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

2016 ◽  
Vol 10 (1) ◽  
pp. 227-244 ◽  
Author(s):  
H.-S. Park ◽  
A. L. Stewart
Keyword(s):  
Sea Ice ◽  
Analytical Model ◽  
Surface Wind ◽  
Open Water ◽  
Sea Ice Concentration ◽  
Efficient Calculation ◽  
Sea Ice Drift ◽  
Wind Input ◽  
Ice Floes ◽  
Arctic Summer

Abstract. The authors present an analytical model for wind-driven free drift of sea ice that allows for an arbitrary mixture of ice and open water. The model includes an ice–ocean boundary layer with an Ekman spiral, forced by transfers of wind-input momentum both through the sea ice and directly into the open water between the ice floes. The analytical tractability of this model allows efficient calculation of the ice velocity provided that the surface wind field is known and that the ocean geostrophic velocity is relatively weak. The model predicts that variations in the ice thickness or concentration should substantially modify the rotation of the velocity between the 10 m winds, the sea ice, and the ocean. Compared to recent observational data from the first ice-tethered profiler with a velocity sensor (ITP-V), the model is able to capture the dependencies of the ice speed and the wind/ice/ocean turning angles on the wind speed. The model is used to derive responses to intensified southerlies on Arctic summer sea ice concentration, and the results are shown to compare closely with satellite observations.

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 The impact of melt ponds on summertime microwave brightness temperatures and sea-ice concentrations

2016 ◽  
Vol 10 (5) ◽  
pp. 2217-2239 ◽  
Author(s):  
Stefan Kern ◽  
Anja Rösel ◽  
Leif Toudal Pedersen ◽  
Natalia Ivanova ◽  
Roberto Saldo ◽  
...  
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
Sea Ice Concentration ◽  
Melt Pond ◽  
Surface Fraction ◽  
Brightness Temperatures ◽  
Ice Surface ◽  
Melt Ponds ◽  
Ice Concentration ◽  
Ice Floes

Abstract. Sea-ice concentrations derived from satellite microwave brightness temperatures are less accurate during summer. In the Arctic Ocean the lack of accuracy is primarily caused by melt ponds, but also by changes in the properties of snow and the sea-ice surface itself. We investigate the sensitivity of eight sea-ice concentration retrieval algorithms to melt ponds by comparing sea-ice concentration with the melt-pond fraction. We derive gridded daily sea-ice concentrations from microwave brightness temperatures of summer 2009. We derive the daily fraction of melt ponds, open water between ice floes, and the ice-surface fraction from contemporary Moderate Resolution Spectroradiometer (MODIS) reflectance data. We only use grid cells where the MODIS sea-ice concentration, which is the melt-pond fraction plus the ice-surface fraction, exceeds 90 %. For one group of algorithms, e.g., Bristol and Comiso bootstrap frequency mode (Bootstrap_f), sea-ice concentrations are linearly related to the MODIS melt-pond fraction quite clearly after June. For other algorithms, e.g., Near90GHz and Comiso bootstrap polarization mode (Bootstrap_p), this relationship is weaker and develops later in summer. We attribute the variation of the sensitivity to the melt-pond fraction across the algorithms to a different sensitivity of the brightness temperatures to snow-property variations. We find an underestimation of the sea-ice concentration by between 14 % (Bootstrap_f) and 26 % (Bootstrap_p) for 100 % sea ice with a melt-pond fraction of 40 %. The underestimation reduces to 0 % for a melt-pond fraction of 20 %. In presence of real open water between ice floes, the sea-ice concentration is overestimated by between 26 % (Bootstrap_f) and 14 % (Bootstrap_p) at 60 % sea-ice concentration and by 20 % across all algorithms at 80 % sea-ice concentration. None of the algorithms investigated performs best based on our investigation of data from summer 2009. We suggest that those algorithms which are more sensitive to melt ponds could be optimized more easily because the influence of unknown snow and sea-ice surface property variations is less pronounced.

scholarly journals Arctic sea ice sensitivity to lateral melting representation in a coupled climate model

2021 ◽  
Author(s):  
Madison Smith ◽  
Marika Holland ◽  
Bonnie Light
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Coupled Climate Model ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Ice Floes

Abstract. The melting of sea ice floes from the edges (lateral melting) results in open water formation and subsequently increases absorption of solar shortwave energy. However, lateral melt plays a small role in the sea ice mass budget in both hemispheres in most climate models (Keen et al., 2020). This is likely influenced by simple parameterizations of this process in sea ice models that are constrained by limited observations. Here we use a coupled climate model (CESM2.0) to assess the sensitivity of modeled sea ice state to the lateral melt parameterization. The results show that sea ice is sensitive both to the parameters determining the effective lateral melt rate, as well as the nuances in how lateral melting is applied to the ice pack. Increasing the lateral melt rate within the range of reasonable values is largely compensated by decreases in the basal melt rate, but can still result in a significant decrease in sea ice concentration and thickness, particularly in the marginal ice zone. We suggest that it is important to consider the efficiency of melt processes at forming open water, which drives the majority of the ice-albedo feedback. Melt processes are more efficient at forming open water in thinner ice scenarios (as we are likely to see in the future), suggesting the importance of well representing thermodynamic evolution. Revisiting model parameterizations of lateral melting with observations will require finding new ways to represent important physical processes.

