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Antarctic Climate Change in the 21st Century (AntClim21)

antclim21 er near surface temperature projections large thumbnail
A high-resolution image of the map can be found  pdf here. (9.06 MB)


Climate model projections of 21st century change in surface air temperature (temperature 2m above the surface) by the end of the 21st century (2069-2098) following a range of low (RCP2.6) medium (RCP4.5) and high (RCP8.5) radiative forcing scenarios of known important climate drivers such as greenhouse gas increases and stratospheric ozone recovery. Each column shows a different season as follows: austral summer is defined as December-February; autumn is March-May; winter is June-August; and spring is September-November. Changes are all relative to the period 1970-1999 in ‘historical’ climate model simulations with observed levels of greenhouse gases and other known natural and anthropogenic factors. Contour intervals are 1 K. The climate model dataset used is the Coupled Model Intercomparison Project Phase 5 (CMIP5) dataset (Taylor et al., 2012).

The projection data from the multiple different climate models was combined using the method detailed in Bracegirdle and Stephenson (2012). This provides more precise and robust projections of Antarctic climate change by accounting for biases associated with sea ice. The observationally-constrained dataset used calibrate the projections is ERA-Interim (Dee et al., 2011). Different numbers of CMIP5 models were available for different scenarios and are listed below.

Strengths and weaknesses


  • Provides a quick summary of the broad changes projected across Antarctica estimated from a wide range of CMIP5 models.
  • Improves on a simple all-model average by taking account of regional biases associated with sea ice (see Bracegirdle and Stephenson (2012) for more details).

Weaknesses and caveats:

  • The global climate models used do not fully resolve the steep and complex mountains around large parts of coastal Antarctica the Antarctic Peninsula
  • The differences between scenarios could in part be due to the differing subsets of models available from each RCP experiment
  • The method of Bracegirdle and Stephenson (2012) should be viewed as a starting point and AntClim21 are currently working towards a broader community-agreed evaluation of climate model projections that will provide further improvements by taking into account a wider range of factors in model performance

Any questions on these maps or requests for further information should be addressed to Tom Bracegirdle (This email address is being protected from spambots. You need JavaScript enabled to view it.).


  • Bracegirdle, T. J., and D. B. Stephenson (2012), Higher precision estimates of regional polar warming by ensemble regression of climate model projections, Clim. Dyn., 39(12), 2805-2821, doi: 10.1007/s00382-012-1330-3.
  • Dee DP, et al. (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597. doi:10.1002/qj.828
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485–498.


We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table XX of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The European Centre for Medium Range Weather Forecasting is

thanked for providing the ERA-Interim datasets.

Models used







antclim jet latitudesummer
antclim jet latitudewinter


This dataset documents the trends and variability in the latitude and strength of the belt of lower-atmosphere westerly winds over the Southern Ocean, referred to as the ‘westerly jet’. Time series of annual mean and seasonal diagnostics are available for the period 1979-present are documented, specifically time series of seasonal and annual mean jet latitude and strength. The diagnostics are derived from the European Centre for Medium Range Weather Forecasts (ECMWF) ERA-Interim reanalysis (Dee et al., 2011), which is an observationally-constrained reconstruction of atmospheric conditions. The broad characterisation of the westerly winds into these simple diagnostics has been found to be useful for understanding long-term climate change due to contrasting drivers of change and impacts on other aspects of the climate system.

The jet indices shown here were calculated following the definition detailed in Bracegirdle et al. (2018). This definition is based on westerly wind in the lower atmosphere (850 hPa, which is approximately 1.5 km above mean sea level). At each latitude the all-longitude (zonal) average was calculatd between 75°S and 10°S. The maximum in this diagnostic is defined as the jet strength and its location defines the jet latitude. This is a very similar approach to that used in a number of other studies, e.g. Kidston and Gerber (2010), Son et al. (2010) and Swart and Fyfe (2012).

More detailed information can be found on this topic at the NCAR/UCAR Climate Data Guide:

Any questions on these time series or requests for further information should be addressed to Tom Bracegirdle (This email address is being protected from spambots. You need JavaScript enabled to view it.).


