* problems using downscaled scenarios in studies of climate effects. lars bakken - the eacc project...

*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?

COUP

Soil moisture

Soil temp.

Water transport

Snow cover

Waterstress

Frost/thawDriving data

Soil erosionPlant growthSoil biology- C- and N model-Trace gas model

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 1980-99Scen80-99= Simulated weather 1980-99

The future wheather: Scen30-49= simulated wheather 2030-49

Snow depth Frost depth

Much less snowin a warmer climate

And soil frost is somewhat more shallow

Colder soils in a warmer climate?

Number of ”frost spells” in the soil:

More frequent freeze/thaw events in a warmer climate?

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

And the Scenarios have a peculiar distribution of rain:

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

The high Scenario-precipitation in July-August resulted in much too high drainage and surface runoff

High erosion!

High erosion in summer

High early-springerosion due to snowmelt on frozen soil

Quo vadis?

Don Quijote & Sancho Panza (Daumier)

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 multidimensionalThe simulated ecological processes are nonlinear To understand the reasons for contrasting results is difficult

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 +1Summer temperature: ∆Tsummer = -1 0 +1Winter precipitation : KPwinter = 0.9 1.0 1.1Summer precipitation: KPsummer = 0.9 1.0 1.1

All combinations: 81 simulations

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