Satellite Retrieval of Microwave Land Surface Emissivity under Clear and Cloudy Skies in China Using Observations from AMSR-E and MODIS

Microwave land surface emissivity (MLSE) is an important geophysical parameter to determine the microwave radiative transfer over land and has broad applications in satellite remote sensing of atmospheric parameters (e.g., precipitation, cloud properties), land surface parameters (e.g., soil moisture, vegetation properties), and the parameters of interactions between atmosphere and terrestrial ecosystem (e.g., evapotranspiration rate, gross primary production rate). In this study, MLSE in China under both clear and cloudy sky conditions was retrieved using satellite passive microwave measurements from Aqua Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), combined with visible/infrared observations from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), and the European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere reanalysis dataset of ERA-20C. Attenuations from atmospheric oxygen and water vapor, as well as the emissions and scatterings from cloud particles are taken into account using a microwave radiation transfer model to do atmosphere corrections. All cloud parameters needed are derived from MODIS visible and infrared instantaneous measurements. Ancillary surface skin temperature as well as atmospheric temperature-humidity profiles are collected from ECMWF reanalysis data. Quality control and sensitivity analyses were conducted for the input variables of surface skin temperature, air temperature, and atmospheric humidity. The ground-based validations show acceptable biases of primary input parameters (skin temperature, 2 m air temperature, near surface relative humidity, rain flag) for retrieving using. The subsequent sensitivity tests suggest that 10 K bias of skin temperature or observed brightness temperature may result in a 4% (~0.04) or 7% (0.07) retrieving error in MLSE at 23.5 GHz. A nonlinear sensitivity in the same magnitude is found for air temperature perturbation, while the sensitivity is less than 1% for 300 g/m2 error in cloud water path. Results show that our algorithm can successfully retrieve MLSE over 90% of the satellite detected land surface area in a typical cloudy day (cloud fraction of 64%), which is considerably higher than that of the 29% area by the clear-sky only algorithms. The spatial distribution of MLSE in China is highly dependent on the land surface types and topography. The retrieved MLSE is assessed by compared with other existing clear-sky AMSR-E emissivity products and the vegetation optical depth (VOD) product. Overall, high consistencies are shown for the MLSE retrieved in this study with other AMSR-E emissivity products across China though noticeable discrepancies are observed in Tibetan Plateau and Qinling-Taihang Mountains due to different sources of input skin temperature. In addition, the retrieved MLSE exhibits strong positive correlations in spatial patterns with microwave vegetation optical depth reported in the literature.

The Potential of a Spaceborne Cloud Radar for the Detection of Stratocumulus Clouds

The radar reflectivity and liquid water content of stratocumulus clouds have been computed from cloud droplet spectra recorded during more than 4000 km of cloud penetrations by an aircraft, and the probability of detecting various values of liquid water content as a function of the radar sensitivity threshold has been derived. The goal of the study is to specify the sensitivity required for any future spaceborne cloud radar. In extensive marine stratocumulus deeper than about 200 m, occasional but ubiquitous drizzle-sized droplets of up to 200 μm dominate the radar return and increase it by between 10 and 20 dB above the cloud droplet contribution to the return, making radar detection easier, although the concentration of the drizzle drops is so low that they have no effect on the liquid water content or effective radius. These occasional drizzle-sized droplets are present throughout the vertical and horizontal extent of such clouds but should evaporate within 200 m of cloud base. On occasion, the drizzle can fall farther and may yield a false measurement of cloud-base altitude, but such cases can be recognized by examining the vertical profile of reflectivity. A radar sensitivity threshold of −30 dBZ would detect 80%, 85%, and 90% of the marine stratocumulus, with a liquid water content above 0.025, 0.05, and 0.075 g m−3, respectively. Because nonprecipitating drizzle droplets are rare in continental stratocumulus, the equivalent figures are reduced to 38%, 33%, and 25%. Improving the sensitivity to −40 dBZ increases detection probability to nearly 100% for both types of cloud. These figures are based on the assumption that the cloud is deep enough to fill the radar pulse volume.