scholarly journals Evaluation of sea-ice thickness from four reanalyses in the Antarctic Weddell Sea

2021 ◽  
Vol 15 (1) ◽  
pp. 31-47
Author(s):  
Qian Shi ◽  
Qinghua Yang ◽  
Longjiang Mu ◽  
Jinfei Wang ◽  
François Massonnet ◽  
...  

Abstract. Ocean–sea-ice coupled models constrained by various observations provide different ice thickness estimates in the Antarctic. We evaluate contemporary monthly ice thickness from four reanalyses in the Weddell Sea: the German contribution of the project Estimating the Circulation and Climate of the Ocean Version 2 (GECCO2), the Southern Ocean State Estimate (SOSE), the Ensemble Kalman Filter system based on the Nucleus for European Modelling of the Ocean (NEMO-EnKF) and the Global Ice–Ocean Modeling and Assimilation System (GIOMAS). The evaluation is performed against reference satellite and in situ observations from ICESat-1, Envisat, upward-looking sonars and visual ship-based sea-ice observations. Compared with ICESat-1, NEMO-EnKF has the highest correlation coefficient (CC) of 0.54 and lowest root mean square error (RMSE) of 0.44 m. Compared with in situ observations, SOSE has the highest CC of 0.77 and lowest RMSE of 0.72 m. All reanalyses underestimate ice thickness near the coast of the western Weddell Sea with respect to ICESat-1 and in situ observations even though these observational estimates may be biased low. GECCO2 and NEMO-EnKF reproduce the seasonal variation in first-year ice thickness reasonably well in the eastern Weddell Sea. In contrast, GIOMAS ice thickness performs best in the central Weddell Sea, while SOSE ice thickness agrees most with the observations from the southern coast of the Weddell Sea. In addition, only NEMO-EnKF can reproduce the seasonal evolution of the large-scale spatial distribution of ice thickness, characterized by the thick ice shifting from the southwestern and western Weddell Sea in summer to the western and northwestern Weddell Sea in spring. We infer that the thick ice distribution is correlated with its better simulation of northward ice motion in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis for understanding the recent variability of sea-ice volume in the Antarctic.

2020 ◽  
Author(s):  
Qian Shi ◽  
Qinghua Yang ◽  
Longjiang Mu ◽  
Jinfei Wang ◽  
François Massonnet ◽  
...  

Abstract. Ocean-sea ice coupled models constrained by varied observations provide different ice thickness estimates in the Antarctic. We evaluate contemporary monthly ice thickness from four reanalyses in the Weddell Sea, the German contribution of the Estimating the Circulation and Climate of the Ocean project, Version 2 (GECCO2), the Southern Ocean State Estimate (SOSE), the Nucleus for European Modelling of the Ocean (NEMO) based ocean-ice model (called NEMO-EnKF), and the Global Ice-Ocean Modeling and Assimilation System (GIOMAS), and with reference observations from ICESat-1, Envisat, upward looking sonars and visual ship-based sea-ice observations. Compared with ICESat-1 altimetry and in situ observations, all reanalyses underestimate ice thickness near the coast of the western Weddell Sea, even though ICESat-1 and visual observations may be biased low. GECCO2 and NEMO-EnKF can well reproduce the seasonal variation of first-year ice thickness in the eastern Weddell Sea. In contrast, GIOMAS ice thickness performs best in the central Weddell Sea, while SOSE ice thickness agrees most with the observations in the southern coast of the Weddell Sea. In addition, only NEMO-EnKF can reproduce the seasonal spatial evolution of ice thickness distribution well, characterized by the thick ice shifting from the southwestern and western Weddell Sea in summer to the western and northwestern Weddell Sea in spring. We infer that the thick ice distribution is correlated with its better simulation of northward ice motion in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis for understanding the recent variability of sea-ice volume in the Antarctic.


2020 ◽  
Author(s):  
Jinfei Wang ◽  
Chao Min ◽  
Robert Ricker ◽  
Qinghua Yang ◽  
Qian Shi ◽  
...  

