scholarly journals On the Origin of the Surface Air Temperature Difference between the Hemispheres in Earth's Present-Day Climate

2013 ◽  
Vol 26 (18) ◽  
pp. 7136-7150 ◽  
Author(s):  
Georg Feulner ◽  
Stefan Rahmstorf ◽  
Anders Levermann ◽  
Silvia Volkwardt
Keyword(s):  
Sea Ice ◽  
Heat Transport ◽  
Air Temperature ◽  
Ocean Circulation ◽  
Temperature Difference ◽  
Greenhouse Gas Emission ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
Polar Regions ◽  
Additional Contribution

Abstract In today's climate, the annually averaged surface air temperature in the Northern Hemisphere (NH) is 1°–2°C higher than in the Southern Hemisphere (SH). Historically, this interhemispheric temperature difference has been attributed to a number of factors, including seasonal differences in insolation, the larger area of (tropical) land in the NH, the particularities of the Antarctic in terms of albedo and temperature, and northward heat transport by ocean circulation. A detailed investigation of these factors and their contribution to the temperature difference, however, has to the authors' knowledge not been performed so far. Here the origin of the interhemispheric temperature difference is traced using an assessment of climatological data and the observed energy budget of Earth as well as model simulations. It is found that for the preindustrial climate the temperature difference is predominantly due to meridional heat transport in the oceans, with an additional contribution from the albedo differences between the polar regions. The combination of these factors (that are to some extent coupled) governs the evolution of the temperature difference over the past millennium. Since the beginning of industrialization the interhemispheric temperature difference has increased due to melting of sea ice and snow in the NH. Furthermore, the predicted higher rate of warming over land as compared to the oceans contributes to this increase. Simulations for the twenty-first century show that the interhemispheric temperature difference continues to grow for the highest greenhouse gas emission scenarios due to the land–ocean warming contrast and the strong loss of Arctic sea ice, whereas the decrease in overturning strength dominates for the more moderate scenarios.

scholarly journals Summertime changes in climate extremes over the peripheral Arctic regions after a sudden sea ice retreat

2021 ◽  
Author(s):  
Steve Delhaye ◽  
Thierry Fichefet ◽  
François Massonnet ◽  
David Docquier ◽  
Rym Msadek ◽  
...  
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Climate Extremes ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Maximum Surface ◽  
Temperature And Precipitation ◽  
Arctic Regions ◽  
Arctic Sea

Abstract. The retreat of Arctic sea ice is frequently considered as a possible driver of changes in climate extremes in the Arctic and possibly down to mid-latitudes. However, it is unclear how the atmosphere will respond to a near-total retreat of summer Arctic sea ice, a reality that might occur in the foreseeable future. This study explores this question by conducting sensitivity experiments with two global coupled climate models run at two different horizontal resolutions to investigate the change in temperature and precipitation extremes during summer over peripheral Arctic regions following a sudden reduction in summer Arctic sea ice cover. An increase in frequency and persistence of maximum surface air temperature is found in all peripheral Arctic regions during the summer when sea ice loss occurs. For each million km2 of Arctic sea ice extent reduction, the absolute frequency of days exceeding the surface air temperature of the climatological 90th percentile increases by ~4 % over the Svalbard area, and the duration of warm spells increases by ~1 day per month over the same region. Furthermore, we find that the 10th percentile of surface daily air temperature increases more than the 90th percentile, leading to a weakened diurnal cycle of surface air temperature. Finally, an increase in extreme precipitation, which is less robust (statistically speaking) than the increase in extreme temperatures, is found in all regions in summer. These findings suggest that a sudden retreat of summer Arctic sea ice clearly impacts the extremes in maximum surface air temperature and precipitation over the peripheral Arctic regions with the largest influence over inhabited islands such as Svalbard or Northern Canada. Nonetheless, even with a large sea ice reduction in regions close to the North Pole, the local precipitation response is relatively small compared to internal climate variability.

scholarly journals Consistently Estimating Internal Climate Variability from Climate Model Simulations

2017 ◽  
Vol 30 (23) ◽  
pp. 9555-9573 ◽  
Author(s):  
Dirk Olonscheck ◽  
Dirk Notz
Keyword(s):  
Climate Variability ◽  
Sea Ice ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
New Method ◽  
Polar Regions ◽  
Internal Climate Variability ◽  
Ensemble Simulations

