| contributor author | Eri Yoshizawa | |
| contributor author | Takashi Kamoshida | |
| contributor author | Koji Shimada | |
| date accessioned | 2023-04-12T18:37:26Z | |
| date available | 2023-04-12T18:37:26Z | |
| date copyright | 2022/12/20 | |
| date issued | 2022 | |
| identifier other | JTECH-D-22-0049.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4289978 | |
| description abstract | In retrievals of sea ice motion vectors (SIMVs) based on passive microwave observations, the use of the high-resolution 89-GHz channel of the Advanced Microwave Scanning Radiometer 2 (AMSR2) has the advantage of enhancing the theoretical precision of correlation-based motion tracking. However, its higher sensitivity to atmospheric moisture than lower-frequency channels links maximum cross-correlation peaks to outlier vectors and obscures signals of valid vectors. This study develops an algorithm to select valid vectors from candidates detected by multiple cross-correlation peaks based on validations with large-scale sea ice displacements extracted from 19- and 37-GHz data after questionable vectors are prefiltered by comparing them with reanalysis surface wind and neighboring vectors. The algorithm selects a vector corresponding to large-scale motion as the optimal vector. The retrieved results from 2013 to 2020 show that by replacing outlier vectors with valid ones detected by second or third cross-correlation peaks, validation with simultaneous observations enables retrieval of more than 60% of the Arctic motion field from 89-GHz data in winter but only 10% in summer; therefore, lower-frequency data are employed for retrievals. The uncertainty assessment using in situ data from acoustic measurements from ocean moorings shows that the algorithm provides daily SIMVs with root-mean-square errors of only 1–2 cm s | |
| publisher | American Meteorological Society | |
| title | Sea Ice Motion Vector Retrievals from AMSR2 89-GHz Data: Validation Algorithm with Simultaneous Multichannel Observations | |
| type | Journal Paper | |
| journal volume | 40 | |
| journal issue | 1 | |
| journal title | Journal of Atmospheric and Oceanic Technology | |
| identifier doi | 10.1175/JTECH-D-22-0049.1 | |
| journal fristpage | 3 | |
| journal lastpage | 13 | |
| page | 3–13 | |
| tree | Journal of Atmospheric and Oceanic Technology:;2022:;volume( 040 ):;issue: 001 | |
| contenttype | Fulltext | |