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Use of Regional Models in Impacts Assessments. L. O. Mearns NCAR Colloquium on Climate and Health NCAR, Boulder, CO July 22, 2004.

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Use of regional models in impacts assessments

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?


Elevation (meters) it make in any given impacts assessment?

2500

2250

2000

1750

1500

1250

1000

750

RegCM Topography

0.5 deg. by 0.5 deg.

500

250

0

Elevation (meters)

-250

3000

2750

NCAR CSM Topography

2.8 deg. by 2.8 deg.

2500

2250

2000

1750

1500

1250

1000

750

500

250

0


Resolutions used in climate models
Resolutions Used in Climate Models it make in any given impacts assessment?

  • 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
Benefits of High Resolution Modeling it make in any given impacts assessment?

  • 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 it make in any given impacts assessment?

  • 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
Regional Modeling Strategy it make in any given impacts assessment?

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
RCM Nesting Technique it make in any given impacts assessment?


Regional climate model schematic

GLCC it make in any given impacts assessment?

Vegetation

Reanalysis & GCM Initial and Boundary Conditions

Rotated

Mercator

Projection

USGS

Topography

Regional Climate Model Schematic

Hadley & OI

Sea Surface

Temperatures


Use of Regional Climate Model Results for Impacts Assessments

  • 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 rcm results for impacts assessments 2
Use of RCM Results for Impacts Assessments 2 Assessments

  • 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
Examples of RCM Use in Climate and Impacts Studies Assessments

  • 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

Regional Climate Modeling and Hydrological Impacts in Southern Africa

Arnell et al., 2003,

J. Geophys.Research




Observed snow pack , March, 1998 Southern Africa

Observed mean annual precipitation

Climate Simulations of Western U.S. Strong Effect of TerrainModel ability to resolve terrain features is critical

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


Elevation (meters) Southern Africa

2500

2250

2000

1750

1500

1250

1000

750

MM5 Topography

0.5 deg. by 0.5 deg.

500

250

0

Elevation (meters)

-250

3000

2750

2500

NCAR/DOE Topography

2.8 deg. by 2.8 deg.

2250

2000

1750

1500

1250

1000

750

500

250

0


Observed and Simulated El Nino Precipitation Anomaly Southern AfricaRCM reproduces mesoscale features associated with ENSO events

Observation

RCM Simulation

NCEP Reanalyses


Global and Regional Simulations of Snowpack Southern AfricaGCM under-predicted and misplaced snow

Regional Simulation

Global Simulation


Climate Change Signals Southern Africa

Temperature

Precipitation

PCM

RCM


Extreme Precipitation/Snowpack Changes Southern AfricaLead to significant changes in streamflow affecting hydropower production, irrigation, flood control, and fish protection


Special Issue of Southern AfricaClimatic Change (60:1-148)

Issues in the Impacts of Climatic Variability and

Change on Agriculture

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

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

  • 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.

  • 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.

  • 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.

  • 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 Southern Africa

  • 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 Southern Africa

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) Southern Africa

Contour from 100 to 4000 by 100 (x1)


Climate Change - Southern AfricaΔ Temperature (oC)

CSIRO

RegCM

CSIRO

RegCM

Summer

Fall

Minimum Temperature

Maximum Temperature

7.00

to

10.00

6.00

to

7.00

5.00

to

6.00

4.00

to

5.00

3.00

to

4.00

2.00

to

3.00

1.00

to

2.00

0.00

to

1.00

-1.00

to

0.00


% Change in Corn Yields Southern Africa


Conclusions Southern Africa

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 (Con’t.) Southern Africa

  • 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.


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
NY Climate & Health Project: Change on Regional Climate and Air Quality over the Northeastern United StatesProject 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
Model Setup Change on Regional Climate and Air Quality over the Northeastern United States

  • 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
A Model Look Into the 2050’s Change on Regional Climate and Air Quality over the Northeastern United States

  • 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
Research questions Change on Regional Climate and Air Quality over the Northeastern United States

  • 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 Model Change on Regional Climate and Air Quality over the Northeastern United States

NASA-GISS

IPCC A2, B2 Scenarios

meteorological variables

Regional Climate

ClimRAMS

MM5

reflectance;

stomatal resistance;

surface roughness

heat

Public Health

Risk Assessment

meteorological

variables:

temp., humidity, etc.

