Use of Regional Models in Impacts Assessments

L. O. Mearns

NCAR

Colloquium on Climate and Health NCAR, Boulder, CO

July 22, 2004

“Most GCMs neither incorporate nor provide information on scales smaller than a few hundred kilometers. The effective size or scale of the ecosystem on which climatic impacts actually occur is usually much smaller than this. We are therefore faced with the problem of estimating climate changes on a local scale from the essentially large-scale results of a GCM.”

Gates (1985)

“One major problem faced in applying GCM projections to regional impact assessments is the coarse spatial scale of the estimates.”

Carter et al. (1994)

But, once we have more regional detail, what difference does it make in any given impacts assessment?

What is the added value?

Do we have more confidence in the more detailed results?

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Elevation (meters)

Elevation (meters)

NCAR CSM Topography2.8 deg. by 2.8 deg.

RegCM Topography 0.5 deg. by 0.5 deg.

Resolutions Used in Climate Models

• High resolution global coupled ocean-atmosphere model simulations are not yet feasible (~ 250 - 300 km)

• High resolution global atmospheric model simulations are feasible for time-slice experiments ~ 50-100 km resolution for 10-30 years (~ 100 km)

• Regional model simulations at resolution 10-30 km are feasible for simulations 20-50 years (~ 50 km)

Benefits of High Resolution Modeling• Improves weather forecasts (e.g., Kalnay et al.

1998), down to to 10 km and improves seasonal climate forecasts, but more work is needed (Mitchell et al., Leung et al., 2002).

• Improves climate simulations of large scale conditions and provides greater regional detail potentially useful for climate change impact assessments

• Often improves simulation of extreme events such as precipitation and extreme phenomena (hurricanes).

Regional Climate Modeling

• Adapted from mesoscale research or weather forecast models. Boundary conditions are provided by large scale analyses or GCMs.

• At higher spatial resolutions, RCMs capture climate features related to regional forcings such as orography, lakes, complex coastlines, and heterogeneous land use.

• GCMs at 200 – 250 km resolution provide reasonable large scale conditions for downscaling.

Regional Modeling Strategy

Nested regional modeling technique • Global model provides:

– initial conditions – soil moisture, sea surface temperatures, sea ice

– lateral meteorological conditions (temperature, pressure, humidity) every 6-8 hours.

– Large scale response to forcing (100s kms)

Regional model provides finer scale response (10s kms)

RCM Nesting Technique

Regional Climate Model Schematic

RotatedRotatedMercatorMercatorProjectionProjection

GLCCGLCCVegetationVegetation

Reanalysis Reanalysis & GCM & GCM

Initial and Initial and Boundary Boundary ConditionsConditions

Hadley & OISea Surface

Temperatures

USGSUSGSTopographyTopography

• Agriculture:

Brown et al., 2000 (Great Plains – U.S.)

Guereña et al., 2001 (Spain)

Mearns et al., 1998, 1999, 2000, 2001, 2003, 2004

(Great Plains, Southeast, and continental US)

Carbone et al., 2003 (Southeast US)

Doherty et al., 2003 (Southeast US)

Tsvetsinskaya et al., 2003 (Southeast U.S.)

Easterling et al., 2001, 2003 (Great Plains, Southeast)

Thomson et al., 2001 (U.S. Pacific Northwest)

Pona et al., (in Mearns, 2001) (Italy)

Use of Regional Climate Model Results for Impacts Assessments

Use of RCM Results for Impacts Assessments 2

• Water Resources:

Leung and Wigmosta, 1999 (US Pacific Northwest)

Stone et al., 2001, 2003 (Missouri River Basin)

Arnell et al., 2003 (South Africa)

Miller et al., 2003 (California)

Wood et al., 2004 (Pacific Northwest)

• Forest Fires:

Wotton et al., 1998 (Canada – Boreal Forest)

• Human Health:

New York City Health Project (ongoing)

Examples of RCM Use in Climate and Impacts Studies

• Precipitation and Hydrology over S. Africa

• Water Resources in Pacific Northwest

• Agriculture - Southeast US

• Human Health – New York

• European Prudence Program

• New Program – NARCCAP

Regional Climate Modeling and Hydrological Impacts in

Southern Africa

Arnell et al., 2003,

J. Geophys. Research

Arnell et al., 2003, J. of Geophys. Res.

Arnell et al., 2003, J. of Geophys. Res.

Climate Simulations of Western U.S. Strong Effect of Terrain

Model ability to resolve terrain features is critical

Observed snow pack , March, 1998 Observed mean annual precipitation

Leung et al., 2004, Climatic Change (Jan.)

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NCAR/DOE Topography2.8 deg. by 2.8 deg.

MM5 Topography 0.5 deg. by 0.5 deg.

