Eötvös Loránd University Department of Meteorology Budapest, Hungary Judit Bartholy Introduction to panel discussion 1: Climate change projections in Europe and Hungary Regional climate model experiments for the Carpathian basin at the Eötvös Loránd University Introduction to panel discussion 1: Climate change projections in Europe and Hungary Regional climate model experiments for the Carpathian basin at the Eötvös Loránd University CLIMATE CHANGE 2007: IMPLICATIONS FOR HUNGARY IPCC OUTREACH EVENT --- CEU, Budapest April 2008

DOWNSCALING TECHNIQUES APPLIED TO GLOBAL CLIMATE MODEL RESULTS FOR THE HUNGARIAN NATIONAL CLIMATE STRATEGY DYNAMICAL - STATISTICAL MODEL APPROACH Downscaling large-scale climate scenarios for the sensitive regions of Hungary (GCM+stochastic model) DYNAMICAL APPROACH WITH NESTED RCMs: 2 experiments at ELU (RegCM, PRECIS) 2 experiments at HMS (REMO, ALADIN) REGIONAL CLIMATE SCENARIOS for on the base of RCM outputs (16 and 8 experiments for A2 and B2 scenarios) PRUDENCE

Adaptation of regional climate models at the Eötvös Loránd University RegCM using 10 km resolution (ICTP / F. Giorgi) PRECIS using 25 km resolution (UK Hadley Centre) First contacts / start of adaptation project Autumn 2005Autumn 2002 Completed model experiments using ERA using HadCM using HadCM3 (A2) Model experiments currently in progress using ECHAM using ECHAM5 (A1B) using ECHAM5 (A1B) using HadCM3 (B2)

RegCM adaptation at the Eötvös Loránd University Adapted version:RegCM 3 and RegCM 3.1 Initial/boundary conditions: ERA40 (1.15°), ECHAM5 (1.25°) with timestep: 6 hr Horizontal resolution:50 km (0.44°), 45 km (0.4°), 25 km (0.22°), 20 km(0.2°), 10 km (0.11°) Vertical levels:14, 18, 23 (sigma coordinates) Timestep: 30 s, 20 s Spin-up period: 1 year, 1 month Model domain:Central/Eastern Europe (with the center at 47.5°N, 18.5°E) Gridpoints: 200×100, 140×120, 110×90, 120×100, 100×80, 94×72, 90×70 Time slices: (reference), (near future), (future) Scenario:IPCC A1B Target domain: Carpathian basin (SW corner at 45.15°N 13.35°E -- NE corner at 49.75° 23.55°E) Applied convective scheme:Kuo, Anthes 1974 MIT-Emanuel, 1991 Grell, Arakawa & Schubert, 1974 (AS74) -- Fritsch & Chappell, 1980 (FC80)

SW = 13.35°E  SW = 45.15°N NE = 23.55°E  NE = 49.75°N Applied grid: 120×100 C = 18.5°E  C = 47.5°N SPATIAL EXTENSION OF THE REGCM SIMULATION AND THE TARGET DOMAIN

PRECIS adaptation at the Eötvös Loránd University Adapted version:PRECIS 1.3 and PRECIS Initial/boundary conditions: ERA40 (1.15°), HadCM3 (1.25°) with timestep: 6 hr Horizontal resolution:50 km (0.44°), 25 km (0.22°) Vertical coordinates:sigma coordinates Timestep: 5 min Spin-up period:1 month Model domain: Central/Eastern Europe Gridpoints: 123×96 NW corner at 53.39°N 2.27°E -- NE corner at 50.57°N 34.38°E SW corner at 39.57°N 3.83°E -- SE corner at 37.2°N 27.94°E Time slices: (reference period), (future) Scenario:IPCC A2 and B2 Target domain: Carpathian basin NW corner at 50°N 5°E -- NE corner at 50°N 27.5°E SW corner at 40°N 5°E -- SE corner at 40°N 27.5°E

SPATIAL EXTENSION OF THE PRECIS SIMULATION AND THE TARGET DOMAIN

EXPECTED TEMPERATURE CHANGE, PRECIS A2 SCENARIO

EXPECTED PRECIPITATION CHANGE, PRECIS A2 SCENARIO

RESULTS OF CONTROL RUNS FOR HUNGARY DIFFERENCE BETWEEN SIMULATED (PRECIS) AND OBSERVED (CRU) DATA

SUMMARY OF EXPECTED CLIMATE CHANGE PRECIS, A2 SCENARIO

CONCLUSIONSCONCLUSIONS More and more evidences support the anthropogenic global climate change, which help to project the amplitude and the range of the expected regional climate changes.More and more evidences support the anthropogenic global climate change, which help to project the amplitude and the range of the expected regional climate changes. Since there is a large variability of GCM projections for the Central European region, therefore regional climate models (using dynamical approach) are essential to reduce the uncertainity of the climate projections in the areaSince there is a large variability of GCM projections for the Central European region, therefore regional climate models (using dynamical approach) are essential to reduce the uncertainity of the climate projections in the area First results (using km horizontal resolution) suggest that regional climate change exceeds the global mean changes in this region --- this implies that decision makers should act as early as possible (e.g., forming adaptation and mitigation strategies)First results (using km horizontal resolution) suggest that regional climate change exceeds the global mean changes in this region --- this implies that decision makers should act as early as possible (e.g., forming adaptation and mitigation strategies)