scholarly journals A new tracking algorithm for sea ice age distribution estimation

2018 ◽  
Vol 12 (6) ◽  
pp. 2073-2085 ◽  
Author(s):  
Anton Andreevich Korosov ◽  
Pierre Rampal ◽  
Leif Toudal Pedersen ◽  
Roberto Saldo ◽  
Yufang Ye ◽  
...  
Keyword(s):  
Sea Ice ◽  
Age Distribution ◽  
Weighted Average ◽  
Ice Age ◽  
Sea Ice Concentration ◽  
Advection Scheme ◽  
Statistical Measures ◽  
Ice Drift ◽  
Ice Concentration ◽  
Sea Ice Drift

Abstract. A new algorithm for estimating sea ice age (SIA) distribution based on the Eulerian advection scheme is presented. The advection scheme accounts for the observed divergence or convergence and freezing or melting of sea ice and predicts consequent generation or loss of new ice. The algorithm uses daily gridded sea ice drift and sea ice concentration products from the Ocean and Sea Ice Satellite Application Facility. The major advantage of the new algorithm is the ability to generate individual ice age fractions in each pixel of the output product or, in other words, to provide a frequency distribution of the ice age allowing to apply mean, median, weighted average or other statistical measures. Comparison with the National Snow and Ice Data Center SIA product revealed several improvements of the new SIA maps and time series. First, the application of the Eulerian scheme provides smooth distribution of the ice age parameters and prevents product undersampling which may occur when a Lagrangian tracking approach is used. Second, utilization of the new sea ice drift product void of artifacts from EUMETSAT OSI SAF resulted in more accurate and reliable spatial distribution of ice age fractions. Third, constraining SIA computations by the observed sea ice concentration expectedly led to considerable reduction of multi-year ice (MYI) fractions. MYI concentration is computed as a sum of all MYI fractions and compares well to the MYI products based on passive and active microwave and SAR products.

scholarly journals A new tracking algorithm for sea ice age distribution estimation

2017 ◽  
Author(s):  
Anton Andreevich Korosov ◽  
Pierre Rampal ◽  
Leif Toudal Pedersen ◽  
Roberto Saldo ◽  
Yufang Ye ◽  
...  
Keyword(s):  
Sea Ice ◽  
Age Distribution ◽  
Weighted Average ◽  
Grid Cell ◽  
Ice Age ◽  
Sea Ice Concentration ◽  
Advection Scheme ◽  
Statistical Measures ◽  
Ice Drift ◽  
Ice Concentration

Abstract. A new algorithm for estimating sea ice age (SIA) distribution based on the Eulerian advection scheme is presented. The advection scheme accounts for the observed divergence/convergence and freezing/melting of sea ice and predicts consequent generation/loss of new ice. The algorithm uses daily gridded sea ice drift and sea ice concentration products from the Ocean and Sea Ice Satellite Application Facility and produces gridded fractions of sea ice of a specific age. Thus, each grid cell of the output product contains a frequency distribution of sea ice age allowing to apply mean, median, weighted average or other statistical measures. The produced SIA maps and time series are compared to the National Snow and Ice Data Center SIA product. Several improvements related to the usage of the new ice drift product, constraining the algorithm by the observed ice concentration and preventing undersampling by the Eulerian scheme are demonstrated. Muliyear ice (MYI) concentration is computed as a sum of all multi-year ice fractions and compared to the MYI products based on passive and active microwave and SAR products.

scholarly journals Improving Multiyear Sea Ice Concentration Estimates with Sea Ice Drift

2016 ◽  
Vol 8 (5) ◽  
pp. 397 ◽  
Author(s):  
Yufang Ye ◽  
Mohammed Shokr ◽  
Georg Heygster ◽  
Gunnar Spreen
Keyword(s):  
Sea Ice ◽  
Sea Ice Concentration ◽  
Ice Drift ◽  
Ice Concentration ◽  
Sea Ice Drift

scholarly journals Simulated impacts of relative climate change and river discharge regulation on sea ice and oceanographic conditions in the Hudson Bay Complex

Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jennifer V. Lukovich ◽  
Shabnam Jafarikhasragh ◽  
Paul G. Myers ◽  
Natasha A. Ridenour ◽  
Laura Castro de la Guardia ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
River Discharge ◽  
Hudson Bay ◽  
Sea Ice Concentration ◽  
Changing Climate ◽  
Ice Drift ◽  
Ice Concentration ◽  
Sea Ice Drift ◽  
Discharge Regulation

