In this project, we are working to quantify and investigate land-atmosphere (L-A) interactions and feedbacks that act primarily through the water and energy cycles as controlled by the state of soil moisture.  Specifically, the researchers will address three questions: 

• First, how does the terrestrial leg of L-A coupling vary in space and time, and how do the physical processes governing coupling determine spatiotemporal variability? 

• Second, how well can the spatiotemporal variability of the terrestrial leg of L-A coupling be characterized using only observations, providing estimates independent of model biases and errors? 

• Third, how can a purely observational product with limited temporal span inform the characterization of trends and extremes in the water and energy cycles? 

The researchers will utilize soil moisture active passive (SMAP) products for process studies in unique and important ways, and apply SMAP for reanalysis model evaluation. The data set will be ideal for evaluation of both operational forecast models (regional and global) and climate models. They will apply Information Theory to modify and improve the formulation of a number of L-A metrics, extracting more signals to inform process understanding and model development. This project will identify gaps and assign quality and uncertainty ratings to each metric and process assessment, identifying areas for future focus.