Ice types and properties package

Rationale behind the "ice types and properties" work package


Ice types and properties

Ice types and properties are best determined at large scale from multi-frequency passive and active microwave sensors (since 1978) which are independent of daylight, and penetrate the atmosphere. These sensors offer daily global coverage, in particular several times a day in Polar Regions. Microwave remote sensing data with additional support from optical satellite sensor products provide the most important sea ice information data today.

However, there still exist several unsolved challenges in the interpretation of microwave data. Among the key questions are the sea ice emissivity and backscatter coefficient, here together denoted as its signature, for the involved ice types with snow layers as a function of (1) the meteorological history (atmospheric temperature, precipitation, wind, ice drift), and (2) the different polarizations and frequencies between 6 and 190 GHz. These uncertainties affect not only surface parameter retrieval but also the retrieval of atmospheric variables. The problem will be investigated in various ways: (1) An analytical model based on the MEMLS emissivity model combined with a thermodynamic snow evolution model will be developed and validated against field observations of snow and ice. A low-cost field experiment to provide adequate data for this purpose is planned. (2) By empirical relations based on satellite and in-situ observed datasets. (3) Comparing satellite observations to simulated ones using NWP atmospheric profiles in radiative transfer calculations.

Once the signature is known to a sufficient accuracy, retrieval of other types than first year and multi-year ice will be attempted, i.e. frazil-pancake ice and thin congelation ice such as nilas and grey ice frequently occurring in the north Atlantic (Greenland Sea and Barents Sea) at the northern limb of the global thermohaline circulation. Backscatter data will be used to distinguish First Year (FY) from Multi-year (MY) ice. Single-parameter methods compensating for the atmospheric influences and integrated retrieval for both surface and atmosphere parameters will be developed to determine continuous and long-term consistent ice drift time series (core theme 2).

The new passive microwave sensors SSM/IS aboard the DMSP satellites and AMSR-E on AQUA together with the scatterometer ASCAT on METOP will be used to address these challenges by exploiting their new features of higher spatial resolution and additional frequencies (AMSR-E) and unified conical scanning at the window and the atmospheric sounding frequencies (SSM/IS), both together anticipating the features of the future operational radiometers CMIS on NPOESS (convergence of the NOAA, DMSP and European polar orbiting satellites METOP) scheduled for launch in 2009.Within the integrated retrieval from passive microwave data, both oceanic and atmospheric parameters (total water vapour, cloud liquid water, temperature profile) will be determined simultaneously, see core theme 2.

The presently operating scatterometer QuikSCAT measures in the Ku-band
(14 GHz).

The next scatterometer, ASCAT (launch end 2005 on METOP) will operate at C-Band (6 GHz). When the ERS-2 (C-band) and NSCAT (Ku-band) scatterometers operated simultaneously (1996-1997), ice type discrimination was greatly improved using both data sets taken at different frequencies. Prior to their joint availability, it will be necessary to derive incidence-angle adjusted backscatter maps from the ASCAT data taken at varying incidence angles.

Ice motion and deformation fields from several satellite sensors satellites (SSM/I),

AMSR-E, QuikScat scatterometry, ENVISAT ASAR, RADARSAT), drifting buoy and experimental in-situ data will be analyzed in order to determine the quality of the ice motion products. In order to retain small scale ice motion features and the comparably lower noise level of the high resolution motion fields, separate developments are undertaken for high and low resolution sensors. Subsequently, data will be interpreted to determine a relationship between small and large-scale ice motions.


Contact person at DTU: Leif Toudal Pedersen