scholarly journals Using Arctic ice mass balance buoys for evaluation of modelled ice energy fluxes

2020 ◽  
Vol 13 (10) ◽  
pp. 4845-4868
Author(s):  
Alex West ◽  
Mat Collins ◽  
Ed Blockley
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Arctic Sea Ice ◽  
Surface Radiation ◽  
Rapid Decline ◽  
Energy Fluxes ◽  
Arctic Sea ◽  
Imperfect Knowledge ◽  
Ice Mass Balance ◽  
Arctic Ice

Abstract. A new method of sea ice model evaluation is demonstrated. Data from the network of Arctic ice mass balance buoys (IMBs) are used to estimate distributions of vertical energy fluxes over sea ice in two densely sampled regions – the North Pole and Beaufort Sea. The resulting dataset captures seasonal variability in sea ice energy fluxes well, and it captures spatial variability to a lesser extent. The dataset is used to evaluate a coupled climate model, HadGEM2-ES (Hadley Centre Global Environment Model, version 2, Earth System), in the two regions. The evaluation shows HadGEM2-ES to simulate too much top melting in summer and too much basal conduction in winter. These results are consistent with a previous study of sea ice state and surface radiation in this model, increasing confidence in the IMB-based evaluation. In addition, the IMB-based evaluation suggests an additional important cause for excessive winter ice growth in HadGEM2-ES, a lack of sea ice heat capacity, which was not detectable in the earlier study. Uncertainty in the IMB fluxes caused by imperfect knowledge of ice salinity, snow density and other physical constants is quantified (as is inaccuracy due to imperfect sampling of ice thickness) and in most cases is found to be small relative to the model biases discussed. Hence the IMB-based evaluation is shown to be a valuable tool with which to analyse sea ice models and, by extension, better understand the large spread in coupled model simulations of the present-day ice state. Reducing this spread is a key task both in understanding the current rapid decline in Arctic sea ice and in constraining projections of future Arctic sea ice change.

Sea ice representation in sea ice model of CICE and Icepack

2020 ◽  
Author(s):  
Caixin Wang ◽  
Mats A. Granskog ◽  
Jens Boldingh Debernard ◽  
Keguang Wang
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
National Laboratory ◽  
Arctic Sea Ice ◽  
Surface Radiation ◽  
Radiation Balance ◽  
Momentum Exchange ◽  
Spectral Radiation ◽  
Ice Mass Balance ◽  
Ice Model

<p>Sea ice is a critical component of the Earth system, playing an important role in high-latitude<br>surface radiation balance and heat, moisture and momentum exchange between atmosphere<br>and ocean. In recent years, rapid changes have been occurring in Arctic sea ice, including<br>decline in ice extent/area, decreasing in ice thickness and volume, and shifting towards a first-<br>year ice (FYI) dominated, rather than multi-year ice (MYI) dominated ice pack. These are one<br>of the most well-known and striking examples of climate change. However, representing<br>these changes in the model is still in question since most of our knowledge is based on MYI.<br>CICE is a sea ice model developed at Los Alamos National Laboratory since 1994. It is<br>widely used to simulate the growth, melt and movement of sea ice, and to resolve the<br>biogeochemical processes. Its column version, Icepack, has been separated from CICE after<br>CICE V5.1.2, which provides additional opportunity for simulating the evolution of drifting<br>sea ice floes. How about the representation of sea ice in a column model (Icepack) and a 3d<br>model (CICE)? In 2012, an ice mass balance buoy (IMB) and a Spectral Radiation Buoy<br>(SRB) were deployed on FYI near the North Pole, and later drifted towards Fram Strait. These<br>buoys collected a complete summer melt season of in-band (350-800 nm) spectral solar<br>radiation and sea ice mass balance data. In this study, we apply the Icepack (version 1.1.1)<br>and CICE (version 5.1.2) to investigate the seasonal evolution of sea ice in 2012 in these two models, and<br>assess how well the physical processes are represented in CICE and Icepack, with the focus<br>on the surface changes.</p>

scholarly journals Estimating the snow depth, the snow–ice interface temperature, and the effective temperature of Arctic sea ice using Advanced Microwave Scanning Radiometer 2 and ice mass balance buoy data

