Co-producing Sea-Ice Predictions with Stakeholders Using Simulation

2021 ◽  
Keyword(s):  
Sea Ice ◽  
Local Community ◽  
Economic Value ◽  
Arctic Region ◽  
Production Model ◽  
The Arctic ◽  
Simulation Game ◽  
Climate Services ◽  
Diverse Range ◽  
Uncertainty Information

Abstract Forecasts of sea-ice evolution in the Arctic region for several months ahead can be of considerable socio-economic value for a diverse range of marine sectors and for local community supply logistics. However, subseasonal-to-seasonal (S2S) forecasts represent a significant technical challenge, while translating user needs into scientifically manageable procedures and robust user confidence requires collaboration among a range of stakeholders. We developed and tested a novel, transdisciplinary co-production approach that combined socio-economic scenarios and participatory, research-driven simulation-gaming to test a new S2S sea-ice forecast system with experienced mariners in the cruise tourism sector. Our custom-developed computerized simulation-game ICEWISE integrated sea-ice parameters, forecast technology and human factors, as a participatory environment for stakeholder engagement. We explored the value of applications-relevant S2S sea-ice prediction and linked uncertainty information. Results suggest that the usefulness of S2S services is currently most evident in schedule-dependent sectors but expected to increase due to anticipated changes in the physical environment and continued growth in Arctic operations. Reliable communication of uncertainty information in sea-ice forecasts must be demonstrated and trialed before users gain confidence in emerging services and technologies. Mariners’ own intuition, experience, and familiarity with forecast service provider reputation impact the extent to which sea-ice information may reduce uncertainties and risks for Arctic mariners. Our insights into the performance of the combined foresight/simulation co-production model in brokering knowledge across a range of domains demonstrates promise. We conclude with an overview of the potential contributions from S2S sea-ice predictions and from experiential co-production models to the development of decision-driven and science-informed climate services.

Prévoir les variations saisonnières de la glace de mer arctique et leurs impacts sur le climat

2020 ◽  
pp. 024
Author(s):  
Rym Msadek ◽  
Gilles Garric ◽  
Sara Fleury ◽  
Florent Garnier ◽  
Lauriane Batté ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Climate Impacts ◽  
The Arctic ◽  
Recent Effort ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Ice Conditions ◽  
Upper Level

L'Arctique est la région du globe qui s'est réchauffée le plus vite au cours des trente dernières années, avec une augmentation de la température de surface environ deux fois plus rapide que pour la moyenne globale. Le déclin de la banquise arctique observé depuis le début de l'ère satellitaire et attribué principalement à l'augmentation de la concentration des gaz à effet de serre aurait joué un rôle important dans cette amplification des températures au pôle. Cette fonte importante des glaces arctiques, qui devrait s'accélérer dans les décennies à venir, pourrait modifier les vents en haute altitude et potentiellement avoir un impact sur le climat des moyennes latitudes. L'étendue de la banquise arctique varie considérablement d'une saison à l'autre, d'une année à l'autre, d'une décennie à l'autre. Améliorer notre capacité à prévoir ces variations nécessite de comprendre, observer et modéliser les interactions entre la banquise et les autres composantes du système Terre, telles que l'océan, l'atmosphère ou la biosphère, à différentes échelles de temps. La réalisation de prévisions saisonnières de la banquise arctique est très récente comparée aux prévisions du temps ou aux prévisions saisonnières de paramètres météorologiques (température, précipitation). Les résultats ayant émergé au cours des dix dernières années mettent en évidence l'importance des observations de l'épaisseur de la glace de mer pour prévoir l'évolution de la banquise estivale plusieurs mois à l'avance. Surface temperatures over the Arctic region have been increasing twice as fast as global mean temperatures, a phenomenon known as arctic amplification. One main contributor to this polar warming is the large decline of Arctic sea ice observed since the beginning of satellite observations, which has been attributed to the increase of greenhouse gases. The acceleration of Arctic sea ice loss that is projected for the coming decades could modify the upper level atmospheric circulation yielding climate impacts up to the mid-latitudes. There is considerable variability in the spatial extent of ice cover on seasonal, interannual and decadal time scales. Better understanding, observing and modelling the interactions between sea ice and the other components of the climate system is key for improved predictions of Arctic sea ice in the future. Running operational-like seasonal predictions of Arctic sea ice is a quite recent effort compared to weather predictions or seasonal predictions of atmospheric fields like temperature or precipitation. Recent results stress the importance of sea ice thickness observations to improve seasonal predictions of Arctic sea ice conditions during summer.

