IMPLICATIONS OF CHANGES IN INSOLATION CHARACTERISTICS FOR LONG-TERM SEA ICE EXTENT DYNAMICS IN THE NORTHERN HEMISPHERE

2021 ◽  
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Sea Ice Extent

scholarly journals Multi-model dynamic climate emulator for solar geoengineering

2016 ◽  
Author(s):  
Douglas G. MacMartin ◽  
Ben Kravitz
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Circulation Model ◽  
Nonlinear Effects ◽  
Accurate Estimate ◽  
Natural Variability ◽  
Sea Ice Extent ◽  
Temperature And Precipitation ◽  
Solar Geoengineering

Abstract. Climate emulators trained on existing simulations can be used to project the climate effects that would result from different possible future pathways of anthropogenic forcing, without relying on general circulation model (GCM) simulations for every possible pathway. We extend this idea to include different amounts of solar geoengineering in addition to different pathways of green-house gas concentrations by training emulators from a multi-model ensemble of simulations from the Geoengineering Model Intercomparison Project (GeoMIP). The emulator is trained on the abrupt 4 x CO2 and a compensating solar reduction simulation (G1), and evaluated by comparing predictions against a simulated 1 % per year CO2 increase and a similarly smaller solar reduction (G2). We find reasonable agreement in most models for predicting changes in temperature and precipitation (including regional effects), and annual-mean Northern hemisphere sea ice extent, with the difference between simulation and prediction typically smaller than natural variability. This verifies that the linearity assumption used in constructing the emulator is sufficient for these variables over the range of forcing considered. Annual-minimum Northern hemisphere sea ice extent is less-well predicted, indicating the limits of the linearity assumption. For future pathways involving relatively small forcing from solar geoengineering, the errors introduced from nonlinear effects may be smaller than the uncertainty due to natural variability, and the emulator prediction may be a more accurate estimate of the forced component of the models' response than an actual simulation would be.

Further development on sea-ice HBI biomarker proxies.

2020 ◽  
Author(s):  
Maria Luisa Sánchez-Montes ◽  
Nikolai Pedentchouk ◽  
Thomas Mock ◽  
Simon Belt ◽  
Lukas Smik
Keyword(s):  
Sea Ice ◽  
The Arctic ◽  
Global Ocean ◽  
Sea Ice Extent ◽  
Climate Conditions ◽  
Crucial Component ◽  
Lipid Biomarker ◽  
Proxy Measure ◽  
Further Development

<p>Sea ice is a crucial component of the Earth’s climate system, which helps regulate global ocean and atmosphere’s temperature. The alarming decline in sea-ice extent and thickness under modern climate conditions has created the urgency to understand the long-term sea-ice variability and mechanisms of change. In recent years, the highly branched isoprenoid (HBI) lipid biomarker IP<sub>25</sub> has emerged as a powerful proxy measure of past sea ice in the Arctic, and its analysis in a variety of marine sediments has provided the foundation for a large number of palaeo sea ice reconstructions spanning thousands to millions of years before present. To date, IP<sub>25</sub> and related HBI-based studies have focussed largely on reconstructions of sea-ice extent and seasonal dynamics. Here we aim to further develop such sea ice proxies by measuring the changes in distribution and isotopic composition of HBIs in HBI-producing diatoms grown under different controlled laboratory conditions. We present preliminary results from the diatom <em>Haslea ostrearia</em> and outline the next steps of our research in the coming year.</p>

scholarly journals Sea-ice and North Atlantic climate response to CO2-induced warming and cooling conditions

2006 ◽  
Vol 52 (178) ◽  
pp. 433-439 ◽  
Author(s):  
Larissa Nazarenko ◽  
Nickolai Tausnev ◽  
James Hansen
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Surface Pressure ◽  
Climate Model ◽  
Global Climate Model ◽  
Ice Cover ◽  
The Arctic ◽  
Normal Surface ◽  
Sea Ice Extent ◽  
Polar Cell

AbstractUsing a global climate model coupled with an ocean and a sea-ice model, we compare the effects of doubling CO2 and halving CO2 on sea-ice cover and connections with the atmosphere and ocean. An overall warming in the 2 × CO2 experiment causes reduction of sea-ice extent by 15%, with maximum decrease in summer and autumn, consistent with observed seasonal sea-ice changes. The intensification of the Northern Hemisphere circulation is reflected in the positive phase of the Arctic Oscillation (AO), associated with higher-than-normal surface pressure south of about 50° N and lower-than-normal surface pressure over the high northern latitudes. Strengthening the polar cell causes enhancement of westerlies around the Arctic perimeter during winter. Cooling, in the 0.5 × CO2 experiment, leads to thicker and more extensive sea ice. In the Southern Hemisphere, the increase in ice-covered area (28%) dominates the ice-thickness increase (5%) due to open ocean to the north. In the Northern Hemisphere, sea-ice cover increases by only 8% due to the enclosed land/sea configuration, but sea ice becomes much thicker (108%). Substantial weakening of the polar cell due to increase in sea-level pressure over polar latitudes leads to a negative trend of the winter AO index. The model reproduces large year-to-year variability under both cooling and warming conditions.