Observed and Simulated El Nino Precipitation Anomaly

RCM reproduces mesoscale features associated

with ENSO events

RCM SimulationObservation

NCEP Reanalyses

Global and Regional Simulations of Snowpack

GCM under-predicted and misplaced snow

Regional Simulation Global Simulation

Climate Change SignalsTemperature Precipitation

PC

MR

CM

Extreme Precipitation/Snowpack ChangesLead to significant changes in streamflow affecting hydropower

production, irrigation, flood control, and fish protection

Special Issue of Climatic Change (60:1-148) Issues in the Impacts of Climatic Variability and

Change on Agriculture 1. Mearns, L. O., Introduction to the Special Issue on the Impacts of Climatic

Variability and Change on Agriculture

2. Mearns, L. O., F. Giorgi, C. Shields, and L. McDaniel, Climate Scenarios for the Southeast US based on GCM and Regional Model Simulations.

3. Tsvetsinskaya, E., L. O. Mearns, T. Mavromatis, W. Gao, L. McDaniel, and M. Downton,The Effect of Spatial Scale of Climate Change Scenarios on Simulated Maize, Wheat, and Rice Production in the Southeastern United States.

4. Carbone, G., W. Kiechle, C. Locke, L. O. Mearns, and L. McDaniel, Response of Soybeans and Sorghum to Varying Spatial Scales of Climate Change Scenarios in the Southeastern United States.

5. Doherty, R. M., L. O. Mearns, R. J. Reddy, M. Downton, and L. McDaniel, A Sensitivity Study of the Impacts of Climate Change at Differing Spatial Scales on Cotton Production in the SE USA.

6. Adams, R. M., B. A. McCarl, and L. O. Mearns, The Economic Effects of Spatial Scale of Climate Scenarios: An Example From U. S. Agriculture.

Models Employed

• Commonwealth Scientific and Industrial Research Organization (CSIRO) GCM – Mark 2 version• Spectral general circulation model

• Rhomboidal 21 truncation (3.2 x 5.6); 9 vertical levels

• Coupled to mixed layer ocean (50 m)

• 30 years control and doubled CO runs

• NCAR RegCM2• 50 km grid point spacing, 14 vertical levels

• Domain covering southeastern U.S.

• 5 year control run

• 5 year doubled CO runs

Domain of RegCM

denotes study area + denotes RegCM Grid Point (~ 0.5o)X denotes CSIRO Grid Point (3.2 o lat. 5.6 o long)

RegCM Topography (meters)

Contour from 100 to 4000 by 100 (x1)

Summer

Fall

Maximum TemperatureMinimum Temperature

CSIRO RegCM CSIRO RegCM

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Climate Change - Δ Temperature (oC)

% Change in Corn Yields

Regionalization of the climate change scenarios matters in terms of the economic indicators of the ASM

• Shows up in aggregate economic welfare (different orders of magnitude);

• Regional patterns of agricultural production are altered;

- more spatial variability with RegCM;- Southern states are more

negatively affected by RegCM.

Conclusions

• The contrast in economic net welfare based

on spatial scale of climate scenarios is

similar in magnitude to the economic

contrast resulting from use of two very

different AOGCM simulations in the US

National Assessment.

Conclusions (Con’t.)

Modeling the Impact of Global Climate and Regional Land Use Change on Regional

Climate and Air Quality over the Northeastern

United States C. Hogrefe, J.-Y. Ku, K. Civerolo, J. Biswas, B. Lynn, D. Werth, R. Avissar, C. Rosenzweig, R. Goldberg, C.

Small, W.D. Solecki, S. Gaffin, T. Holloway, J. Rosenthal, K. Knowlton, and P.L. Kinney

This project is supported by the U.S. Environmental Projection Agency under STAR grant R-82873301

NY Climate & Health Project:

Project Components

• Model Global Climate

• Model and Evaluate Land Use

• Model Regional Climate

• Model Regional Air Pollution (ozone, PM2.5)

• Evaluate Health Impacts (heat, air pollution)– For 2020s, 2050s, and 2080s

Model Setup• GISS coupled global ocean/atmosphere model driven by

IPCC greenhouse gas scenarios (“A2” high CO2 scenario presented here)

• MM5 regional climate model takes initial and boundary conditions from GISS GCM

• MM5 is run on 2 nested domains of 108km and 36km over the U.S.

• CMAQ is run at 36km to simulate ozone• 1996 U.S. Emissions processed by SMOKE and – for

some simulations - scaled by IPCC scenarios• Simulations periods : June – August 1993-1997

June – August 2053-2057

A Model Look Into the 2050’s

• How will modeled temperature and ozone in the northeastern U.S. change under the “A2” (high CO2 growth) scenario (assume constant VOC and NOx emissions)?

• How will CMAQ ozone predictions change when IPCC “A2” projected changes in ozone precursor emissions (VOC+8%, NOx+29.5%) are included in the simulation?

Research questions

• Health Risk Assessment:– Deaths due to short-term heat exposures

– Hospital admissions due to short-term ozone exposures

• Development of model linkages• Scale Intercomparison: as we go from 108 -> 36

-> 4km scale, what difference do we see in impact estimates? How do model results compare at different scales for NY metro region.

