Research and Application News
Evaluating the Efficiency of Data Assimilation
07 January 2019
Information is lost when researchers combine statistical models and remote sensing data, but just how much is often unclear. A new study offers a framework to measure the inefficiency.
The 20th century statistician George Box is widely credited with the remark that "essentially all [statistical] models are wrong, but some are useful." And it's true: As abstractions of the real world, models can only generalize the systems we study. The same holds for remotely sensed data, often collected via satellite or aircraft.
Source: EOS - Earth & Space Science News
Image credit: Dr. Amy McNally (NASA Goddard Space Flight Center) - A member of the SMAP team collecting soil moisture data for calibration and validation in Yanco, Australia.