The Passive Microwave section of NRL’s Remote Sensing Division has a well-established research focus on understanding the physics behind and modeling how snow, ice, and soil moisture are viewed by passive microwave and visible/IR sensors (e.g. AMSR, VIIRS, PACE, GOES, and SMAP satellites or ship-based or airborne sensors.) Radiative transfer modeling and satellite-based spectral analysis are vital tools for this research and build the theoretical basis for future operational algorithms and sensors. Additionally, this modeling is validated by careful analysis of in situ ground truth data so an understanding of how such data is collected and aggregated is important.

This research effort seeks to improve upon and leverage new techniques and resources to better understand and retrieve characteristics of the cryosphere and soil moisture. Specific subjects of interest include (but are not limited to) (1) Snow depth and snow water equivalent on both land and ice, necessary for cold weather tactical mobility, gap-crossing capabilities, and numerical weather prediction. (2) High-resolution day and nighttime Arctic sea ice concentration data vital for the safe transport of ships and submarines year round. (3) Accurate, temporally and spatially high-resolution soil moisture measurements required for data assimilation in numerical weather prediction models. (4) Operational transition of algorithms.

Candidates from a broad range of backgrounds are encouraged to apply, including individuals with experience in remote sensing, atmospheric sciences, oceanography, engineering, earth science and geophysics, or space weather.

key words

Remote sensing; cryosphere; soil moisture; sea ice; snow; satellite data analysis; passive microwave; Vis/IR; radiative transfer modeling

Citizenship:  Open to U.S. citizens and permanent residents

Level:  Open to Postdoctoral applicants