New climate models reveal faster and larger increases in Arctic precipitation than previously projected

AbstractAs the Arctic continues to warm faster than the rest of the planet, evidence mounts that the region is experiencing unprecedented environmental change. The hydrological cycle is projected to intensify throughout the twenty-first century, with increased evaporation from expanding open water areas and more precipitation. The latest projections from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) point to more rapid Arctic warming and sea-ice loss by the year 2100 than in previous projections, and consequently, larger and faster changes in the hydrological cycle. Arctic precipitation (rainfall) increases more rapidly in CMIP6 than in CMIP5 due to greater global warming and poleward moisture transport, greater Arctic amplification and sea-ice loss and increased sensitivity of precipitation to Arctic warming. The transition from a snow- to rain-dominated Arctic in the summer and autumn is projected to occur decades earlier and at a lower level of global warming, potentially under 1.5 °C, with profound climatic, ecosystem and socio-economic impacts.

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Accelerated hydrological cycle over the Sanjiangyuan region induces more streamflow extremes at different global warming levels

10.5194/hess-2020-354 ◽

2020 ◽

Author(s):

Peng Ji ◽

Xing Yuan ◽

Feng Ma ◽

Ming Pan

Keyword(s):

Global Warming ◽

Land Surface ◽

Yangtze River ◽

Climate Models ◽

Hydrological Cycle ◽

Yellow River ◽

Coupled Model ◽

Ecological Processes ◽

Intercomparison Project ◽

Streamflow Extremes

Abstract. Serving source water for the Yellow, Yangtze and Lancang-Mekong rivers, the Sanjiangyuan region concerns ~ 700 million people over its downstream areas. Recent research suggests that the Sanjiangyuan region will become wetter in a warming future, but future changes in streamflow extremes remain unclear due to the complex hydrological processes over high-land areas and limited knowledge of the influences of land cover change and CO2 physiological forcing. Based on high resolution land surface modeling during 1979~2100 driven by the climate and ecological projections from 11 newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models, we show that different accelerating rates of precipitation and evapotranspiration at 1.5 °C global warming level induce 55 % more dry extremes over Yellow river and 138 % more wet extremes over Yangtze river headwaters compared with the reference period (1985~2014). An additional 0.5 °C warming leads to a further nonlinear and more significant increase for both dry extremes over Yellow river (22 %) and wet extremes over Yangtze river (64 %). The combined role of CO2 physiological forcing and vegetation greening, which used to be neglected in hydrological projections, is found to alleviate dry extremes at 1.5 and 2.0 °C warming levels but to intensify dry extremes at 3.0 °C warming level. Moreover, vegetation greening contributes half of the differences between 1.5 and 3.0 °C warming levels. This study emphasizes the importance of ecological processes in determining future changes in streamflow extremes, and suggests a dry gets drier, wet gets wetter condition over headwaters.

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Accelerated hydrological cycle over the Sanjiangyuan region induces more streamflow extremes at different global warming levels

Hydrology and Earth System Sciences ◽

10.5194/hess-24-5439-2020 ◽

2020 ◽

Vol 24 (11) ◽

pp. 5439-5451

Author(s):

Peng Ji ◽

Xing Yuan ◽

Feng Ma ◽

Ming Pan

Keyword(s):