Abstract. The crucial role that Antarctic sea ice plays in the global climate system is strongly linked to its thickness. While in situ observations are too sparse in the Antarctic to determine long-term trends of the Antarctic sea ice thickness on a global scale, satellite radar altimetry data can be applied with a promising prospect. A newly released Envisat-derived product from the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI), including sea ice freeboard and sea ice thickness, covers the entire Antarctic year-round from 2002 to 2012. In this study, the SICCI Envisat sea ice thickness in the Antarctic is firstly compared with a conceptually new proposed ICESat ice thickness that has been derived from an algorithm employing modified ice density. Both data sets have been validated with the Weddell Sea upward looking sonar measurements (ULS), indicating that ICESat agrees better with field observations. The inter-comparisons are conducted for three seasons except winter based on the ICESat operating periods. According to the results, the deviations between Envisat and ICESat sea ice thickness are different considering different seasons, years and regions. More specifically, the smallest average deviation between Envisat and ICESat sea ice thickness exists in spring by −0.03 m while larger deviations exist in summer and autumn by 0.86 m and 0.62 m, respectively. Although the smallest absolute deviation occurs in spring 2005 by 0.02 m, the largest correlation coefficient appears in autumn 2004 by 0.77. The largest positive deviation occurs in the western Weddell Sea by 1.03 m in summer while the largest negative deviation occurs in the Eastern Antarctic by −0.25 m in spring. Potential reasons for those deviations mainly deduce from the limitations of Envisat radar altimeter affected by the weather conditions and the surface roughness as well as the different retrieval algorithms. The better performance in spring of Envisat has a potential relation with relative humidity.


Ocean Science ◽  
2005 ◽  
Vol 1 (3) ◽  
pp. 145-157 ◽  
Author(s):  
W. Lefebvre ◽  
H. Goosse

Abstract. The global sea ice-ocean model ORCA2-LIM is used to investigate the impact of the thermal and mechanical forcing associated with the Southern Annular Mode (SAM) on the Antarctic sea ice-ocean system. The model is driven by idealized forcings based on regressions between the wind stress and the air temperature at one hand and the SAM index the other hand. The wind-stress component strongly affects the overall patterns of the ocean circulation with a northward surface drift, a downwelling at about 45° S and an upwelling in the vicinity of the Antarctic continent when the SAM is positive. On the other hand, the thermal forcing has a negligible effect on the ocean currents. For sea ice, both the wind-stress (mechanical) and the air temperature (thermal) components have a significant impact. The mechanical part induces a decrease of the sea ice thickness close to the continent and a sharp decrease of the mean sea ice thickness in the Weddell sector. In general, the sea ice area also diminishes, with a maximum decrease in the Weddell Sea. On the contrary, the thermal part tends to increase the ice concentration in all sectors except in the Weddell Sea, where the ice area shrinks. This thermal effect is the strongest in autumn and in winter due to the larger temperature differences associated with the SAM during these seasons. The sum of the thermal and mechaninal effects gives a dipole response of sea ice to the SAM, with a decrease of the ice area in the Weddell Sea and around the Antarctic Peninsula and an increase in the Ross and Amundsen Seas during high SAM years. This is in good agreement with the observed response of the ice cover to the SAM.


2021 ◽  
Author(s):  
Yushi Morioka ◽  
Doroteaciro Iovino ◽  
Andrea Cipollone ◽  
Simona Masina ◽  
Swadhin Behera

<p>Skillful sea-ice prediction in the Antarctic Ocean remains a big challenge due to paucity of sea-ice observations and insufficient representation of sea-ice processes in climate models. This study demonstrates that the Antarctic sea-ice concentration (SIC) prediction is significantly improved using a coupled general circulation model (SINTEX-F2) in which the model’s SIC and sea-ice thickness (SIT) are initialized with the ocean/sea-ice reanalysis product (C-GLORSv7). It is found that the wintertime SIT initialization adds positive values to the prediction skills of the summertime SIC, most effectively in the Weddell Sea where the SIT climatology and variability are the largest among the Antarctic Seas. Examination of the SIT balance during low sea-ice years of the Weddell Sea shows that negative SIT anomalies initialized in June retain the memory throughout austral winter (July-September) owing to horizontal advection of the SIT anomalies by sea-ice velocities. The negative SIT anomalies continue to develop in austral spring (October-December) owing to more incoming solar radiation via ice-albedo feedback and the associated warming of mixed layer. This results in further sea-ice decrease during austral summer (January-March). Concomitantly, the model reasonably reproduces atmospheric circulation anomalies in the Amundsen-Bellingshausen Seas as well as the Weddell Sea during the development of the negative sea-ice anomalies. These results provide solid evidence that the wintertime SIT initialization benefits skillful summertime sea-ice prediction in the Antarctic Seas.</p>


Author(s):  
Kazuhiro Naoki ◽  
Jinro Ukita ◽  
Fumihiko Nishio ◽  
Masashige Nakayama ◽  
Josefino C. Comiso ◽  
...  

