ERMITAGE
Enhancing Robustness and Model
Integration for the Assessment
of Global Environmental change
SECOND ANNUAL MEETING
AND
WORKSHOP
WELCOME!!
OBJECTIVES
• The second annual meeting (Day 1): progress,
advances and gaps focusing on model
integration;
• The second workshop (Days 2 and 3): a
tutorial on the user interface of the
developing framework model and elicit
direction from stakeholders on subsequent
developments.
Tuesday 25 Annual meeting: Introduction and Progress on Climate - Land
Surface - Economy Feedback Modelling
08.30 – 09.00
09.00 – 09.15
09.15 – 10.00
Coffee
Organisation of the meeting – B. Pizzileo and N.Wegener
N. Edwards: feedback from
-
SAB meeting
10.00 – 10.45
Interim Report and First Review Meeting
Statistical emulation and uncertainties (WP3) – Holden, Garthwaite and Oyebamiji
10.45 – 11.45
Land Use Session (WP5, 7) – Gerten and Leimbach
11.45 – 13.15
Note : Coffee available during the session.
Energy, Economy and Climate (WP6, 8) – Joshi and Labriet
13.15 – 14.15
14.15 – 14.45
14.45 – 15.30
15.30 – 16.00
16.00 – 16.45
16.45 – 17.30
17.30
‘TIAM-WORLD web applications for results dissemination’ - Kanudia
Lunch
Janet Sumner: ‘Using short form video for dissemination of research’
Multi-agent action and reaction (WP10) – Haurie
Coffee Break
Sustainable land and water use (WP11) – Warren, Wallace, Hiscock
Global to local downscaling (WP9) – Babonneau, Wallace/Warren
Shuttle service from Cecilienhof to Mercure
Note: no service from Mercure to the restaurant as they are opposite to each other
18.30
19.00 – 22.00
22.00
Shuttle service from Cecilienhof to the restaurant
Dinner at the restaurant « Der Hammer ».
Address : Am Neuen Markt 9a-b, 14467 Potsdam
Shuttle service from the restaurant to Cecilienhof
Wednesday 26 Workshop: Format of the portal and global discussion with
external stakeholders
08.15
08.30 – 09.00
09.00 – 09.45
09.45 – 11.45
11.45 – 13.15
13.15 – 14.15
14.15 – 16.00
16.00 – 17.30
17.30 – 18.30
18.30
Shuttle service from Mercure to Cecilienhof
Coffee
Ottmar Edenhofer: "Scenarios and Honest Brokerage - An IPCC
Perspective"
WP4 Format of the portal: Climascope/Cias/CIAS-live/BFG demo Warren, Goswami, Ford
Note : Coffee available during the discussion.
Plenary discussion within the project focused on target
dissemination
Lunch
Discussion between ERMITAGE partners (Prioritising coupled model
experiments and analyses)
Global discussion with stakeholders (Identification of knowledge
gaps, hot topics and sustainability indicators): Sear, Smith, Pascoe
Note : Coffee available during the discussion.
PMB meeting
Shuttle service from Cecilienhof to Mercure
Thursday 27
Workshop: Parallel sessions (small-group discussions with
stakeholders); Dissemination
08.15
Shuttle service from Mercure to Cecilienhof
08.30 – 09.00
Coffee
09.00 – 11.00
Parallel sessions: small-group discussions with stakeholders
C. Pascoe (Moderator: R. Ford); S. Schäfter and L. Rüttinger
(Moderator D. Gerten); C.Sear; S. Smith
11.00 – 13.00
Parallel sessions: within work packages and brain storming based
on priority couplings/outputs.
Note : Coffee available during the discussion.
13.00 – 14.00
Lunch
14.00 – 14.15
WP1: Project management: website, achievements and next
requirements – B. Pizzileo.
14.15 – 16.00
Plenary: maximising impact of applied analyses (with particular
focus on stakeholders’ suggestions).
Wrap-up and conclusions
INTERNET
ID: Individual
Password: Individual
No more than 12!
ERMITAGE
Enhancing Robustness and Model
Integration for the Assessment
of Global Environmental change
SECOND ANNUAL MEETING
AND
WORKSHOP
ENJOY IT!!
ERMITAGE
Enhancing Robustness and Model
Integration for the Assessment
of Global Environmental change
Notes from Advisory Board & Mid-term review
SAB







