THE QUANTIFICATION OF THE IMPORTANCE OF THE SEA ICE BUDGET IN THE CLIMATE SYSTEM - Final report
The overall objective is to quantify the importance of a better knowledge of sea ice budget on relevant climate processes such as freshwater budget, thermohaline circulation and deep water formation. The retrieval of the key parameter sea ice thickness from remote sensing techniques poses a major ch...
| Main Authors: | , , , , , |
|---|---|
| Format: | Report |
| Language: | English |
| Published: |
2001
|
| Subjects: | |
| Online Access: | https://zenodo.org/record/7639020 https://doi.org/10.5281/zenodo.7639020 |
| Summary: | The overall objective is to quantify the importance of a better knowledge of sea ice budget on relevant climate processes such as freshwater budget, thermohaline circulation and deep water formation. The retrieval of the key parameter sea ice thickness from remote sensing techniques poses a major challenge compared with the observation of sea ice extent and ice concentration. The specific objectives are: • To examine the sensitivity of state of the art dynamic-themodynamic sea ice models to changes in sea ice thickness. • To derive observation requirements (e.g. requirements for accuracy, repeatability and temporal-spatial coverage) senarios for the estimation of sea ice thickness in the Arctic. • Perform a sensitivity study of the importance of sea ice volume fluxes for freshwater budgets, thermohaline circulation and deep water formation in high latitude regions. Based on the results the observation requirements for ice thickness the analysis shall be updated and refined. In order to meet these objectives five tasks have been conducted. In Task 1 the most important data sets are ice area and concentration from satellite passive microwave data and ice velocity data from drifting buoys and satellite data. Retrieval of ice thickness data from satellite altimeter is discussed based on recent analysis of ERS data carried out at UCL. The results of the Sea Ice Model Intercomparison Project (SIMIP) are reivewed where the performance of different ice rheologies are assessed. Finally, satellite data assimilation in ice models is mentioned, reflecting that only limited work has been done in this field. Task 2 used ice velocity data from the Arctic Ocean Buoy Programme and satellite data from NOAA to compare with model simulations. Extensive model validation has been done for ice extent and concentration, where merged SMMR and SSMI data have been used to assess the basic model scenario. UCL has also made a comparison of ERS altimeter thickness with the model simulations at University of Kiel and the Hadley Centre showing ... |
|---|