P7.8
Accounting for Partially Cloud-Filled Pixels to Improve the Retrieval of Cloud Properties
Louis Nguyen, NASA/LRC, Hampton, Va; and P. Minnis, M. M. Khaiyer, T. Uttal, J. M. Comstock, and X. Dong
Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral and multi-resolution imager data, taken during the 2002 Cirrus Regional Study of Tropical Anvils and Cirrus Layers – Florida Area Cirrus Experiment (CRYSTAL-FACE) and the Atmospheric Radiation Measurement Program (ARM) Southern Great Plain (SGP) March 2000 Intensive Observation Period (IOP), are analyzed with the algorithm used for the ARM and the Clouds and Earth’s Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a simple clear-sky threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each resolution. These retrievals are compared with ground-base radar reflectivity techniques at the ARMS SGP and CRYSTAL-FACE sites. This technique is most likely to yield improvements for low and midlevel layer clouds that have little thermal variability in cloud height.
Poster Session 7, Retrievals and Cloud Products: Part 1
Thursday, 23 September 2004, 9:30 AM-11:00 AM
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