Focus on tools is fundamental
Target dissemination, KT people
New feedbacks:
GW, price, food-fuel, fire, conflict
Elaborate SSPs show alternatives
Identify research priorities (weak links)
Align target msgs and audience with
media and activities
SAB Outputs







ToDo:
Tools and analyses
To Publish:
Protocols?
Model - question matrix
Accessible papers (NCC, New Sci etc)
…
EU Review meeting




‘Success story’ needs policy impact
Reviewers liked:
Emulation
Nonlinearity
 Some French cities hitting water constraints
 Inter-regional conflict
 Uncertainty
 Climascope
 Needs more explanation in places
Motive: sustainability
Coupling via emulation
Emulators replace complex computer models by
simple analytic functions
V (q ) = a + åi=1 biqi + åi=1 å j>i cijqiq j + å d q
n
n
n
n
2
i=1 i i
Allows factor analysis and model coupling…
Goal: full-model coupling
What now?







One year of project
Six months to Brussels meeting
HowTo:
Integrate analysis?
Deliver framework tools?
Demonstrate policy insights?
Target dissemination?
Call: ENV.2010.4.2.1-1
– Improved integration of environmental change
and related policy models.
– Transparency of methodologies and public
access to allow for linking up of further
models.
– Policy relevance.
– Sustainable development challenges.
ERMITAGE





Extend modular frameworks
Spatially resolved climate + economy
Account for uncertainty + conflict
Consistent policy analysis
Sustainability: agriculture, energy, water
Scenario setting
Suitable land for cropland expansion
Ref & M
Ref –
No bioenergy demand
M–
Bioenergy for CC Mitigation
M_FC
M_FC –
Bioenergy for CC Mitigation
& Forest Conservation
PLASIM-ENTS
emulator and
ERMITAGE
couplings
2005 to 2105
Radiative forcing pathway (CO2e)
& CO2 concentration pathway
CO2e Tchebyshev coeffs TC1e, TC2e, TC3e
CO2 Tchebyshev coeffs TC1a, TC2a, TC3a
10 spatio-temporal EOFs
PC emulation
Linear regression
Evaporation
Emulate climate: ten output time slices
Decadal averages centered on
1/1/2010 to 1/1/2100
188-member emulated ensemble
Seasonal fields at T21 (~5°) resolution
Precipitation
Cloud cover
SAT
SAT variability
HDD/CDD
TIAM
hydropower
CLIMGEN
LPJmL_em
GEMINI crop
impacts
GEMINI
health impacts
GEMINI
energy demands
TIAM
energy demands
Enhancing Robustness and Model Integration
for the Assessment Of Global
Environmental Change
(ERMITAGE)
Statistical emulation for environmental
sustainability analysis
Environment, Earth & Ecosystem,
The Open University, UK
by
Oluwole Oyebamiji
ERMITAGE Conference @PIK Germany
25-27 Sept 2012
Supervisors:
Prof. Paul Garthwaite, Dr. Neil Edwards, Dr. Phil Holden
ERMITAGE
The ERMITAGE link together several key component models
into a common framework to better understand the
management and interaction of land, water and the earth’s
climate system.
Component models are:


