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Explore the benefits and strategies of using regional climate models for assessing impacts on agriculture, water resources, forest fires, and human health. Learn about the added value of detailed results and the importance of spatial scale in future climate simulations.
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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
Elevation (meters) 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 • 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 versusother factors regarding simulating future climate?
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) • White et al., 2006 (California (wine))
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 forcurrent and2040-2060 • Goal: Examine the effects of climate change on water resources in the western US Leung et al., 2004
Global and Regional Simulations of SnowpackGCM under-predicted and misplaced snow Regional Simulation Global Simulation
Climate Change Signals Temperature Precipitation PCM RCM
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 Hogrefe et al., 2004 U.S. EPA STAR Program
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 Model 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
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
Changes in Ozone with Climate Change 2020 Current (ppb) 2080 2050 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 Climate Christensen 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 Scenarios JJA HadAMH: B2 JJA RegCM: B2 WARM WARM JJA HadAMH: A2 JJA RegCM: A2 WARM HOT
NARCCAP North American Regional Climate Change Assessment Program Multiple AOGCM and RCM Climate Scenarios Project over North America www.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 multiplehigh resolutionregional climatescenarios for use in impacts models
NARCCAP PLAN 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 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
Final Thoughts • Exploration of multiple uncertainties • Establishing greater confidence in high resolution simulations