Global climate model scenarios downscaled for Canada
David Price Northern Forestry Centre, Edmonton
CIF e-Lecture, 14 March 2012
Downscaled climate scenarios for Canada - 14 March 2012
Acknowledgements Slide 2
Dan McKenney Marty Siltanen Pia Papadopol Kevin Lawrence John Pedlar Kathy Campbell Yonghe Wang (all the above are with CFS)
Mike Hutchinson (Australian National University, Canberra)
Linda Joyce (USDA Forest Service, Ft Collins CO)
Dave Coulson (USDA Forest Service, Ft Collins CO)
Canadian Centre for Climate Modelling and Analysis (CCCMA)
US National Center for Atmospheric Research (NCAR)
G. Strand (UCAR) Australia: Commonwealth Scientific and
Industrial Research Organisation (CSIRO) M. Collier, M. Dix, and T. Hirst
(CSIRO Marine and Atmospheric Research Division)
Japan: Center for Climate System Research, University of Tokyo, National Institute for Environmental Studies, Frontier Research Center for Global Change
Many reviewers in Canada and the USA of two reports published in 2011.
Downscaled climate scenarios for Canada - 14 March 2012
Outline
Techniques: Downscaling and ANUSPLIN Selecting GCMs and GHG scenarios
Results Maps Graphs
Sample applications Testing the climate models Biophysical variables and moisture indices
Concluding remarks Publications & data distribution
Slide 3
Downscaled climate scenarios for Canada - 14 March 2012
Outline
Techniques: Downscaling and ANUSPLIN Selecting GCMs and GHG scenarios
Results Maps Graphs
Sample applications Testing the climate models Biophysical variables and moisture indices
Concluding remarks Publications & data distribution
Slide 4
Downscaled climate scenarios for Canada - 14 March 2012
What is Downscaling? Slide 5
Diagram from: D. Viner, CRU, University of East Anglia
―Downscaling‖ is using coarse spatial resolution data to generate information that is more useful at smaller scales
Dynamical: physically consistent simulations of weather at GCM timesteps but at higher spatial resolution. RCMs are the prime example.
Statistical: many methods to relate GCM results to observed weather and climate.
Spatial interpolation:
relatively simple and largely empirical, but robust!
Downscaled climate scenarios for Canada - 14 March 2012
About ANUSPLIN
Mike Hutchinson at Australian National University (Canberra)
FORTRAN program for application of multi-variate thin-plate splines
(typically up to 4 independent variables, more covariates)
Most applications routinely incorporate a spatially (and temporally)
varying dependence on elevation
A key element is that ANUSPLIN minimizes General Cross Validation (GCV)
statistic – an objective method to select the best interpolation models,
optimize data smoothing, and provide estimates of predictive error
Diagnostics help to identify data errors
ANUSPLIN continually being updated Check out http://fennerschool.anu.edu.au/publications/software/anusplin.php Numerous applications worldwide, many independent of Hutchinson’s group
Lots of references available: see CFS GLFC web site for a list and links: http://cfs.nrcan.gc.ca/subsite/glfc-climate
Slide 6
Downscaled climate scenarios for Canada - 14 March 2012
Ideally, we want to capture the climate change signal generated by the GCM, but corrected for the GCM’s ―inaccuracies‖ in representing reality
We use the ―Delta method‖, based on a reference period for which we also have observed data (e.g., 1961-1990)
Interpolated long-term monthly means (30-year ―normals‖) provide a reference data set with spatial detail
We then add the change signal (i.e., the temperature difference) to the observed climate normals for the reference period, interpolated to the same coordinates.
Requires processing of GCM data to convert them to deltas WRT the same period in the simulation.
Slide 7
Normalizing the GCM data
Downscaled climate scenarios for Canada - 14 March 2012
Correcting for GCM ―inaccuracy‖ Slide 8
Step 1: Determine mean of observations for reference period.
Downscaled climate scenarios for Canada - 14 March 2012
Slide 9
Correcting for GCM ―inaccuracy‖
Step 1: Determine mean of observations for reference period.
Step 2: Determine mean of GCM projection for reference period.
Downscaled climate scenarios for Canada - 14 March 2012
Slide 10
Correcting for GCM ―inaccuracy‖
Step 1: Determine mean of observations for reference period.
