Quantifying Arctic Storm Risk in a Changing Climate

2021 ◽  
Author(s):  
Alexander Vessey ◽  
Kevin Hodges ◽  
Len Shaffrey ◽  
Jonathan Day
Keyword(s):  
Climate Models ◽  
Relative Vorticity ◽  
Horizontal Resolution ◽  
Future Climate ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Sea Level Pressure ◽  
Tracking Method ◽  
Storm Tracking ◽  
Storm Characteristics

<p>The Arctic has undergone significant change over the past few decades, and there has been great reductions in Arctic sea ice extent. The Arctic ocean has become more accessible, and this has allowed for more human activity in the Arctic.  The risk of storms impacting human activities in the Arctic has consequently increased, and as sea ice extent continues to decline in the near-future, the risk of storms impacting human activities in the Arctic is likely to increase further.  In this study, the present climatology of Arctic storms is evaluated between modern reanalysis datasets, and the future climatology of Arctic storms is also evaluated in climate model simulations.</p><p>There are multiple reanalysis datasets available from different institutions, which each give an approximation of past atmospheric conditions over the last few decades.  In addition, there are multiple storm tracking methods, which may impact the climatology of Arctic storms that is identified in a reanalysis datasets.  In this study, we aimed to improve the understanding of Arctic storms by assessing their characteristics in multiple global reanalyses, the ECMWF-Interim Reanalysis (ERA-Interim), the 55-Year Japanese Reanalysis (JRA-55), the NASA-Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2), and the NCEP-Climate Forecast System Reanalysis (NCEP-CFSR), using the same storm tracking method based on 850 hPa relative vorticity and mean sea level pressure.  In addition, the response of Arctic storms to climate change has been evaluated in the UPSCALE climate simulations, and the affect of horizontal resolution on the representation of future Arctic storminess has been assessed.</p><p>The results show that there are no significant trends in Arctic storm characteristics between 1980-2017, even though the Arctic has undergone rapid change.  Although some similar Arctic storm characteristics are found between the reanalysis datasets, there are generally higher differences between the reanalyses in winter (DJF) than in summer (JJA).  In addition, substantial differences can arise between using the same storm tracking method based on 850 hPa relative vorticity or mean sea level pressure, which adds to the uncertainty associated with current Arctic storm characteristics.</p><p>The results also show that Arctic storms will change significantly in a future climate, particularly in their spatial distribution.  Differences have been found between the future simulations of Arctic storms between an ensemble of high resolution climate models (25km) and low resolution climate models (130km), which adds uncertainty to how Arctic storms may change in a future climate.  The possible reasons for why the representation of future climate Arctic storms may be different in climate models of differing horizontal resolution has been explored.</p>

scholarly journals An Inter-Comparison of Arctic Synoptic Scale Storms between Four Global Reanalysis Datasets

2020 ◽  
Author(s):  
Alexander Vessey ◽  
Kevin Hodges ◽  
Len Shaffrey ◽  
Jonathan Day
Keyword(s):  
Sea Level ◽  
Relative Vorticity ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Tracking Method ◽  
Level Pressure ◽  
Storm Tracking ◽  
Storm Characteristics

<p>Arctic sea ice has reduced significantly over recent decades and is projected to reduce further over this century. This has made the Arctic more accessible and increased opportunities for the expansion of business and industrial activities.  As a result, the exposure and risk of humans and infrastructure to extreme storms will increase in the Arctic.</p><p>Our understanding of the current risk from storms comes from analysing the past, for example, by using storm tracking algorithms to detect storms in reanalysis datasets.  However, there are multiple reanalysis datasets available from different institutions and there are multiple storm tracking methods.  Previous studies have found that there can be differences between reanalysis datasets and between storm tracking methods in the climatology of storms, particularly in mid-latitude regions rather than the Arctic.  In this study, we aimed to improve the understanding of Arctic storms by assessing their characteristics in multiple global reanalyses, the ECMWF-Interim Reanalysis (ERA-Interim), the 55-Year Japanese Reanalysis (JRA-55), the NASA-Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2), and the NCEP-Climate Forecast System Reanalysis (NCEP-CFSR), using the same storm tracking method based on 850 hPa relative vorticity and mean sea level pressure.</p><p>The results from this study show that there are no significant trends in Arctic storm characteristics between 1980-2017, even though the Arctic has undergone rapid change.  Although some similar Arctic storm characteristics are found between the reanalysis datasets, there are generally higher differences between the reanalyses in winter (DJF) than in summer (JJA).  In addition, substantial differences can arise between using the same storm tracking method based on 850 hPa relative vorticity or mean sea level pressure, which adds to the uncertainty associated with current Arctic storm characteristics.</p>

scholarly journals Evaluation of Arctic warming in mid-Pliocene climate simulations

