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The North American Regional Climate Change Assessment Program (NARCCAP) Linda O. Mearns National Center for Atmospheric Research. SAMSI Climate Change Workshop Research Triangle Park, NC February 18, 2010. Global Climate Models. Regional Climate Models. - PowerPoint PPT Presentation
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The North American Regional Climate Change Assessment Program
(NARCCAP)
Linda O. MearnsNational Center for Atmospheric Research
SAMSI Climate Change Workshop Research Triangle Park, NC
February 18, 2010
Global Climate Models
Regional Climate Models
What high resolution is really good for
• In certain specific contexts, provides insights on realistic climate response to high resolution forcing (e.g. mountains, complex coast lines)
• For coupling climate models to other models that require high resolution (e.g. air quality models – for air pollution studies)
Advantages of higher resolution
North America at 50 km grid spacing
North America at typical global climate model resolution
Hadley Centre AOGCM (HadCM3), 2.5˚ (lat) x 3.75˚ (lon), ~ 280 km
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 AOGCMs)
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 (10s km)
response
The North American Regional Climate Change Assessment Program (NARCCAP)
•Exploration of multiple uncertainties in regional model and global climate model regional projections
•Development of multiple high resolution regionalclimate scenarios for use in impacts assessments.
•Further evaluation of regional model performance over North America
•Exploration of some remaining uncertainties in regional climate modeling(e.g., importance of compatibility of physics in nesting and nested models)
•Program has been funded by NOAA-OGP, NSF, DOE, USEPA-ORD – 4-year program
Initiated in 2006, it is an international program that will servethe climate scenario needs of the United States, Canada, and northern Mexico.
www.narccap.ucar.edu
NARCCAP - TeamLinda O. Mearns, NCAR
Ray Arritt, Iowa State; Dave Bader, LLNL and Oakridge National Lab; Melissa Bukovsky, NCAR;
Richard Jones, Wilfran Moufouma-Okia, UK Hadley Centre; Sébastien Biner, Daniel Caya, Ouranos
(Quebec); Phil Duffy, Climate Central; Dave Flory, Iowa State; William Gutowski, Iowa State; Isaac Held,
GFDL; Bill Kuo, NCAR; René Laprise, UQAM; Ruby Leung, Yun Qian, PNNL; Larry McDaniel, Seth
McGinnis, Don Middleton, NCAR; Ana Nunes, Scripps; Doug Nychka, NCAR, John Roads*, Scripps; Steve
Sain, NCAR; Lisa Sloan, Mark Snyder, UC Santa Cruz, Gene Takle, Iowa State
* Deceased June 2008
NARCCAP Domain
Organization of Program• Phase I: 25-year RCM simulations using NCEP-Reanalysis
boundary conditions (1979—2004)
• Phase II: Climate Change Simulations
– Phase IIa: RCM runs (50 km res.) nested in AOGCMs current and future
– Phase IIb: Time-slice experiments at 50 km res. (GFDL and NCAR CAM3). For comparison with RCM runs.
• Quantification of uncertainty at regional scales – probabilistic approaches
• Scenario formation and provision to impacts community led by NCAR.
• Opportunity for double nesting (over specific regions) to include participation of other RCM groups (e.g., for NOAA OGP RISAs, CEC, New York Climate and Health Project, U. Nebraska).
Phase I
• All 6 RCMs have completed the reanalysis-driven runs (RegCM3, WRF, CRCM, ECPC RSM, MM5, HadRM3)
• Results are shown here for 1980-2004 from six RCMs
• Configuration:– common North America domain (some differences due
to horizontal coordinates)– horizontal grid spacing 50 km– boundary data from NCEP/DOE Reanalysis 2– boundaries, SST and sea ice updated every 6 hours
Regions Analyzed
Boreal forest
Pacific coast
California coast
Deep South
Great LakesMaritimes
Upper Mississippi
River
Coastal CaliforniaCoastal California• Mediterranean climate: wet winters and
very dry summers (Koeppen types Csa, Csb).
– More Mediterranean than the Mediterranean Sea region.
• ENSO can have strong effects on interannual variability of precipitation.
