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Mo T.,The Center for Satellite Applications and Research
Journal of Atmospheric and Oceanic Technology | Year: 2010

Daily mean brightness temperatures over Antarctica derived from measurements by three Advanced Microwave Sounding Unit-A (AMSU-A) radiometers on board NOAA-18, NOAA-19, and MetOp-A satellites are studied. To demonstrate the characteristics of the data over this test site, time series of daily averages of the brightness temperatures are constructed. These time series provide a useful pattern of annual variation of the AMSU-A measurements for intercalibration of microwave radiometers on board multiple satellites. To investigate the diurnal effect on the measurements, the time series of daily averaged brightness temperatures are constructed separately for the ascending and descending passes. Results show that there are little diurnal differences in measurements during the Antarctic winter months from each satellite. Therefore these measurements provide a practical approach to obtain relative channel biases of intersatellite data. The monthly averages of the measurements over July 2009 are employed to obtain the relative channel biases because it is the coldest month in Antarctica. The resultant channel biases for the three satellites are within the range of 60.1 K for channels 1-5 and 60.3 K for channels 6-15. This is strong evidence that Antarctica is a potentially good test site for intercalibration of microwave radiometers on board multiple satellites. The small relative biases at channels 1-5 indicate that Antarctica is a very stable test site that is particularly useful for intercalibration of measurements from the window channels. The establishment of a natural test site for calibration references is important for calibration and validation of spaceborne microwave instruments. © 2010 American Meteorological Society. Source


Pavolonis M.J.,The Center for Satellite Applications and Research
Journal of Applied Meteorology and Climatology | Year: 2010

Infrared measurements can be used to obtain quantitative information on cloud microphysics, including cloud composition (ice, liquid water, ash, dust, etc.), with the advantage that the measurements are independent of solar zenith angle. As such, infrared brightness temperatures (BT) and brightness temperature differences (BTD) have been used extensively in quantitative remote sensing applications for inferring cloud composition. In this study it is shown that BTDs are fundamentally limited and that a more physically based infrared approach can lead to significant increases in sensitivity to cloud microphysics, especially for optically thin clouds. In lieu of BTDs, a derived radiative parameter b, which is directly related to particle size, habit, and composition, is used. Although the concept of effective absorption optical depth ratios b has been around since the mid-1980s, this is the first study to explore the use of b for inferring cloud composition in the total absence of cloud vertical boundary information. The results showed that, even in the absence of cloud vertical boundary information, one could significantly increase the sensitivity to cloud microphysics by converting the measured radiances to effective emissivity and constructing effective absorption optical depth ratios from a pair of spectral emissivities in the 8-12-μm "window." This increase in sensitivity to cloud microphysics is relative to BTDs constructed from the same spectral pairs. In this article, the focus is on describing the physical concepts (which can be applied to narrowband or hyperspectral infrared measurements) used in constructing the β data space. © 2010 American Meteorological Society. Source


Foster M.J.,University of Wisconsin - Madison | Heidinger A.,The Center for Satellite Applications and Research
Journal of Climate | Year: 2013

Satellite drift is a historical issue affecting the consistency of those few satellite records capable of being used for studies on climate time scales. Here, the authors address this issue for the Pathfinder Atmospheres Extended (PATMOS-x)/Advanced Very High Resolution Radiometer (AVHRR) cloudiness record, which spans three decades and 11 disparatesensors.Atwo-harmonic sinusoidal function is fit to a mean diurnal cycle of cloudiness derived over the course of the entire AVHRRrecord. The authors validate this function against measurements from Geostationary Operational Environmental Satellite (GOES) sensors, finding good agreement, and then test the stability of the diurnal cycle over the course ofthe AVHRR record. It is found that the diurnal cycle is subject to some interannual variability over land but that the differences are somewhat offset when averaged over an entire day. The fit function is used to generate daily averaged time series of ice, water, andtotal cloudiness over the tropics, where it is found that the diurnal correction affects the magnitude and even the sign of long-term cloudiness trends. A statistical method is applied to determine the minimum length of time required to detect significant trends, andthe authors find that only recently have they begun generating satellite records of sufficient length to detect trends in cloudiness. © 2013 American Meteorological Society. Source


Gao S.,CAS Institute of Atmospheric Physics | Li X.,The Center for Satellite Applications and Research
Quarterly Journal of the Royal Meteorological Society | Year: 2011

The precipitation efficiencies (RMPE, CMPE, and LSPE) can be defined as the ratio of rain rate to rainfall sources in the rain microphysical budget, the cloud microphysical budget, and the surface rainfall budget, respectively. The estimate of RMPE from grid-scale data serves as the true precipitation efficiency since the rain rate is a diagnostic term in the tropical rain microphysical budget. The accuracy of precipitation efficiency estimates with CMPE and LSPE is compared to that of RMPE by analyzing data from a 21-day two-dimensional cloud-resolving model simulation with imposed large-scale vertical velocity, zonal wind, and horizontal advection obtained from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The results show CMPE is generally smaller than RMPE. The root-mean-squared difference between RMPE and LSPE is larger than the standard deviation of RMPE. Thus, water vapour process data cannot be used to estimate precipitation efficiency. Copyright © 2011 Royal Meteorological Society. Source


Walther A.,University of Wisconsin - Madison | Heidinger A.K.,The Center for Satellite Applications and Research
Journal of Applied Meteorology and Climatology | Year: 2012

This paper describes the daytime cloud optical and microphysical properties (DCOMP) retrieval for the Pathfinder Atmosphere's Extended (PATMOS-x) climate dataset. Within PATMOS-x, DCOMP is applied to observations from the Advanced Very High Resolution Radiometer and employs the standard bispectral approach to estimate cloud optical depth and particle size. The retrievals are performed within the optimal estimation framework. Atmospheric-correction and forward-model parameters, such as surface albedo and gaseous absorber amounts, are obtained from numerical weather prediction reanalysis data and other climate datasets. DCOMP is set up to run on sensors with similar channel settings and has been successfully exercised on most current meteorological imagers. This quality makes DCOMP particularly valuable for climate research. Comparisons with the Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 dataset are used to estimate the performance of DCOMP. © 2012 American Meteorological Society. Source

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