ESSIC Assistant Research Engineer Soni Yatheendradas and ESSIC/CICS-MD Assistant Research Scientist Jicheng Liu recently collaborated on a study titled “The Efficiency of Data Assimilation” published in the EOS Journal Water Resources Research.
In the piece, the authors offer a framework to quantify information loss from data assimilation through measuring information in models, observations, and evaluation data.
The piece was highlighted in a recent EOS Research Spotlight that details the inevitability of uncertainty and how this framework can be used to help real inefficiencies.
Yatheendradas is affiliated with the Hydrological Sciences Lab at NASA GSFC. His current work include leading optimization/uncertainty components on NASA’s Land Information System (LIS) software especially for SUSMAP applications, Machine and Deep Learning applied to spatial downscaling and retrieval in snow remote sensing, and multivariate hydrologic data assimilation for model structural learning and process-diagnostics.
Liu is also a Visiting Scientist with the National Oceanic and Atmospheric Administration’s (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS). His current research interests include developing soil moisture retrieval algorithms using data from microwave satellite sensors.
Click here to read the original article: “The Efficiency of Data Assimilation”.