Step 2: Determine mean of GCM projection for reference period.
Step 3: Calculate delta values by subtracting (or dividing by) the GCM mean from Step 2
Downscaled climate scenarios for Canada - 14 March 2012
Slide 11
Correcting for GCM ―inaccuracy‖
Step 1: Determine mean of observations for reference period.
Step 2: Determine mean of GCM projection for reference period.
Step 3: Calculate delta values by subtracting (or dividing by) the GCM mean from Step 2
Step 4: Calculate corrected GCM data by adding (or multiplying by) the observed mean from Step 1
Downscaled climate scenarios for Canada - 14 March 2012
Selected GCM Scenarios
Projection data generated by GCMs from CCCma (Canada), CSIRO (Australia), NCAR (USA) and NIES (Japan). [Data also available from IPCC 3rd Assessment (TAR, 2001) (CCCma, CSIRO, Hadley Centre (UK) and NCAR.] SRES A2: increasing population, little technological change, greater
deforestation, pollution and CO2 emissions SRES B1: as A2, but rapid global shift towards resource-efficient technologies
and reduced GHG emissions SRES B2: as B1, but more local efforts to increase resource efficiency and
reduce emissions SRES A1B: higher population growth than A2, with balance of energy from fossil
and renewable sources
Monthly time series extending from 1961 to 2100, gridded to 5 arcminute (1/12 degree lat/lon) resolution – about 10 km.
20 data sets in total. Lots of ways to use these data!
Nakićenović et al. 2000. IPCC Special Report on Emissions Scenarios.
Slide 12
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IPCC AR4 GHG Scenarios Slide 13
Downscaled climate scenarios for Canada - 14 March 2012
GCM spatial resolutions vary Slide 14
Downscaled climate scenarios for Canada - 14 March 2012
GCM input data sets Slide 15
GCM1 IPCC AR4 scenario(s)
Monthly variable(s)2 Source3 Time period
CGCM31MR 20C3M, A1B, A2, B1
pr, tas, rsds, hur, huss, psl, uas, vas
CMIP3 1961–2100
CGCM31MR 20C3M, A1B, A2, B1
tasmin, tasmax CCCma 1961–2100
CSIROMK35 20C3M, A1B, A2, B1
pr, tas, tasmin, tasmax, rsds, psl, uas, vas, hur, huss (except B1)
CMIP3 1961–2100
CSIROMK35 B1 huss CSIRO 2001–2100
MIROC32MR 20C3M, A1B, A2, B1
pr, tas, tasmin, tasmax, rsds, hur, huss, psl, uas, vas
CMIP3 1961–2100
NCARCCSM3 20C3M, A1B, B1
pr, tas, tasmin, tasmax, rsds, hur, huss, psl, uas, vas
CMIP3 1961–2099
NCARCCSM3 A2 pr, tas, tasmin, tasmax, rsds, hur, huss, psl, uas, vas
ESG 1961–2099
Downscaled climate scenarios for Canada - 14 March 2012
Outline
Techniques: Downscaling and ANUSPLIN Selecting GCMs and GHG scenarios
Results Maps Graphs
Applications Testing the climate models Biophysical variables and moisture indices
Concluding remarks Publications & data distribution
Slide 16
Downscaled climate scenarios for Canada - 14 March 2012
Slide 17
These maps show ―absolute‖ temperatures. It is very hard to see the changes over 100+ simulated years!
Projected changes in Tmax
Downscaled climate scenarios for Canada - 14 March 2012
Projected changes in Precip Slide 18
These maps show ―absolute‖ total annual precipitation. Again, it is very hard to see the changes over 100+ simulated years! It would be just as hard to see differences among different GCMs when forced by the same GHG emissions scenario.