2020 ◽  
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.

scholarly journals Evaluation of Arctic warming in mid-Pliocene climate simulations

2020 ◽  
Vol 16 (6) ◽  
pp. 2325-2341
Author(s):  
Wesley de Nooijer ◽  
Qiong Zhang ◽  
Qiang Li ◽  
Qiang Zhang ◽  
Xiangyu Li ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Meridional Overturning Circulation ◽  
Future Climate ◽  
The Arctic ◽  
Future Climate Change ◽  
Sea Ice Extent ◽  
Current Form ◽  
Arctic Warming ◽  
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 period, 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 -10.4×106 km2, with a MMM anomaly of -5.6×106 km2, which constitutes a decrease of 53 % compared to the pre-industrial period. The majority (11 out of 16) of models simulate summer sea-ice-free conditions (≤1×106 km2) in their mPWP simulation. The ensemble tends to underestimate SAT in the Arctic when compared to available reconstructions, although the degree of underestimation varies strongly between the simulations. 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 regard 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 than CMIP5 future climate simulations and an increase instead of a decrease in Atlantic Meridional Overturning Circulation (AMOC) strength compared to pre-industrial period. 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.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

Sea ice and atmosphere interactions and predictability: preliminary results using HadGEM3

2020 ◽  
Author(s):  
Daniela Flocco ◽  
Ed Hawkins ◽  
Leandro Ponsoni ◽  
Francois Massonnet ◽  
Daniel Feltham ◽  
...  
Keyword(s):  
Sea Ice ◽  
Initial Conditions ◽  
Complete Information ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Sea Level Pressure ◽  
Sea Ice Thickness ◽  
Climate Forecasts ◽  
Ice Conditions

<p>Arctic sea ice extent has steadily declined in the past 30 years. Aside from the global impact on climate change, regional information on the sea ice presence and on its impact on oceanic and atmospheric patterns has witnessed a growing interest. There is a growing need for seasonal-to-decadal timescale climate forecasts to help inform local communities and industry stakeholders.</p><p>Here we examine the influence of sea-ice thickness observations on the predictability of the sea-ice and atmospheric circulation. We perform paired sets of ensembles with the HadGEM3 GCM starting from different initial conditions in a present-day control run. One set of ensembles start with complete information about the sea-ice conditions, and one set have degraded information. We investigate how the pairs of ensembles predict the subsequent evolution of the sea-ice, sea level pressure and circulation within the Arctic and beyond with the aim of quantifying the value of sea-ice observations for improving predictions.</p>

scholarly journals Assessment of sea ice simulations in the CMIP5 models

2015 ◽  
Vol 9 (1) ◽  
pp. 399-409 ◽  
Author(s):  
Q. Shu ◽  
Z. Song ◽  
F. Qiao
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Linear Trend ◽  
Ocean Modeling ◽  
The Arctic ◽  
Cmip5 Models ◽  
Output Data ◽  
Sea Ice Extent ◽  
The Antarctic ◽  
Assimilation System

Abstract. The historical simulations of sea ice during 1979 to 2005 by the Coupled Model Intercomparison Project Phase 5 (CMIP5) are compared with satellite observations, Global Ice-Ocean Modeling and Assimilation System (GIOMAS) output data and Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) output data in this study. Forty-nine models, almost all of the CMIP5 climate models and earth system models with historical simulation, are used. For the Antarctic, multi-model ensemble mean (MME) results can give good climatology of sea ice extent (SIE), but the linear trend is incorrect. The linear trend of satellite-observed Antarctic SIE is 1.29 (±0.57) × 105 km2 decade−1; only about 1/7 CMIP5 models show increasing trends, and the linear trend of CMIP5 MME is negative with the value of −3.36 (±0.15) × 105 km2 decade−1. For the Arctic, both climatology and linear trend are better reproduced. Sea ice volume (SIV) is also evaluated in this study, and this is a first attempt to evaluate the SIV in all CMIP5 models. Compared with the GIOMAS and PIOMAS data, the SIV values in both the Antarctic and the Arctic are too small, especially for the Antarctic in spring and winter. The GIOMAS Antarctic SIV in September is 19.1 × 103 km3, while the corresponding Antarctic SIV of CMIP5 MME is 13.0 × 103 km3 (almost 32% less). The Arctic SIV of CMIP5 in April is 27.1 × 103 km3, which is also less than that from PIOMAS SIV (29.5 × 103 km3). This means that the sea ice thickness simulated in CMIP5 is too thin, although the SIE is fairly well simulated.

