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 Benefits of Increasing the Model Resolution for the Seasonal Forecast Quality in EC-Earth

2016 ◽  
Vol 29 (24) ◽  
pp. 9141-9162 ◽  
Author(s):  
C. Prodhomme ◽  
L. Batté ◽  
F. Massonnet ◽  
P. Davini ◽  
O. Bellprat ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
System Development ◽  
Essential Feature ◽  
Seasonal Prediction ◽  
Arctic Sea Ice ◽  
Forecast System ◽  
Sea Ice Extent ◽  
The Pacific ◽  
Realistic Representation

Abstract Resolution in climate models is thought to be an important factor for advancing seasonal prediction capability. To test this hypothesis, seasonal ensemble reforecasts are conducted over 1993–2009 with the European community model EC-Earth in three configurations: standard resolution (~1° and ~60 km in the ocean and atmosphere models, respectively), intermediate resolution (~0.25° and ~60 km), and high resolution (~0.25° and ~39 km), the two latter configurations being used without any specific tuning. The model systematic biases of 2-m temperature, sea surface temperature (SST), and wind speed are generally reduced. Notably, the tropical Pacific cold tongue bias is significantly reduced, the Somali upwelling is better represented, and excessive precipitation over the Indian Ocean and over the Maritime Continent is decreased. In terms of skill, tropical SSTs and precipitation are better reforecasted in the Pacific and the Indian Oceans at higher resolutions. In particular, the Indian monsoon is better predicted. Improvements are more difficult to detect at middle and high latitudes. Still, a slight improvement is found in the prediction of the winter North Atlantic Oscillation (NAO) along with a more realistic representation of atmospheric blocking. The sea ice extent bias is unchanged, but the skill of the reforecasts increases in some cases, such as in summer for the pan-Arctic sea ice. All these results emphasize the idea that the resolution increase is an essential feature for forecast system development. At the same time, resolution alone cannot tackle all the forecast system deficiencies and will have to be implemented alongside new physical improvements to significantly push the boundaries of seasonal prediction.

scholarly journals SEAS5: The new ECMWF seasonal forecast system

2018 ◽  
Author(s):  
Stephanie J. Johnson ◽  
Timothy N. Stockdale ◽  
Laura Ferranti ◽  
Magdalena Alonso Balmaseda ◽  
Franco Molteni ◽  
...  
Keyword(s):  
Sea Ice ◽  
Decadal Variability ◽  
Seasonal Forecast ◽  
Arctic Sea Ice ◽  
Prediction Skill ◽  
The Arctic ◽  
Western Boundary ◽  
Forecast System ◽  
Enso Prediction ◽  
Ice Model

Abstract. In this paper we describe SEAS5, ECMWF’s fifth generation seasonal forecast system, which became operational in November 2017. Compared to its predecessor, System 4, SEAS5 is a substantially changed forecast system. It includes upgraded versions of the atmosphere and ocean models at higher resolutions, and adds a prognostic sea ice model. Here, we describe the configuration of SEAS5 and summarise the most noticeable results from a set of diagnostics including biases, variability, teleconnections and forecast skill. An important improvement in SEAS5 is the reduction of the Equatorial Pacific cold tongue bias, which is accompanied by a more realistic ENSO amplitude and an improvement in ENSO prediction skill over the central-west Pacific. Improvements in two-metre temperature skill are also clear over the tropical Pacific. SST biases in the northern extratropics change due to increased ocean resolution, especially in regions associated with western boundary currents. The increased ocean resolution exposes a new problem in the northwest Atlantic, where SEAS5 fails to capture decadal variability of the North Atlantic subpolar gyre, resulting in a degradation of DJF two-metre temperature prediction skill in this region. The prognostic sea ice model improves seasonal predictions of sea ice cover, although some regions and seasons suffer from biases introduced by employing a fully dynamical model rather than the simple, empirical scheme used in System 4. There are also improvements in two-metre temperature skill in the vicinity of the Arctic sea-ice edge. Cold temperature biases in the troposphere improve, but increase at the tropopause. Biases in the extratropical jets are larger than in System 4: extratropical jets are too strong, and displaced northwards in summer. In summary, development and added complexity since System 4 has ensured SEAS5 is a state-of-the-art seasonal forecast system which continues to display a particular strength in ENSO prediction.

scholarly journals Modulation of Arctic Sea Ice Loss by Atmospheric Teleconnections from Atlantic Multidecadal Variability