2005 ◽  
Vol 2 (3) ◽  
pp. 299-329 ◽  
Author(s):  
W. Lefebvre ◽  
H. Goosse

Abstract. The global sea ice-ocean model ORCA2-LIM is used to investigate the impact of the thermal and mechanical forcing associated to the Southern Annular Mode (SAM) on the Antarctic sea ice-ocean system. To do so, the model is driven by idealized forcings based on regressions of the wind stress and the air temperature to SAM. The wind-stress component strongly affects the overall patterns of the ocean circulation with a northward surface drift, a downwelling at about 45° S and an upwelling in the vicinity of the Antarctic continent when SAM is positive. On the other hand, the thermal forcing has a negligible effect on the ocean currents. For sea ice, both the wind-stress (mechanical) and the air temperature (thermal) components have a significant impact. The mechanical part induces a decrease of the sea ice thickness close to the continent and a sharp decrease of the mean sea ice thickness in the Weddell sector. In general, the sea ice area also diminishes, with a maximum decrease in the Weddell Sea. On the contrary, the thermal part tends to increase the ice concentration in all sectors except in the Weddell Sea, where the ice area shrinks. This thermal effect is the strongest in autumn and in winter due to the larger temperature differences associated with SAM during these seasons. The sum of the thermal and mechaninal effects gives a dipole response of sea ice to the SAM, with a decrease of the ice area in the Weddell Sea and around the Antarctic Peninsula and an increase in the Ross and Amundsen Seas during high SAM years. This is in good agreement with the observed response of the ice cover to SAM.


2021 ◽  
Author(s):  
Sutao Liao ◽  
Hao Luo ◽  
Jinfei Wang ◽  
Qian Shi ◽  
Jinlun Zhang ◽  
...  

Abstract. Antarctic sea ice is an important component of the Earth system. However, its role in the Earth system is still not very clear due to limited Antarctic sea ice thickness (SIT) data. A reliable sea ice reanalysis can be useful to study Antarctic SIT and its role in the Earth system. Among various Antarctic sea ice reanalysis products, the Global Ice-Ocean Modeling and Assimilation System (GIOMAS) output is widely used in the research of Antarctic sea ice. As more Antarctic SIT observations with quality control are released, a further evaluation of Antarctic SIT from GIOMAS is conducted in this study based on in-situ and satellite observations. Generally, though only sea ice concentration is assimilated, GIOMAS can basically reproduce the observed variability of sea ice volume and its changes in the trend before and after 2013, indicating that GIOMAS is a good option to study the long-term variation of Antarctic sea ice. However, due to deficiencies in model and asymmetric changes in SIT caused by assimilation, GIOMAS underestimates Antarctic SIT especially in deformed ice regions, which has an impact on not only the mean state of SIT but also the variability. Thus, besides the further development of model, assimilating additional sea ice observations (e.g., SIT and sea ice drift) with advanced assimilation methods may be conducive to a more accurate estimation of Antarctic SIT.


2021 ◽  
Author(s):  
Fengguan Gu ◽  
Qinghua Yang ◽  
Frank Kauker ◽  
Changwei Liu ◽  
Guanghua Hao ◽  
...  

Abstract. Single-column sea ice models are used to focus on the thermodynamic evolution of the ice. Generally these models are forced by atmospheric reanalysis in absence of atmospheric in situ observations. Here we assess the sea ice thickness (SIT) simulated by a single-column model (ICEPACK) with in situ observations obtained off Zhongshan Station for the austral winter of 2016. In the reanalysis the surface air temperature is about 1 °C lower, the total precipitation is about 2 mm day−1 larger, and the surface wind speed is about 2 m s−1 higher compared to the in situ observations, respectively. Using sensitivity experiments we evaluate the simulation bias in sea ice thickness due to the uncertainty in the individual atmospheric forcing variables. We show that the unrealistic precipitation in the reanalysis leads to a bias of 14.5 cm in sea ice thickness and of 17.3 cm in snow depth. In addition, our data show that increasing snow depth works to gradually inhibits the growth of sea ice associated with thermal blanketing by the snow due to changing the vertical heat flux. Conversely, given suitable conditions, the sea ice thickness may grow suddenly when the snow load gives rise to flooding and leads to snow-ice formation. A potential mechanism to explain the different characteristics of the precipitation bias on snow and sea ice is discussed. The flooding process for landfast sea ice might cause different effect compared to pack ice, thus need to be reconsidered in ICEPACK. Meanwhile, the overestimation in surface wind speed in reanalysis is likely responsible for the underestimation in simulated snow depth, however this had little influence on the modelled ice thickness.


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