scholarly journals Record high Pacific Arctic seawater temperatures and delayed sea ice advance in response to episodic atmospheric blocking

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tsubasa Kodaira ◽  
Takuji Waseda ◽  
Takehiko Nose ◽  
Jun Inoue
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
The Arctic ◽  
Atmospheric Blocking ◽  
Sea Ice Extent ◽  
The Pacific ◽  
Arctic Sea ◽  
Highly Correlated

AbstractArctic sea ice is rapidly decreasing during the recent period of global warming. One of the significant factors of the Arctic sea ice loss is oceanic heat transport from lower latitudes. For months of sea ice formation, the variations in the sea surface temperature over the Pacific Arctic region were highly correlated with the Pacific Decadal Oscillation (PDO). However, the seasonal sea surface temperatures recorded their highest values in autumn 2018 when the PDO index was neutral. It is shown that the anomalous warm seawater was a rapid ocean response to the southerly winds associated with episodic atmospheric blocking over the Bering Sea in September 2018. This warm seawater was directly observed by the R/V Mirai Arctic Expedition in November 2018 to significantly delay the southward sea ice advance. If the atmospheric blocking forms during the PDO positive phase in the future, the annual maximum Arctic sea ice extent could be dramatically reduced.

scholarly journals Synoptic climatological approach associated with three recent summer heatwaves in the Canadian Arctic

2020 ◽  
Vol 11 (S1) ◽  
pp. 233-250 ◽  
Author(s):  
Farahnaz Fazel-Rastgar
Keyword(s):  
Sea Ice ◽  
Canadian Arctic ◽  
Arctic Region ◽  
Low Pressure ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
The North ◽  
Pressure Centre ◽  
Temperature Records ◽  
Arctic Temperature

Abstract The observed unusually high temperatures in the Arctic during recent decades can be related to the Arctic sea ice declines in summer 2007, 2012 and 2016. Arctic dipole formation has been associated with all three heatwaves of 2007, 2012 and 2016 in the Canadian Arctic. Here, the differences in weather patterns are investigated and compared with normal climatological mean (1981–2010) structures. This study examines the high-resolution datasets from the North American Regional Reanalysis model. During the study periods, the north of Alaska has been affected by the low-pressure tongue. The maximum difference between Greenland high-pressure centre and Alaska low-pressure tongue for the summers of 2012, 2016 and 2007 are 8 hPa, 7 hPa and 6 hPa, respectively, corresponding and matching to the maximum summer surface Canadian Arctic temperature records. During anomalous summer heatwaves, low-level wind, temperatures, total clouds (%) and downward radiation flux at the surface are dramatically changed. This study shows the surface albedo has been reduced over most parts of the Canadian Arctic Ocean during the mentioned heatwaves (∼5–40%), with a higher change (specifically in the eastern Canadian Arctic region) during summer 2012 in comparison with summer 2016 and summer 2007, agreeing with the maximum surface temperature and sea ice decline records.

scholarly journals The potential of sea ice leads as a predictor for summer Arctic sea ice extent

2018 ◽  
Vol 12 (12) ◽  
pp. 3747-3757 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Jiping Liu ◽  
Fengming Hui
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Strong Relationship ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Leads ◽  
Arctic Sea Ice Extent

Abstract. The Arctic sea ice extent throughout the melt season is closely associated with initial sea ice state in winter and spring. Sea ice leads are important sites of energy fluxes in the Arctic Ocean, which may play an important role in the evolution of Arctic sea ice. In this study, we examine the potential of sea ice leads as a predictor for summer Arctic sea ice extent forecast using a recently developed daily sea ice lead product retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS). Our results show that July pan-Arctic sea ice extent can be predicted from the area of sea ice leads integrated from midwinter to late spring, with a prediction error of 0.28 million km2 that is smaller than the standard deviation of the observed interannual variability. However, the predictive skills for August and September pan-Arctic sea ice extent are very low. When the area of sea ice leads integrated in the Atlantic and central and west Siberian sector of the Arctic is used, it has a significantly strong relationship (high predictability) with both July and August sea ice extent in the Atlantic and central and west Siberian sector of the Arctic. Thus, the realistic representation of sea ice leads (e.g., the areal coverage) in numerical prediction systems might improve the skill of forecast in the Arctic region.