2019 ◽  
Vol 32 (5) ◽  
pp. 1419-1441 ◽  
Author(s):  
Frederic S. Castruccio ◽  
Yohan Ruprich-Robert ◽  
Stephen G. Yeager ◽  
Gokhan Danabasoglu ◽  
Rym Msadek ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atlantic Multidecadal Variability ◽  
Sea Level Pressure ◽  
Atmospheric Teleconnections ◽  
Arctic Sea ◽  
Long Term Trend

Abstract Observed September Arctic sea ice has declined sharply over the satellite era. While most climate models forced by observed external forcing simulate a decline, few show trends matching the observations, suggesting either model deficiencies or significant contributions from internal variability. Using a set of perturbed climate model experiments, we provide evidence that atmospheric teleconnections associated with the Atlantic multidecadal variability (AMV) can drive low-frequency Arctic sea ice fluctuations. Even without AMV-related changes in ocean heat transport, AMV-like surface temperature anomalies lead to adjustments in atmospheric circulation patterns that produce similar Arctic sea ice changes in three different climate models. Positive AMV anomalies induce a decrease in the frequency of winter polar anticyclones, which is reflected both in the sea level pressure as a weakening of the Beaufort Sea high and in the surface temperature as warm anomalies in response to increased low-cloud cover. Positive AMV anomalies are also shown to favor an increased prevalence of an Arctic dipole–like sea level pressure pattern in late winter/early spring. The resulting anomalous winds drive anomalous ice motions (dynamic effect). Combined with the reduced winter sea ice formation (thermodynamic effect), the Arctic sea ice becomes thinner, younger, and more prone to melt in summer. Following a phase shift to positive AMV, the resulting atmospheric teleconnections can lead to a decadal ice thinning trend in the Arctic Ocean on the order of 8%–16% of the reconstructed long-term trend, and a decadal trend (decline) in September Arctic sea ice area of up to 21% of the observed long-term trend.

scholarly journals Impacts of Assimilating Satellite Sea Ice Concentration and Thickness on Arctic Sea Ice Prediction in the NCEP Climate Forecast System

2017 ◽  
Vol 30 (21) ◽  
pp. 8429-8446 ◽  
Author(s):  
Zhiqiang Chen ◽  
Jiping Liu ◽  
Mirong Song ◽  
Qinghua Yang ◽  
Shiming Xu
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Forecast System ◽  
Climate Forecast System ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Ice Concentration

Here sea ice concentration derived from the Special Sensor Microwave Imager/Sounder and thickness derived from the Soil Moisture and Ocean Salinity and CryoSat-2 satellites are assimilated in the National Centers for Environmental Prediction Climate Forecast System using a localized error subspace transform ensemble Kalman filter (LESTKF). Three ensemble-based hindcasts are conducted to examine impacts of the assimilation on Arctic sea ice prediction, including CTL (without any assimilation), LESTKF-1 (with initial sea ice assimilation only), and LESTKF-E5 (with every 5-day sea ice assimilation). Assessment with the assimilated satellite products and independent sea ice thickness datasets shows that assimilating sea ice concentration and thickness leads to improved Arctic sea ice prediction. LESTKF-1 improves sea ice forecast initially. The initial improvement gradually diminishes after ~3-week integration for sea ice extent but remains quite steady through the integration for sea ice thickness. Large biases in both the ice extent and thickness in CTL are remarkably reduced through the hindcast in LESTKF-E5. Additional numerical experiments suggest that the hindcast with sea ice thickness assimilation dramatically reduces systematic bias in the predicted ice thickness compared with sea ice concentration assimilation only or without any assimilation, which also benefits the prediction of sea ice extent and concentration due to their covariability. Hence, the corrected state of sea ice thickness would aid in the forecast procedure. Increasing the number of ensemble members or extending the integration period to generate estimates of initial model states and uncertainties seems to have small impacts on sea ice prediction relative to LESTKF-E5.

scholarly journals Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years

2017 ◽  
Vol 11 (1) ◽  
pp. 65-79 ◽  
Author(s):  
Lars H. Smedsrud ◽  
Mari H. Halvorsen ◽  
Julienne C. Stroeve ◽  
Rong Zhang ◽  
Kjell Kloster
Keyword(s):  
Sea Ice ◽  
Surface Pressure ◽  
Decadal Variability ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Fram Strait ◽  
Sea Ice Extent ◽  
Radar Images ◽  
Data Record

