Satellite Remote Sensing and Product Development
Satellites are a valuable tool for observing important aspects of the climate system on global scales. Extracting useful information from satellite observations is not always easy, though, since these measurements are very indirect and frequently need models and assumptions to convert them into useful parameters. A significant aspect of our research centers on developing improved multi-sensor approaches for estimating atmospheric radiative heating and precipitation, key components of the global atmospheric energy and water cycles.
Atmospheric Radiative Heating
Among our top priorities is to explore new ways to use state-of-the-art measurements from NASAs Earth Observing System (EOS) satellites to determine the amount of energy that is received at different levels of the atmosphere over the globe. We currently oversee the development and distribution of two independent radiative flux and heating rate products; one derived from TRMM observations (1998-2010) and another based on A-Train observations (June 2006-present). These datasets not only provide radiative flux information at the top of the atmosphere and surface but also the distribution of radiative heating within the atmosphere - a critical player in defining the general circulation.
Rainfall Incidence and Intensity Estimates from CloudSat
Cloud radars like the one aboard CloudSat have more sensitivity to drizzle and light rainfall than conventional satellite precipitation sensor and, therefore, provide the most direct measure of precipitation occurrence from space. Our research group currently leads the development of the CloudSat rainfall detection and intensity estimation algorithms and we are now exploring new ways to analyze these datasets to better understand the importance of light rainfall in the global water cycle.
CloudSat Retrievals of Falling Snow
Snowfall provides a vital source of fresh water for a large fraction of the global population and also plays an important role in the Earth's climate through its impact on planetary albedo and surface heat fluxes and by freshening the high-latitude North Atlantic oceans. Yet until the launch of CloudSat, snowfall was generally not well monitored on global scales. As an extension of our rainfall algorithm development work, our group has also designed and implemented a snowfall retrieval algorithm for CloudSat that is now being used to measure the amount of snow that falls around the globe such as the snowfall scene shown at the right. We are currently focused on evaluating the physical assumptions that form the basis of this algorithm using aircraft observations collected during recent field experiments and using these datasets to evaluate the representation of cold-season precipitation climate models.