This paper introduces and applies a new method to consistently estimate internal climate variability for all models within a multimodel ensemble. The method regresses each model’s estimate of internal variability from the preindustrial control simulation on the variability derived from a model’s ensemble simulations, thus providing practical evidence of the quasi-ergodic assumption. The method allows one to test in a multimodel consensus view how the internal variability of a variable changes for different forcing scenarios. Applying the method to the CMIP5 model ensemble shows that the internal variability of global-mean surface air temperature remains largely unchanged for historical simulations and might decrease for future simulations with a large CO2 forcing. Regionally, the projected changes reveal likely increases in temperature variability in the tropics, subtropics, and polar regions, and extremely likely decreases in midlatitudes. Applying the method to sea ice volume and area shows that their respective internal variability likely or extremely likely decreases proportionally to their mean state, except for Arctic sea ice area, which shows no consistent change across models. For the evaluation of CMIP5 simulations of Arctic and Antarctic sea ice, the method confirms that internal variability can explain most of the models’ deviation from observed trends but often not the models’ deviation from the observed mean states. The new method benefits from a large number of models and long preindustrial control simulations, but it requires only a small number of ensemble simulations. The method allows for consistent consideration of internal variability in multimodel studies and thus fosters understanding of the role of internal variability in a changing climate.

Winter arctic sea-ice cover variability and the prediction of spring vegetation growth over Eurasia

2020 ◽  
Author(s):  
Liuqing Ji ◽  
Ke Fan
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Prediction Models ◽  
Surface Air Temperature ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Hybrid Scheme ◽  
Coupled Modes ◽  
Previous Season

<p align="justify">The changes in Eurasian vegetation not only have important effects on regional climate, but also have effects on global temperatures and the carbon cycle<span>. </span>In this study, the interannual linkage between spring vegetation <span>growth</span> over Eurasia and winter sea-ice cover over the Barents Sea (SICBS), as well as the <span>prediction of spring Euraisan vegetation </span>are investigated. The Normalized Difference Vegetation Index (NDVI) derived from the advanced very high resolution radiometer is used as the proxy of vegetation <span>growth</span>. During 1982–2015, the winter SICBS is significantly correlated with the spring NDVI over Eurasia (NDVIEA). The positive (negative) winter SICBS anomalies tend to increase (decrease) the spring NDVIEA. The increased winter SICBS corresponds to higher winter surface air temperature and soil temperature over most parts of Eurasia, and in turn, corresponds to less winter snow cover and less snow water equivalent. The persistent less and thinner snow cover from winter to spring over Eurasia, especially over Western and Central Siberia, tends to induce increased surface air temperature through decreased surface albedo and less snowmelt latent heat. Subsequently, the increased surface air temperature corresponding to increased SICBS contributes to higher vegetation <span>growth</span> over Eurasia in spring and vice versa. <span>Based on this linkage, s</span>easonal predictions of spring NDVI over Eurasia are explored by applying the year-to-year increment approach. The prediction models were developed based on the coupled modes of singular value decomposition analyses between Eurasian NDVI and climate factors. One synchronous predictor, the spring surface air temperature from the NCEP<span>’</span>s Climate Forecast System (SAT-CFS), and three previous-season predictors (winter SICBS, winter sea surface temperature over the equatorial Pacific (SSTP), and winter North Atlantic Oscillation (NAO) were chosen to develop four single-predictor schemes: the SAT-CFS scheme, SICBS scheme, SSTP scheme, and NAO scheme. Meanwhile, a statistical scheme that involves the three previous-season predictors (i.e., SICBS, SSTP, and NAO) and a hybrid scheme that includes all four predictors are also proposed. To evaluate the prediction skills of the schemes, one-year-out cross-validation and independent hindcast results are analyzed, revealing the hybrid scheme as having the best prediction skill in terms of both the spatial pattern and the temporal variability of spring Eurasian NDVI.</p>

Seasonal Variability in the Mechanisms Behind the 2020 Siberian Heatwaves

2022 ◽  
pp. 1-44
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Atmospheric Circulation ◽  
Air Temperature ◽  
Land Surface ◽  
Arctic Oscillation ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Stratospheric Polar Vortex

