scholarly journals Snow on Arctic sea ice: model representation and last decade changes

2015 ◽  
Vol 9 (5) ◽  
pp. 5681-5718 ◽  
Author(s):  
K. Castro-Morales ◽  
R. Ricker ◽  
R. Gerdes

Abstract. Together with sea ice, Arctic snow has experienced vast changes during the last decade due to a warming climate. Thus, it is relevant to study the past and present changes of Arctic snow to understand the implications to the sea ice component, precipitation, heat and radiation budgets. In this study, we analyze the changes of snow depth between 2000 and 2013 at regional scale represented in an Arctic coupled sea ice-general circulation model. We evaluate the model performance by direct comparison of the modeled snow depths (hs_mod) to snow depths from radar measurements from the NASA Operation IceBridge (hs_OIB) during the flight campaigns completed from 2009 to 2013. Despite the description of the snow in our model is simple (i.e. single layer without explicit snow redistribution processes) as in many current sea-ice models; the latitudinal distribution of hs_mod in the western Arctic is in good agreement to observations. The hs_mod is on average 3 cm thicker than hs_OIB in latitudes > 76° N. According to the model results, the hs in 2013 decreased 21 % with respect to the multi-year mean between 2000 and 2013. This snow reduction occurred mainly in FYI dominated areas, and is in good agreement to the year-to-year loss of sea ice, also well reproduced by the model. In a simple snow mass budget, our results show that 65 % of the yearly accumulated snow is lost by sublimation and snowmelt due to the heat transfer between the snow/ice interface and the atmosphere. Although the snow layer accumulates again every year, the long-term reduction in the summer sea-ice extent ultimately affects the maximum spring accumulation of snow. The model results exhibit a last decade thinning of the snowpack that is however one order of magnitude lower than previous estimates based on radar measurements. We suggest that the later is partially due to the lack of explicit snow redistribution processes in the model, emphasizing the need to include these in current sea-ice models to improve the snow representations.

2013 ◽  
Vol 26 (16) ◽  
pp. 6092-6104 ◽  
Author(s):  
Matthieu Chevallier ◽  
David Salas y Mélia ◽  
Aurore Voldoire ◽  
Michel Déqué ◽  
Gilles Garric

Abstract An ocean–sea ice model reconstruction spanning the period 1990–2009 is used to initialize ensemble seasonal forecasts with the Centre National de Recherches Météorologiques Coupled Global Climate Model version 5.1 (CNRM-CM5.1) coupled atmosphere–ocean general circulation model. The aim of this study is to assess the skill of fully initialized September and March pan-Arctic sea ice forecasts in terms of climatology and interannual anomalies. The predictions are initialized using “full field initialization” of each component of the system. In spite of a drift due to radiative biases in the coupled model during the melt season, the full initialization of the sea ice cover on 1 May leads to skillful forecasts of the September sea ice extent (SIE) anomalies. The skill of the prediction is also significantly high when considering anomalies of the SIE relative to the long-term linear trend. It confirms that the anomaly of spring sea ice cover in itself plays a role in preconditioning a September SIE anomaly. The skill of predictions for March SIE initialized on 1 November is also encouraging, and it can be partly attributed to persistent features of the fall sea ice cover. The present study gives insight into the current ability of state-of-the-art coupled climate systems to perform operational seasonal forecasts of the Arctic sea ice cover up to 5 months in advance.


2016 ◽  
Author(s):  
Douglas G. MacMartin ◽  
Ben Kravitz

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.


2012 ◽  
Vol 6 (6) ◽  
pp. 1383-1394 ◽  
Author(s):  
F. Massonnet ◽  
T. Fichefet ◽  
H. Goosse ◽  
C. M. Bitz ◽  
G. Philippon-Berthier ◽  
...  

