scholarly journals Comparison between AMSR-E ASI sea-ice concentration product, MODIS and pseudo-ship observations of the Antarctic sea-ice edge

2015 ◽  
Vol 56 (69) ◽  
pp. 45-52 ◽  
Author(s):  
Xi Zhao ◽  
Haoyue Su ◽  
Alfred Stein ◽  
Xiaoping Pang
Keyword(s):  
Sea Ice ◽  
Average Distance ◽  
Sea Ice Concentration ◽  
Earth Observing System ◽  
Antarctic Sea Ice ◽  
Spatial Coverage ◽  
Ice Concentration ◽  
Ice Edge ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Antarctic

AbstractThe performance of passive microwave sea-ice concentration products in the marginal ice zone and at the ice edge draws much attention in accuracy assessments. In this study, we generated 917 pseudo-ship observations from four Moderate Resolution Imaging Spectroradiometer (MODIS) images based on the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol to assess the quality of the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) ARTIST (Arctic Radiation and Turbulence Interaction STudy) Sea Ice (ASI) concentrations at the ice edge in Antarctica. The results indicate that the ASI pixels in the pseudo-ASPeCt observations have a mean ice concentration of 13% and are significantly different from the well-established 15% threshold. The average distance between the pseudo-ice edge and the 15% threshold contour is ~10 km. The correlation between the sea-ice concentration (SIC), SICASI and SICMODIS values at the ice edge was considerably lower than the high coefficients obtained from a transect analysis. Underestimation of SICASI occurred in summer, whereas no clear bias was observed in winter. The proposed method provides an opportunity to generate a new source of reference data in which the spatial coverage is wider and more flexible than in traditional in situ observations.

scholarly journals Antarctic sea-ice extents and concentrations: comparison of satellite and ship measurements from International Polar Year cruises

2011 ◽  
Vol 52 (57) ◽  
pp. 318-326 ◽  
Author(s):  
Burcu Ozsoy-Cicek ◽  
Stephen F. Ackley ◽  
Anthony Worby ◽  
Hongjie Xie ◽  
Jan Lieser
Keyword(s):  
Sea Ice ◽  
Passive Microwave ◽  
Sea Ice Concentration ◽  
International Polar Year ◽  
Sea Ice Extent ◽  
Earth Observing System ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
International Polar ◽  
Ice Edge

AbstractAntarctic Sea Ice Processes and Climate (ASPeCt) ship-based ice observations, conducted during the Sea Ice Mass Balance in the Antarctic (SIMBA) and Sea Ice Physics and Ecosystem eXperiment (SIPEX) International Polar Year (IPY) cruises (September–October 2007), are used to validate remote-sensing measurements of ice extent and concentration. Observations include varied sea-ice types at and inside the ice edge of West (~90˚ W) and East (~120˚ E) Antarctica. Time series of Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) ice extents and US National Ice Center (NIC) ice edges were obtained for the 2007–08 periods bracketing the period these cruises were conducted. A comparison between passive microwave satellite imagery and ASPeCt observations of sea-ice concentration during two cruises was also performed. In 90˚W regions, the concentrated pack ice indicated good correlation between ship observations and passive microwave estimates of the ice concentration (R2 = 0.80). In the marginal zone of West Antarctica and over nearly the entire sea-ice zone of East Antarctica, correlation dropped to R2 < 0.60. These findings are consistent with other studies comparing passive microwave and ship observations and further verify that the East Antarctic sea-ice zone is more marginal in character. There are significant ice-edge differences between AMSR-E and NIC between late November 2007 and early March 2008 such that the AMSR-E sea-ice extent estimate is 1–2 × 106 km2 less than the NIC estimate.

scholarly journals Observed Concentration Budgets of Arctic and Antarctic Sea Ice

2016 ◽  
Vol 29 (14) ◽  
pp. 5241-5249 ◽  
Author(s):  
Paul R. Holland ◽  
Noriaki Kimura
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Ice Melting ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Anthropogenic Contribution ◽  
Ice Edge ◽  
The Antarctic

Abstract In recent decades, Antarctic sea ice has expanded slightly while Arctic sea ice has contracted dramatically. The anthropogenic contribution to these changes cannot be fully assessed unless climate models are able to reproduce them. Process-based evaluation is needed to provide a clear view of the capabilities and limitations of such models. In this study, ice concentration and drift derived from AMSR-E data during 2003–10 are combined to derive a climatology of the ice concentration budget at both poles. This enables an observational decomposition of the seasonal dynamic and thermodynamic changes in ice cover. In both hemispheres, the results show spring ice loss dominated by ice melting. In other seasons ice divergence maintains freezing in the inner pack while advection causes melting at the ice edge, as ice is transported beyond the region where it is thermodynamically sustainable. Mechanical redistribution provides an important sink of ice concentration in the central Arctic and around the Antarctic coastline. This insight builds upon existing understanding of the sea ice cycle gained from ice and climate models, and the datasets may provide a valuable tool in validating such models in the future.