  • Bracegirdle, T. J., P. Hyder, C. R. Holmes, in press: CMIP5 diversity in southern westerly jet projections related to historical sea ice area; strong link to strengthening and weak link to shift. J. Climate, doi:10.1175/jcli-d-17-0320.1.
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553-597, doi:10.1002/qj.828.
  • Kidston, J., and E. P. Gerber, 2010: Intermodel variability of the poleward shift of the austral jet stream in the CMIP3 integrations linked to biases in 20th century climatology. Geophys. Res. Lett., 37, L09708, doi:10.1029/2010gl042873.
  • Son, S. W., and Coauthors, 2010: Impact of stratospheric ozone on Southern Hemisphere circulation change: A multimodel assessment. Journal of Geophysical Research-Atmospheres, 115, D00M07, doi:10.1029/2010JD014271.
  • Swart, N. C., and J. C. Fyfe, 2012: Observed and simulated changes in the Southern Hemisphere surface westerly wind-stress. Geophys. Res. Lett., 39, L16711, doi:10.1029/2012gl052810.


The European Centre for Medium Range Weather Forecasting is thanked for providing the ERA-Interim datasets.

Great Antarctic Climate Hack logoOctober 9 - 12th, 2017 in La Jolla, CA at Scripps Institution of Oceanography

If you are still interested in joining remotely or attending in person, please register here.

pdf Draft Workshop Agenda (122 KB)  (10 October 2017)

#GreatAntarcticClimateHack will be held October 9-12, 2017 at the Scripps Institution of Oceanography Forum, La Jolla, CA. Our first-ever Climate Hack will focus on bringing Antarctic and Southern Ocean observations to bear on evaluating the latest generation of climate and earth system models, producing new climate model metrics for the 21st century.

#GreatAntarcticClimateHack is a workshop to train non-modeling experts to use observational datasets to interrogate CMIP model results, thereby creating new model metrics and validation tools. The aim of the workshop is to facilitate preparation for the next IPCC report for a much broader science community, increase non-traditional climate modeling publications, and learn to apply/utilize data sets that help develop model validation skills. This first workshop will accommodate 50 participants on site, and 50 participants to join remotely online.

Logistical Details

Meeting Location: UCSD Scripps Institution of Oceanography

Robert Paine Scripps Forum (Scripps Seaside Forum)
8610 Kennel Way (formally Discovery Way) 
La Jolla, CA 92037

The Robert Paine Scripps Forum (aka Scripps Seaside Forum) is located at the southwestern-most end of the Scripps Institution of Oceanography campus facing the Pacific Ocean. 
(interactive map)

GACH HotelHotel

The La Jolla Shores Hotel is within walking distance to Scripps Institution of Oceanography (20 minutes along the ocean), but we will have shuttle service available for those who prefer. 

*Mention the GACH when making your reservation.  A group booking rate was available until June 16th. 

**Please do not book your hotel until your application has been accepted.

La Jolla Shores Hotel
7955 La Jolla Shores Drive
La Jolla CA 92037

Overnight Parking $28

To walk from the hotel to Scripps along the ocean (approximately 1 mile), go north (right out of the hotel) on La Jolla Shores Drive to Avenida de La Playa and turn left (west). If you wish to walk on the beach, continue to the end of Avenida de la Playa (ends at the beach). If you wish to walk on pavement, make a right (north) on Camino del Oro.

Air travel

The closest airport is San Diego International Airport/Lindbergh Field (SAN) which is 12 miles from La Jolla.

Ground Transportation

To get to the hotel from the airport, take a taxi to the above address.

If You Are Driving

Parking passes are available for those who are driving to Scripps. Please use parking lot P002 or P003. We will distribute parking passes to those who need them the morning of the meeting.

Airport to Hotel: Map

Registration - If you are still interested in joining, please register here.

Organizing Committee

Joellen Russell, Jeff Severinghaus, Nancy Bertler, Thomas Bracegridle, Alia Khan

News and Updates from the AntClim21 Community