scholarly journals A model for the Artic mixed layer circulation under a melted lead: Implications on the near-surface temperature maximum formation

2020 ◽  
Author(s):  
Alberto Alvarez
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Mixed Layer ◽  
Circulation Pattern ◽  
Acoustic Properties ◽  
The Arctic ◽  
Near Surface ◽  
Ice Surface ◽  
Storage Rate ◽  
Surface Convection

Abstract. Leads in the sea ice pack have been extensively studied due to their climate relevance. An intense heat exchange between the ocean and the atmosphere occurs at leads in winter. As a result, a major salt input to the Arctic mixed layer is generated at these locations by brine rejection. Leads also constitute preferential melting locations in the early melting season, but their oceanography and climate relevance, if any, still remain unexplored during this period of the year. This study investigates the oceanographic circulation under a melted lead, resulting from the combined effect of the lead geometry, solar radiation and sea ice melting. Results derived from an idealized framework, suggest the daily generation of near surface convection cells that extend from the lead sides to the lead center. Convection cells disappear when melting is diminished during the period of minimum solar insolation. The cyclical generation and evolution of convection cells with the solar cycle, impacts the heat storage rate in the mixed layer below the lead. The contribution of this circulation pattern to the generation of the Near Surface Temperature Maximum (NSTM), is discussed in terms of its capability to inject warm surface waters below the open and sea ice surface. It has been suggested that the NSTM probably affects the oceanographic structure and acoustic properties of the upper ocean and the overlying ice cover.

scholarly journals Numerical investigation of the Arctic ice-ocean boundary layer; implications for air-sea gas fluxes

2016 ◽  
Author(s):  
A. Bigdeli ◽  
B. Loose ◽  
S. T. Cole
Keyword(s):  
Sea Ice ◽  
Water Column ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
The Arctic ◽  
Layer Depth ◽  
Near Surface ◽  
Resolution Model ◽  
Simplifying Assumptions ◽  
Vertical Spacing

Abstract. In ice-covered regions it can be challenging to determine air-sea exchange – for heat and momentum, but also for gases like carbon dioxide and methane. The harsh environment and relative data scarcity make it difficult to characterize even the physical properties of the ocean surface. Here, we seek a mechanistic interpretation for the rate of air-sea gas exchange (k) derived from radon-deficits. These require an estimate of the water column history extending 30 days prior to sampling. We used coarse resolution (36 km) regional configuration of the MITgcm with fine near surface vertical spacing (2 m) to evaluate the capability of the model to reproduce conditions prior to sampling. The model is used to estimate sea-ice velocity, concentration and mixed-layer depth experienced by the water column. We then compared the model results to existing field data including satellite, moorings and Ice-tethered profilers. We found that model-derived sea-ice coverage is 88 to 98 % accurate averaged over Beaufort Gyre, sea-ice velocities have 78 % correlation which resulted in 2 km/day error in 30 day trajectory of sea-ice. The model demonstrated the capacity to capture the broad trends in the mixed layer although with a bias and model water velocities showed only 29 % correlation with actual data. Overall, we find the course resolution model to be an inadequate surrogate for sparse data, however the simulation results are a slight improvement over several of the simplifying assumptions that are often made when surface ocean geochemistry, including the use of a constant mixed layer depth and a velocity profile that is purely wind-driven.

scholarly journals Satellite-observed variability and trend in sea-ice extent, surface temperature, albedo and clouds in the Arctic

2001 ◽  
Vol 33 ◽  
pp. 457-473 ◽  
Author(s):  
Josefino C. Comiso
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Ice Cover ◽  
Warming Trend ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
North American Continent ◽  
The North ◽  
Ice Surface

AbstractRecent observations of a decreasing ice extent and a possible thinning of the ice cover in the Arctic make it imperative that detailed studies of the current Arctic environment are made, especially since the region is known to be highly sensitive to a potential change in climate. A continuous dataset of microwave, thermal infrared and visible satellite data has been analyzed for the first time to concurrently study in spatial detail the variability of the sea-ice cover, surface temperature, albedo and cloud statistics in the region from 1987 to 1998. Large warming anomalies during the last four years (i.e. 1995−98) are indeed apparent and spatially more extensive than previous years. The largest surface temperature anomaly occurred in 1998, but this was confined mainly to the western Arctic and the North American continent, while cooling occurred in other areas. The albedo anomalies show good coherence with the sea-ice concentration anomalies except in the central region, where periodic changes in albedo are observed, indicative of interannual changes in duration and areal extent of melt ponding and snow-free ice cover. The cloud-cover anomalies are more difficult to interpret, but are shown to be well correlated with the expected warming effects of clouds on the sea-ice surface. The results from trend analyses of the data are consistent with a general warming trend and an ice-cover retreat that appear to be even larger during the last dozen years than those previously reported.

