Our research incorporates innovative combinations of satellite observations and numerical models to examine energy and water balance in the Earth-atmosphere system. This requires a coordinated effort to develop and evaluate satellite data products, analyze the resulting datasets to probe relationships between the principal components of the global energy and water cycles, and use this information to evaluate the representation of key physical processes in both mesoscale and climate models. Through this combination of remote sensing, field work, data mining, and numerical modeling we hope to gain a better understanding of the climate system and evaluate our ability to predict its evolution.
Ongoing research in our group includes developing new multi-sensor, global, atmospheric radiative heating datasets from the Tropical Rainfall Measuring Mission and the A-Train as well as light rainfall and snowfall retrieval algorithms for CloudSat. We then analyze these data products along with measurements from other satellites to refine estimates of global energy balance and quantify the impact of aerosols on clouds and precipitation. To verify the findings from our satellite studies, we have contributed to several field experiments such as the Light Precipitation Validation Experiment (LPVEx) in Helsinki, Finland where we collected in situ measurements of liquid and frozen precipitation from the ground and aboard aircraft to evaluate and improve satellite precipitation estimates at high latitudes. To learn more about this work and our other research projects use the above tabs.