Antarctic Seasonal Pressure Reconstructions 1905-2013
Overview:
This project created seasonal reconstructions for many of the long-term Antarctic station records, in order to understand better the relative roles of natural variability and change during the 20th Century. Using midlatitude pressure records that were significantly correlated to the individual station being reconstructed, a principal component regression reconstruction technique was employed. The records were extended back to 1905 for all locations, and several different approaches were attempted:
NOTE: Any reconstructions termed 'original' reconstructions are any reconstructions not using 'pseudo' data. Reconstructions using 'pseudo' data from reanalysis products are termed 'pseudo' reconstructions.
We provide here all the reconstruction data for each station (which can be accessed by downloading the data attached), including the best overall reconstructions for all stations.
Acknowledgments:
This work is supported by funding from the National Science Foundation, through the Antarctic Oceanic and Atmospheric Sciences award PLR-1341621
Relevant Publications:
For further information on the reconstruction methodology, please see the seasonal SAM index reconstructions, or the following publications:
Contacts:
For additional information, please feel free to email Dr. Ryan L. Fogt (fogtr@ohio.edu)
RECONSTRUCTION PERFORMANCE
The evaluation statistics for the best performing original reconstructions for all the 'full period' reconstructions are summarized in the tables below. Full details on the length of the records (both for midlatitude and Antarctic stations reconstructed) and other skill measures can be found in Fogt et al. 2016.
December-January-February (DJF)
Stations | Calibration Correlation | Validation Correlation | Reduction of Error | Coefficient of Efficiency |
---|---|---|---|---|
Amundsen-Scott Bellingshausen Byrd Casey Davis Dumont Esperanza Faraday Halley Marambio Marsh / O'Higgins Mawson McMurdo / Scott Base Mirny Novolazarevskaya Rothera Syowa Vostok | 0.859 0.830 0.826 0.794 0.754 0.816 0.909 0.899 0.923 0.760 0.819 0.885 0.872 0.842 0.873 0.886 0.773 0.832 | 0.790 0.733 0.732 0.746 0.660 0.779 0.813 0.820 0.890 0.637 0.725 0.813 0.824 0.737 0.843 0.805 0.710 0.774 | 0.737 0.761 0.745 0.749 0.765 0.750 0.826 0.808 0.852 0.742 0.743 0.783 0.760 0.709 0.780 0.798 0.671 0.792 | 0.615 0.652 0.617 0.675 0.647 0.685 0.652 0.665 0.789 0.659 0.635 0.655 0.674 0.528 0.729 0.652 0.598 0.702 |
March-April-May (MAM)
Stations | Calibration Correlation | Validation Correlation | Reduction of Error | Coefficient of Efficiency |
---|---|---|---|---|
Amundsen-Scott Bellingshausen Byrd Casey Davis Dumont Esperanza Faraday Halley Marambio Marsh / O'Higgins Mawson McMurdo / Scott Base Mirny Novolazarevskaya Rothera Syowa Vostok | 0.721 0.853 0.668 0.559 0.738 0.660 0.785 0.819 0.608 0.725 0.719 0.742 0.678 0.717 0.779 0.699 0.719 0.660 | 0.678 0.818 0.603 0.486 0.660 0.606 0.748 0.778 0.529 0.670 0.770 0.671 0.635 0.677 0.732 0.635 0.638 0.609 | 0.520 0.739 0.473 0.313 0.554 0.441 0.615 0.672 0.369 0.637 0.565 0.551 0.459 0.514 0.627 0.503 0.545 0.464 | 0.456 0.682 0.385 0.222 0.438 0.353 0.557 0.601 0.269 0.586 0.559 0.438 0.401 0.456 0.570 0.411 0.430 0.409 |
June-July-August (JJA)
Stations | Calibration Correlation | Validation Correlation | Reduction of Error | Coefficient of Efficiency |
---|---|---|---|---|
Amundsen-Scott Bellingshausen Byrd Casey Davis Dumont Esperanza Faraday Halley Marambio Marsh / O'Higgins Mawson McMurdo / Scott Base Mirny Novolazarevskaya Rothera Syowa Vostok | 0.685 0.914 0.563 0.765 0.683 0.731 0.853 0.871 0.721 0.814 0.884 0.667 0.793 0.787 0.818 0.810 0.574 0.723 | 0.578 0.884 0.391 0.712 0.595 0.650 0.823 0.841 0.612 0.760 0.838 0.555 0.632 0.648 0.689 0.765 0.423 0.659 | 0.469 0.836 0.376 0.586 0.492 0.534 0.733 0.758 0.519 0.776 0.809 0.444 0.630 0.619 0.675 0.644 0.376 0.535 | 0.316 0.779 0.213 0.503 0.372 0.412 0.680 0.706 0.365 0.737 0.746 0.290 0.375 0.398 0.472 0.571 0.220 0.446 |
September-October-November (SON)
Stations | Calibration Correlation | Validation Correlation | Reduction of Error | Coefficient of Efficiency |
---|---|---|---|---|
Amundsen-Scott Bellingshausen Byrd Casey Davis Dumont Esperanza Faraday Halley Marambio Marsh / O'Higgins Mawson McMurdo / Scott Base Mirny Novolazarevskaya Rothera Syowa Vostok | 0.619 0.853 0.765 0.698 0.623 0.641 0.762 0.769 0.676 0.697 0.711 0.616 0.731 0.635 0.581 0.623 0.594 0.615 | 0.395 0.819 0.621 0.529 0.545 0.540 0.712 0.747 0.536 0.633 0.647 0.557 0.612 0.534 0.505 0.522 0.546 0.514 | 0.383 0.745 0.637 0.461 0.405 0.411 0.581 0.591 0.457 0.579 0.601 0.370 0.534 0.445 0.332 0.434 0.363 0.385 | 0.085 0.689 0.448 0.224 0.295 0.277 0.502 0.557 0.262 0.514 0.530 0.291 0.357 0.285 0.250 0.362 0.304 0.259 |
DATA
Please click here for access to all of the best performing reconstructions in an MS Excel spreadsheet.
To access more data pertaining to each station individually, please download individual station data provided above on this page. The attached .txt files for each individual station provide the overall best reconstructions by season. The .xlsx files provide all reconstructions for each station and method used.
Last Revised: May 2016