Project Details
Projekt
A Monte-Carlo ensemble of Antarctic passive-microwave sea-ice concentrations: Identifying error sources and characteristics for machine-learning supported uncertainty quantification
Applicant
Dr. Andreas Wernecke
Subject Area
Oceanography
Term
since 2023
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 522421911
The Antarctic sea ice cover is an important factor in the characterization of the Earth’s climate. It is an active component in many processes, governing the fluxes at the ocean surface. The aim of this project is to improve our understanding of the sources of uncertainty in sea-ice concentration observations as well as their representation for the quantification of uncertainties in integrated metrics such as the total sea ice area. The sources of uncertainty are to be de-tangled with the help of the spatio-temporal characteristics of physical properties causing uncertainties in the SIC. An machine learning approach is used to turn an uncertainty correlation model (based on observations) into an ensemble representation. This user friendly representation helps to quantify uncertainties of all applications of satellite remote sensing sea ice concentration. Finally, the links of the Antarctic sea ice, and by extension the Antarctic seas in general, to the global climate system are to reassessed under consideration of their uncertainties.
DFG Programme
Infrastructure Priority Programmes