scholarly journals Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

2012 ◽  
Vol 9 (2) ◽  
pp. 1009-1043 ◽  
Author(s):  
G. Dybkjær ◽  
R. Tonboe ◽  
J. Høyer
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Temperature Data ◽  
Coupled Systems ◽  
The Arctic ◽  
In Situ Observation ◽  
Clear Sky ◽  
Ice Surface ◽  
Ice Surface Temperature

Abstract. The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions are prevailing during spring in the Arctic while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveal that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measures complicates the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

scholarly journals Radiometrie measurements of sea-ice surface temperature in East Antarctica

1998 ◽  
Vol 27 ◽  
pp. 466-470
Author(s):  
Kelvin J. Michael ◽  
Clemente S. Hungria ◽  
R. A. Massom
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Snow Cover ◽  
Open Water ◽  
Thermal Infrared ◽  
Near Surface ◽  
Video Footage ◽  
Antarctic Sea Ice ◽  
Ice Surface ◽  
Ice Conditions

This paper presents surface temperature data collected over East Antarctic sea ice by two thermal infrared radiometers mounted on the RSV Aurora Australis in March-May 1993. Operating at wavelengths equivalent to those utilised by channels 4 and 5 of AVHRR and similar channels of ATSR, the radiometers provided high-reso-lution data on surface (skin) temperature along the ship track. Additional information on the sea-ice conditions was obtained from hourly observations made from The ship's bridge, video footage and direct measurements made at ice stations. Following calibration, time series of temperatures from each of the radiometers were compared wi th ice-surface and near-surface air temperatures. Observed changes in the surface temperature are related to different snow and ice conditions. For a given air temperature, the surface temperature depends upon the thickness of ice and its snow cover. While open water areas (leads) have temperatures near -2.0°C, thick ice is characterised by surface temperatures which approximate those of the air. Taken as a whole, the along-track profile of surface temperature provides a proxy estimate of The proportion of open water and thin ice with in the pack. The presence of a snow cover has a significant effect on the surface temperature. It is anticipated that the results will be of use in the validation of sea-ice models and satellite thermal infrared data.

scholarly journals Comparison of Leads Mapping in the Arctic Ocean Between Landsat and MODIS Ice Surface Temperature Products

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Xiaoping Pang ◽  
Pei Fan ◽  
Xi Zhao ◽  
Qing Ji
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Single Channel ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Landsat 8 ◽  
Ice Surface ◽  
Arctic Sea ◽  
Split Window Algorithm ◽  
Ice Surface Temperature

<p><strong>Abstract.</strong> Leads are linear or wedge-shaped openings in the sea ice cover. They account for about half of the sensible heat transfer from the Arctic Ocean to the atmosphere in winter, though the sea surface area covered by them is only 1%~2% of the total sea ice area, thus monitoring leads changes and mapping leads distributions become an essential role on Arctic researches. Sea ice surface temperature (IST) product from Moderate Resolution Imaging Spectroradiometer (MODIS) is the most used source of leads monitoring and mapping, however, due to the coarse spatial resolution (1km at swath level), it suffers from mixed pixel effect when describes the temperature variations on thin leads (10m~100m), thus an IST product with a finer spatial resolution is needed. Though several surface temperature retrieval algorithms had been introduced based on Landsat 8 thermal imagery, none of them were validated in Arctic sea ice region. Given that the special weather conditions such as air temperature inversion were not taken into consideration, these algorithms may not always suitable for IST acquisition in Arctic. In this paper, we applied five mainstream IST algorithms (three split window algorithms and two single channel methods) on Arctic sea ice, compared the Landsat 8 IST with corresponding MODIS IST product, and validated all the satellite ISTs by in situ temperature measurements from drifting buoys. Compared to the buoy ISTs, the single channel method through web-based atmosphere correction tool provided by Barsi et al. (2003) offers the best accuracy. The split window algorithm proposed by Du et al. (2015) ranks the second, but constrained by the banding effect due to the stripe noise. Split window algorithm introduced by Jiménez-Muñoz et al. (2014) coincides with MODIS IST product best. All of the three methods mentioned above have slightly better accuracy than MODIS IST, particular in thin leads areas, which indicated that Landsat based leads map will provide us a better insight of Arctic sea ice. All the satellite ISTs tend to underestimate the surface temperature than those measured by buoys.</p>

scholarly journals Impacts of Arctic Sea Ice on Cold Season Atmospheric Variability and Trends Estimated from Observations and a Multi-model Large Ensemble

2021 ◽  
pp. 1-64
Author(s):  
Yu-Chiao Liang ◽  
Claude Frankignoul ◽  
Young-Oh Kwon ◽  
Guillaume Gastineau ◽  
Elisa Manzini ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
General Circulation ◽  
Cold Season ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Variability ◽  
Large Ensemble ◽  
Near Surface ◽  
Arctic Sea

AbstractTo examine the atmospheric responses to Arctic sea-ice variability in the Northern Hemisphere cold season (October to following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily-varying sea-ice, sea-surface temperature, and radiative forcings prescribed during the 1979-2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multi-model ensemble mean (MMEM) shows decreasing sea-level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea-ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drives a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual co-variability between sea-ice extent in the Barents-Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the co-variability in MMEMs. The interannual sea-ice decline followed by a negative North Atlantic Oscillation-like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea-ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship.

