[대기] [대기과학세미나] 4.9.(화) 이정길 박사(KIST)
일시 : 2024-04-09(화) 16:00 ~ 17:00
연사 : 이정길 박사
소속 : 한국과학기술연구원(KIST)
문의 : 02-880-6723
장소 : 501동 504호 세미나실
Title: Data assimilation of satellite-derived Arctic sea ice thickness
[Abstract]
The impact of assimilating satellite-derived Arctic sea ice thickness (SIT) on simulating sea ice conditions is investigated using a data assimilation (DA) system based on the ensemble optimal interpolation using Community Ice CodE version 5 (CICE5). The DA of the SIT satellite products from CryoSat-2 (CS2) and SMOS during the winter significantly reduces the climatological bias of sea ice concentration (SIC) and SIT in both sea ice melt and freeze seasons. The idealized experiments of reducing SIT suggest that the enhanced ice bottom melting process plays a crucial role in reducing positive bias in SIC over the marginal ice zones during the winter. The impact of DA of each product during the winter is explored on seasonal time scale. The DA of CS2 has positive impact on the improvement in climatological bias in sea ice amount, where that of SMOS improves the representations of interannual variability in sea ice variables.
The reliable estimation and initialization through DA for Arctic SIT during the summer season had been hampered by the lack of available observations attributed to the limitations of retrieval algorithm for satellite. Recently, satellite-derived products of summer Arctic SIT have been successfully obtained through sophisticated retrieval algorithm. SIT from CS2 and Advanced Microwave Scanning Radiometer 2 (AMSR2) have been provided during the boreal summer. The underestimated SIE and SIT in control simulation without any DA during summer are effectively corrected by assimilating AMSR2, whereas the degree of the correction is less pronounced with the DA of CryoSat-2. The differential impact of the two satellite datasets can be attributed to disparities in their resolution and quality; the high spatiotemporal resolution of AMSR2 led to effective corrections for SIT compared to DA of CryoSat-2.
[Abstract]
The impact of assimilating satellite-derived Arctic sea ice thickness (SIT) on simulating sea ice conditions is investigated using a data assimilation (DA) system based on the ensemble optimal interpolation using Community Ice CodE version 5 (CICE5). The DA of the SIT satellite products from CryoSat-2 (CS2) and SMOS during the winter significantly reduces the climatological bias of sea ice concentration (SIC) and SIT in both sea ice melt and freeze seasons. The idealized experiments of reducing SIT suggest that the enhanced ice bottom melting process plays a crucial role in reducing positive bias in SIC over the marginal ice zones during the winter. The impact of DA of each product during the winter is explored on seasonal time scale. The DA of CS2 has positive impact on the improvement in climatological bias in sea ice amount, where that of SMOS improves the representations of interannual variability in sea ice variables.
The reliable estimation and initialization through DA for Arctic SIT during the summer season had been hampered by the lack of available observations attributed to the limitations of retrieval algorithm for satellite. Recently, satellite-derived products of summer Arctic SIT have been successfully obtained through sophisticated retrieval algorithm. SIT from CS2 and Advanced Microwave Scanning Radiometer 2 (AMSR2) have been provided during the boreal summer. The underestimated SIE and SIT in control simulation without any DA during summer are effectively corrected by assimilating AMSR2, whereas the degree of the correction is less pronounced with the DA of CryoSat-2. The differential impact of the two satellite datasets can be attributed to disparities in their resolution and quality; the high spatiotemporal resolution of AMSR2 led to effective corrections for SIT compared to DA of CryoSat-2.
첨부파일 (1개)
- Abstract_jglee.docx (19 KB, download:8)
