CLIMAG LESSONS LEARNED AND FUTURE CHALLENGES A CLIMATE SCIENCE PERSPECTIVE By Hartmut Grassl Max Planck Institute for Meteorology Hamburg, Germany

A CLIMATE SCIENCE PERSPECTIVE 1)Short History 1979 First World Climate Conference in Geneva “WE NEED A WORLD CLIMATE PROGRAMME” 1980 WMO and ICSU started the WORLD CLIMATE RESEARCH PROGRAMME 1985 TOGA started and brought the breakthrough to some skill for SEASONAL CLIMATE ANOMALY PREDICTIONS FOR ENSO AFFECTED REGIONS 1994 End of TOGA, its legacy: APPLY PREDICTIONS FOR AGRICULTURE 1995 & 1996 Plea for application in agriculture by the JSC of WCRP LAUNCH OF THE IDEA OF CLIMAG 1998 START cares for the “baby” 1999 First CLIMAG Workshop, WMO, Geneva

2)Variability of Present Climate and Climate Change are Linked Climate change will bring changed frequency distributions of all climate parameters. Examples: 1)Precipitation amount per event has increased in all areas with stagnant or increasing total amount but also at slightly less total amount 2)Daily temperature amplitudes shrank for most land climates 3)Temperature frequency distributions show a tendency to broaden Coping with climate variability thus means learning to adapt to climate change A CLIMATE SCIENCE PERSPECTIVE

3)Predictions Should Add Information on Changed Frequency Distributions Extreme weather probabilities change more strongly than means of, e.g., precipitation. Therefore, predictions have to add estimates of changed probabilities for extremes or high impact weather. This can be achieved by searching for frequency distributions tailored to the circulation patterns distribution prevailing during the prediction period. 4)New and/or Better Existing Observational Networks are the Drivers of Model Improvement and thus of Improved Climate Anomaly Predictions At least the observation of upper ocean structure, sea ice cover, soil moisture and snow water equivalent are required for the full exploitation of predictability on intra-seasonal, seasonal and interannual time scales. The best promotion of predictions is higher skill. progress envisaged: full implementation of ARGO launch of SMOS by ESA in 2006 integrated European projects launch of Aquarius by NASA A CLIMATE SCIENCE PERSPECTIVE

6)Evaluation of Forecast Skill by WCRP Model performance is differing strongly between empirical, hybrid and high resolution coupled models. Therefore, we have to perform model intercomparisons and prediction skill evaluations by a neutral moderator, e.g. WCRP’s CLIVAR project. 5)The gap between medium range weather forecasts and seasonal predictions has to be closed, especially through soil moisture and snow water equivalent information. In most applications onset of rains or length of dry spell is the key information needed. 7)CLIMAG is more important to developing countries as skill is higher in tropical areas, agriculture’s share of GDP is larger and vulnerability to climate variability is often high. 8)Climate Science is detecting possibilities to extend predictions of anomalies reaching into the decadal time scale by higher resolution global coupled models. COPES will try to detect the predictability level. A CLIMATE SCIENCE PERSPECTIVE

9)CLIMAG can be seen as the pilot project for the agricultural part of the seamless climate prediction envisaged under COPES (Co-ordinated Observation and Prediction of the Earth System), now started by WCRP. 10)CLIMAG, through START and IRI, was a small inter-programme project, which may have gone unnoticed by the parent organizations (IGBP, WCRP, IHDP) to some extent. ESSP should acknowledge this early contribution to GECAFS and set the stage for continuation on larger scale. 11)All inter- and transdisciplinary research needs robust infrastructures, i.e. combined sponsorship of NGO(s) and intergovernmental institutions. 12)There is no clear separation between research results and later operational applications. All global change research is policy relevant and can get immediate application. Hence GECAFS, WMO and FAO have to join their efforts. A CLIMATE SCIENCE PERSPECTIVE