2019 ◽  
Vol 13 (4) ◽  
pp. 1283-1296 ◽  
Author(s):  
Lise Kilic ◽  
Rasmus Tage Tonboe ◽  
Catherine Prigent ◽  
Georg Heygster
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Effective Temperature ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Interface Temperature ◽  
Microwave Frequencies ◽  
Arctic Sea ◽  
Ice Mass Balance

Abstract. Mapping sea ice concentration (SIC) and understanding sea ice properties and variability is important, especially today with the recent Arctic sea ice decline. Moreover, accurate estimation of the sea ice effective temperature (Teff) at 50 GHz is needed for atmospheric sounding applications over sea ice and for noise reduction in SIC estimates. At low microwave frequencies, the sensitivity to the atmosphere is low, and it is possible to derive sea ice parameters due to the penetration of microwaves in the snow and ice layers. In this study, we propose simple algorithms to derive the snow depth, the snow–ice interface temperature (TSnow−Ice) and the Teff of Arctic sea ice from microwave brightness temperatures (TBs). This is achieved using the Round Robin Data Package of the ESA sea ice CCI project, which contains TBs from the Advanced Microwave Scanning Radiometer 2 (AMSR2) collocated with measurements from ice mass balance buoys (IMBs) and the NASA Operation Ice Bridge (OIB) airborne campaigns over the Arctic sea ice. The snow depth over sea ice is estimated with an error of 5.1 cm, using a multilinear regression with the TBs at 6, 18, and 36 V. The TSnow−Ice is retrieved using a linear regression as a function of the snow depth and the TBs at 10 or 6 V. The root mean square errors (RMSEs) obtained are 2.87 and 2.90 K respectively, with 10 and 6 V TBs. The Teff at microwave frequencies between 6 and 89 GHz is expressed as a function of TSnow−Ice using data from a thermodynamical model combined with the Microwave Emission Model of Layered Snowpacks. Teff is estimated from the TSnow−Ice with a RMSE of less than 1 K.

scholarly journals Using Arctic ice mass balance buoys for evaluation of modelled ice energy fluxes

2019 ◽  
Author(s):  
Alex West ◽  
Mat Collins ◽  
Ed Blockley
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
The North ◽  
Energy Evaluation ◽  
Ice Mass Balance ◽  
Arctic Ice

Abstract. Arctic sea ice has declined rapidly over recent decades. Models predict that the Arctic will be nearly ice-free by mid-century, but the spread in predictions of sea ice extent is currently large. The reasons for this spread are poorly understood, partly due to a lack of observations with which the processes by which Arctic atmospheric and oceanic forcing affect sea ice state can be examined. In this study, a method of estimating fluxes of top melt, top conduction, basal conduction and ocean heat flux from Arctic ice mass balance buoy elevation and temperature data is presented. The derived fluxes are used to evaluate modelled fluxes from the coupled climate model HadGEM2-ES in two densely sampled regions of the Arctic, the North Pole and Beaufort Sea. The evaluation shows the model to overestimate the magnitude of summer top melting fluxes, and winter conductive fluxes, results which are physically consistent with an independent sea ice and surface energy evaluation of the same model.

scholarly journals Estimating the snow depth, the snow-ice interface temperature, and the effective temperature of Arctic sea ice using Advanced Microwave Scanning Radiometer 2 and Ice Mass Balance buoys data

2018 ◽  
Author(s):  
Lise Kilic ◽  
Rasmus Tage Tonboe ◽  
Catherine Prigent ◽  
Georg Heygster
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Effective Temperature ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Interface Temperature ◽  
Microwave Frequencies ◽  
Arctic Sea ◽  
Ice Mass Balance

