CliSAP successfully finished in 2018. Climate research continues in the Cluster of Excellence "CLICCS".

Seasonal predictability arising from El Niño and stratospheric variability

03.03.2015

Climate predictions for the next season, so called seasonal predictions, are often produced using extended weather forecast models. Scientists from Universität Hamburg around Prof. Johanna Baehr and from Max Planck Institute for Meteorology (MPI-M) and the German Meteorological Service (DWD) present in two new publications a seasonal prediction system which is based on the global Earth system model MPI-ESM instead.

Within this new DWD-MPI-M-UHH seasonal prediction system they investigate the seasonal predictability of winters over Northern Europe. Ensemble hindcast simulations are performed in an MPI-ESM setup for seasonal forecasts. The prediction system is initialised in the atmosphere, ocean and sea-ice component, and ensemble generation is realised through oceanic bred-vectors (Baehr et al., 2014).

The researchers find increased predictability over Northern Europe for 3 to 5 months in advance for winters that follow El Niño events. Such winters are likely to show a negative NAO signal, though only if such winters also show major sudden stratospheric warming events (Domeisen et al., 2015). The findings suggest that establishing predictive skill over Northern Europe depends not only on the adequate representation of tropospheric variability but also on the adequate representation of both oceanic variability and stratospheric variability.

The model reproduces the El Niño teleconnection through the stratosphere, which involves a deepened Aleutian Low in the Northern Pacific connected to a warm anomaly in the Northern winter stratosphere. The stratospheric anomaly signal then propagates downward into the troposphere through the winter season.


Publications:
Domeisen, D., Butler, A., Fröhlich, K., Bittner, M., Mueller, W. A., & Baehr, J. (2015). Seasonal predictability over Europe arising from El Niño and stratospheric variability in the MPI-ESM seasonal prediction system. Journal of Climate, 28, 256-271. doi:10.1175/JCLI-D-14-00207.1.
journals.ametsoc.org/doi/abs/10.1175/JCLI-D-14-00207.1

Baehr, J., Fröhlich, K., Botzet, M., Domeisen, D., Kornblueh, L., Notz, D., Piontek, R., Pohlmann, H., Tietsche, S., & Mueller, W. A. (2014). The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model. doi:10.1007/s00382-014-2399-7.
link.springer.com/article/10.1007%2Fs00382-014-2399-7

Contact:
Prof. Dr. Johanna Baehr
Cluster of Excellence CliSAP
Universität Hamburg / Institute of Oceanography
Center for Earth System Research and Sustainability (CEN)
Phone: +49 40 42838 7736
Email: johanna.baehrdummy@uni-hamburgdummy2.de

Dr. Wolfgang Müller
Max Planck Institute for Meteorology
Phone: +49 40 41173 370
Email: wolfgang.muellerdummy@mpimet.mpgdummy2.de

 

(News taken with kind permission from the MPI-M)