Global Climate ModelNASA-GISS

Land Use / Land CoverSLEUTH,

Remote Sensing

Regional ClimateClimRAMS

MM5

Air QualityMODELS-3

Public HealthRisk Assessment

reflectance; stomatal resistance;surface roughness

heat

OzonePM2.5

meteorologicalvariables:

temp., humidity, etc.

meteorological variables

IPCC A2, B2 Scenarios

IPCC A2, B2 Scenarios

Daily Maximum O3 Predictions July 9 - 14, 1996

MM5 Current Climate

GCM and RCMProjections

Tests with 12 and 4 km Resolution

RCMs and Simulation of Extremes

Do they do better?

1993 Midwest Summer Flood

USHCN ObservationsUSHCN Observations

RegCMRegCM

• Record high rainfall (>200 year event)

• Thousands homeless• 48 deaths• $15-20 billion in Damage

J. Pal

1988 Great North American Drought

CRU ObservationsCRU Observations

RegCMRegCM

• Driest/warmest since 1936• $30 billion in Agricultural

Damage

Putting spatial resolution in the context of other uncertainties

• Must consider the other major uncertainties regarding future climate in addition to the issue of spatial scale – what is the relative importance of uncertainty due to spatial scale?

• These include: – Specifying alternative future emissions of ghgs

and aerosols – Modeling the global climate response to the

forcings (i.e., differences among GCMs)

PRUDENCE Project

Multiple AOGCMs and RCMs over Europe: Simulations of Future

Climate

Summary of RegCM3Results for A2 and B2 scenariosNested in HADAM3 time-slice

• RegCM3 – 50 km • HadAM3 time slice – 100 km • Years – 1961-1990 vs.

2070 –2099• Control run results • Changes in Climate

Giorgi et al., 2004

Emissions ScenariosCO2 Emissions

(Gt C)CO2 Concentrations

(ppm)

A2

A2

B2

B2

Map of Domain & Topography

Winter Precipitation: Reference Simulation

DJF CRU

DJF RegCMDJF HadAMH

Summer Surface Air Temperature: Reference Simulation

JJA CRU

JJA RegCMJJA HadAMH

Summer Precipitation: Reference SimulationJJA CRU

JJA RegCMJJA HadAMH

Winter Temperature Change: B2 & A2 ScenariosDJF HadAMH: B2 DJF RegCM: B2

DJF RegCM: A2DJF HadAMH: A2

WARM WARM

HOT WARM

Summer Temperature Change: B2 & A2 ScenariosJJA HadAMH: B2 JJA RegCM: B2

JJA RegCM: A2JJA HadAMH: A2

WARM WARM

HOT WARM

Summer Precipitation Change: B2 & A2 Scenarios

DRY DRY

WETWET

JJA HadAMH: B2 JJA RegCM: B2

JJA RegCM: A2JJA HadAMH: A2

DRY DRY

WETWET

NARCCAP North American Regional

Climate Change Assessment Program

Multiple AOGCM and RCM Climate Scenarios Project over North

America

ParticipantsLinda O. Mearns, National Center for

Atmosheric Research,

Ray Arritt, Iowa State, George Boer, CCCma, Daniel Caya, OURANOS, Phil

Duffy, LLNL, Filippo Giorgi, Abdus Salam ICTP, William Gutowski, Iowa

State, Isaac Held, GFDL, Richard Jones, Hadley Centre, Rene Laprise, UQAM,

Ruby Leung, PNNL, Jeremy Pal, ICTP, John Roads, Scripps, Lisa Sloan, UC Santa Cruz, Ron Stouffer, GFDL, Gene Takle, Iowa State, Warren Washington, NCAR,

Francis Zwiers, CCCma

Main NARCCAP Goals

Exploration of multiple uncertainties in regional model and global climate model regional projections

  Development of multiple high resolution regional climate scenarios for use in impacts models

 

NARCCAP domain

A2 Emissions Scenario

GFDL CCSM HADAM3link to European

Prudence

CGCM3

1960-1990 current 2040-2070 futureProvide boundary conditions

MM5Iowa State/PNNL

RegCM3UC Santa CruzICTP

CRCMQuebec,Ouranos

HADRM3Hadley Centre

RSMScripps

WRFNCAR/PNNL

NARCCAP PLAN

A2 Emissions Scenario

GFDLAOGCM

CCSM

Global Time Slice / RCM Comparisonat same resolution (50km)

Six RCMS50 km

GFDLTime slice

50 km

CAM3Time slice

50km

compare compare

When to Use High Resolution

• Consider the importance of regional detail compared to other uncertainties in project

• High resolution useful when there are high resolution forcings: complex topography, complex coastlines, islands, heterogeneous land-use

• Consider also statistical downscaling (Wilby)• More guidance on web at: www. ipcc-ddc.cru.uea.ac.uk