Regional Climate Modeling: A Tool for Decision-Makers

PROJECT TO INTERCOMPARE REGIONAL CLIMATE SIMULATIONS

Regional Climate Modeling:A Tool for Decision-Makers

Eugene S. TakleAgronomy Department

Geological and Atmospheric Science Department

Iowa State UniversityAmes, Iowa 50011

[email protected]

Institute for Science and SocietyIowa State University

4 May 2004


Outline Evidence for global climate change Future atmospheric carbon dioxide concentrations Simulations of global climate and future climate

change Implications for stream flow and

nutrient loss International collaboration for understanding

water and energy cycles Summary

Carbon Dioxide and Temperature


2004


2004

2040


Stabilization at 550 ppm


“Business as Usual”(fossil intensive)

2100


Associated Climate Changes Global sea-level has increased 1-2 mm/yr Duration of ice cover of rivers and lakes decreased by 2 weeks in N.

Hemisphere Arctic ice has thinned substantially, decreased in extent by 10-15% Reduced permafrost in polar, sub-polar, mountainous regions Growing season lengthened by 1-4 days in N. Hemisphere Retreat of continental glaciers on all continents Poleward shift of animal and plant ranges Snow cover decreased by 10% Earlier flowering dates Coral reef bleaching

Source: Intergovernmental Panel on Climate Change, 2001 Report

Mann, M. E., R. S. Bailey, and M. K. Hughes, 1999: Geophysical Research Letters 26, 759.



Source: Jerry Meehl, National Center for Atmospheric Research

Source: National Center for Atmospheric Research


40% Probability

5% Probability


Climate Change Projected for 2100

Rapid Economic Growth

Slower Economic Growth

IPCC Summary for Policy Makers

An increasing body of observations gives a collective picture of a warming world and other changes in the climate system

Emissions of greenhouse gases and aerosols due to human activities continue to alter the atmosphere in ways that are expected to affect the climate

IPCC Summary for Policy Makers, cont’d

Confidence in the ability of models to project future climate has increased

There is new and stronger evidence that most of the warming observed over the last 50 years is attributable to human activities








Anthropogenic climate change will persist for many centuries

Further action is required to address remaining gaps in information and understanding

http://www.grida.no/climate/vital/38.htm


Climate Surprises

Breakdown of the ocean thermohaline circulation (Greenland melt water)

Breakoff of the West Antarctic Ice Sheet

ClimateCold Warm

Ic e V

olum

e

0

AntarcticaGreenland


Regional Climate Change for the US Midwest

Observed and projected changes in climate

Impact on water quantity and water quality

Policy implications

For the Midwest Warming will be greater for winter than summer Warming will be greater at night than during the

day A 3oF rise in summer daytime temperature triples

the probability of a heat wave Growing season will be longer (8-9 days longer

now than in 1950) More precipitation Likely more soil moisture in summer More rain will come in intense rainfall events Higher stream flow, more flooding

Sub-Basins of theSub-Basins of theUpper MississippiUpper MississippiRiver BasinRiver Basin

119 sub-basins

Outflow measuredat Grafton, IL

Approximately oneobserving stationper sub-basin

Approximately onemodel grid pointper sub-basin


Soil Water Assessment Tool (SWAT)

Long-term, continuous watershed simulation model (Arnold et al,1998)

Assesses impacts of climate and management on yields of water, sediment, and agricultural chemicals

Physically based, including hydrology, soil temperature, plant growth, nutrients, pesticides and land management

Daily time steps

SWAT Output with Various Sources SWAT Output with Various Sources of Climate Inputof Climate Input

Validation of SWAT:Validation of SWAT:Annual Stream Flow at Grafton, ILAnnual Stream Flow at Grafton, IL

Validation of SWAT:Validation of SWAT:Monthly Stream Flow at Grafton, ILMonthly Stream Flow at Grafton, IL

