth R. Knapp, Alisa H. Young, Hilawe Semunegus, Anand K. Inamdar, and William Hankins


The International Satellite Cloud Climatology Project (ISCCP) began collecting data in the 1980s to help understand the distribution of clouds. Since then, it has provided important information on clouds in time and space and their radiative characteristics. However, it was apparent from some long-term time series of the data that there are some latent artifacts related to the changing satellite coverage over the more than 30 years of the record. Changes in satellite coverage effectively create secular changes in the time series of view zenith angle (VZA) for a given location. There is an inconsistency in the current ISCCP cloud detection algorithm related to VZA: two satellites viewing the same location from different VZAs can produce vastly different estimates of cloud amount. Research is presented that shows that a simple change to the cloud detection algorithm can vastly increase the consistency. This is accomplished by making the cloud–no cloud threshold VZA dependent. The resulting cloud amounts are more consistent between different satellites and the distributions are shown to be more spatially homogenous. Likewise, the more consistent spatial data lead to more consistent temporal statistics.

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