Near-global total cloud frequencies and multilayered cloud frequencies derived from AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), and GLAS (Geoscience Laser Altimeter System) were analyzed and compared. The GLAS retrievals can be used to quantify the amount of cloud that may go undetected from satellite imagers such AVHRR and MODIS and to help validate satellite cloud overlap detection algorithms. Model sensitivity studies indicate that clouds with a total column optical depth of 0.5 or less may often go undetected by AVHRR and MODIS. The GLAS data show that such cloudy observations comprised 18.3% (14.5%) of all cloudy GLAS footprints during the most convectively active (least convectively active) portion of the day. Where the most (least) convectively active time period is defined as local solar noon plus (minus) 12 hours. It was also shown that the zonal mean total cloud frequency from GLAS and AVHRR and GLAS and MODIS are well correlated but often differ in magnitude because of thin clouds or small-scale cloud systems that are missed by the AVHRR and MODIS cloud detection algorithms. With the exception of the polar regions, the AVHRR and GLAS and the MODIS (via the Visible/Infrared Imager/Radiometer Suite algorithm) and GLAS multilayered cloud frequencies are in good agreement.
The NOAA/NESDIS Office of Research and Applications (ORA) has embarked on a pilot data stewardship project aimed at improving the data record from the Advanced Very High Resolution Radiometer (AVHRR). One part of this larger project includes the generation of a new cloud climatology from the Extended AVHRR Pathfinder Atmospheres (PATMOS-x) data set. Included within the PATMOS-x data-stream is a full suite of cloud products including various cloud amounts. This paper compares the PATMOS-x cloud amount time series for all July data (1982-2004) to the cloud amount time series from the International Satellite Cloud Climatology Project (ISCCP) and University of Wisconsin High Resolution Infrared Sounder (UW/HIRS) data sets. The results indicate that the large intersatellite discontinuities in the total amount seen in the original PATMOS are reduced in PATMOS-x. The total cloud for July time series from PATMOS-x, UW/HIRS and PATMOS show little trend over the period studied but that ISCCP time series does indicate a continuous downward trend When comparing the time series of high cloud amount, it was that PATMOS-x shows no significant trend in high cloud from 20S to 20N.
Radiances and brightness temperatures from three near-infrared/infrared channels that are available on most current and past satellite imagers were used to develop automated algorithms for identifying multilayered cloud systems (cloud overlap) and cirrus clouds at night. The cloud overlap algorithm uses information from the 3.75 micron, 11 micron, and 12 micron regions of the spectrum and the cirrus algorithm uses 3.75 micron and 11 micron channel data. The cloud overlap algorithm was developed assuming that a scene with cloud overlap consists of a semitransparent ice cloud that overlaps a lower cloud composed of liquid water droplets. Cirrus clouds are taken to be high ice clouds with a visible optical depth of 5.0 or less. The algorithms are applied to single satellite pixels that are already assumed to be cloudy based on cloud mask information. The utility of each algorithm was demonstrated on two different Moderate Resolution Imaging Spectroradiometer (MODIS) scenes and the cloud overlap algorithm was validated against millimeter radar-derived cloud boundaries. Overall the results show that both algorithms have the potential to be very useful for nighttime cloud studies.
The newly available Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) data set was used to retrieve cloud amount, cloud optical depth, cloud particle phase and size, cloud temperature, surface temperature, surface broadband albedo, radiation fluxes and cloud forcing in the Arctic for the period 1982-1999. The spatial and temporal distributions of those retrieved Arctic climate parameters together with an analysis of their seasonal and interannual variability, especially surface and cloud properties are presented here. The present study indicates that the Arctic has been warming in spring, summer and autumn, the decadal rates are 1.1°C degree, 0.68°C degree and 0.70°C degree, respectively. While in winter the Arctic has been cooling at the decadal rate of -0.34°C degree. The Arctic surface broadband albedo also signals the warming trend of the Arctic at the decadal rate of -3.0% at the confidence level of 98.8% in autumn, indicating a longer melt period and later freeze-up. Results also show that the Arctic has become cloudier in spring and summer, but less cloudy in winter.
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