Abstract. We examine the recent (1979–2010) and future (2011–2100) characteristics of the summer Arctic sea ice cover as simulated by 29 Earth system and general circulation models from the Coupled Model Intercomparison Project, phase 5 (CMIP5). As was the case with CMIP3, a large intermodel spread persists in the simulated summer sea ice losses over the 21st century for a given forcing scenario. The 1979–2010 sea ice extent, thickness distribution and volume characteristics of each CMIP5 model are discussed as potential constraints on the September sea ice extent (SSIE) projections. Our results suggest first that the future changes in SSIE with respect to the 1979–2010 model SSIE are related in a complicated manner to the initial 1979–2010 sea ice model characteristics, due to the large diversity of the CMIP5 population: at a given time, some models are in an ice-free state while others are still on the track of ice loss. However, in phase plane plots (that do not consider the time as an independent variable), we show that the transition towards ice-free conditions is actually occurring in a very similar manner for all models. We also find that the year at which SSIE drops below a certain threshold is likely to be constrained by the present-day sea ice properties. In a second step, using several adequate 1979–2010 sea ice metrics, we effectively reduce the uncertainty as to when the Arctic could become nearly ice-free in summertime, the interval [2041, 2060] being our best estimate for a high climate forcing scenario.


2011 ◽  
Vol 4 (2) ◽  
pp. 483-509 ◽  
Author(s):  
S. J. Phipps ◽  
L. D. Rotstayn ◽  
H. B. Gordon ◽  
J. L. Roberts ◽  
A. C. Hirst ◽  
...  

Abstract. The CSIRO Mk3L climate system model is a coupled general circulation model, designed primarily for millennial-scale climate simulations and palaeoclimate research. Mk3L includes components which describe the atmosphere, ocean, sea ice and land surface, and combines computational efficiency with a stable and realistic control climatology. This paper describes the model physics and software, analyses the control climatology, and evaluates the ability of the model to simulate the modern climate. Mk3L incorporates a spectral atmospheric general circulation model, a z-coordinate ocean general circulation model, a dynamic-thermodynamic sea ice model and a land surface scheme with static vegetation. The source code is highly portable, and has no dependence upon proprietary software. The model distribution is freely available to the research community. A 1000-yr climate simulation can be completed in around one-and-a-half months on a typical desktop computer, with greater throughput being possible on high-performance computing facilities. Mk3L produces realistic simulations of the larger-scale features of the modern climate, although with some biases on the regional scale. The model also produces reasonable representations of the leading modes of internal climate variability in both the tropics and extratropics. The control state of the model exhibits a high degree of stability, with only a weak cooling trend on millennial timescales. Ongoing development work aims to improve the model climatology and transform Mk3L into a comprehensive earth system model.


2017 ◽  
Vol 30 (11) ◽  
pp. 3945-3962 ◽  
Author(s):  
James A. Screen

Abstract The loss of Arctic sea ice is already having profound environmental, societal, and ecological impacts locally. A highly uncertain area of scientific research, however, is whether such Arctic change has a tangible effect on weather and climate at lower latitudes. There is emerging evidence that the geographical location of sea ice loss is critically important in determining the large-scale atmospheric circulation response and associated midlatitude impacts. However, such regional dependencies have not been explored in a thorough and systematic manner. To make progress on this issue, this study analyzes ensemble simulations with an atmospheric general circulation model prescribed with sea ice loss separately in nine regions of the Arctic, to elucidate the distinct responses to regional sea ice loss. The results suggest that in some regions, sea ice loss triggers large-scale dynamical responses, whereas in other regions sea ice loss induces only local thermodynamical changes. Sea ice loss in the Barents–Kara Seas is unique in driving a weakening of the stratospheric polar vortex, followed in time by a tropospheric circulation response that resembles the North Atlantic Oscillation. For October–March, the largest spatial-scale responses are driven by sea ice loss in the Barents–Kara Seas and the Sea of Okhotsk; however, different regions assume greater importance in other seasons. The atmosphere responds very differently to regional sea ice losses than to pan-Arctic sea ice loss, and the response to pan-Arctic sea ice loss cannot be obtained by the linear addition of the responses to regional sea ice losses. The results imply that diversity in past studies of the simulated response to Arctic sea ice loss can be partly explained by the different spatial patterns of sea ice loss imposed.


