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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
“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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0
-250 3000
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2500
2250
2000
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1000
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0
Elevation (meters)
Elevation (meters)
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
5.00 to
6.00
3.00 to
4.00
-1.00 to
0.00
7.00 to
10.00
6.00 to
7.00
2.00 to
3.00
4.00 to
5.00
1.00 to
2.00
0.00 to
1.00
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
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