Regional Climate Change Projections in NW Europe

Transcription

1 Transnational Forestry Management Strategies in Response to Regional Climate Change Impacts (ForeStClim) Regional Climate Change Projections in NW Europe State-of-the-Art Report Project Team C (WP1 - Regional Climate Scenarios) Dr. Laurent Pfister (leader Team C) Dr. Klaus Görgen Public Research Centre - Gabriel Lippmann Department of Environment and Agro-Biotechnologies (EVA) 41, rue du Brill, L-4422 Belvaux, Grand-Duchy of Luxembourg pfister@lippmann.lu, v02_r

2 Background and motivation Future increase of the climate system's variability; changes in the frequency and intensity of meteorological extreme events; robust large-scale changes of the precipitation regime (e.g. decrease of summer-, increase of winter precipitation in Central Europe) (e.g. IPCC, 4AR WG1, 2007) Variable impacts on managed (anthropogenic) and unmanaged (natural) systems, depending on their sensitivity and vulnerability (ecology, economy, infrastructure, transport, energy production, water management, etc.) The focus of ForeStClim are managed forest ecosystems Atmospheric changes (changes of temperature and precipitation) lead to a modification of processes in the bio-, hydro- and pedosphere and geomorphological processes, these alter via complex feedbacks the surfaceatmosphere coupling in turn Even under an efficient climate change mitigation policy, climate change is going to have primarily negative impacts in the upcoming years Decision makers need adequate adaptation and mitigation strategies to minimize adverse effects of climate change Improved knowledge on the potential impacts including uncertainties means an extension of the informed options open to users

3 Global climate change, main variables: TMP and A-PCP AOGCM projections of surface warming Projected surface temperature changes for the early and late 21st century relative to the period 1980 to IPCC (2007) AR4-WG1 Technical Summary

4 Global climate change, main variables: TMP and A-PCP Multi-model projected patterns of precipitation changes Spatial patterns of multi-model mean for changes by the period 2090 to 2099 relative to 1980 to 1999 (% change) based on the SRES A1B scenario. December to February means are in the left figure, June to August means in the right figure. Changes are plotted only where more than 66% of the models agree on the sign of the change. The stippling indicates areas where more than 90% of the models agree on the sign of the change. Summary of changes from IPCC 4AR Those assessments are too coarse, hence we need regionalized data IPCC (2007) AR4-WG1 Technical Summary

5 Main objectives of Team C Main objectives Provision of regional atmospheric model outputs as forcing / input data to other teams Organisation of information exchange pathways between partners Work is grouped into actions 1. Preparation of atmospheric forcing and validation data, data processing, as well as data handling and storage of the modelling results 2. Setting up of a climate data dissemination centre for the project 3. Organisation and coordination of data exchange via specified interfaces between team C and team D (WP2) models 4. Downscaling of (existing) model data (either GCM and / or RCM) based on IPCC emission scenarios 5. Derivation of interactions between plant physiology / changed forest features and the atmosphere by coupling models and/or implementing forest data into atmospheric models

6 Project partners in Team C CRP-GL/EVA, Centre de Recherche Public Gabriel Lippmann, Département Environnement et Agro-biotechnologies (LUX) FAWF, Landesforsten Rheinland-Pfalz, Research Institute for Forest Ecology and Forestry, Forest inventory, Forest services (DEU) CLUWRR, Newcastle University, School of Civil Engineering and Geoscience, Centre for Land Use and Water Resources Research (GBR) ALICE, Environmental & Human Sciences Division, Forest Research (GBR) GIP, Groupement d'interêt Public d'aménagement et de Développement du Territoire (FRA)

7 Deliverables of Team C 1. Multi-model (transient) (bias corrected) regional climate change simulations (projections and controls) up to 2100 based on the IPCC-emission-scenarios A1B, A2, B1. Provided by EVA. 2. Climate change impact maps. CLUWRR: Production of a map of the different regions demonstrating the predicted impacts of climate change on a number of variables identified as being particularly relevant by the stakeholder community. FAWF: Climate change maps for the project s regions. 3. Water availability maps, run-off and discharge maps, storm risk maps. FAWF: Water availability maps as a planning tool for forest management to assess the possible water supply of trees. Run-off and discharge maps are the basis for planning of flood protection in forests. Storm risk maps are the basis for a silviculture risk management against storm damages.

8 Team C in the overall ForeStClim structure Linkages, feedbacks and work-flows ForeStClim application form (2008)

9 Atmospheric observational data and regional climate change projections available Observational station data are available from various networks (national weather services, other specific networks) Gridded reference datasets are e.g. available from the FP6 Ensembles project for selected variables (TMP, A-PCP; 1950 to 2006) Various projects have produced GCM and RCM climate change projections apart from the 4AR IPCC model simulations Latest extensive datasets (all relevant GCMs combined with a multitude of RCMs) are available from the FP6 Ensembles project, data from this project are intended to form the bases of the atmospheric forcing data to be used either as is (direct forcing) or as input to the atmospheric models provided within ForeStClim Spatial resolution of Ensembles data: 25 km x 25 km Time-span: up to 2050, some up to 2100 The ForeStClim project is intended to become an affiliated partner in the Ensembles project

10 UBA (2008) Klimaauswirkungen und Anpassung in Deutschland, Phase 1 Example for a regional climate change projection REMO-UBA, A1B, summer, TMP and A-PCP Change of mean summer temperature (compared to ) Change of mean summer rainfall (compared to )

11 Example for a regional climate change projection REMO-UBA, A1B, summer days per year UBA (2008) Klimaauswirkungen und Anpassung in Deutschland, Phase 1

12 Regional climate change projections for ForeStClim Depending on the needs of the other groups additional high-resolution atmospheric model runs are planned / foreseen; intermediate datasets are needed Various bias correction schemes are under review to correct model output data for systematic errors Probabilistic ensembles of multi-model climate change projections help to quantify uncertainties; benchmarks can help to identify systematic errors OcCC (2007) Klimaänderung und die Schweiz 2050

13 Structure of data flow-paths and processing frameworks Definition of the study areas/regions (GB, F, D, L, ) for the regional / local high resolution model runs to be based on forest inventories Cross-check with partners from Team D what data format and output variables will be needed before any start of modelling (precise definition of programming interfaces) Definition of IPCC scenarios and climate change projections to be used for the large-scale forcing of the regional atmospheric modelling tools Regional downscaling in every study area/region (GB, F, D, L, NL) with every partner s model involved in working package C

14 Links to other work-packages Team C is intended to be a management centre for the modelling and observational data, strong links exists to partners from Team D Development / preparation / handling / analysis of climate change projections by Team C as main inputs for Team D (precise synchronisation of efforts) Identification of identical areas/regions between Team C and Team D Cross-check on data formats and variables Data and information on climate conditions over the past 30 years (or more if available) in the context of forest stand sensitivity analysis (including water balance sensitivity assessments) Investigations on stand shifts (according to past, current and future climate conditions) Calibration, validation and uncertainty assessments of models (in both Team C and Team D) Feed-back mechanisms: the climate projections provided by Team C are likely to have fundamental consequences on the evolution of land-surface properties, which in turn might modify the surface-atmosphere coupling; these changes might be incorporated into the lower boundary forcing of the land-surface models in the regional atmospheric models

15 Transnational Forestry Management Strategies in Response to Regional Climate Change Impacts (ForeStClim) Team C / WP1 - Regional Climate Scenarios Thank you for your attention