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Seasonal forecasting

nino.png Short description: Studies of seasonal predictability over the tropics and Europe associated with potential sources of seasonal predictability such as ENSO events.

Seasonal forecasting is a promising research area linked to a great variety of practical applications from different socio-economics sectors such as energy management, agriculture management, health planing or tourism and also related to weather risk and security issues such as, disaster forecasts and prevention, food security or water source management. The potential economic benefits of such predictions lie in planning the future in all fields that depend on climate to some degree being of special interest within the context of climate change adaptation.

The goal of this area is predicting climate seasonal anomalies a few months in advance, and requires the use of complex coupled atmosphere-ocean models. It is believed that the ocean confer some memory to the atmosphere due to its larger heat capacity. Therefore, it would be possible to enhance the predictability horizon associated with the atmosphere including the ocean variability. The coupling between the atmosphere and ocean is quite strong in the tropical region giving rise to one of the prime example of seasonal climate variability El Niño and La Niña phenomena. Although the origins of El Niño and La Niña lie in the tropical Pacific, the weather in many places around the world is affected by these events; however the strength of that teleconnection depends strongly on the location and season (Halpert and Ropelewsky 1992). Prediction models continue to be improved examinating new sources of seasonal predictability due to land surface soil moisture, ice cover and stratosphere circulations.

In the last decades, a considerable effort has been made to improve the understanding of the physical phenomena responsible of the observed seasonal variability and to transfer the advances to the operational numerical forecasting systems. Nowadays, most of the major meteorological institutions around the world have developed Ensemble Prediction Systems (EPS) for operational seasonal forecasting based on coupled atmosphere-ocean general circulation models. Some examples are the ECMWF forecasting Systems [Anderson et al., 2003], the NCEP CFS [Saha et al., 2006], the Australian POAMA [Wang et al., 2001], and the recent European EURO-SIP multi-model resulting from the DEMETER project [Palmer et al., 2004].

Key Reading:

  • A. Troccoli, M. Harrison, D. L. T. Anderson and S. J. Mason (Eds) (2008) Seasonal Climate: Forecasting and Managing Risk. NATO Science Series, Springer Academic Publishers. pdf
  • B. Kirtman and A. Pirani (2008) WCRP Position Paper on Seasonal Prediction. WCRP Informal Report No. 3/2008. ICPO Publication No. 127 pdf
  • T. N. Palmer and D. L. T. Anderson (1994) The prospects for seasonal forecasting-A review paper, Quart. J. Meteorol. Soc., 120, 755–793.
  • T. N. Palmer et al (2004) Development of a European multimodel ensemble system for seasonal--to--interannual prediction DEMETER, 85, Bulletin of the American Meteorological Society 853-872 pdf

Activities of the Santander Meteorology Group:
Seasonal forecasting is one of the main research topics developed in our group. This work is supported by different projects from both EU (DEMETER and ENSEMBLES) and Spanish government (SEASONAL and SEASONAL 2) funding. The study is focused on the following issues:

  • Robust validation of seasonal forecasts from different Ensemble Forecast Systems (DEMETER, ENSEMBLES).
  • Statistical assessment of the operational ECMWF seasonal forecast System in Spain.
  • Determination of sources of seasonal predictability, such as the ENSO events over Europe. Teleconnection studies.
  • Application of different statistical downscaling methods to improve the skill of seasonal forecasts.

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