scholarly journals Climate change between the mid and late Holocene in northern high latitudes – Part 2: Model-data comparisons

2010 ◽  
Vol 6 (5) ◽  
pp. 609-626 ◽  
Author(s):  
Q. Zhang ◽  
H. S. Sundqvist ◽  
A. Moberg ◽  
H. Körnich ◽  
J. Nilsson ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Barents Sea ◽  
Arctic Region ◽  
Summer Temperature ◽  
The Arctic ◽  
High Latitudes ◽  
Climate Response ◽  
Model Data ◽  
Model Simulations

Abstract. The climate response over northern high latitudes to the mid-Holocene orbital forcing has been investigated in three types of PMIP (Paleoclimate Modelling Intercomparison Project) simulations with different complexity of the modelled climate system. By first undertaking model-data comparison, an objective selection method has been applied to evaluate the capability of the climate models to reproduce the spatial response pattern seen in proxy data. The possible feedback mechanisms behind the climate response have been explored based on the selected model simulations. Subsequent model-model comparisons indicate the importance of including the different physical feedbacks in the climate models. The comparisons between the proxy-based reconstructions and the best fit selected simulations show that over the northern high latitudes, summer temperature change follows closely the insolation change and shows a common feature with strong warming over land and relatively weak warming over ocean at 6 ka compared to 0 ka. Furthermore, the sea-ice-albedo positive feedback enhances this response. The reconstructions of temperature show a stronger response to enhanced insolation in the annual mean temperature than winter and summer temperature. This is verified in the model simulations and the behaviour is attributed to the larger contribution from the large response in autumn. Despite a smaller insolation during winter at 6 ka, a pronounced warming centre is found over Barents Sea in winter in the simulations, which is also supported by the nearby northern Eurasian continental and Fennoscandian reconstructions. This indicates that in the Arctic region, the response of the ocean and the sea ice to the enhanced summer insolation is more important for the winter temperature than the synchronous decrease of the insolation.

scholarly journals The role of moisture transport for precipitation in the inter-annual and inter-daily fluctuations of the Arctic sea ice extension

2019 ◽  
Vol 10 (1) ◽  
pp. 121-133 ◽  
Author(s):  
Luis Gimeno-Sotelo ◽  
Raquel Nieto ◽  
Marta Vázquez ◽  
Luis Gimeno
Keyword(s):  
Sea Ice ◽  
Moisture Transport ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Melting ◽  
Sea Ice Extent ◽  
Moisture Sources ◽  
Arctic Sea

Abstract. By considering the moisture transport for precipitation (MTP) for a target region to be the moisture that arrives in this region from its major moisture sources and which then results in precipitation in that region, we explore (i) whether the MTP from the main moisture sources for the Arctic region is linked with inter-annual fluctuations in the extent of Arctic sea ice superimposed on its decline and (ii) the role of extreme MTP events in the inter-daily change in the Arctic sea ice extent (SIE) when extreme MTP simultaneously arrives from the four main moisture regions that supply it. The results suggest (1) that ice melting at the scale of inter-annual fluctuations against the trend is favoured by an increase in moisture transport in summer, autumn, and winter and a decrease in spring and, (2) on a daily basis, extreme humidity transport increases the formation of ice in winter and decreases it in spring, summer, and autumn; in these three seasons extreme humidity transport therefore contributes to Arctic sea ice melting. These patterns differ sharply from that linked to the decline on a long-range scale, especially in summer when the opposite trend applies, as ice melt is favoured by a decrease in moisture transport for this season at this scale.

scholarly journals Determination of a melt-onset date for Arctic sea-ice regions using passive-microwave data

1997 ◽  
Vol 25 ◽  
pp. 382-387 ◽  
Author(s):  
Mark R. Anderson
Keyword(s):  
Sea Ice ◽  
Arctic Region ◽  
Arctic Sea Ice ◽  
Passive Microwave ◽  
The Arctic ◽  
Horizontal Channel ◽  
Onset Date ◽  
Atmospheric Conditions ◽  
Brightness Temperatures