Abstract. Mapping Sea Ice Concentration (SIC) and understanding sea ice properties and variability is important especially today with the recent Arctic sea ice decline. Moreover, accurate estimation of the sea ice effective temperature (Teff) at 50 GHz is needed for atmospheric sounding applications over sea ice and for noise reduction in SIC estimates. At low microwave frequencies, the sensitivity to atmosphere is low, and it is possible to derive sea ice parameters due to the penetration of microwaves in the snow and ice layers. In this study, we propose simple algorithms to derive the snow depth, the snow-ice interface temperature (TSnow-Ice) and the Teff of Arctic sea ice from microwave brightness temperatures (TBs). This is achieved using the Round Robin Data Package of the ESA sea ice CCI project, which contains TBs from the Advanced Microwave Scanning Radiometer 2 (AMSR2) collocated with measurements from Ice Mass Balance (IMB) buoys and the NASA Operation Ice Bridge (OIB) airborne campaigns over the Arctic sea ice. The snow depth over sea ice is estimated with an error of ~ 6 cm using a multilinear regression with the TBs at 6 V, 18 V, and 36 V. The TSnow-Ice is retrieved using a linear regression as a function of the snow depth and the TBs at 10 V or 6 V. The Root Mean Square Errors (RMSEs) obtained are 1.69 and 1.95 K respectively, with the 10 V and 6 V TBs. The Teff at microwave frequencies between 6 and 89 GHz is expressed as a function of TSnow-Ice using data from a thermodynamical model combined with the Microwave Emission Model of Layered Snow-packs. Teffs are estimated from the TSnow-Ice with a RMSE of less than 1 K.

scholarly journals Snow contribution to first-year and second-year Arctic sea ice mass balance north of Svalbard

2017 ◽  
Vol 122 (3) ◽  
pp. 2539-2549 ◽  
Author(s):  
Mats A. Granskog ◽  
Anja Rösel ◽  
Paul A. Dodd ◽  
Dmitry Divine ◽  
Sebastian Gerland ◽  
...  
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Arctic Sea Ice ◽  
First Year ◽  
Arctic Sea ◽  
Ice Mass Balance ◽  
Second Year

scholarly journals Ice mass-balance buoys: a tool for measuring and attributing changes in the thickness of the Arctic sea-ice cover

2006 ◽  
Vol 44 ◽  
pp. 205-210 ◽  
Author(s):  
Jacqueline A. Richter-Menge ◽  
Donald K. Perovich ◽  
Bruce C. Elder ◽  
Keran Claffey ◽  
Ignatius Rigor ◽  
...  
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
North Pole ◽  
The Arctic ◽  
Central Basin ◽  
The North ◽  
Arctic Sea ◽  
Ice Mass Balance

AbstractRecent observational and modeling studies indicate that the Arctic sea-ice cover is undergoing significant climate-induced changes, affecting both its extent and thickness. The thickness or, more precisely, the mass balance of the ice cover is a key climate-change indicator since it is an integrator of both the surface heat budget and the ocean heat flux. Accordingly, efforts are underway to develop and deploy in situ observing systems which, when combined with satellite remote-sensing information and numerical models, can effectively monitor and attribute changes in the mass balance of the Arctic sea-ice cover. As part of this effort, we have developed an autonomous ice mass-balance buoy (IMB), which is equipped with sensors to measure snow accumulation and ablation, ice growth and melt, and internal ice temperature, plus a satellite transmitter. The IMB is unique in its ability to determine whether changes in the thickness of the ice cover occur at the top or bottom of the ice cover, and hence provide insight into the driving forces behind the change. Since 2000, IMBs have been deployed each spring from the North Pole Environmental Observatory and in several other areas, including a few in the Beaufort Sea and Central Basin. At this point, the collective time series is too short to draw significant and specific conclusions regarding interannual and regional variability in ice mass balance. Comparisons of available data indicate that ice surface ablation is greater in the Beaufort region (67–80 cm), relative to the North Pole (0–30 cm), consistent with a longer period of melt in the more southerly location. Ablation at the bottom of the ice (22 cm), maximum ice thickness (235 cm) and maximum snow depth (28 cm) were comparable in the two regions.

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