Global Warming ◽

Land Surface ◽

Yangtze River ◽

Climate Models ◽

Hydrological Cycle ◽

Yellow River ◽

Coupled Model ◽

Ecological Processes ◽

Intercomparison Project ◽

Streamflow Extremes

Abstract. Serving source water for the Yellow, Yangtze and Lancang-Mekong rivers, the Sanjiangyuan region affects 700 million people over its downstream areas. Recent research suggests that the Sanjiangyuan region will become wetter in a warming future, but future changes of streamflow extremes remain unclear due to the complex hydrological processes over high-land areas and limited knowledge of the influences of land cover change and CO2 physiological forcing. Based on high-resolution land surface modeling during 1979–2100 driven by the climate and ecological projections from 11 newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models, we show that different accelerating rates of precipitation and evapotranspiration at 1.5 ∘C global warming level induce 55 % more dry extremes over Yellow River and 138 % more wet extremes over Yangtze River headwaters compared with the reference period (1985–2014). An additional 0.5 ∘C warming leads to a further nonlinear and more significant increase for both dry extremes over Yellow River (22 %) and wet extremes over Yangtze River (64 %). The combined role of CO2 physiological forcing and vegetation greening, which used to be neglected in hydrological projections, is found to alleviate dry extremes at 1.5 and 2.0 ∘C warming levels but to intensify dry extremes at 3.0 ∘C warming level. Moreover, vegetation greening contributes half of the differences between 1.5 and 3.0 ∘C warming levels. This study emphasizes the importance of ecological processes in determining future changes in streamflow extremes and suggests a “dry gets drier, wet gets wetter” condition over the warming headwaters.

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Observation-based selection of climate models projects Arctic ice-free summers around 2035

Communications Earth & Environment ◽

10.1038/s43247-021-00214-7 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

David Docquier ◽

Torben Koenigk

Keyword(s):

Model Selection ◽

Sea Ice ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Arctic Sea Ice ◽

Global Climate Models ◽

The Arctic ◽

Arctic Sea ◽

Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

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Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽

10.3390/atmos12020174 ◽

2021 ◽

Vol 12 (2) ◽

pp. 174

Author(s):

Günther Heinemann ◽

Sascha Willmes ◽

Lukas Schefczyk ◽

Alexander Makshtas ◽

Vasilii Kustov ◽

...

Keyword(s):

Sea Ice ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Open Water ◽

The Arctic ◽

Late Winter ◽

Good Representation ◽

Hourly Temperature ◽

Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

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Greenhouse-gas contribution to Arctic sea-ice loss

10.5194/egusphere-egu21-3720 ◽

2021 ◽

Author(s):

Yeon-Hee Kim ◽

Seung-Ki Min

Keyword(s):

Sea Ice ◽

Greenhouse Gas ◽

Coupled Model ◽

Arctic Sea Ice ◽

The Arctic ◽

Detection Analysis ◽

External Forcings ◽

Arctic Sea ◽

Intercomparison Project ◽

Arctic Sea Ice Loss

Arctic sea-ice area (ASIA) has been declining rapidly throughout the year during recent decades, but a formal quantification of greenhouse gas (GHG) contribution remains limited. This study conducts an attribution analysis of the observed ASIA changes from 1979 to 2017 by comparing three satellite observations with the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model simulations using an optimal fingerprint method. The observed ASIA exhibits overall decreasing trends across all months with stronger trends in warm seasons. CMIP6 anthropogenic plus natural forcing (ALL) simulations and GHG-only forcing simulations successfully capture the observed temporal trend patterns. Results from detection analysis show that ALL signals are detected robustly for all calendar months for three observations. It is found that GHG signals are detectable in the observed ASIA decrease throughout the year, explaining most of the ASIA reduction, with a much weaker contribution by other external forcings. We additionally find that the Arctic Ocean will occur ice-free in September around the 2040s regardless of the emission scenario.

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CMIP5 Projections of Arctic Amplification, of the North American/North Atlantic Circulation, and of Their Relationship

Journal of Climate ◽

10.1175/jcli-d-14-00589.1 ◽

2015 ◽

Vol 28 (13) ◽

pp. 5254-5271 ◽

Cited By ~ 112

Author(s):

Elizabeth A. Barnes ◽

Lorenzo M. Polvani

Keyword(s):

