1. * http://www.nlh.no/?avd=54 Problems using downscaled scenarios in studies of climate effects. Lars Bakken - The EACC project - Our first trials (and errors)* More scenarios? Better scenarios? Simple wheather manipulations? Wheather generators?

2. COUP Soil moisture Soil temp. Water transport Snow cover Water stress Frost/thaw Driving data Soil erosion Plant growth Soil biology - C- and N model -Trace gas model

3. The scenarios: Dynamic downscaling (HIRHAM) based on: - AOGCM ECHAM4/OPYC3 with the GSDIO integration - IPCC IS92a scenario The control period: 1980-99: Obs80-99 = Observed wheather 1980-99 Scen80-99= Simulated weather 1980-99 The future wheather: Scen30-49= simulated wheather 2030-49

4. Snow depth Frost depth Much less snow in a warmer climate And soil frost is somewhat more shallow

5. Colder soils in a warmer climate? Number of ”frost spells” in the soil: More frequent freeze/thaw events in a warmer climate?

6. The summer is more problematic: The Scenarios are wet and cold!

7. And the Scenarios have a peculiar distribution of rain:

8. The cool and wet summers delayed the phenological development The high and frequent precipitation resulted in moist grains => Much delayed grain harvest!

9. The high Scenario-precipitation in July-August resulted in much too high drainage and surface runoff High erosion!

10. High erosion in summer High early-spring erosion due to snow melt on frozen soil

11. Quo vadis? Don Quijote & Sancho Panza (Daumier)

12. Several scenarios => More uncertainty Longer scenarios => Better statistics But the climate models will gradually become better… - Simulations driven by climate scenarios tend to be anecdotic - the simulations are not causally transparent - general respons patterns cannot be ”extracted” The difference between two scenarios are multidimensional The simulated ecological processes are nonlinear  To understand the reasons for contrasting results is difficult

13. Alternative 1: Simple manipulations of observed wheather - Additive for temperature (seasonal og whole year) - Multiplicative for prcipiation - Or stochastic Factorial model experiments => interactions detected Winter temperature: ∆T winter = -1 0 +1 Summer temperature: ∆T summer = -1 0 +1 Winter precipitation : KP winter = 0.9 1.0 1.1 Summer precipitation: KP summer = 0.9 1.0 1.1 All combinations: 81 simulations

14. Wheather generators - Based on existing weather => reliable weather ”quality” ? - Parameterized by contrasting climate scenarios  plausible combinations ? -Many or long time periods simulated => Statistics will be OK