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Dr Antje Weisheimer (she)

Principal NCAS Research Fellow

Research theme

  • Climate physics

Sub department

  • Atmospheric, Oceanic and Planetary Physics

Research groups

  • Predictability of weather and climate
Antje.Weisheimer@physics.ox.ac.uk
Telephone: 01865 (2)82441
Robert Hooke Building, room S43
ECMWF
NCAS
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Warming Stripes for Oxford from 1814-2019

Warming Stripes for Oxford from 1814-2019.

Model uncertainty in seasonal to decadal forecasting - insight from the ENSEMBLES project.

ECMWF Newsletter ECMWF 122 (2010) 21-26

Authors:

A Weisheimer, FJ Doblas-Reyes, TN Palmer

Decadal climate prediction with the ECMWF coupled forecast system: Impact of ocean observations. ECMWF Tech Memo.

(2010) 633

Authors:

FJ Doblas-Reyes, MA Balmaseda, A Weisheimer, TN Palmer

Forecast quality assessment of the ENSEMBLES seasonal-to-decadal Stream 2 hindcasts. ECMWF Tech Memo.

ECMWF (2010) 621

Authors:

FJ Doblas-Reyes, A Weisheimer, TN Palmer, JM Murphy, D Smith

Reply

Bulletin of the American Meteorological Society 90:10 (2009) 1551-1554

Authors:

TN Palmer, FJ Doblas-Reyes, A Weisheimer, MJ Rodwell
More details from the publisher

ENSEMBLES: A new multi-model ensemble for seasonal-to-annual predictions - Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs

Geophysical Research Letters 36:21 (2009)

Authors:

A Weisheimer, FJ Doblas-Reyes, TN Palmer, A Alessandri, A Arribas, M Déqué, N Keenlyside, M MacVean, A Navarra, P Rogel

Abstract:

A new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4-6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of ∼0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data. Copyright 2009 by the American Geophysical Union.
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