Arka Mitra

The poor representation of clouds in global climate models (GCMs) remain the single largest source of uncertainty in climate modeling studies. In order to better test and constrain GCMs, it is imperative to have accurate, long-term global measurements of cloud structure and properties on the scale that only our long-term passive sensors on satellites, such as MISR or MODIS can provide us. Cloud-top-height (CTH) is one of the most important cloud properties for climate research, with an increase of cloud heights leading to a net warming effect on the Earth's climate while a lowering scenario would lead to net cooling.

With that in mind, the overarching goal of my research is to – 

(i) improve our capabilities in detecting cloud vertical structure, especially under conditions of cloud overlap, 
(ii) recognize and remove systematic biases in our satellite records of cloud top height (CTH) by combining products from multiple platforms, 3D radiative transfer (RT) simulations and measurements from field campaigns, and, 
(iii) analyze fused satellite products of nearly two decades to detect long-term trends and address the possibility of multi-decadal cloud feedbacks in our satellite records.