In this analysis, we examine relative contributions from climate change and river discharge regulation to changes in marine conditions in the Hudson Bay Complex using a subset of five atmospheric forcing scenarios from the Coupled Model Intercomparison Project Phase 5 (CMIP5), river discharge data from the Hydrological Predictions for the Environment (HYPE) model, both naturalized (without anthropogenic intervention) and regulated (anthropogenically controlled through diversions, dams, reservoirs), and output from the Nucleus for European Modeling of the Ocean Ice-Ocean model for the 1981–2070 time frame. Investigated in particular are spatiotemporal changes in sea surface temperature, sea ice concentration and thickness, and zonal and meridional sea ice drift in response to (i) climate change through comparison of historical (1981–2010) and future (2021–2050 and 2041–2070) simulations, (ii) regulation through comparison of historical (1981–2010) naturalized and regulated simulations, and (iii) climate change and regulation combined through comparison of future (2021–2050 and 2041–2070) naturalized and regulated simulations. Also investigated is use of the diagnostic known as e-folding time spatial distribution to monitor changes in persistence in these variables in response to changing climate and regulation impacts in the Hudson Bay Complex. Results from this analysis highlight bay-wide and regional reductions in sea ice concentration and thickness in southwest and northeast Hudson Bay in response to a changing climate, and east-west asymmetry in sea ice drift response in support of past studies. Regulation is also shown to amplify or suppress the climate change signal. Specifically, regulation amplifies sea surface temperatures from April to August, suppresses sea ice loss by approximately 30% in March, contributes to enhanced sea ice drift speed by approximately 30%, and reduces meridional circulation by approximately 20% in January due to enhanced zonal drift. Results further suggest that the offshore impacts of regulation are amplified in a changing climate.

scholarly journals Assimilation of sea surface temperature, sea ice concentration and sea ice drift in a model of the Southern Ocean

2015 ◽  
Vol 93 ◽  
pp. 22-39 ◽  
Author(s):  
Alexander Barth ◽  
Martin Canter ◽  
Bert Van Schaeybroeck ◽  
Stéphane Vannitsem ◽  
François Massonnet ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Sea Ice Concentration ◽  
Ice Drift ◽  
Ice Concentration ◽  
Sea Ice Drift

scholarly journals An analytical model for wind-driven Arctic summer sea ice drift

2015 ◽  
Vol 9 (2) ◽  
pp. 2101-2133
Author(s):  
H.-S. Park ◽  
A. L. Stewart
Keyword(s):  
Sea Ice ◽  
Analytical Model ◽  
Arctic Sea Ice ◽  
Sea Ice Concentration ◽  
Ice Drift ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Sea Ice Drift ◽  
Ice Velocity ◽  
Arctic Summer

Abstract. The authors present an approximate analytical model for wind-induced sea-ice drift that includes an ice–ocean boundary layer with an Ekman spiral in the ocean velocity. This model provides an analytically tractable solution that is most applicable to the marginal ice zone, where sea-ice concentration is substantially below 100%. The model closely reproduces the ice and upper-ocean velocities observed recently by the first ice-tethered profiler equipped with a velocity sensor (ITPV). The analytical tractability of our model allows efficient calculation of the sea-ice velocity provided that the surface wind field is known and that the ocean surface geostrophic velocity is relatively weak. The model is applied to estimate intraseasonal variations in Arctic sea ice cover due to short-timescale (around 1 week) intensification of the southerly winds. Utilizing 10 m surface winds from ERA-Interim reanalysis, the wind-induced sea-ice velocity and the associated changes in sea-ice concentration are calculated and compared with satellite observations. The analytical model captures the observed reduction of Arctic sea-ice concentration associated with the strengthening of southerlies on intraseasonal time scales. Further analysis indicates that the wind-induced surface Ekman flow in the ocean increases the sea-ice drift speed by 50% in the Arctic summer. It is proposed that the southerly wind-induced sea-ice drift, enhanced by the ocean's surface Ekman transport, can lead to substantial reduction in sea-ice concentration over a timescale of one week.

scholarly journals SITool (v1.0) – a new evaluation tool for large-scale sea ice simulations: application to CMIP6 OMIP

2021 ◽  
Author(s):  
Xia Lin ◽  
François Massonnet ◽  
Thierry Fichefet ◽  
Martin Vancoppenolle
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Ice Thickness ◽  
Evaluation Tool ◽  
Sea Ice Concentration ◽  
Ice Drift ◽  
Ice Concentration ◽  
Edge Location ◽  
Intercomparison Project ◽  
The Mean