Downscaled climate scenarios for Canada - 14 March 2012
Changes in annual means (SRES A2, 2080s)
Slide 19
Temperature Increase (°C) Precipitation Change (ratio)
CGCM3.1 - Canada
CSIRO Mk 3.5 - Australia
MIROC3.2 - Japan
NCAR CCSM3 - USA
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Analysis by Canadian ecozones Slide 20
Downscaled climate scenarios for Canada - 14 March 2012
Slide 21 Annual Mean Daily Tmin Prairies subhumid ecozone (Parkland)
Tem
pera
ture
(°C
)
(Historical data ~45 years)
Downscaled climate scenarios for Canada - 14 March 2012
Slide 22 Winter (DJF) Mean Daily Tmin Boreal Plains ecozone
Tem
pera
ture
(°C
)
Downscaled climate scenarios for Canada - 14 March 2012
Slide 23 Summer (JJA) Mean Daily Tmax Atlantic Maritime ecozone
Tem
pera
ture
(°C
)
Downscaled climate scenarios for Canada - 14 March 2012
Slide 24 Summer (JJA) Mean Vapour Pressure Atlantic Maritime ecozone
Vapo
ur p
ress
ure
(kPa
)
(No historical record)
Downscaled climate scenarios for Canada - 14 March 2012
Slide 25 Fall (SON) Total Precipitation Mixedwood Plains ecozone
Tota
l Pre
cipi
tatio
n (m
m)
Downscaled climate scenarios for Canada - 14 March 2012
M
Slide 26 Winter (DJF) Mean Daily Solar Radn Boreal Shield W ecozone
MJ
m-2
day
-1 (No historical record)
Downscaled climate scenarios for Canada - 14 March 2012
Slide 27 Winter (DJF) Mean Daily Solar Radn Boreal Shield W ecozone
10-year moving averages
MJ
m-2
day
-1
Downscaled climate scenarios for Canada - 14 March 2012
Pacific Maritime Montane Cordillera Atlantic Maritime
Prairies Aspen parkland Mixedwood Plains
2050
2090
Which GCM scenarios are best for a regional study? It depends….
Slide 28
Downscaled climate scenarios for Canada - 14 March 2012
Taiga Plains Boreal Shield W Boreal Shield E
Boreal Cordillera Boreal Plains Hudson Plains
2050 2090
Which GCM scenarios are best for a regional study? It depends….
Slide 29
Downscaled climate scenarios for Canada - 14 March 2012
IPCC AR4 GHG Scenarios Slide 30
Downscaled climate scenarios for Canada - 14 March 2012
Taiga Plains Hudson Plains
Aspen Parkland Boreal Shield E
Ann
ual M
ean
Dai
ly T
min
(°C
)
Boreal Plains
Temperature trends by ecozone — 1960 to 2100
Slide 31
Downscaled climate scenarios for Canada - 14 March 2012
Taiga Plains Hudson Plains
Aspen Parkland Boreal Shield E
Ann
ual M
ean
Dai
ly T
min
(°C
)
Boreal Plains
Temperature trends by ecozone — 1960 to 2100
Slide 32
Downscaled climate scenarios for Canada - 14 March 2012
Precipitation trends by ecozone — 1960 to 2100
Taiga Plains Hudson Plains
Aspen Parkland Boreal Shield E
Ann
ual T
otal
Pre
cipi
tatio
n (m
m)
Boreal Plains
Slide 33
Downscaled climate scenarios for Canada - 14 March 2012
Outline
Techniques: Downscaling and ANUSPLIN Selecting GCMs and GHG scenarios
Results Maps Graphs
Applications Testing the climate models Biophysical variables and moisture indices
Concluding remarks Publications & data distribution
Slide 34
Downscaled climate scenarios for Canada - 14 March 2012
Do GCMs really work? Slide 35
www.globalwarmingart.com
Data from: Meehl et al. 2004. J. Clim. 17: 3721-3727. Jones and Moberg. 2003. J. Clim. 16: 206-223.
Downscaled climate scenarios for Canada - 14 March 2012 Ensemble_a2_MaxT_July Ensemble_a2_MinT_January
Overestimating Tmax
Underestimating observed Tmin— it was warmer in 1990-2005 than the GCMs predicted!