Climate system: MAGICC6 (ClimGEN)
Land use change impacts on water resources: LPJmL
NPP
 Net primary production could be defined as the net flux of
carbon from the atmosphere into plants per unit time
 NPP data set is used to calibrate, parameterize and
evaluate in terrestrial carbon modelling
 How much carbon exists in the biosphere?
 Where exactly is it stored?
 NPP acts as a source of reliable information on the level
of global carbon estimate
Emulator
Emulator is a statistical approximation to the simulator.
It is a fast surrogate for a computationally expensive
computer model, a big model that takes time to run.
Simulator is a mathematical representations of a physical
System implemented with a computer codes.
It has been used to investigate complex physical systems
in various applications.
Usefulness of emulator
Simulation runs take longer time and expensive to run
 Interpolation
 Uncertainty analysis
 Sensitivity analysis
 Calibration purpose

Available methods
Spline interpolation
 Gaussian process
 MCMC
 Monte Carlo
 Kalman filtering

Applied methods
 OLS***
 PLS
 PCA
 Censored regression***
Overview
Develop a statistical model that would represent the
relationship between MAGICC6/ClimGEN and (LPJmL)
Data
Monthly data from 2001-2100
 0.5 by 0.5 spatial resolution
 4 RCP’s (2.6,4.5,6.0, 8.5)

4 climate models
 HadGEM1 (Hadley Centre Global Environmental Model, version 1 )
 IPSLCM4 (Institut Pierre Simon Laplace model)
 GISS-MODELEH (Goddard Institute for Space Studies)
 CCSR−MIROC32HI (Model for Interdisciplinary Research on
climate)
Outputs from LPJmL
 NPP***
 Heterotrophic respiratory carbon
 Fire carbon
 Crop yield***
(i) Temperate cereals
(ii) Rice
(iii) Maize
Inputs from ClimGEN
 Surface temperature
 Precipitation
 Wet day frequency
 Cloud cover
 CO2 emission
NPP results

Fitted a joint model to the 4 RCP’s

Variable selection (step algorithm)