Abstract Record breaking heatwaves and wildfires immersed Siberia during the boreal spring of 2020 following an anomalously warm winter. Springtime heatwaves are becoming more common in the region, with statistically significant trends in the frequency, magnitude, and duration of heatwave events over the past four decades. Mechanisms by which the heatwaves occur and contributing factors differ by season. Winter heatwave frequency is correlated with the atmospheric circulation, particularly the Arctic Oscillation, while the frequency of heatwaves during the spring months is highly correlated with aspects of the land surface including snow cover, albedo, and latent heat flux. Idealized AMIP-style experiments are used to quantify the contribution of suppressed Arctic sea ice and snow cover over Siberia on the atmospheric circulation, surface energy budget, and surface air temperature in Siberia during the winter and spring of 2020. Sea ice concentration contributed to the strength of the stratospheric polar vortex and Arctic Oscillation during the winter months, thereby influencing the tropospheric circulation and surface air temperature over Siberia. Warm temperatures across the region resulted in an earlier than usual recession of the winter snowpack. The exposed land surface contributed to up to 20% of the temperature anomaly during the spring through the albedo feedback and changes in the ratio of the latent and sensible heat fluxes. This, in combination with favorable atmospheric circulation patterns, resulted in record breaking heatwaves in Siberia in the spring of 2020.

scholarly journals Contribution of sea ice albedo and insulation effects to Arctic amplification in the EC-Earth Pliocene simulation

2019 ◽  
Vol 15 (1) ◽  
pp. 291-305 ◽  
Author(s):  
Jianqiu Zheng ◽  
Qiong Zhang ◽  
Qiang Li ◽  
Qiang Zhang ◽  
Ming Cai
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
Response Analysis ◽  
Turbulent Heat ◽  
Arctic Amplification ◽  
Sst Warming

Abstract. In the present work, we simulate the Pliocene climate with the EC-Earth climate model as an equilibrium state for the current warming climate induced by rising CO2 in the atmosphere. The simulated Pliocene climate shows a strong Arctic amplification featuring pronounced warming sea surface temperature (SST) over the North Atlantic, in particular over the Greenland Sea and Baffin Bay, which is comparable to geological SST reconstructions from the Pliocene Research, Interpretation and Synoptic Mapping group (PRISM; Dowsett et al., 2016). To understand the underlying physical processes, the air–sea heat flux variation in response to Arctic sea ice change is quantitatively assessed by a climate feedback and response analysis method (CFRAM) and an approach similar to equilibrium feedback assessment. Given the fact that the maximum SST warming occurs in summer while the maximum surface air temperature warming happens during winter, our analyses show that a dominant ice-albedo effect is the main reason for summer SST warming, and a 1 % loss in sea ice concentration could lead to an approximate 1.8 W m−2 increase in shortwave solar radiation into open sea surface. During the winter months, the insulation effect induces enhanced turbulent heat flux out of the sea surface due to sea ice melting in previous summer months. This leads to more heat released from the ocean to the atmosphere, thus explaining why surface air temperature warming amplification is stronger in winter than in summer.

scholarly journals Contribution of sea-ice albedo and insulation effects to Arctic amplification in the EC-Earth Pliocene simulation

2018 ◽  
Author(s):  
Jianqiu Zheng ◽  
Qiong Zhang ◽  
Qiang Li ◽  
Qiang Zhang ◽  
Ming Cai
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
Response Analysis ◽  
Turbulent Heat ◽  
Arctic Amplification ◽  
Maximum Warming

Abstract. In the present work, we simulate the Pliocene climate with EC-Earth climate model as an analogue for current warming climate induced by massive CO2 in the atmosphere. The simulated Pliocene climate shows a strong Arctic amplification featured by pronounced warming sea surface temperature (SST) over North Atlantic in particular over Greenland Sea and Baffin Bays, which is comparable with geological SST reconstructions from PRISM. To understand the underlying physical processes, the air-sea heat flux variation in response to Arctic sea-ice change is quantitatively assessed by a climate feedback and response analysis method (CFRAM) and an equilibrium feedback assessment (EFA)-like approach. Giving the facts that the maximum warming in SST occurs in summer while the maximum warming in surface air temperature happens during winter, our analyses show that dominant ice-albedo effect is the main reason for summer SST warming, a 1 % loss in sea-ice concentration could lead to an approximate 2 W m-2 increase in shortwave solar radiation into open sea surface. During winter month, the insulation effect induces enhanced turbulent heat flux out of sea surface due to sea-ice melting in previous summer months. This leads to more heat release from the ocean to atmosphere, thus explaining the stronger surface air temperature warming amplification in winter than in summer.

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