North Atlantic ◽

Climate Models ◽

Coupled Model ◽

Arctic Region ◽

The Arctic ◽

Cmip5 Models ◽

Arctic Amplification ◽

Arctic Warming ◽

The North ◽

Sequence Of Events

Abstract Recent studies have hypothesized that Arctic amplification, the enhanced warming of the Arctic region compared to the rest of the globe, will cause changes in midlatitude weather over the twenty-first century. This study exploits the recently completed phase 5 of the Coupled Model Intercomparison Project (CMIP5) and examines 27 state-of-the-art climate models to determine if their projected changes in the midlatitude circulation are consistent with the hypothesized impact of Arctic amplification over North America and the North Atlantic. Under the largest future greenhouse forcing (RCP8.5), it is found that every model, in every season, exhibits Arctic amplification by 2100. At the same time, the projected circulation responses are either opposite in sign to those hypothesized or too widely spread among the models to discern any robust change. However, in a few seasons and for some of the circulation metrics examined, correlations are found between the model spread in Arctic amplification and the model spread in the projected circulation changes. Therefore, while the CMIP5 models offer some evidence that future Arctic warming may be able to modulate some aspects of the midlatitude circulation response in some seasons, the analysis herein leads to the conclusion that the net circulation response in the future is unlikely to be determined solely—or even primarily—by Arctic warming according to the sequence of events recently hypothesized.

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Evaluation of Arctic warming in mid-Pliocene climate simulations

10.5194/cp-2020-64 ◽

2020 ◽

Cited By ~ 1

Author(s):

Wesley de Nooijer ◽

Qiong Zhang ◽

Qiang Li ◽

Qiang Zhang ◽

Xiangyu Li ◽

...

Keyword(s):

Sea Ice ◽

Climate Models ◽

Future Climate ◽

The Arctic ◽

Future Climate Change ◽

Sea Ice Extent ◽

Current Form ◽

Arctic Warming ◽

Amplification Ratio ◽

Climate Simulations

Abstract. Palaeoclimate simulations improve our understanding of the climate, inform us about the performance of climate models in a different climate scenario, and help to identify robust features of the climate system. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), derived from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2). The PlioMIP2 ensemble simulates Arctic (60–90° N) annual mean surface air temperature (SAT) increases of 3.7 to 11.6 °C compared to the pre-industrial, with a multi-model mean (MMM) increase of 7.2 °C. The Arctic warming amplification ratio relative to global SAT anomalies in the ensemble ranges from 1.8 to 3.1 (MMM is 2.3). Sea ice extent anomalies range from −3.0 to −10.4 × 06 km2 with a MMM anomaly of −5.6 × 106 km2, which constitutes a decrease of 53 % compared to the pre-industrial. The majority (11 out of 16) models simulate summer sea ice-free conditions (≤ 1 × 06 km2) in their mPWP simulation. The ensemble tends to underestimate SAT in the Arctic when compared to available reconstructions. The simulations with the highest Arctic SAT anomalies tend to match the proxy dataset in its current form better. The ensemble shows some agreement with reconstructions of sea ice, particularly with regards to seasonal sea ice. Large uncertainties limit the confidence that can be placed in the findings and the compatibility of the different proxy datasets. We show that, while reducing uncertainties in the reconstructions could decrease the SAT data-model discord substantially, further improvements are likely to be found in enhanced boundary conditions or model physics. Lastly, we compare the Arctic warming in the mPWP to projections of future Arctic warming and find that the PlioMIP2 ensemble simulates greater Arctic amplification, an increase instead of a decrease in AMOC strength compared to pre-industrial, and a lesser strengthening of northern modes of variability than CMIP5 future climate simulations. The results highlight the importance of slow feedbacks in equilibrium climate simulations, and that caution must be taken when using simulations of the mPWP as an analogue for future climate change.

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Refinement of future Arctic sea-ice projections

10.21203/rs.3.rs-223865/v1 ◽

2021 ◽

Author(s):

David Docquier ◽

Torben Koenigk

Keyword(s):

Model Selection ◽

Sea Ice ◽

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Arctic Sea Ice ◽

Global Climate Models ◽

The Arctic ◽

Arctic Sea ◽

Area And Volume

Abstract Arctic sea ice has been retreating at unprecedented pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) in order to reduce these uncertainties. We select the models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to smaller Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of the future Arctic sea-ice loss when including all models.

