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Chen, Yan

Publications and source records attributed to Chen, Yan.

149 records · Page 9

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

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Detection and Retrieval of Multi-Layered Cloud Properties Using Satellite Data

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Minnis, Patrick↗

Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data

Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

Minnis, Patrick↗

Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

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Clear-Sky Narrowband Albedo Variations Derived from VIRS and MODIS Data

A critical parameter for detecting clouds and aerosols and for retrieving their microphysical properties is the clear-sky radiance. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the visible (VIS; 0.63 m) and near-infrared (NIR; 1.6 or 2.13 m) channels available on same satellites as the CERES scanners. Another channel often used for cloud and aerosol, and vegetation cover retrievals is the vegetation (VEG; 0.86- m) channel that has been available on the Advanced Very High Resolution Radiometer (AVHRR) for many years. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. Snow albedo is typically estimated without considering the underlying surface type. The albedo for a surface blanketed by snow, however, should vary with surface type because the vegetation often emerges from the snow to varying degrees depending on the vertical dimensions of the vegetation. For example, a snowcovered prairie will probably be brighter than a snowcovered forest because the snow typically falls off the trees exposing the darker surfaces while the snow on a grassland at the same temperatures will likely be continuous and, therefore, more reflective. Accounting for the vegetation-induced differences should improve the capabilities for distinguishing snow and clouds over different surface types and facilitate improvements in the accuracy of radiative transfer calculations between the snow-covered surface and the atmosphere, eventually leading to improvements in models of the energy budgets over land. This paper presents a more complete analysis of the CERES spectral clear-sky reflectances to determine the variations in clear-sky top-of-atmosphere (TOA) albedos for both snow-free and snow-covered surfaces for four spectral channels using data from Terra and Aqua.. The results should be valuable for improved cloud retrievals and for modeling radiation fields.

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