Abstract. A new long-term data record of Fram Strait sea ice area export from 1935 to 2014 is developed using a combination of satellite radar images and station observations of surface pressure across Fram Strait. This data record shows that the long-term annual mean export is about 880 000 km2, representing 10 % of the sea-ice-covered area inside the basin. The time series has large interannual and multi-decadal variability but no long-term trend. However, during the last decades, the amount of ice exported has increased, with several years having annual ice exports that exceeded 1 million km2. This increase is a result of faster southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Evaluating the trend onwards from 1979 reveals an increase in annual ice export of about +6 % per decade, with spring and summer showing larger changes in ice export (+11 % per decade) compared to autumn and winter (+2.6 % per decade). Increased ice export during winter will generally result in new ice growth and contributes to thinning inside the Arctic Basin. Increased ice export during summer or spring will, in contrast, contribute directly to open water further north and a reduced summer sea ice extent through the ice–albedo feedback. Relatively low spring and summer export from 1950 to 1970 is thus consistent with a higher mid-September sea ice extent for these years. Our results are not sensitive to long-term change in Fram Strait sea ice concentration. We find a general moderate influence between export anomalies and the following September sea ice extent, explaining 18 % of the variance between 1935 and 2014, but with higher values since 2004.

scholarly journals Brief communication: Increasing shortwave absorption over the Arctic Ocean is not balanced by trends in the Antarctic

2017 ◽  
Vol 11 (5) ◽  
pp. 2111-2116 ◽  
Author(s):  
Christian Katlein ◽  
Stefan Hendricks ◽  
Jeffrey Key
Keyword(s):  
Sea Ice ◽  
Cloud Cover ◽  
Arctic Sea Ice ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
The Antarctic

Abstract. On the basis of a new, consistent, long-term observational satellite dataset we show that, despite the observed increase of sea ice extent in the Antarctic, absorption of solar shortwave radiation in the Southern Ocean poleward of 60° latitude is not decreasing. The observations hence show that the small increase in Antarctic sea ice extent does not compensate for the combined effect of retreating Arctic sea ice and changes in cloud cover, which both result in a total increase in solar shortwave energy deposited into the polar oceans.

scholarly journals Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years

2016 ◽  
Author(s):  
Lars H. Smedsrud ◽  
Mari H. Halvorsen ◽  
Julienne C. Stroeve ◽  
Rong Zhang ◽  
Kjell Kloster
Keyword(s):  
Sea Ice ◽  
Arctic Basin ◽  
Recent Decade ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Fram Strait ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. The Arctic Basin exports between 600,000 and 1 million km2 of it's sea ice cover southwards through Fram Strait each year, or about 10 % of the sea-ice covered area inside the basin. During winter, ice export results in growth of new and relatively thin ice inside the basin, while during summer or spring, export contributes directly to open water further north that enhances the ice-albedo feedback during summer. A new updated time series from 1935 to 2014 of Fram Strait sea ice area export shows that the long-term annual mean export is about 880,000 km2, with large inter-annual and multidecadal variability, and no long-term trend over the past 80 years. Nevertheless, the last decade has witnessed increased ice export, with several years having annual ice export that exceed 1 million km2. Evaluating the trend onwards from 1979, when satellite based sea ice coverage became more readily available, reveals an increase in annual export of about +6 % per decade. The observed increase is caused by higher southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Spring and summer area export increased more (+11 % per decade) than in autumn and winter (+2.6 % per decade). Contrary to the last decade, the 1950–1970 period had relatively low export during spring and summer, and consistently mid-September sea ice extent was higher during these decades than both before and afterwards. We thus find that export anomalies during spring have a clear influence on the following September sea ice extent in general, and that for the recent decade, the export may be partially responsible for the accelerating decline in Arctic sea ice extent.

scholarly journals Skillful prediction of northern climate provided by the ocean

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Marius Årthun ◽  
Tor Eldevik ◽  
Ellen Viste ◽  
Helge Drange ◽  
Tore Furevik ◽  
...  
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Arctic Sea Ice ◽  
Statistical Regression ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Northern Climate ◽  
Arctic Sea Ice Extent ◽  
Anomalous Heat

Abstract It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981–2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020.

Sign in / Sign up

Export Citation Format

Share Document