Use of Regional Climate Models in Impacts

Assessments L. O. Mearns

Institute for the Study of Society and the Environment

National Center for Atmospheric Research

Colloquium on Climate and Health Boulder, Colorado

July 17, 2006

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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)

Now that we can 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?

How important is spatial scale versus other factors regarding simulating future climate?

• 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)

White et al., 2006 (California (wine))

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 (Southern Africa)

Miller et al., 2003 (California)

Payne et al., 2004 (Columbia River Basin)

Wood et al., 2004 (Pacific Northwest)

• Forest Fires:

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

• Human Health:

Hogrefe et al., 2004 (New York City)

Examples of RCM Use in Climate and Impacts Studies

• Water Resources – Pacific Northwest

• Agriculture – Wine Production in US

• Human Health – New York

• European Prudence Program

• New Program – NARCCAP

ACPI Climate Change Studies

• One control and 3 ensemble future PCM simulations were used to drive the RCM for current and 2040-2060

• Goal: Examine the effects of climate change on water resources in the western US

Leung et al., 2004

Global and Regional Simulations of Snowpack

GCM under-predicted and misplaced snow

Regional Simulation Global Simulation

Climate Change SignalsTemperature Precipitation

PC

MR

CM

Effects of Climate Change on Water Resources of the Columbia River Basin

• Change in snow water equivalent: – PCM: - 16% – RCM: - 32%

• Change in average annual runoff: – PCM: 0%– RCM: - 10%

Payne et al., 2004

Changes in Extremes – A2 scenario RegCM3 nested in FV-GCM

Changes in T95 event frequency (days per year) and T95 mean heat wave length (days per event)

Diffenbaugh et al., 2005

Climate Change and Wine Production in the US

Extreme heat could, by the end of the 21st century, result in loss of 80 percent of wine growing area in the US.

Significant shift in wine growing areas, to the Northwest and Northeast. Current wine growing areas in California, for example, would no longer be viable areas for wine production.

White et al., 2006

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

U.S. EPA STAR Program

Hogrefe et al., 2004

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

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

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

Daily Maximum O3 Predictions July 9 - 14, 1996

Tests with 12 and 4 km Resolution

Changes in Ozone with Climate Change

2020Current

(ppb)

2050 2080

Hogrefe et al. 2004

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)

Programs Exploring Multiple Uncertainties

• PRUDENCE - over Europe

• NARCCAP – over North America • CREAS: Cenários REgionais de Mudança de

Clima para América do Sul

(Regional Climate Change Scenarios for South America)

PRUDENCE Project

Multiple AOGCMs and RCMs over Europe: Simulations of Future

ClimateChristensen et al., 2006

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• A2 and B2 SRES

scenarios

Giorgi et al., 2004

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

JJA RegCM: A2JJA HadAMH: A2

WARM WARM

HOT WARM

NARCCAP North American Regional

Climate Change Assessment Program

Multiple AOGCM and RCM Climate Scenarios Project over North

Americawww.narccap.ucar.edu

Participants

Linda O. Mearns, National Center for Atmosheric Research,

Ray Arritt, Iowa State, 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,

Doug Nychka, NCAR Jeremy Pal, ICTP, John Roads, Scripps, Lisa Sloan, UC Santa Cruz, Ron Stouffer, GFDL, Gene Takle, Iowa State, Bill Collins, 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

Final Thoughts

• Exploration of multiple uncertainties

• Establishing greater confidence in high resolution simulations