GCM “validation” (15 years of observed data vs. simulated) Slide 36
Downscaled climate scenarios for Canada - 14 March 2012
Biophysical variables Slide 37
No. Variable Description
1 Annual Mean Temperature Annual mean of monthly mean temperatures
2 Mean Diurnal Range Annual mean of monthly mean daily temperature ranges
3 Isothermality (2) / (7) 4 Temperature Seasonality Standard deviation of monthly mean
temperature estimates expressed as a percentage of their mean
5 Max Temperature of Warmest Period Highest monthly maximum temperature
6 Min Temperature of Coldest Period Lowest monthly minimum temperature
7 Temperature Annual Range (5) – (6) 8 Mean Temperature of Wettest
Quarter Mean temperature of three wettest months
9 Mean Temperature of Driest Quarter Mean temperature of three driest months
10 Mean Temperature of Warmest Quarter
Mean temperature of three warmest months
11 Mean Temperature of Coldest Quarter
Mean temperature of three coldest months
12 Annual Precipitation Sum of monthly precipitation values
13 Precipitation of Wettest Period Precipitation of the wettest month
14 Precipitation of Driest Period Precipitation of the driest month
15 Precipitation Seasonality Standard deviation of monthly precipitation estimates expressed as a percentage of their mean
16 Precipitation of Wettest Quarter Total precipitation of three wettest months
17 Precipitation of Driest Quarter Total precipitation of three driest months
18 Precipitation of Warmest Quarter Total precipitation of three warmest months
19 Precipitation of Coldest Quarter Total precipitation of three coldest months
20 Start of Growing Season Date when daily mean temperature first meets or exceeds 5 °C for five consecutive days in spring
21 End of Growing Season Date when daily minimum temperature first falls below -2 °C after 1 August
22 Growing Season Length (21) – (20) 23 Total Precipitation for Period 1 Total precipitation of three months prior to
(20) 24 Total Precipitation for Period 3 Total precipitation during (22) 25 Growing Degree Days for Period 3 Total degree days during (22), accumulated
for all days where mean temperature exceeds 5 °C.
26 Annual Minimum Temperature Annual mean of monthly minimum temperatures
27 Annual Maximum Temperature Annual mean of monthly maximum temperatures
28 Mean Temperature for Period 3 Mean temperature during (22) 29 Temperature Range for Period 3 Highest minus lowest temperature during (22)
Downscaled climate scenarios for Canada - 14 March 2012
Range of approaches to calculating balance of annual precipitation and evapotranspiration, the latter a function of temperature and radiation. Climate Moisture Index (Hogg 1994, 1997) PDSI (Palmer 1965)
Considerable interest in projecting how climate change will affect water supplies, availability, and hence ecosystems and communities… E.g., Dai (2011)…
We are investigating implications for Canadian forest regions using our own data
Projecting Future Drought Slide 38
Downscaled climate scenarios for Canada - 14 March 2012
Slide 39 The future global context?
Dai 2011. WIRES Climate Change 2: 45-66. doi: 10.1002/wcc.81
-20 -10 -6 -3 -1 0 +1 +3 +6 +10 +20 10-yr average Palmer Drought Severity Index from IPCC AR4
(A1B scenario, 22 models,)
1955 1980
2005 2035
2065 2095
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Projections of Hogg CMI Slide 40
1961-1990 2011-2040
2041-2070 2071-2100
SRES A2 averages of four GCMs
Maps prepared by Y. Wang, NRCan
Downscaled climate scenarios for Canada - 14 March 2012
Outline
Techniques: Downscaling and ANUSPLIN Selecting GCMs and GHG scenarios
Results Maps Graphs
Applications Testing the climate models Biophysical variables and moisture indices
Concluding remarks Publications & data distribution
Slide 41
Downscaled climate scenarios for Canada - 14 March 2012
Data distribution - GLFC Slide 42
http://cfs.nrcan.gc.ca/projects/3/3
Downscaled climate scenarios for Canada - 14 March 2012
Data distribution - GLFC Slide 43
http://cfs.nrcan.gc.ca/projects/3/3
Downscaled climate scenarios for Canada - 14 March 2012
Concluding Remarks
We have created a suite of several national-scale climate scenarios which allow us to explore a range of potential impacts
We chose a simple downscaling approach that is easy to understand and provides robust data for application over large regions It is not clear that other methods give results that
are more meaningful, especially considering all the assumptions and errors in current GCMs. (Not suggesting there is anything wrong with other downscaling methods!)
Data are freely available to anyone on request!
Slide 44
Downscaled climate scenarios for Canada - 14 March 2012
Publications Slide 45
http://www.fs.fed.us/rm/pubs/rmrs_gtr263.pdf http://cfs.nrcan.gc.ca/publications?id=32971