RegCM2 Simulation DomainRegCM2 Simulation Domain

Red = global model grid point Green/blue = regional model grid points

Annual Stream Flow Simulated by SWATAnnual Stream Flow Simulated by SWATDriven by the RegCM2 Regional ClimateDriven by the RegCM2 Regional Climate

Model with NNR Lateral Boundary ConditionsModel with NNR Lateral Boundary Conditions

Mean Monthly Precipitation Simulated by Mean Monthly Precipitation Simulated by the RegCM2 Regional Climate Model the RegCM2 Regional Climate Model

with NNR Lateral Boundary Conditionswith NNR Lateral Boundary Conditions

Seasonal Stream Flow Simulated by SWATSeasonal Stream Flow Simulated by SWATDriven by the RegCM2 Regional ClimateDriven by the RegCM2 Regional Climate

Model with NNR Lateral Boundary ConditionsModel with NNR Lateral Boundary Conditions

“Warming Hole”

TTmaxmax (JJA) (JJA)˚C

Ten-Year Mean Precipitation Generated by the RegCM2 Ten-Year Mean Precipitation Generated by the RegCM2 Regional Climate Model Driven with HadCM2 Regional Climate Model Driven with HadCM2

Global Model Results for the Contemporary and Global Model Results for the Contemporary and Future Scenario (2040s) ClimateFuture Scenario (2040s) Climate

Ten-Year Mean Monthly Stream Flow Generated by the Ten-Year Mean Monthly Stream Flow Generated by the RegCM2 Regional Climate Model Driven RegCM2 Regional Climate Model Driven

with HadCM2 Global Model Results for the with HadCM2 Global Model Results for the Contemporary and Future Scenario (2040s) ClimateContemporary and Future Scenario (2040s) Climate

Comparison of Simulated Stream Flow under Comparison of Simulated Stream Flow under Climate Change with Various Model BiasesClimate Change with Various Model Biases

Relation of Runoff to Precipitation Relation of Runoff to Precipitation for Various Climatesfor Various Climates


Regional Climate Modeling for Informing Policy on Water Quality

How does the combination of climate change and land use impact water quality?

Use nitrates and sediment as indicators What alternative land management

strategies will improve water quality? What policies need to be

implemented to achieve this water quality improvement?

Maquoketa Watershed

Scenario 1: all Agriculture

Scenario 2: all Forest

Scenario 3: N. half Agric. and S. half Forest.

Scenario 4: S. half Agric. and N. half Forest.

Scenario 5: Upper half Agric. and lower half Forest.

Scenario 6: Lower half Agric. and upper half Forest.

Scenario 7: Main channel basins - Agric.

Scenario 8: Main channel basins - Forest.

Scenario 1995 (normal year) 1993 (wet year) 1988 (dry year)

Flow Sediment yield Nitrate

Scenario 1

- - -

Scenario 2

-0.01 1.00 0.99

Scenario 3

-0.02 0.42 0.52

Scenario 4

0.00 0.55 0.48

Scenario 5

-0.03 0.75 0.60

Scenario 6

0.03 0.21 0.40

Scenario 7

-0.02 0.68 0.74

Scenario 8

0.02 0.28 0.25

Fractional changes in mean annual flow and yield under various scenarios normalized by the fractional change in area from all-agricultural for the scenario.

Scenario 1995 (normal year) 1993 (wet year) 1988 (dry year)

Flow Sediment yield Nitrate

Scenario 1

- - -

Scenario 2

-0.01 1.00 0.99

Scenario 3

-0.02 0.42 0.52

Scenario 4

0.00 0.55 0.48

Scenario 5

-0.03 0.75 0.60

Scenario 6

0.03 0.21 0.40

Scenario 7

-0.02 0.68 0.74

Scenario 8

0.02 0.28 0.25

Fractional changes in mean annual flow and yield under various scenarios normalized by the fractional change in area from all-agricultural for the scenario.