Although the formation and melt of sea ice are primarily functions of the annual radiation cycle, atmospheric sensible-heat forcing does serve to delay or advance the timing of such events. Additionally, if atmospheric conditions in the Arctic were to vary due to climate change it may have significant influence on ice conditions. Therefore, this paper investigates a methodology to determine melt-onset dale distribution, both spatially and temporally, in the Arctic Ocean and surrounding sea-ice covered regions.Melt determination is made by a threshold technique using the spectral signatures of the horizontal brightness temperatures (19 GHz horizontal channel minus the 37 GHz horizontal channel) obtained from the Special Sensor Microwave Imager (SSM/I) passive-microwave sensor. Passive-microwave observations are used to identify melt because of the large increase in emissivity that occurs when liquid water is present. Emissivity variations are observed in the brightness temperatures due to the different scattering, absorption and penetration depths of the snowpack from the available satellite channels during melt. Monitoring the variations in the brightness temperatures allows the determination of melt-onset dates.Analysis of daily brightness temperature data allows spatial variations in the date of the snow inch onset for sea ice to be detected. Since the data are gridded on a daily basis, a climatology of daily melt-onset dates can be produced for the Arctic region. From this climatology, progression of melt can be obtained and compared inter-annually.

Comparison of sea ice concentrations from ASI, BT and NT2 algorithms with ERA-Interim dataset in the Arctic and Antarctic regions

2020 ◽  
Author(s):  
Shuang Liang ◽  
Jiangyuan Zeng ◽  
Zhen Li
Keyword(s):  
Sea Ice ◽  
Temporal Distribution ◽  
Arctic Region ◽  
The Arctic ◽  
Polar Regions ◽  
Significant Discrepancy ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Long Time ◽  
Mean Square Difference

<p>Evaluating the performance and consistency of passive microwave (PM) sea ice concentration (SIC) products derived from different algorithms is critical since a good knowledge of the quality of the satellite SIC products is essential for their application and improvement. To comprehensively evaluate the performance of satellite SIC in long time series and the whole polar regions (both Arctic and Antarctic), in the study we examined the spatial and temporal distribution of the discrepancy between four PM satellite SIC products with the ERA-Interim sea ice fraction dataset (ERA SIC) during the period of 2015-2018. The four PM SIC products include the DMSP SSMIS with Arctic Radiation and Turbulence Interaction Study Sea Ice (ASI) algorithm (SSMIS/ASI), the GCOM-W AMSR2 with NASA Bootstrap (BT) algorithm (AMSR2/BT), the Chinese Feng Yun-3B with enhanced NASA Team (NT2) sea ice algorithm (FY3B/NT2), and the Chinese Feng Yun-3C with NT2 (FY3C/NT2) at a spatial resolution of 12.5 km.</p><p>The results show the spatial patterns of PM SIC products are generally in good agreement with ERA SIC. The comparison of monthly and annual SIC shows that the largest bias and root mean square difference (RMSD) for the PM SIC products mainly occur in summer and the marginal ice zone, indicating that there are still many uncertainties in PM SIC products in such period and region. Meanwhile, the daily sea ice extent (SIE) and sea ice area (SIA) derived from the four PM SIC products can generally well reflect the variation trend of SIE and SIA in Arctic and Antarctic. The largest bias of SIE and SIA are above 4×10<sup>6</sup> km<sup>2</sup> when the sea ice reaches the maximum and minimum value, and the daily bias of SIE and SIA vary seasonally and regionally, which is mainly concentrated from June to October in Arctic. In general, among the four PM SIC products, the SSMIS/ASI product performs the best compared with ERA SIC though it usually underestimates SIC with a negative bias. The FY3B/NT2 and FY3C/NT2 products show more significant discrepancy with higher RMSD and bias in Arctic and Antarctic compared with the SSMIS/ASI and AMSR2/BT. The AMSR2/BT product performs much better in Antarctic than in Arctic and it always overestimates ERA SIC with a positive bias. The consistency of the four PM products concerning ERA SIC in the Antarctic region is generally superior to that in Arctic region.</p>

High interannual variability of sea ice thickness in the Arctic region

Nature ◽  
2003 ◽  
Vol 425 (6961) ◽  
pp. 947-950 ◽  
Author(s):  
Seymour Laxon ◽  
Neil Peacock ◽  
Doug Smith
Keyword(s):  
Sea Ice ◽  
Interannual Variability ◽  
Arctic Region ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
The Arctic Region
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