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Perspectives on future sea ice and navigability in the Arctic

The Cryosphere ◽

10.5194/tc-15-5473-2021 ◽

2021 ◽

Vol 15 (12) ◽

pp. 5473-5482

Author(s):

Jinlei Chen ◽

Shichang Kang ◽

Wentao Du ◽

Junming Guo ◽

Min Xu ◽

...

Keyword(s):

Sea Ice ◽

Coupled Model ◽

Open Water ◽

Circulation Pattern ◽

The Arctic ◽

Sea Ice Concentration ◽

Sea Ice Extent ◽

Sea Ice Thickness ◽

Transportation Accessibility ◽

Decadal Rate

Abstract. The retreat of sea ice has been found to be very significant in the Arctic under global warming. It is projected to continue and will have great impacts on navigation. Perspectives on the changes in sea ice and navigability are crucial to the circulation pattern and future of the Arctic. In this investigation, the decadal changes in sea ice parameters were evaluated by the multi-model from the Coupled Model Inter-comparison Project Phase 6, and Arctic navigability was assessed under two shared socioeconomic pathways (SSPs) and two vessel classes with the Arctic transportation accessibility model. The sea ice extent shows a high possibility of decreasing along SSP5-8.5 under current emissions and climate change. The decadal rate of decreasing sea ice extent will increase in March but decrease in September until 2060, when the oldest ice will have completely disappeared and the sea ice will reach an irreversible tipping point. Sea ice thickness is expected to decrease and transit in certain parts, declining by −0.22 m per decade after September 2060. Both the sea ice concentration and volume will thoroughly decline at decreasing decadal rates, with a greater decrease in volume in March than in September. Open water ships will be able to cross the Northern Sea Route and Northwest Passage between August and October during the period from 2045 to 2055, with a maximum navigable percentage in September. The time for Polar Class 6 (PC6) ships will shift to October–December during the period from 2021 to 2030, with a maximum navigable percentage in October. In addition, the central passage will be open for PC6 ships between September and October during 2021–2030.

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Antarctic sea ice decline delayed well into the 21st century in a high-resolution climate projection

10.5194/egusphere-egu2020-20837 ◽

2020 ◽

Author(s):

Thomas Rackow ◽

Sergey Danilov ◽

Helge F. Goessling ◽

Hartmut H. Hellmer ◽

Dmitry V. Sein ◽

...

Keyword(s):

Global Warming ◽

High Resolution ◽

Sea Ice ◽

Climate Models ◽

Climate Model ◽

The Arctic ◽

Alternative Mechanism ◽

Sea Ice Extent ◽

Antarctic Sea Ice ◽

Sea Ice Decline

Despite ongoing global warming and strong sea ice decline in the Arctic, the sea ice extent around the Antarctic continent has not declined during the satellite era since 1979. This is in stark contrast to existing climate models that tend to show a strong negative sea ice trend for the same period; hence the confidence in projected Antarctic sea-ice changes is considered to be low. In the years since 2016, there has been significantly lower Antarctic sea ice extent, which some consider a sign of imminent change; however, others have argued that sea ice extent is expected to regress to the weak decadal trend in the near future.In this presentation, we show results from climate change projections with a new climate model that allows the simulation of mesoscale eddies in dynamically active ocean regions in a computationally efficient way. We find that the high-resolution configuration (HR) favours periods of stable Antarctic sea ice extent in September as observed over the satellite era. Sea ice is not projected to decline well into the 21st century in the HR simulations, which is similar to the delaying effect of, e.g., added glacial melt water in recent studies. The HR ocean configurations simulate an ocean heat transport that responds differently to global warming and is more efficient at moderating the anthropogenic warming of the Southern Ocean. As a consequence, decrease of Antarctic sea ice extent is significantly delayed, in contrast to what existing coarser-resolution climate models predict.Other explanations why current models simulate a non-observed decline of Antarctic sea-ice have been put forward, including the choice of included sea ice physics and underestimated simulated trends in westerly winds. Our results provide an alternative mechanism that might be strong enough to explain the gap between modeled and observed trends alone.

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