Predicted mean decadal change in NPP for each
successive decades from 2001-2100

Sensitivity analysis
Cross
MIROCHI MIROCHI MIROCHI MIROCHI GISSHI
validatio 2.6
4.5
6.0
8.5
4.5
n R^2
GISSHI,
.88
HADGEM,
IPSL
(3,6,8.5)
.81
.86
.85
.89
 Model R^2=0.77
 Simulated and validated NPP change are similar
 Predicted high NPP in tropical climate and low in
savannah region
There is a wide variation between the observed and
predicted
There are noticeable changes all over the world
 Significant variables are temperature and wet day
frequency
Crop yield
Temperate cereal***
 Rice***
 Maize***
 Oil crops (Groundnut, rapeseed, Soybeans,
Sunflower)
Censored regression is used when the data on the
response variable is limited, or is difficult to observe the full
response variable.
Why not OLS?
References
Cressie, N. (1993). Statistics for Spatial Data. John Wiley \& Sons, New York.
Holden, P.B., Edwards, N.R., Oliver, K.I.C., Lenton, T.M. and Wilkinson, R.D. (2010).
A probabilistic calibration of climate sensitivity and terrestrial carbon change in GENIE-1,
Climate Dynamics, 35,785-806
Holden, P.B. and Edwards, N.R. (2010). Dimensionally reduced emulation of an AOGCM for
application to Integrated Assessment Modelling, Geophysical Research Letters, 37.
Lieth, H.F.H. (1975). Primary production of the major vegetation units of the world. In: Primary
Productivity of the Biosphere (H. Lieth, and R.H. Whittaker, eds.). Ecological Studies 14.
Springer-Verlag, New York and Berlin, 203-215.
Kennedy, M.C. and O'Hagan, A. (2001). Bayesian callibration of computer models (with discussion).
Journal of the Royal Statistical Society, 63, 425–464.
Oakley, J.E. and O'Hagan, A. (2004). Probabilistic sensitivity analysis of complex models:
A Bayesian approach. Journal of the Royal Statistical Society, 66, 751-769.
Clark, D.A., Brown, I.S, Kicklighter, D.W., et al., (2001). Net primary production in tropical forests:
An evaluation and synthesis of existing field data. Ecological Applications, 11(2),371–384.
Santner, T., Williams, B. and Notz, W. (2003). The Design and Analysis of Computer Experiments.
Springer Verlag, New York.
Garthwaite, P.H. (1994). An interpretation of partial least squares. Journal of the American Statistical
Association, 89(425), 122-127.
ERMITAGE WP 7
Economy and land use
Marian Leimbach, Jan P. Dietrich, David Klein,
Teresa Lenz, Alexander Popp, Anselm Schultes,
Anne Biewald, Florian Humpenöder
(PIK)
Maryse Labriet, Amit Kanudia
(ENERIS)
Potsdam, 25-27 September 2012
Agricultural-economy link
Co2 tax
Climate target/
Emission constraint
Agricultural trade
bioenergy prices
LULUC emissions
Land use
carbon price
bioenergy demand
food demand
Economy
2nd generation bioenergy:
substantial role in future energy systems ?
Unresolved issues
• Cost-efficient bioenergy potential
• Sustainability issues
o Food security
o Water security
o Climate change mitigation
o Biodiversity
Coupled model framework
Model framework to explore potential contribution of bioenergy
to climate change mitigation, including its costs and trade-offs
LPJmL - global vegetation and hydrology model
MAgPIE - global land use optimization model
REMIND- global energy-economy-climate model
Scenario setting
Suitable land for cropland expansion
Ref & M
Ref –
No bioenergy demand
M–
Bioenergy for CC Mitigation
M_FC
M_FC –
Bioenergy for CC Mitigation
& Forest Conservation
Mitigation scenarios M & M_FC aim to keep the 2°C target
Results: Cropland expansion
Total cropland share
2095
2055
2015
2095
100
200
300
400
Total cropland area [mio ha]
Bioenergy cropland share
2095
Results: Cropland expansion
Total cropland share [%]
2095
2055
2015
2095
2095
Results: Cropland expansion
Total cropland share [%]
2095
2055
2015
2095
2095
Results: Yield increases
Results: Food and water security
Experiments in the SSP world
Increasing socio-economic
Challenges for
to Mitigation
mitigation
challenges
Inverse approach: Cover the range of socio-economic
challenges for mitigation & adaptation
SSP 15
SSP
SSP 33
SSP
SSP 2
SSP
SSP2 1
SSP 44
SSP
Challengessocio-economic
to Adaptation
Increasing
challenges for adaptation
SSP Population Scenarios (IIASA)
9000
12000
SSP1
8000
AFR
LAM
7000
MEA
6000
OAS
5000
USA
4000
RUS
JPN
3000
IND
2000
CHN
1000
8000
6000
4000
2000
EUR
ROW
0
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
9000