Improving Regional Climate Models Project to Intercompare Regional Climate

Simulations Transferability Working Group of GEWEX


Project to Intercompare Regional Climate Simulations (PIRCS)

PIRCS MissionTo provide a common framework for evaluating

strengths and weaknesses of regional climate models and their component procedures through

systematic, comparative simulationsPIRCS Co-Directors

http://www.pircs.iastate.edu/

Ray Arritt [email protected] Gutowski [email protected] Takle [email protected]

mailto:[email protected]







Danish Met. Inst. (HIRHAM4; J.H. Christensen, O.B. Christensen)Danish Met. Inst. (HIRHAM4; J.H. Christensen, O.B. Christensen) Université du Québec à Montréal (D. Caya, S. Biner)Université du Québec à Montréal (D. Caya, S. Biner) Scripps Institution of Oceanography (RSM; J. Roads, S. Chen)Scripps Institution of Oceanography (RSM; J. Roads, S. Chen) NCEP (RSM; S.-Y. Hong) NCEP (RSM; S.-Y. Hong) NASA - Marshall (MM5/BATS; W. Lapenta)NASA - Marshall (MM5/BATS; W. Lapenta) CSIRO (DARLAM; J. McGregor, J. Katzfey)CSIRO (DARLAM; J. McGregor, J. Katzfey) Colorado State University (ClimRAMS; G. Liston)Colorado State University (ClimRAMS; G. Liston) Iowa State University (RegCM2; Z. Pan)Iowa State University (RegCM2; Z. Pan) Iowa State University (MM5/LSM; D. Flory)Iowa State University (MM5/LSM; D. Flory) Univ. of Maryland / NASA-GSFC (GEOS; M. Fox-Rabinovitz)Univ. of Maryland / NASA-GSFC (GEOS; M. Fox-Rabinovitz) SMHI / Rossby Centre (RCA; M. Rummukainen, C. Jones)SMHI / Rossby Centre (RCA; M. Rummukainen, C. Jones) NOAA (RUC2; G. Grell)NOAA (RUC2; G. Grell) ETH (D. Luethi)ETH (D. Luethi) Universidad Complutense Madrid (PROMES; M.Gaertner)Universidad Complutense Madrid (PROMES; M.Gaertner) Université Catholique du Louvain (P. Marbaix)Université Catholique du Louvain (P. Marbaix) Argnonne National Lab (MM5 V3; J. Taylor, J. Larson)Argnonne National Lab (MM5 V3; J. Taylor, J. Larson) St. Louis University (Z. Pan)St. Louis University (Z. Pan)

PIRCS Participating GroupsPIRCS Participating Groups

La Plata

• Develop the ability to predict the variations of global and regional hydrological processes and water resources, and their response to environmental change.

• Foster the development of observing techniques, data management, and assimiliation systems suitable for operational application to long-range weather forecasts, hydrology, and climate predictions.

• Determine the hydrological cycle and energy fluxes by means of global measurements of observable atmospheric and surface properties.

• Model the global hydrological cycle and its impact on the atmosphere, oceans, and on the land surface.

OBJECTIVES

Global Energy and Water Cycle Experiment

Phase II Primary Science Questions

Is the Water Cycle Accelerating?

1. Are the Earth’s Energy Budget and Water Cycle Changing?

3. Can We Predict these Changes on up to S - IA?

2. How do Processes Contribute to Feedback and Causes of Natural Variability?

4. What are the Impacts of these Changes on Water Resources?

Updated GEWEX Science Questions :

Data Management

Water and Energy Budget Studies

Water Resource Applications Project

Sources and Cycling of Water

Extremes

Predictability

Transferability

CEOP IAEA

GAME


Summary

Regional climate models demonstrate sufficient skill to be useful for driving some climate impacts assessment models for the purpose of informing policy makers and decision-makers of vulnerabilities and opportunities associated with future climate change


For More Information

See my online Global Change course:

http://www.meteor.iastate.edu/gccourse

Contact me directly:

[email protected]







Documents

Regional Climate Modeling: A Tool for Decision-Makers