scholarly journals Comparison of Passive Microwave Data with Shipborne Photographic Observations of Summer Sea Ice Concentration along an Arctic Cruise Path

2019 ◽  
Vol 11 (17) ◽  
pp. 2009 ◽  
Author(s):  
Qingkai Wang ◽  
Peng Lu ◽  
Yongheng Zu ◽  
Zhijun Li ◽  
Matti Leppäranta ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Moving Average ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Passive Microwave ◽  
Sea Ice Concentration ◽  
Melt Ponds ◽  
Ice Concentration ◽  
Arctic Navigation

Arctic sea ice concentration (SIC) has been studied extensively using passive microwave (PM) remote sensing. This technology could be used to improve navigation along vessel cruise paths; however, investigations on this topic have been limited. In this study, shipborne photographic observation (P-OBS) of sea ice was conducted using oblique-oriented cameras during the Chinese National Arctic Research Expedition in the summer of 2016. SIC and the areal fractions of open water, melt ponds, and sea ice (Aw, Ap, and Ai, respectively) were determined along the cruise path. The distribution of SIC along the cruise path was U-shaped, and open water accounted for a large proportion of the path. The SIC derived from the commonly used PM algorithms was compared with the moving average (MA) P-OBS SIC, including Bootstrap and NASA Team (NT) algorithms based on Special Sensor Microwave Imager/Sounder (SSMIS) data; and ARTIST sea ice, Bootstrap, Sea Ice Climate Change Initiative, and NASA Team 2 (NT2) algorithms based on Advanced Microwave Scanning Radiometer 2 (AMSR2) data. P-OBS performed better than PM remote sensing at detecting low SIC (< 10%). Our results indicate that PM SIC overestimates MA P-OBS SIC at low SIC, but underestimates it when SIC exceeds a turnover point (TP). The presence of melt ponds affected the accuracy of the PM SIC; the PM SIC shifted from an overestimate to an underestimate with increasing Ap, compared with MA P-OBS SIC below the TP, while the underestimation increased above the TP. The PM algorithms were then ranked; SSMIS-NT and AMSR2-NT2 are the best and worst choices for Arctic navigation, respectively.

Unexpectedly high dimethyl sulfide concentration in high-latitude Arctic sea ice melt ponds

2019 ◽  
Vol 21 (10) ◽  
pp. 1642-1649 ◽  
Author(s):  
Keyhong Park ◽  
Intae Kim ◽  
Jung-Ok Choi ◽  
Youngju Lee ◽  
Jinyoung Jung ◽  
...  
Keyword(s):  
Sea Ice ◽  
High Latitude ◽  
Dimethyl Sulfide ◽  
Arctic Sea Ice ◽  
Sulfide Concentration ◽  
Sea Ice Concentration ◽  
Ice Melt ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Ice Concentration

Dimethyl sulfide (DMS) production in the northern Arctic Ocean has been considered to be minimal because of high sea ice concentration and extremely low productivity.

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.

Retrieval of Arctic sea ice freeboard from passive microwave data using deep neural network

2020 ◽  
Author(s):  
Junhwa Chi ◽  
Hyun-Cheol Kim ◽  
Sung Jae Lee
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Arctic Sea Ice ◽  
Passive Microwave ◽  
Retrieval Algorithm ◽  
Sea Ice Concentration ◽  
Ice Volume ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Microwave Sensors

&lt;p&gt;Changes in Arctic sea ice cover represent one of the most visible indicators of climate change. While changes in sea ice extent affect the albedo, changes in sea ice volume explain changes in the heat budget and the exchange of fresh water between ice and the ocean. Global climate simulations predict that Arctic sea ice will exhibit a more significant change in volume than extent. Satellite observations show a long-term negative trend in Arctic sea ice&amp;#160; during all seasons, particularly in summer. Sea ice volume has been estimated by ICESat and CryoSat-2 satellites, and then NASA&amp;#8217;s second-generation spaceborne lidar mission, ICESat-2 has successfully been launched in 2018. &amp;#160;Although these sensors can measure sea ice freeboard precisely, long revisit cycles and narrow swaths are problematic for monitoring of the freeboard in the entire of Arctic ocean effectively. Passive microwave sensors are widely used in retrieval of sea ice concentration. Because of the capability of high temporal resolution and wider swaths, these sensors enable to produce daily sea ice concentration maps over the entire Arctic ocean. Brightness temperatures from passive microwave sensors are often used to estimate sea ice freeboard for first-year ice, but it is difficult to associate with physical characteristics related to sea ice height of multi-year ice. In machine learning community, deep learning has gained attention and notable success in addressing more complicated decision making using multiple hidden layers. In this study, we propose a deep learning based Arctic sea ice freeboard retrieval algorithm incorporating the brightness temperature data from the AMSR2 passive microwave data and sea ice freeboard data from the ICESat-2. The proposed retrieval algorithm enables to estimate daily freeboard for both first- and multi-year ice over the entire Arctic ocean. The estimated freeboard values from the AMSR2 are then quantitatively and qualitatively compared with other sea ice freeboard or thickness products. &amp;#160;&lt;/p&gt;

scholarly journals Assessing the Potential of Enhanced Resolution Gridded Passive Microwave Brightness Temperatures for Retrieval of Sea Ice Parameters

2020 ◽  
Vol 12 (16) ◽  
pp. 2552
Author(s):  
Walter N. Meier ◽  
J. Scott Stewart
Keyword(s):  
Sea Ice ◽  
Correlation Method ◽  
Open Water ◽  
Circulation Pattern ◽  
Time Of Day ◽  
Passive Microwave ◽  
Sea Ice Concentration ◽  
Microwave Brightness Temperature ◽  
Enhanced Resolution ◽  
Ice Concentration

A new enhanced resolution gridded passive microwave brightness temperature (TB) product is used to estimate sea ice concentration and motion. The effective resolution of the TBs is found to be roughly twice that of the standard 25 km resolution, though the gridded resolution of the distributed product is higher. Enhanced resolution sea ice concentrations from the Bootstrap algorithm show more detail in the sea ice, including relatively small open water regions within the ice pack. Sea ice motion estimates from the enhanced resolution TBs using a maximum cross-correlation method show a smoother motion circulation pattern; in comparison to buoys, RMS errors are 15–20% lower than motion estimates from the standard resolution fields and the magnitude of the bias is smaller as well. The enhanced resolution product includes other potentially beneficial characteristics, including twice-daily grids based on local time of day and a complete timeseries of data from nearly all multi-channel passive microwave radiometers since 1978. These enhanced resolution TBs are potential new source for long-term records of sea ice concentration, motion, age, melt, as well as salinity and ocean-atmosphere fluxes.

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 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.

A physical algorithm to measure sea ice concentration from passive microwave remote sensing data

2015 ◽  
Vol 56 (8) ◽  
pp. 1578-1589 ◽  
Author(s):  
V.V. Tikhonov ◽  
I.A. Repina ◽  
M.D. Raev ◽  
E.A. Sharkov ◽  
V.V. Ivanov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Sea Ice Concentration ◽  
Passive Microwave Remote Sensing ◽  
Sensing Data ◽  
Ice Concentration
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