scholarly journals Retrieval of Summer Sea Ice Concentration in the Pacific Arctic Ocean from AMSR2 Observations and Numerical Weather Data Using Random Forest Regression

2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Effects ◽  
Sea Ice Concentration ◽  
Air Temperatures ◽  
The Pacific ◽  
Ice Concentration

The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change and important information for the development of a more economically valuable Northern Sea Route. Passive microwave (PM) sensors have provided information on the SIC since the 1970s by observing the brightness temperature (TB) of sea ice and open water. However, the SIC in the Arctic estimated by operational algorithms for PM observations is very inaccurate in summer because the TB values of sea ice and open water become similar due to atmospheric effects. In this study, we developed a summer SIC retrieval model for the Pacific Arctic Ocean using Advanced Microwave Scanning Radiometer 2 (AMSR2) observations and European Reanalysis Agency-5 (ERA-5) reanalysis fields based on Random Forest (RF) regression. SIC values computed from the ice/water maps generated from the Korean Multi-purpose Satellite-5 synthetic aperture radar images from July to September in 2015–2017 were used as a reference dataset. A total of 24 features including the TB values of AMSR2 channels, the ratios of TB values (the polarization ratio and the spectral gradient ratio (GR)), total columnar water vapor (TCWV), wind speed, air temperature at 2 m and 925 hPa, and the 30-day average of the air temperatures from the ERA-5 were used as the input variables for the RF model. The RF model showed greatly superior performance in retrieving summer SIC values in the Pacific Arctic Ocean to the Bootstrap (BT) and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithms under various atmospheric conditions. The root mean square error (RMSE) of the RF SIC values was 7.89% compared to the reference SIC values. The BT and ASI SIC values had three times greater values of RMSE (20.19% and 21.39%, respectively) than the RF SIC values. The air temperatures at 2 m and 925 hPa and their 30-day averages, which indicate the ice surface melting conditions, as well as the GR using the vertically polarized channels at 23 GHz and 18 GHz (GR(23V18V)), TCWV, and GR(36V18V), which accounts for atmospheric water content, were identified as the variables that contributed greatly to the RF model. These important variables allowed the RF model to retrieve unbiased and accurate SIC values by taking into account the changes in TB values of sea ice and open water caused by atmospheric effects.

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 Airborne observations and simulations of three-dimensional radiative interactions between Arctic boundary layer clouds and ice floes

2015 ◽  
Vol 15 (14) ◽  
pp. 8147-8163 ◽  
Author(s):  
M. Schäfer ◽  
E. Bierwirth ◽  
A. Ehrlich ◽  
E. Jäkel ◽  
M. Wendisch
Keyword(s):  
Boundary Layer ◽  
Radiative Transfer ◽  
Sea Ice ◽  
Three Dimensional ◽  
Open Water ◽  
Radiative Effects ◽  
Arctic Boundary Layer ◽  
Boundary Layer Clouds ◽  
Ice Edge ◽  
Ice Floes

Abstract. Based on airborne spectral imaging observations, three-dimensional (3-D) radiative effects between Arctic boundary layer clouds and highly variable Arctic surfaces were identified and quantified. A method is presented to discriminate between sea ice and open water under cloudy conditions based on airborne nadir reflectivity γλ measurements in the visible spectral range. In cloudy cases the transition of γλ from open water to sea ice is not instantaneous but horizontally smoothed. In general, clouds reduce γλ above bright surfaces in the vicinity of open water, while γλ above open sea is enhanced. With the help of observations and 3-D radiative transfer simulations, this effect was quantified to range between 0 and 2200 m distance to the sea ice edge (for a dark-ocean albedo of αwater = 0.042 and a sea-ice albedo of αice = 0.91 at 645 nm wavelength). The affected distance Δ L was found to depend on both cloud and sea ice properties. For a low-level cloud at 0–200 m altitude, as observed during the Arctic field campaign VERtical Distribution of Ice in Arctic clouds (VERDI) in 2012, an increase in the cloud optical thickness τ from 1 to 10 leads to a decrease in Δ L from 600 to 250 m. An increase in the cloud base altitude or cloud geometrical thickness results in an increase in Δ L; for τ = 1/10 Δ L = 2200 m/1250 m in case of a cloud at 500–1000 m altitude. To quantify the effect for different shapes and sizes of ice floes, radiative transfer simulations were performed with various albedo fields (infinitely long straight ice edge, circular ice floes, squares, realistic ice floe field). The simulations show that Δ L increases with increasing radius of the ice floe and reaches maximum values for ice floes with radii larger than 6 km (500–1000 m cloud altitude), which matches the results found for an infinitely long, straight ice edge. Furthermore, the influence of these 3-D radiative effects on the retrieved cloud optical properties was investigated. The enhanced brightness of a dark pixel next to an ice edge results in uncertainties of up to 90 and 30 % in retrievals of τ and effective radius reff, respectively. With the help of Δ L, an estimate of the distance to the ice edge is given, where the retrieval uncertainties due to 3-D radiative effects are negligible.

