Name
Abstract | ||
|---|---|---|
This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: (1) the National Aeronautics and Space Administration Team (NT) algorithm and (2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over- or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper were assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7, 18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 a- - nd 18.7 GHz to these factors to improve snow depth retrievals from spaceborne passive microwave sensors |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/TGRS.2006.880619 | Geoscience and Remote Sensing, IEEE Transactions |
Keywords | Field | DocType |
hydrological techniques,radiative transfer,radiometers,remote sensing,sea ice,snow,surface roughness,10.7 GHz,18.7 GHz,37 GHz,AD 2003 03,AMSR-Ice03 field campaign,Advanced Microwave Scanning Radiometer,Alaska,Barrow,National Aeronautics and Space Administration Team algorithm,Polarimetric Scanning Radiometer,USA,airborne passive microwave observations,brightness temperatures,instrument calibration,polarization ratios,radiative transfer model,sea ice algorithms,sea ice concentrations,sea ice products,snow depth algorithm,snow depth retrievals,spaceborne passive microwave sensors,surface roughness,surface snow,Passive microwave,remote sensing,sea ice | Sea ice concentration,Sea ice,Remote sensing,Sea ice thickness,Atmospheric radiative transfer codes,Sea ice emissivity modelling,Snow,Mathematics,Surface roughness,Radiometer | Journal |
Volume | Issue | ISSN |
44 | 11 | 0196-2892 |
Citations | PageRank | References |
4 | 1.18 | 4 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julienne C. Stroeve | 1 | 43 | 12.06 |
| T. Markus | 2 | 188 | 45.80 |
| James A. Maslanik | 3 | 27 | 5.54 |
| Donald J. Cavalieri | 4 | 57 | 9.63 |
| Albin J. Gasiewski | 5 | 71 | 19.68 |
| John F. Heinrichs | 6 | 15 | 5.23 |
| Jon Holmgren | 7 | 17 | 5.22 |
| Donald Perovich | 8 | 60 | 15.28 |
| Matthew Sturm | 9 | 30 | 8.82 |