Mechanisms for the variation of sea ice extent in the northern hemisphere

2001 ◽  
Vol 106 (C12) ◽  
pp. 31319-31331 ◽  
Author(s):  
Noriaki Kimura ◽  
Masaaki Wakatsuchi
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Sea Ice Extent

scholarly journals Antarctic and Southern Ocean Sea-Ice and Climate Trends

1990 ◽  
Vol 14 ◽  
pp. 127-130 ◽  
Author(s):  
T.H Jacka
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Data Sets ◽  
Climate Trends ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
South Pacific Ocean ◽  
Computer Based ◽  
Long Term Trends

A computer-based climate monitoring project is described. Data sets include monthly and annual mean surface temperatures and pressures for occupied stations in Antarctica, the Southern Ocean and South Pacific Ocean; and monthly Antarctic sea-ice extent at each 10° of longitude.Simple statistical analyses of the data sets reveal a mean warming of ~0.15°C (10 a)−1 since the mid 1950s for Antarctic coastal stations and of ~0.04°C (10 a)−1 since the mid 1940s for the ocean stations. The sea-ice record from 1973 to 1988 reveals that the average northern ice limit has decreased at ~0.23°lat. (10 a)−1. Despite apparently compatible long-term trends of temperature and sea-ice extent, annual fluctuations of temperature and ice extent are highly variable and are not well correlated.

scholarly journals Record Low Northern Hemisphere Sea Ice Extent in March 2015

2016 ◽  
Vol 97 (12) ◽  
pp. S136-S140 ◽  
Author(s):  
Neven S. Fučkar ◽  
François Massonnet ◽  
Virginie Guemas ◽  
Javier García-Serrano ◽  
Omar Bellprat ◽  
...  
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Sea Ice Extent

scholarly journals Seasonal Prediction of Arctic Sea Ice Extent from a Coupled Dynamical Forecast System

2013 ◽  
Vol 141 (4) ◽  
pp. 1375-1394 ◽  
Author(s):  
Wanqiu Wang ◽  
Mingyue Chen ◽  
Arun Kumar
Keyword(s):  
Sea Ice ◽  
Seasonal Prediction ◽  
Arctic Sea Ice ◽  
Prediction Skill ◽  
Forecast System ◽  
Sea Ice Extent ◽  
Term Trend ◽  
Fully Coupled ◽  
Long Term Trend

Abstract While fully coupled atmosphere–ocean models have been used to study the seasonal predictability of sea ice variations within the context of models’ own variability, their capability in predicting the observed sea ice at the seasonal time scales is not well assessed. In this study, sea ice predictions from the recently developed NCEP Climate Forecast System, version 2 (CFSv2), a fully coupled atmosphere–ocean model including an interactive dynamical sea ice component, are analyzed. The focus of the analysis is the performance of CFSv2 in reproducing observed Northern Hemisphere sea ice extent (SIE). The SIE climatology, long-term trend, interannual variability, and predictability are assessed. CFSv2 contains systematic biases that are dependent more on the forecast target month than the initial month, with a positive SIE bias for the forecast for January–September and a negative SIE bias for the forecast for October–December. A large source of seasonal prediction skill is from the long-term trend, which is underestimated in the CFSv2. Prediction skill of interannual SIE anomalies is found to be primarily within the first three target months and is largest in the summer and early fall. The performance of the prediction of sea ice interannual variations varies from year to year and is found to be related to initial sea ice thickness. Potential predictability based on the forecast ensemble, its dependence on model deficiencies, and implications of the results from this study for improvements in the seasonal sea ice prediction are discussed.

scholarly journals Arctic sea ice variability and trends, 1979–2010

2012 ◽  
Vol 6 (4) ◽  
pp. 881-889 ◽  
Author(s):  
D. J. Cavalieri ◽  
C. L. Parkinson
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Bering Sea ◽  
Arctic Sea Ice ◽  
Negative Trend ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Regions ◽  
Arctic Sea ◽  
The Bering Sea

Abstract. Analyses of 32 yr (1979–2010) of Arctic sea ice extents and areas derived from satellite passive microwave radiometers are presented for the Northern Hemisphere as a whole and for nine Arctic regions. There is an overall negative yearly trend of −51.5 ± 4.1 × 103 km2 yr−1 (−4.1 ± 0.3% decade−1) in sea ice extent for the hemisphere. The yearly sea ice extent trends for the individual Arctic regions are all negative except for the Bering Sea: −3.9 ± 1.1 × 103 km2 yr−1 (−8.7 ± 2.5% decade−1) for the Seas of Okhotsk and Japan, +0.3 ± 0.8 × 103 km2 yr−1 (+1.2 ± 2.7% decade−1) for the Bering Sea, −4.4 ± 0.7 × 103 km2 yr−1 (−5.1 ± 0.9% decade−1) for Hudson Bay, −7.6 ± 1.6 × 103 km2 yr−1 (−8.5 ± 1.8% decade−1) for Baffin Bay/Labrador Sea, −0.5 ± 0.3 × 103 km2 yr−1 (−5.9 ± 3.5% decade−1) for the Gulf of St. Lawrence, −6.5 ± 1.1 × 103 km2 yr−1 (−8.6 ± 1.5% decade−1) for the Greenland Sea, −13.5 ± 2.3 × 103 km2 yr−1 (−9.2 ± 1.6% decade−1) for the Kara and Barents Seas, −14.6 ± 2.3 × 103 km2 yr−1 (−2.1 ± 0.3% decade−1) for the Arctic Ocean, and −0.9 ± 0.4 × 103 km2 yr−1 (−1.3 ± 0.5% decade−1) for the Canadian Archipelago. Similarly, the yearly trends for sea ice areas are all negative except for the Bering Sea. On a seasonal basis for both sea ice extents and areas, the largest negative trend is observed for summer with the next largest negative trend being for autumn. Both the sea ice extent and area trends vary widely by month depending on region and season. For the Northern Hemisphere as a whole, all 12 months show negative sea ice extent trends with a minimum magnitude in May and a maximum magnitude in September, whereas the corresponding sea ice area trends are smaller in magnitude and reach minimum and maximum values in March and September.

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