scholarly journals Satellite-observed sea ice area flux through Baffin Bay: 1988–2015

2018 ◽  
Author(s):  
Haibo Bi ◽  
Yunhe Wang ◽  
Xiuli Xu ◽  
Yu Liang ◽  
Jue Huang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Vital Role ◽  
Positive Trend ◽  
Sea Ice Concentration ◽  
Baffin Bay ◽  
The North ◽  
Time Period ◽  
Sea Ice Drift ◽  
The North Atlantic Oscillation ◽  
Increasing Trends

Abstract. Sea ice export through Baffin Bay plays a vital role in modulating the meridional overturning process in the downstream Labrador Sea. In this study, satellite-derived sea ice products are explored to obtain the sea ice flux (SIF) through three passages (referred to as A, B, and C for the north, middle, and south passages, respectively) of Baffin Bay. Over the period 1988–2015, the average annual (October–September) sea ice area export is 555 × 103 km2, 642 × 103 km2, and 551 × 103 km2 through passages A, B, and C, respectively. These amounts are less than that observed through the Fram Strait (FS, 707 × 103 km2). Clear increasing trends in annual sea ice export on the order of 53.1 × 103 km2/de and 43.2 × 103 km2/de are identified at passages A and B, respectively. The trend at the south passage (C), however, is slightly negative (−13.3 × 103 km2/de). The positive trends in annual SIF at A and B are primarily attributable to the increase during winter months, which is triggered by the accelerated sea ice motion (SIM) and partly compensated by the reduced sea ice concentration (SIC). During the summer months, the sea ice export through each Baffin Bay passage usually presents a negative trend, primarily because of the decline in SIM and it is further enhanced by a dramatic decrease in SIC. A significant positive trend in the net SIF (i.e. net ice inflow) is found for between the passages A (or B) and C at 54.5 (or 64.2) × 103 km2/de. Therefore, Baffin Bay may have presented a greater convergence of ice. Overall, the connection between Baffin Bay sea ice export and the North Atlantic Oscillation (NAO) is tenuous, although the correlation is sensitive to variations in the selected time period. In contrast, the association with the cross-gate sea level pressure difference (SLPD) is robust in Baffin Bay (R = 0.69–0.71 depending on the passages), but relatively weaker compared with that in the FS (R = 0.74). Baffin Bay is bounded by Baffin Island to the west and Greenland to the east, thus, sea ice drift is not converted to the free state observed in the FS.

scholarly journals Tropical Pacific SST Drivers of Recent Antarctic Sea Ice Trends

2016 ◽  
Vol 29 (24) ◽  
pp. 8931-8948 ◽  
Author(s):  
Ariaan Purich ◽  
Matthew H. England ◽  
Wenju Cai ◽  
Yoshimitsu Chikamoto ◽  
Axel Timmermann ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Ross Sea ◽  
Surface Wind ◽  
Tropical Pacific ◽  
Sea Ice Concentration ◽  
Amundsen Sea ◽  
Model Simulations ◽  
Antarctic Sea Ice

Abstract A strengthening of the Amundsen Sea low from 1979 to 2013 has been shown to largely explain the observed increase in Antarctic sea ice concentration in the eastern Ross Sea and decrease in the Bellingshausen Sea. Here it is shown that while these changes are not generally seen in freely running coupled climate model simulations, they are reproduced in simulations of two independent coupled climate models: one constrained by observed sea surface temperature anomalies in the tropical Pacific and the other by observed surface wind stress in the tropics. This analysis confirms previous results and strengthens the conclusion that the phase change in the interdecadal Pacific oscillation from positive to negative over 1979–2013 contributed to the observed strengthening of the Amundsen Sea low and the associated pattern of Antarctic sea ice change during this period. New support for this conclusion is provided by simulated trends in spatial patterns of sea ice concentrations that are similar to those observed. These results highlight the importance of accounting for teleconnections from low to high latitudes in both model simulations and observations of Antarctic sea ice variability and change.

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