2016 ◽  
Author(s):  
Manabu Abe ◽  
Toru Nozawa ◽  
Tomoo Ogura ◽  
Kumiko Takata

Abstract. This study investigates the effect of sea ice reduction on Arctic cloud cover in historical simulations with the coupled Atmosphere-Ocean general circulation model MIROC5. Arctic sea ice has been shown to exhibit substantial reductions under simulated global warming conditions since the 1970s, particularly in September. This simulated reduction is consistent with satellite observation results. However, Arctic cloud cover increases significantly during October, leading to extensive reductions in sea ice because of the enhanced heat and moisture fluxes from the underlying ocean. Sensitivity experiments with the atmospheric model MIROC5 clearly show that sea ice reduction causes increased cloud cover. Increased cloud cover occurs primarily in the lower troposphere; however, clouds in the thin surface layers directly above the ocean decrease despite the increased moisture flux because the surface air temperature rises in these thin layers, causing the relative humidity to decrease. As cloud cover increases, the cloud radiative effect cause an increase in the surface downward longwave radiation (DLR) by approximately 40–60 % compared with changes in clear-sky surface DLR in fall. These results suggest that an increase in Arctic cloud cover as a result of reduced sea ice coverage may further melt the sea ice and enhance the feedback processes of Arctic warming.


2012 ◽  
Vol 6 (4) ◽  
pp. 2931-2959 ◽  
Author(s):  
F. Massonnet ◽  
T. Fichefet ◽  
H. Goosse ◽  
C. M. Bitz ◽  
G. Philippon-Berthier ◽  
...  

Abstract. We examine the recent (1979–2010) and future (2011–2100) characteristics of the summer Arctic sea ice cover as simulated by 29 Earth system and general circulation models from the Coupled Model Intercomparison Project, phase 5 (CMIP5). As was the case with CMIP3, a large inter-model spread persists in the simulated summer sea ice losses over the 21st century for a given forcing scenario. The initial 1979–2010 sea ice properties (including the sea ice extent, thickness distribution and volume characteristics) of each CMIP5 model are discussed as potential constraints on the September sea ice extent (SSIE) projections. Our results suggest first that the SSIE anomalies (compared to the 1979–2010 model SSIE) are related in a complicated manner to the initial 1979–2010 sea ice model characteristics, due to the large diversity of the CMIP5 population (at a given time, some models are in an ice-free state while others are still on the track of ice loss). In a new diagram (that does not consider the time as an independent variable) we show that the transition towards ice-free conditions is actually occuring in a very similar manner for all models. For these reasons, some quantities that do not explicitly depend on time, such as the year at which SSIE drops below a certain threshold, are likely to be constrained. In a second step, using several adequate 1979–2010 sea ice metrics, we effectively reduce the uncertainty as to when the Arctic could become nearly ice-free in summertime (between 2041 and 2060 for a high climate forcing scenario).


2020 ◽  
Vol 6 (36) ◽  
pp. eaaz9588
Author(s):  
Miriam C. Jones ◽  
Max Berkelhammer ◽  
Katherine J. Keller ◽  
Kei Yoshimura ◽  
Matthew J. Wooller

Anomalously low winter sea ice extent and early retreat in CE 2018 and 2019 challenge previous notions that winter sea ice in the Bering Sea has been stable over the instrumental record, although long-term records remain limited. Here, we use a record of peat cellulose oxygen isotopes from St. Matthew Island along with isotope-enabled general circulation model (IsoGSM) simulations to generate a 5500-year record of Bering Sea winter sea ice extent. Results show that over the last 5500 years, sea ice in the Bering Sea decreased in response to increasing winter insolation and atmospheric CO2, suggesting that the North Pacific is highly sensitive to small changes in radiative forcing. We find that CE 2018 sea ice conditions were the lowest of the last 5500 years, and results suggest that sea ice loss may lag changes in CO2 concentrations by several decades.


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