0
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
SSP5
8000
Population in
million
SSP2
10000
7000
6000
5000
4000
3000
2000
1000
0
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
SSP GDP scenarios (OECD)
500000
450000
AFR
SSP1
400000
350000
LAM
350000
MEA
300000
OAS
300000
400000
SSP2
250000
USA
250000
RUS
200000
150000
100000
JPN
150000
IND
100000
CHN
50000
200000
50000
EUR
0
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
ROW
0
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
800000
700000
600000
GDP in billion
USD(2005) at
MER
SSP5
500000
400000
300000
200000
100000
0
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Results: Global food demand
Results: Global crop land area
BAU
550 ppm
Results: Annual TC rates (global)
BAU
550 ppm
Results: 2nd generation bioenergy
cropland
BAU
550 ppm
Results: 2nd generation bioenergy
production
Results: Primary energy consumption (globalSSP2)
BAU
450 ppm
550 ppm
Results: Bioenergy consumption (global – SSP2)
BAU
450 ppm
550 ppm
Results: Price of biomass
Results: CO2 emissions from energy system
(SSP2)
450 ppm
550 ppm
Results: Food price index (regional)
Results: Net trade of food crops
Conclusions
Bioenergy from dedicated crops: cost-efficient contribution to ES in CC mitigation scenarios
Most attractive due to its potential for generating negative emissions (CCS)
Restrictions on land availability (forest conservation):
affects bioenergy potentials in the short but not in the long run
 less land available for cropland expansion can partially
be absorbed by higher rates of technological change
But: forest conservation & bioenergy for climate change mitigation:
conflicts in respect of food supply and water resource management
Integrated policies for energy, land use and water management
Next steps
• Improved representation of trade (food crop
and biomass trade)
• BFG coupling
• MAgPIE-TIAM coupling
Total GHG emissions
BAU
450 ppm
Maryse 19 pages
VEDA web tools for
collaboration and
dissemination
Amit Kanudia
ERMITAGE workshop | Potsdam | 26 Sep 2012
Motivation
• Advanced data visualization to analyze large
multi-dimensional datasets.
– GIS, animation and more
• Geographically dispersed collaborators need to
share results
• Need to engage sector and region experts in
results analysis
• Make large number of scenario accessible to
stakeholders/policy makers to enable a restricted
“what if” analysis
• Make presentations
Multi-model/scenario/region analysis with VEDA*
Model
Results
OR
VEDA-Back End
Import
&
Q-Checks
Local
Other
sources
Post-processing
• Shares
• Intensities
• Growth rates
• Scen Diff
• Stat analysis
VEDA-Back End
Local
VEDA WEB Viewer
www
* Versatile
Data Analyst
ASP .NET/JavaScript
Examples on www
• RCP emissions from TIAM-World
• Other models
• TSViewer:
http://kanors.com/TSViewer/TSV.aspx?Prj=k
emr-rcp
<guest/guest>
• Explorer:
http://kanors.com/vedaexplorer/Home.asp
x
ERMITAGE MEETING: Potsdam. 24 – 27 September 2012
Kevin Hiscock, School of Environmental Sciences, UEA, UK.
k.hiscock@uea.ac.uk
Definition of ‘groundwater footprint’ (GF)
The aquifer area, AA, required to sustain groundwater use and groundwaterdependent ecosystems of a region of interest, such as an aquifer, catchment or
community.
Values of GF/AA > 1 indicate unsustainable groundwater consumption that could
affect groundwater availability and groundwater-dependent ecosystems.
Values of GF/AA >> 1 would suggest unsustainable groundwater mining, for example
of fossil groundwater recharged under past climatic conditions.
Size of the global groundwater footprint:
(131.8 ± 24.9) x 106 km2
or
3.5 ± 0.7 times the actual area of hydrologically active aquifers
Groundwater footprints of aquifers that are important in agriculture are
larger than their geographic areas
The global groundwater footprint is dominated by a handful of countries including
China, India, Iran, Mexico, Pakistan, Saudi Arabia and the United States.
The majority of aquifers in the world have groundwater footprints of less than 106 km2
and that 80% of aquifers have values of GF/AA < 1, suggesting that groundwater
depletion globally is not ubiquitous.
Schematic of water storage
compartments (boxes) and flows
(arrows) within each 0.5o grid cell of
the WaterGAP Global Hydrology Model
(WGHM version 2.1h). Water use
estimates for each source in each grid