scholarly journals The efficient global primitive equation climate model SPEEDO

2009 ◽  
Vol 2 (2) ◽  
pp. 1115-1155 ◽  
Author(s):  
C. A. Severijns ◽  
W. Hazeleger
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
State Of The Art ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
Future Climate ◽  
Wave Number ◽  
Future Climate Change ◽  
Change Scenario ◽  
Primitive Equation

Abstract. The efficient primitive-equation coupled atmosphere-ocean model SPEEDO is presented. The model includes an interactive sea-ice and land component. SPEEDO is a global earth system model of intermediate complexity. It has a horizontal resolution of T30 (triangular truncation at wave number 30) and 8 vertical layers in the atmosphere, and a horizontal resolution of 2 degrees and 20 levels in the ocean. The parameterizations in SPEEDO are developed in such a way that it is a fast model suitable for large ensembles or long runs on a workstation. The model has no flux correction. We compare the mean state and inter-annual variability of the model with observational fields of the atmosphere and ocean. In particular the atmospheric circulation, the mid-latitude patterns of variability and teleconnections from the tropics are well simulated. To show the model's capabilities, we performed a long control run and an ensemble experiment with enhanced greenhouse gasses. The long control run shows that the model is stable. CO2 doubling and future climate change scenario experiments show a climate sensitivity of 1.84 K W−1 m−2, which is within the range of state-of-the-art climate models. The spatial response patterns are comparable to state-of-the-art, higher resolution models. However, for very high greenhouse concentrations the parameterizations are not valid. We conclude that the model is suitable for past, current and future climate simulations and for exploring wide parameter ranges and mechanisms of variability. However, as with any model, users should be careful when using the model beyond the range of physical realism of the parameterizations and model setup.

scholarly journals September Arctic Sea Ice minimum prediction – a new skillful statistical approach

2018 ◽  
Author(s):  
Monica Ionita ◽  
Klaus Grosfeld ◽  
Patrick Scholz ◽  
Renate Treffeisen ◽  
Gerrit Lohmann
Keyword(s):  
Sea Ice ◽  
Statistical Model ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Sea Ice Extent ◽  
Important Indicator ◽  
Predictive Skill

Abstract. Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

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

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

<p>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.</p><p>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 21<sup>st</sup> 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.</p><p>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.</p>

scholarly journals A Regime Shift in Seasonal Total Antarctic Sea Ice Extent in the 20th Century

2021 ◽  
Author(s):  
Ryan Fogt ◽  
Amanda Sleinkofer ◽  
Marilyn Raphael ◽  
Mark Handcock
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Climate Models ◽  
Historical Context ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Coupled Climate Models ◽  
High Degree ◽  
The Antarctic

Abstract In stark contrast to the Arctic, there have been statistically significant positive trends in total Antarctic sea ice extent since 1979, despite a sudden decline in sea ice in 2016(1–5) and increasing greenhouse gas concentrations. Attributing Antarctic sea ice trends is complicated by the fact that most coupled climate models show negative trends in sea ice extent since 1979, opposite of that observed(6–8). Additionally, the short record of sea ice extent (beginning in 1979), coupled with the high degree of interannual variability, make the record too short to fully understand the historical context of these recent changes(9). Here we show, using new robust observation-based reconstructions, that 1) these observed recent increases in Antarctic sea ice extent are unique in the context of the 20th century and 2) the observed trends are juxtaposed against statistically significant decreases in sea ice extent throughout much of the early and middle 20th century. These reconstructions are the first to provide reliable estimates of total sea ice extent surrounding the continent; previous proxy-based reconstructions are limited(10). Importantly, the reconstructions continue to show the high degree of interannual Antarctic sea ice extent variability that is marked with frequent sudden changes, such as observed in 2016, which stress the importance of a longer historical context when assessing and attributing observed trends in Antarctic climate(9). Our reconstructions are skillful enough to be used in climate models to allow better understanding of the interconnected nature of the Antarctic climate system and to improve predictions of the future state of Antarctic climate.

Sign in / Sign up

Export Citation Format

Share Document