Accounting for partially cloud-filled pixels to improve the retrieval of cloud properties using high-resolution data
| Nguyen, Louis | NASA Langley |
| Minnis, Patrick | NASA Langley Research Center |
| Khaiyer, Mandana | Analytical Services and Material, Inc. |
| Nordeen, Michele | AS&M/NASA Langley |
| Heck, Patrick | University of Wisconsin |
| Palikonda, Rabindra | Analytical Services & Materials Inc, |
| Comstock, Jennifer | Pacific Northwest National Laboratory |
| Long, Chuck | Pacific Northwest National Laboratory |
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. The retrievals of optically thin water clouds and broken cloud could be improved by using high-resolution VIS data from Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) imager to differentiate the two. Although the nominal resolution for most channels on the GOES and MODIS 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 area taken during the Atmospheric Radiation Measurement Program (ARM) Southern Great Plain (SGP) March 2000 Intensive Observation Period (IOP) and the 2002 Cirrus Regional Study of Tropical Anvils and Cirrus Layers – Florida Area Cirrus Experiment (CRYSTAL-FACE) and are analyzed with the visible infrared solar-infrared split-window technique (VISST) 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 using the cloud mask. In this study, a simple clear-sky reflectance threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. Clear-sky and cloud mask inputs will be evaluated to assess the sensitivity of these thresholds. 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 the cloud liquid water path (LWP) from ground-based microwave radiometers (MWR) at the ARM SGP central and extended facilities to determine the impact of using high-resolution VIS pixels. The satellite retrieved cloud fraction will be compared with the total sky imager (TSI) at the ARM SGP sites. Cloud with Low Optical [Water] Depths (CLOWD) is an important cloud system that occurs frequently over the ARM SGP site and off the coast of California where the Marine Stratus Radiation Aerosol and Drizzle (MASRAD) Intensive Operational Period (IOP) will be conducted in 2005. This paper will also focus on improving the cloud thickness, LWP, height, cloud fraction, optical depth, and particle size estimates in CLOWD conditions.
This poster will be displayed at the ARM Science Team Meeting.