Carmen Nab

Carmen Nab

Profile
Profile Display Name:

Carmen Nab

E-mail Address:

carmen.nab.18@ucl.ac.uk

Start Year

2020 (Cohort 7)

Research interests:
Hobbies and interests:

PhD Project
PhD Title

CryoSat-2 radar penetration over Arctic sea ice

Research Theme

Earth, Atmosphere and Ocean Processes

Primary Supervisor
Primary Institution

UCL

Secondary Supervisor
Secondary Institution

UCL

CASE Partner

Met Office

CASE Supervisor

Dr Davi Mignac Carneiro & Dr Matthew Martin

Abstract

Accurate monitoring and modeling of Arctic sea ice thickness is vital to understanding the region’s effects on regional and global climates, shipping routes, and wildlife living on and under the ice. Satellite radar altimeters offer a valuable tool for estimating sea ice thickness, where the travel time of a radar pulse to the sea ice surface and back is measured to obtain the radar freeboard, a proxy for the height of the ice above the surrounding sea water. The method for converting radar freeboard estimates to sea ice thickness requires an assumption regarding the fractional depth of the snowpack penetrated by radar waves (α), which then return to the instrument. All current winter sea ice thickness retrieval methods assume full radar penetration through the snowpack (α = 1). A growing body of research has shown this not to be the case in reality, with snow and weather properties affecting the ability of radar waves to penetrate the snowpack. Uncertainties in the radar freeboard and assumed radar penetration contribute to the overall error in calculated sea ice thickness, with an overestimation of α causing an overestimation in sea ice thickness, without competing biases. This thesis aims to improve our understanding of CryoSat-2 snow penetration over Arctic sea ice and its representation in modelling frameworks.

Policy Impact
Background Reading
Publications
Datasets

Daily-resolution pan-Arctic Radar and Laser Freeboard Zenodo. Contributors: Carmen Nab

Activities
Conferences and Workshops
  • ESA Living Planet Symposium 2022. Poster: Synoptic variability in satellite radar altimeter-derived sea ice thickness.
  • Cryosphere 2022. Poster: Synoptic variability in satellite radar altimeter-derived sea ice thickness.
Training courses
  • AI4Svalbard, hosted by SIOS.
  • Data Assimilation Training Course, hosted by ECMWF.
  • Multi-annual to Decadal Climate Predictability Workshop, hosted by CLIVAR.

Social Links
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