scholarly journals Variability in Antarctic sea ice from 1998-2017

2018 ◽  
Author(s):  
Zhankai Wu ◽  
Xingdong Wang
Keyword(s):  
Sea Ice ◽  
First Year ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Ice Melt ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
The Antarctic ◽  
Melt Duration ◽  
Multiyear Ice

This study was based on the daily sea ice concentration data from the National Snow and Ice Data Center (Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA) from 1998 to 2017. The Antarctic sea ice was analysed from the total sea ice area (SIA), first year ice area, first year ice melt duration, and multiyear ice area. On a temporal scale, the changes in sea ice parameters were studied over the whole 20 years and for two 10-year periods. The results showed that the total SIA increased by 0.0083×106 km2 yr-1 (+2.07% dec-1) between 1998 and 2017. However, the total SIA in the two 10-year periods showed opposite trends, in which the total SIA increased by 0.026×106 km2 yr-1 between 1998 and 2007 and decreased by 0.0707×106 km2 yr-1 from 2008 to 2017. The first year ice area increased by 0.0059×106 km2 yr-1 and the melt duration decreased by 0.0908 days yr-1 between 1998 and 2017. The multiyear ice area increased by 0.0154×106 km2 yr-1 from 1998 to 2017, and the increase in the last 10 years was about 12.1% more than that in the first 10 years. On a spatial scale, the Entire Antarctica was divided into two areas, namely West Antarctica (WA) and East Antarctica (EA), according to the spatial change rate of sea ice concentration. The results showed that WA had clear warming in recent years; the total sea ice and multiyear ice areas showed a decreasing trend; multiyear ice area sharply decreased and reached the lowest value in 2017, and accounted for only about 10.1% of the 20-year average. However, the total SIA and multiyear ice area all showed an increased trend in EA, in which the multiyear ice area increased by 0.0478×106 km2 yr-1. Therefore, Antarctic sea ice presented an increasing trend, but there were different trends in WA and EA. Different sea ice parameters in WA and EA showed an opposite trend from 1998 to 2007. However, the total SIA, first year ice area, and multiyear ice area all showed a decreasing trend from 2008-2017, especially the total sea ice and first year ice, which changed almost the same in 2014-2017. In summary, although the Antarctic sea ice has increased slightly over time, it has shown a decreasing trend in recent years.

scholarly journals Impact of surface wind biases on the Antarctic sea ice concentration budget in climate models

2016 ◽  
Vol 105 ◽  
pp. 60-70 ◽  
Author(s):  
O. Lecomte ◽  
H. Goosse ◽  
T. Fichefet ◽  
P.R. Holland ◽  
P. Uotila ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Surface Wind ◽  
Sea Ice Concentration ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
The Antarctic

scholarly journals Antarctic summer sea ice concentration and extent: comparison of ODEN 2006 ship observations, satellite passive microwave and NIC sea ice charts

2008 ◽  
Vol 2 (4) ◽  
pp. 623-647 ◽  
Author(s):  
B. Ozsoy-Cicek ◽  
H. Xie ◽  
S. F. Ackley ◽  
K. Ye
Keyword(s):  
Sea Ice ◽  
Linear Trend ◽  
Passive Microwave ◽  
The Arctic ◽  
Poor Correlation ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
Ice Edge

Abstract. Antarctic sea ice cover has shown a slight increase in overall observed ice extent as derived from satellite mapping from 1979 to 2008, contrary to the decline observed in the Arctic regions. Spatial and temporal variations of the Antarctic sea ice however remain a significant problem to monitor and understand, primarily due to the vastness and remoteness of the region. While satellite remote sensing has provided and has great future potential to monitor the variations and changes of sea ice, uncertainties remain unresolved. In this study, the National Ice Center (NIC) ice edge and the AMSR-E (Advanced Microwave Scanning Radiometer – Earth Observing System) ice extent are examined, while the ASPeCt (Antarctic Sea Ice Process and Climate) ship observations from the Oden expedition in December 2006 are used as ground truth to verify the two products during Antarctic summer. While there is a general linear trend between ASPeCt and AMSR-E ice concentration estimates, there is poor correlation (R2=0.41) and AMSR-E tends to underestimate the low ice concentrations. We also found that the NIC sea ice edge agrees well with ship observations, while the AMSR-E shows the ice edge further south, consistent with its poorer detection of low ice concentrations. The northward extent of the ice edge at the time of observation (NIC) had mean values varying from 38 km to 102 km greater on different days for the area as compared with the AMSR-E sea ice extent. For the circumpolar area as a whole in the December period examined, AMSR-E therefore underestimates the area inside the ice edge at this time by up to 14% or, 1.5 million km2 less area, compared to the NIC ice charts. These differences alone can account for more than half of the purported sea ice loss between the pre 1960s and the satellite era suggested earlier from comparative analysis of whale catch data with satellite derived data. Preliminary comparison of satellite scatterometer data suggests better resolution of low concentrations than passive microwave, and therefore better fidelity with ship observations and NIC charts of the area inside the ice edge during Antarctic summer.