Abstract. The Sea Ice Evaluation Tool (SITool) described in this paper is a performance metrics and diagnostics tool developed to evaluate the skill of bi-polar model reconstructions of sea ice concentration, extent, edge location, drift, thickness, and snow depth. It is a Python-based software and consists of well-documented functions used to derive various sea ice metrics and diagnostics. Here, the SITool version 1.0 (v1.0) is introduced and documented, and is then used to evaluate the performance of global sea ice reconstructions from nine models that provided sea ice output under the experimental protocols of the Coupled Model Intercomparison Project 6 (CMIP6) Ocean Model Intercomparison Project with two different atmospheric forcing datasets: the Coordinated Ocean-ice Reference Experiments version 2 (CORE-II) and the updated Japanese 55-year atmospheric reanalysis (JRA55-do). Two sets of observational references for sea ice concentration, thickness, snow depth, and ice drift are systematically used to reflect the impact of observational uncertainty on model performance. Based on available model outputs and observational references, the ice concentration, extent, and edge location during 1980–2007, as well as the ice thickness, snow depth, and ice drift during 2003–2007 are evaluated. It is found that (1) in general, model biases are larger than observational uncertainties and model performances are primarily consistent compared to different observational references, (2) By changing the atmospheric forcing from CORE-II to JRA55-do reanalysis data, the overall performance (mean state, interannual variability and trend) of the simulated sea ice areal properties in both hemispheres, as well as the mean ice thickness simulation in the Antarctic, the mean snow depth and ice drift simulations in both hemispheres are improved, (3) the simulated sea ice areal properties are also improved in the model with increased spatial resolution, (4) for the cross-metric analysis, there is no link between the performance in one variable and the performance in another. The SITool is an open-access version-controlled software that can run on a wide range of CMIP6 compliant sea ice outputs. The current version of SITool (v1.0) is primarily developed to evaluate atmosphere-forced simulations and it could be eventually extended to fully coupled models.

scholarly journals Abrupt transitions in Arctic open water area

2016 ◽  
Author(s):  
Michael A. Goldstein ◽  
Amanda H. Lynch ◽  
Todd E. Arbetter ◽  
Florence Fetterer
Keyword(s):  
Sea Ice ◽  
Structural Breaks ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Ice Age ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Atlantic Sector ◽  
Water Fraction ◽  
Ice Concentration

Abstract. September open water fraction in the Arctic is analyzed using the satellite era record of ice concentration (1979–2014). This analysis suggests that there is a statistically significant breakpoint (shift in the mean) and increase in the variance around 1988 and another breakpoint around 2007 in the Pacific sector. These structural breaks are robust to the choice of algorithm used for deriving sea ice concentration from satellite data, and are also apparent in other measures of open water, such as operational ice charts and the record of navigable days from Barrow to Prudhoe Bay. Breakpoints in the Atlantic sector record of open water are evident in 1988 and 2007 but more weakly significant. The breakpoints appear to be associated with concomitant shifts in average ice age, and tend to lead change in Arctic circulation regimes. These results support the thesis that Arctic sea ice may have critical points beyond which a return to the previous state is less likely.

scholarly journals SITool (v1.0) – a new evaluation tool for large-scale sea ice simulations: application to CMIP6 OMIP

2021 ◽  
Vol 14 (10) ◽  
pp. 6331-6354
Author(s):  
Xia Lin ◽  
François Massonnet ◽  
Thierry Fichefet ◽  
Martin Vancoppenolle
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Model Performance ◽  
Evaluation Tool ◽  
Sea Ice Concentration ◽  
Ice Drift ◽  
Ice Concentration ◽  
Edge Location ◽  
Intercomparison Project ◽  
The Mean

Abstract. The Sea Ice Evaluation Tool (SITool) described in this paper is a performance metrics and diagnostics tool developed to evaluate the skill of Arctic and Antarctic model reconstructions of sea ice concentration, extent, edge location, drift, thickness, and snow depth. It is a Python-based software and consists of well-documented functions used to derive various sea ice metrics and diagnostics. Here, SITool version 1.0 (v1.0) is introduced and documented, and is then used to evaluate the performance of global sea ice reconstructions from nine models that provided sea ice output under the experimental protocols of the Coupled Model Intercomparison Project phase 6 (CMIP6) Ocean Model Intercomparison Project with two different atmospheric forcing datasets: the Coordinated Ocean-ice Reference Experiments version 2 (CORE-II) and the updated Japanese 55-year atmospheric reanalysis (JRA55-do). Two sets of observational references for the sea ice concentration, thickness, snow depth, and ice drift are systematically used to reflect the impact of observational uncertainty on model performance. Based on available model outputs and observational references, the ice concentration, extent, and edge location during 1980–2007, as well as the ice thickness, snow depth, and ice drift during 2003–2007 are evaluated. In general, model biases are larger than observational uncertainties, and model performance is primarily consistent compared to different observational references. By changing the atmospheric forcing from CORE-II to JRA55-do reanalysis data, the overall performance (mean state, interannual variability, and trend) of the simulated sea ice areal properties in both hemispheres, as well as the mean ice thickness simulation in the Antarctic, the mean snow depth, and ice drift simulations in both hemispheres are improved. The simulated sea ice areal properties are also improved in the model with higher spatial resolution. For the cross-metric analysis, there is no link between the performance in one variable and the performance in another. SITool is an open-access version-controlled software that can run on a wide range of CMIP6-compliant sea ice outputs. The current version of SITool (v1.0) is primarily developed to evaluate atmosphere-forced simulations and it could be eventually extended to fully coupled models.

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