R. Arritt
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12
15
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
mm
/day
RCM3 MM5IECPC CRCMWRFP HRM3Observed (GPCC) Observed (UDEL)Observed (CRUT) Ensemble
1982-83 El Nino
1997-98 El Nino
multi-year drought
Monthly time series of precipitation in coastal California
small spread, high skill
Correlation with Observed Precipitation - Coastal California
Model Correlation
HadRM3 0.857
RegCM3 0.916
MM5 0.925
RSM 0.945
CRCM 0.946
WRF 0.918
Ensemble 0.947
Ensemble mean has a higher correlation than any model
All models have high correlations with observed monthly time series of precipitation.
Deep SouthDeep South• Humid mid-latitude climate with substantial
precipitation year around (Koeppen type Cfa).
• Past studies have found problems
with RCM simulations of
cool-season precipitation in this region.
Monthly Time Series - Deep South
Model Correlation
HadRM3 0.489
RegCM3 0.231
MM5 0.343
RSM 0.649
CRCM 0.649
WRF 0.513
Ensemble 0.640
Two models (RSM and CRCM) perform much better. These models inform the domain interior about the large scale.
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1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
mm
/da
y
RCM3 MM5I ECPCCRCM WRFP HRM3Observed (GPCC) Observed (UDEL) Observed (CRUT)Ensemble
Ensemble (black curve)
Monthly Time Series - Deep South
Model Correlation
HadRM3 0.489
RegCM3 0.231
MM5 0.343
RSM 0.649
CRCM 0.649
WRF 0.513
Ensemble 0.640
RSM+CRCM 0.727
A “mini ensemble” of RSM and CRCM performs best in this region.
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1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
mm
/da
y
RCM3 MM5I ECPCCRCM WRFP HRM3Observed (GPCC) Observed (UDEL) Observed (CRUT)Ensemble
Ensemble (black curve)
A2 Emissions Scenario
GFDL CCSMHADCM3CGCM3
1971-2000 current 2041-2070 futureProvide boundary conditions
MM5Iowa State/PNNL
RegCM3UC Santa CruzICTP
CRCMQuebec,Ouranos
HADRM3Hadley Centre
RSMScripps
WRFNCAR/PNNL
NARCCAP PLAN – Phase II
CAM3Time slice
50km
GFDLTime slice
50 km
GCM-RCM Matrix
GFDL CGCM3 HADCM3 CCSM
MM5 X X1
RegCM X1** X**
CRCM X1** X
HADRM X X1**
RSM X1 X
WRF X X1
*CAM3 X
*GFDL X**
1 = chosen first GCM *= time slice experiments Red = run completed ** = data loaded
AOGCMS
RCMs
Phase II (Climate Change) Results
Change in Winter TemperatureUK Models
Change in Summer TemperatureUK Models
Uncertainty across two RCMs nested in same GCM for % Change in Winter Precipitation
Global Model Regional Model 1 Regional Model 2
Effect of two different GCMs driving one RCM – % change in winter precipitation
GCMs
RCM RegCM3
GFDLCGCM3
A2 Emissions Scenario
GFDLAOGCM
NCARCCSM
Global Time Slice / RCM Comparisonat same resolution (50km)
Six RCMS50 km
GFDLAGCM
Time slice50 km
CAM3Time slice
50km
compare compare
RegCM3 in GFDL% Change Precip - Winter
Quantification of Uncertainty
• The four GCM simulations already ‘situated’ probabilistically based on earlier work (Tebaldi et al., 2004, 2005)
• RCM results nested in particular GCM would be represented by a probabilistic model (derived assuming probabilistic context of GCM simulation)
• Use of performance metrics to differentially weight the various model results – will use different metrics – including process level expert judgment - determine sensitivity of final pdfs to various methods
NARCCAP Project Timeline
1/06 8/09
6/1012/07
AOGCM Boundaries available
9/07
Phase 1
Future Climate 1
9/08
Current Climate1
Current and Future 2 Project Start
Time slices
Archiving Procedures - Implementation
Phase IIb
Phase IIa
The NARCCAP User Community
Three user groups:
• Further dynamical or statistical downscaling
• Regional analysis of NARCCAP results
• Use results as scenarios for impacts and adaptation
studies
www.narccap.ucar.edu
To sign up as user, go to web site – contact Seth McGinnis
,
Over 200 hundred users registered
End