This repository contains code, data, and documentation for our bachelor thesis at the Technical University of Denmark (DTU) in collaboration with the Danish Meteorological Institute (DMI). The project explores the use of simulated CIMR (Copernicus Imaging Microwave Radiometer) and MWI (Microwave Imager) data for sea ice applications.
- Process & analyze simulated CIMR and MWI data
- Investigate their potential for retrieving sea ice concentration (SIC) and snow depth
- Compare simulated observations with outputs from the CICE sea ice model
- Evaluate retrieval algorithm performance under different ice conditions
- Quantify the impact of footprint resolution on sea ice estimates
- Support development of high-resolution satellite products for climate research
All data used and generated in this project can be found here:
📎 Google Drive Data Folder
Contents include:
- SMRT brightness temperature simulations
- Sea ice and snow property inputs from DMI-CICE
- CIMR and MWI frequency-specific sensor configurations
- Retrieval outputs from SIC and snow depth algorithms
- SMRT Radiative Transfer Modeling for passive microwave simulation
- Snow/Ice Layering Schemes based on literature and model outputs
- Sensor Emulation for CIMR (high-resolution, wide-swath) and MWI (lower resolution)
- Retrieval Algorithms tested:
- Bristol SIC algorithm
- Rostosky et al. (2018) snow depth algorithm
- Footprint Mismatch Assessment for evaluating coarse vs. fine spatial resolutions
- Coarser resolution (MWI) caused significant overestimation of sea ice extent
- CIMR's 5 km resolution preserved key features in marginal ice zones
- Bristol algorithm was sensitive to snow depth on FYI, leading to positive biases
- Rostosky snow depth retrieval failed on MYI and bare ice, indicating a need for recalibration
- Combining data from both sensors may reduce regional uncertainty in retrieval products
Select references:
- Shokr & Sinha (2015) – Sea Ice: Physics and Remote Sensing
- Ulaby et al. (1986) – Microwave Remote Sensing: Active and Passive
- Rostosky et al. (2018) – Snow depth retrieval algorithm
- Galeazzi et al. (2023) – CIMR mission overview
- Meier & Stewart (2019) – Uncertainty from footprint mismatch
- Wernecke et al. (2024) – Passive microwave intercomparison studies
Full reference list is available in the accompanying thesis PDF.
- Ida Grum-Schwensen Andersen
- Josephine Juul
Supervised by:
- Dr. Rasmus Tonboe (DTU Space)
- Dr. Till Rasmussen (DMI)
This project supports the development of next-generation Earth observation missions for Arctic sea ice monitoring. It highlights the importance of high-resolution radiometry and physically consistent retrieval methods for accurate climate assessment.