EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Fingerprinting Precipitation Processes in Remote-Sensing Observations

Ana Barros, Steven Chavez, Lihui Ji, and Malarvizhi Arulraj
Ana Barros et al.
  • Duke University, Pratt School of Engineering, Department of Civil and Environmental Engineering, Durham NC, United States of America (

The distinctive fingerprints of precipitation processes in multifrequency measurements from GOES-East and GPM sensors are characterized using ground-based observations (rain gauges, disdrometers, spectrometers, radars, etc.) and microphysical-dynamical models.  The focus is on low-level warm rain processes, including the life-cycle of hydrometeors from CN activation until they reach the land surface, not resolved by numerical weather prediction models and missed by remote observing systems on the ground or satellites.  That is, the Terra Obscura of orographic precipitation. We propose and demonstrate a framework to infer local physical-statistical constraints from satellite measurements to improve quantitative precipitation estimates (QPE) in complex terrain regions globally.

How to cite: Barros, A., Chavez, S., Ji, L., and Arulraj, M.: Fingerprinting Precipitation Processes in Remote-Sensing Observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13676,, 2021.