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Larry L. Stowe
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Herbert Jacobowitz, Larry L. Stowe, George Ohring, Andrew Heidinger, Kenneth Knapp, and Nicholas R. Nalli

As part of the joint National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) Pathfinder program, the NOAA National Environmental Satellite, Data, and Information Service (NESDIS) has created a research-quality global atmospheric dataset through the reprocessing of Advanced Very High Resolution Radiometer (AVHRR) observations since 1981. The AVHRR is an imaging radiometer that flies on NOAA polar-orbiting operational environmental satellites (POES) measuring radiation reflected and emitted by the earth in five spectral channels. Raw AVHRR observations were recalibrated using a vicarious calibration technique for the reflectance channels and an appropriate treatment of the nonlinearity of the infrared channels. The observations are analyzed in the Pathfinder Atmosphere (PATMOS) project to obtain statistics of channel radiances, cloud amount, top of the atmosphere radiation budget, and aerosol optical thickness over ocean. The radiances and radiation budget components are determined for clear-sky and all-sky conditions. The output products are generated on a quasi-equalarea grid with an approximate 110 km × 110 km spatial resolution and twice-a-day temporal resolution, and averaged over 5-day (pentad) and monthly time periods. PATMOS data span the period from September 1981 through June 2001. Analyses show that the PATMOS data in their current archived form are sufficiently accurate for studies of the interaction of clouds and aerosol with solar and terrestrial radiation, and of climatic phenomena with large signals (e.g., the annual cycle, monsoons, ENSOs, or major volcanic eruptions). Global maps of the annual average of selected products are displayed to illustrate the capability of the dataset to depict the climatological fields and the spatial detail and relationships between the fields, further demonstrating how PATMOS is a unique resource for climate studies. Smaller climate signals, such as those associated with global warming, may be more difficult to detect due to the presence of artifacts in the time series of the products. Principally, these are caused by the drift of each satellite's observation time over its mission. A statistical method, which removes most of these artifacts, is briefly discussed. Quality of the products is assessed by comparing the adjusted monthly mean time series for each product with those derived from independent satellite observations. The PATMOS dataset for the monthly means is accessible at

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Paul H. Hwang, Larry L. Stowe, H. Y. Michael Yeh, H. Lee Kyle, and the Cloud Data Processing Team

A total of six years (April 1979 to March 1985) of continuous measurements from the Temperature Humidity Infrared Radiometer (THIR) and the Total Ozone Mapping Spectrometer (TOMS), both on the Nimbus-7 satellite, have been processed to form the Nimbus-7 Global Cloud Climatology (N7GCC). The cloud-estimation algorithms utilize THIR “11.5-micron” radiances, TOMS-derived “0.37-micron” reflectivities, climatological temperature lapse rates and concurrent surface temperatures, and snow-ice information. (The last two items are taken from the Air Force three-dimensional nephanalysis archive.) This cloud climatology gives, near local noon and midnight, the fractional area covered by high-level clouds middle-level clouds and low-altitude clouds, and the total fractional area covered by all clouds (total cloud). Statistics are also given for the special cloud types: cirrus, deep convective, and warm low-altitude clouds. The cloud and clear-sky radiances, together with correlative surface temperatures, are included. These products have the same spatial resolution and temporal (daily and monthly) resolution as the independently derived concurrent Nimbus-7 Earth Radiation Budget data set. The N7GCC has been compared with preliminary results from the International Satellite Cloud Climatology Project (ISCCP) and with other cloud data sets. For July 1983, the mean global cover was estimated to be 49 percent by N7GCC and 63 percent by ISCCP. Older cloud climatologies showed average July global cloud cover in the 50 percent to 60 percent range.

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