The MODIS ice surface temperature product as an indicator of sea ice minimum over the Arctic Ocean

2014 ◽  
Vol 152 ◽  
pp. 99-108 ◽  
Author(s):  
Daehyun Kang ◽  
Jungho Im ◽  
Myong-In Lee ◽  
Lindi J. Quackenbush
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Arctic Ocean ◽  
The Arctic ◽  
Ice Surface ◽  
The Arctic Ocean ◽  
Ice Surface Temperature

scholarly journals Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

Ocean Science ◽  
2012 ◽  
Vol 8 (6) ◽  
pp. 959-970 ◽  
Author(s):  
G. Dybkjær ◽  
R. Tonboe ◽  
J. L. Høyer
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Temperature Data ◽  
Coupled Systems ◽  
The Arctic ◽  
In Situ Observation ◽  
Clear Sky ◽  
Ice Surface ◽  
Ice Surface Temperature

Abstract. The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

The impact of shallow stratification on air-sea CO2 flux in the summer Arctic Ocean

2021 ◽  
Author(s):  
Yuanxu Dong ◽  
Dorothee Bakker ◽  
Thomas Bell ◽  
Peter Liss ◽  
Ian Brown ◽  
...  
Keyword(s):  
Surface Water ◽  
Wind Speed ◽  
Sea Ice ◽  
Surface Temperature ◽  
Arctic Ocean ◽  
The Arctic ◽  
Near Surface ◽  
Ice Melt ◽  
The Arctic Ocean ◽  
The Impact

&lt;p&gt;Air-sea carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) flux is often indirectly estimated by the bulk method using the i&lt;em&gt;n-situ&lt;/em&gt; air-sea difference in CO&lt;sub&gt;2&lt;/sub&gt; fugacity and a wind speed dependent parameterisation of the gas transfer velocity (&lt;em&gt;K&lt;/em&gt;). In the summer, sea-ice melt in the Arctic Ocean generates strong shallow stratification with significant gradients in temperature, salinity, dissolved inorganic carbon (DIC) and alkalinity (TA), and thus a near-surface CO&lt;sub&gt;2&lt;/sub&gt; fugacity &amp;#160;(&lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt;) gradient. This gradient can cause an error in bulk air-sea CO&lt;sub&gt;2&lt;/sub&gt; flux estimates when the &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt; is measured by the ship&amp;#8217;s underway system at ~5 m depth. Direct air-sea CO&lt;sub&gt;2&lt;/sub&gt; flux measurement by eddy covariance (EC) is free from the impact of shallow stratification because the EC CO&lt;sub&gt;2&lt;/sub&gt; flux does not rely on a &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt; measurement. In this study, we use summertime EC flux measurements from the Arctic Ocean to back-calculate the sea surface &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt; and temperature and compare them with the underway measurements. We show that the EC air-sea CO&lt;sub&gt;2&lt;/sub&gt; flux agrees well with the bulk flux in areas less likely to be influenced by ice melt (salinity &gt; 32). However, in regions with salinity less than 32, the underway &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt; is higher than the EC estimate of surface &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt; and thus the bulk estimate of ocean CO&lt;sub&gt;2&lt;/sub&gt; uptake is underestimated. The &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt; difference can be partly explained by the surface to sub-surface temperature difference. The EC estimate of surface temperature is lower than the sub-surface water temperature and this difference is wind speed-dependent. Upper-ocean salinity gradients from CTD profiles suggest likely difference in DIC and TA concentrations between the surface and sub-surface water. These DIC and TA gradients likely explain much of the near-surface &lt;em&gt;f&lt;/em&gt;CO&lt;sub&gt;2w&lt;/sub&gt; gradient. Accelerating summertime loss of sea ice results in additional meltwater, which enhances near-surface stratification and increases the uncertainty of bulk air-sea CO&lt;sub&gt;2&lt;/sub&gt; flux estimates in polar regions.&lt;/p&gt;

scholarly journals Cloud and boundary layer interactions over the Arctic sea ice in late summer

2013 ◽  
Vol 13 (18) ◽  
pp. 9379-9399 ◽  
Author(s):  
M. D. Shupe ◽  
P. O. G. Persson ◽  
I. M. Brooks ◽  
M. Tjernström ◽  
J. Sedlar ◽  
...  
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Late Summer ◽  
Arctic Sea Ice ◽  
Cloud Formation ◽  
The Arctic ◽  
Mixing Processes ◽  
Near Surface ◽  
Air Masses ◽  
Arctic Sea

Abstract. Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud–atmosphere–surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near-surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean–ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back-trajectory analyses suggest that these warm air masses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these air masses, providing necessary support for cloud formation. On the occasions when cloud–surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixed-layer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below.

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