Retrieving the antarctic sea-ice concentration based on AMSR-E 89 GHz data

2013 ◽  
Vol 32 (9) ◽  
pp. 38-43
Author(s):  
Qinglong Yu ◽  
Hui Wang ◽  
Liying Wan ◽  
Haibo Bi
Keyword(s):  
Sea Ice ◽  
Sea Ice Concentration ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
The Antarctic

scholarly journals Observed Evidence of an Impact of the Antarctic Sea Ice Dipole on the Antarctic Oscillation

2011 ◽  
Vol 24 (16) ◽  
pp. 4508-4518 ◽  
Author(s):  
Qigang Wu ◽  
Xiangdong Zhang
Keyword(s):  
Sea Ice ◽  
Geopotential Height ◽  
Lead Time ◽  
Antarctic Oscillation ◽  
Atmospheric Variability ◽  
Sea Ice Concentration ◽  
Maximum Covariance Analysis ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
The Antarctic

Abstract A lagged maximum covariance analysis (MCA) is applied to investigate the linear covariability between monthly sea ice concentration (SIC) and 500-mb geopotential height (Z500) in the Southern Hemisphere (SH). The dominant signal is the atmospheric forcing of SIC anomalies throughout the year, but statistically significant covariances are also found between austral springtime Z500 and prior SIC anomalies up to four months earlier. The MCA pattern is characterized by an Antarctic dipole (ADP)-like pattern in SIC and a positively polarized Antarctic Oscillation (AAO) in Z500. Such long lead-time covariance suggests the forcing of the AAO by persistent ADP-like SIC anomalies. The leading time of SIC anomalies provides an implication for skillful predictability of springtime atmospheric variability.

scholarly journals Variability in Antarctic sea ice from 1998-2017

2018 ◽  
Author(s):  
Zhankai Wu ◽  
Xingdong Wang
Keyword(s):  
Sea Ice ◽  
First Year ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Ice Melt ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
The Antarctic ◽  
Melt Duration ◽  
Multiyear Ice

This study was based on the daily sea ice concentration data from the National Snow and Ice Data Center (Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA) from 1998 to 2017. The Antarctic sea ice was analysed from the total sea ice area (SIA), first year ice area, first year ice melt duration, and multiyear ice area. On a temporal scale, the changes in sea ice parameters were studied over the whole 20 years and for two 10-year periods. The results showed that the total SIA increased by 0.0083×106 km2 yr-1 (+2.07% dec-1) between 1998 and 2017. However, the total SIA in the two 10-year periods showed opposite trends, in which the total SIA increased by 0.026×106 km2 yr-1 between 1998 and 2007 and decreased by 0.0707×106 km2 yr-1 from 2008 to 2017. The first year ice area increased by 0.0059×106 km2 yr-1 and the melt duration decreased by 0.0908 days yr-1 between 1998 and 2017. The multiyear ice area increased by 0.0154×106 km2 yr-1 from 1998 to 2017, and the increase in the last 10 years was about 12.1% more than that in the first 10 years. On a spatial scale, the Entire Antarctica was divided into two areas, namely West Antarctica (WA) and East Antarctica (EA), according to the spatial change rate of sea ice concentration. The results showed that WA had clear warming in recent years; the total sea ice and multiyear ice areas showed a decreasing trend; multiyear ice area sharply decreased and reached the lowest value in 2017, and accounted for only about 10.1% of the 20-year average. However, the total SIA and multiyear ice area all showed an increased trend in EA, in which the multiyear ice area increased by 0.0478×106 km2 yr-1. Therefore, Antarctic sea ice presented an increasing trend, but there were different trends in WA and EA. Different sea ice parameters in WA and EA showed an opposite trend from 1998 to 2007. However, the total SIA, first year ice area, and multiyear ice area all showed a decreasing trend from 2008-2017, especially the total sea ice and first year ice, which changed almost the same in 2014-2017. In summary, although the Antarctic sea ice has increased slightly over time, it has shown a decreasing trend in recent years.

scholarly journals DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations

2021 ◽  
pp. 1-6
Author(s):  
Hao Luo ◽  
Qinghua Yang ◽  
Longjiang Mu ◽  
Xiangshan Tian-Kunze ◽  
Lars Nerger ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Southern Ocean ◽  
Sea Ice ◽  
Coupled Model ◽  
Sea Ice Concentration ◽  
Model Free ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
Data Assimilation System ◽  
Assimilation System

Abstract To improve Antarctic sea-ice simulations and estimations, an ensemble-based Data Assimilation System for the Southern Ocean (DASSO) was developed based on a regional sea ice–ocean coupled model, which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. To validate the performance of DASSO, experiments were conducted from 15 April to 14 October 2016. Generally, assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. Besides considering uncertainties in the operational atmospheric forcing data, a covariance inflation procedure in data assimilation further improves the simulation of Antarctic sea ice, especially SIT. The results demonstrate the effectiveness of assimilating sea-ice observations in reconstructing the state of Antarctic sea ice, but also highlight the necessity of more reasonable error estimation for the background as well as the observation.

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