Land Use / Land Cover

SLEUTH,

Remote Sensing

Ozone

PM2.5

Air Quality

MODELS-3

IPCC A2, B2 Scenarios


Daily maximum o 3 predictions july 9 14 1996
Daily Maximum O Change on Regional Climate and Air Quality over the Northeastern United States3 Predictions July 9 - 14, 1996


Mm5 current climate
MM5 Current Climate Change on Regional Climate and Air Quality over the Northeastern United States


GCM and RCM Change on Regional Climate and Air Quality over the Northeastern United States

Projections


Tests with 12 and 4 km resolution
Tests with 12 and 4 km Resolution Change on Regional Climate and Air Quality over the Northeastern United States


Rcms and simulation of extremes

RCMs and Simulation of Extremes Change on Regional Climate and Air Quality over the Northeastern United States

Do they do better?


1993 midwest summer flood
1993 Midwest Summer Flood Change on Regional Climate and Air Quality over the Northeastern United States

  • Record high rainfall (>200 year event)

  • Thousands homeless

  • 48 deaths

  • $15-20 billion in Damage

USHCN Observations

J. Pal

RegCM


1988 great north american drought

RegCM Change on Regional Climate and Air Quality over the Northeastern United States

1988 Great North American Drought

CRU Observations

  • Driest/warmest since 1936

  • $30 billion in Agricultural Damage


Putting spatial resolution in the context of other uncertainties
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

PRUDENCE Project uncertainties

Multiple AOGCMs and RCMs over Europe: Simulations of Future Climate


Summary of regcm3 results for a2 and b2 scenarios nested in hadam3 time slice
Summary of RegCM3 uncertaintiesResults 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 scenarios
Emissions Scenarios uncertainties

CO2 Emissions

(Gt C)

CO2 Concentrations

(ppm)

A2

A2

B2

B2



Winter Precipitation: Reference uncertaintiesSimulation

DJF CRU

DJF HadAMH

DJF RegCM


Summer Surface Air Temperature: Reference Simulation uncertainties

JJA CRU

JJA HadAMH

JJA RegCM


Summer Precipitation: Reference Simulation uncertainties

JJA CRU

JJA HadAMH

JJA RegCM


Winter Temperature Change: B2 & A2 Scenarios uncertainties

DJF HadAMH: B2

DJF RegCM: B2

WARM

WARM

DJF HadAMH: A2

DJF RegCM: A2

WARM

HOT


Summer Temperature Change: B2 & A2 Scenarios uncertainties

JJA HadAMH: B2

JJA RegCM: B2

WARM

WARM

JJA HadAMH: A2

JJA RegCM: A2

WARM

HOT


Summer Precipitation Change: B2 & A2 Scenarios uncertainties

JJA HadAMH: B2

JJA RegCM: B2

WET

WET

DRY

DRY

JJA HadAMH: A2

JJA RegCM: A2

WET

WET

DRY

DRY


Narccap north american regional climate change assessment program

NARCCAP uncertaintiesNorth American Regional Climate Change Assessment Program

Multiple AOGCM and RCM Climate Scenarios Project over North America


Participants

Participants uncertainties

Linda 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, WarrenWashington, NCAR, Francis Zwiers, CCCma


Main narccap goals
Main NARCCAP Goals uncertainties

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

  Development of multiplehigh resolutionregional climatescenarios for use in impacts models


Narccap domain
NARCCAP domain uncertainties


NARCCAP PLAN uncertainties

A2 Emissions Scenario

HADAM3

link to European

Prudence

GFDL

CCSM

CGCM3

Provide boundary conditions

2040-2070 future

1960-1990 current

CRCM

Quebec,

Ouranos

RegCM3

UC Santa Cruz

ICTP

HADRM3

Hadley Centre

RSM

Scripps

WRF

NCAR/

PNNL

MM5

Iowa State/

PNNL


Global Time Slice / RCM Comparison uncertainties

at same resolution (50km)

A2 Emissions Scenario

GFDL

AOGCM

CCSM

Six RCMS

50 km

CAM3

Time slice

50km

GFDL

Time slice

50 km

compare

compare


When to use high resolution
When to Use High Resolution uncertainties

  • 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


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