cell computed with GWSWUSE
Qb – outflow from groundwater to surface
water; controlled by an outflow coefficient,
kg, set globally at 0.01 day-1
Döll et al. Journal of Geodynamics (2012)
Global water use during the period 1998-2002, including groundwater fractions
Impact of human water use on seasonal amplitude
(SA) of total water storage (TWS)
(a) SA computed as the grid-cell specific value of
maximum mean monthly TWS minus minimum
mean monthly TWS, averaged over 1998-2002,
taking account of water withdrawals, in mm.
(b) Change of SA with water withdrawals relative to
SA without withdrawals, in percent of SA
without water withdrawals (positive values
indicate that water withdrawals increase SAs of
TWS)
Döll et al. Journal of Geodynamics (In Press)
Scatter plots of
recession coefficient,
kbf vs. various
catchment
parameters and
WHYMAP (2010)
hydrogeological
classes
Qt  Qoe
 kbf t
Qo - discharge at the start of
baseflow recession
Qt - discharge at later time, t
kbf - aquifer or recession
coefficient
Q data from the Global Runoff Database
from the GRDC
Peña-Arancibia et al. Hydrology and Earth System Sciences (2010)
Pan-tropical map of baseflow recession coefficient using the exponential
regression equation and mean annual rainfall (MAR)
Peña-Arancibia et al. Hydrology and Earth System Sciences (2010)
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA, UK.
craig.wallace@uea.ac.uk
WP11: Sustainable land and water use:
How can we model groundwater changes in the ERMITAGE / CIAS framework?
Presently LPJmL:
Precip
Transpiration
Evap
Plants
Land Runoff
Soil water
content
Subsurface run off
Surface
water store
Subsurface run off at base of column
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA, UK.
craig.wallace@uea.ac.uk
WP11: Sustainable land and water use:
How can we model groundwater changes in the ERMITAGE / CIAS framework?
Two developments opportunities:
Soil water
content
Surface
water store
Subsurface run off at base of column
1:
Rg
Groundwater
Store
2:
Kbf
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA, UK.
craig.wallace@uea.ac.uk
WP11: Sustainable land and water use:
1: Rg
Rg
Döll et al 2008 – WaterGAP model:
Groundwater Store
Rg = Rl * fgw
i: Relief [Fischer, 1999]
ii: Soil texture [UN FAO]
iii: Hydrogeology [multiple data sets]
iv: Permafrost / glacial coverage [NH only Brown 1998]
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA, UK.
craig.wallace@uea.ac.uk
WP11: Sustainable land and water use:
2: Kbf
Kbf
Groundwater Store
Empirical calculation:
Kbf ≈ Qt – Qt-1
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA, UK.
craig.wallace@uea.ac.uk
WP11: Sustainable land and water use:
2: Kbf
Arancibia (2011) -- 183 catchments
Van Dijk (2010) -- 167 catchments
Global River Discharge Centre
data
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA, UK.
craig.wallace@uea.ac.uk
WP11: Sustainable land and water use:
2: Kbf
Predictor
r^2
Mean Annual Precip
-0.65
Aridity Index (annual)
-0.64
Moisture Index (monthly)
-0.64
Tree cover (!)
-0.43
Slope Index
-0.43
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP11: Sustainable land and water use:
How can we model groundwater changes in the ERMITAGE / CIAS framework?
Soil water
content
Surface
water store
Subsurface run off at base of column
Döll et al 2008
4 gridded fields to calculate fgw
1:
Rg
Groundwater
Store
2:
Kbf
could do: Qt – Qt-1
or
Kbf = predictors
To do’s
Compute kbf
Link to LPJmL to compute ΔSgw (and Δh)
Compute ΔSgw for future linked climate/crop/water scenarios
Target date: May 2013
EU-FP7 ERMITAGE Project
Task 9.2
Vertical linkage TIMES-like models of different scopes
Delivery date: End of May
Partners: ORDECSYS (TL) and ENERIS
Objective of the Work Package
Improve the vertical integration of Markal-like models having different
spacial scales.
Objective of the Work Package
Energy
market
Climate
module
WORLD
(TIAM)
Global
mitigation
goal
CC impacts
Local adaptation
options
Intermittent production
of renew. energy
Smart
grids
GENEVA
(ETEM)
GIS
Local
mitigation goal
Proposition of workplan (1/3)
Step 1: Harmonize the different technology databases. => October
Step 2: Focus on energy prices. => December
TIAM-WORLD
Trends of energy prices are computed
endogenously in TIAM-WORLD (dual prices)
TIMES-SWITZ.
TIMES-SWITZ. determines domestic electric
prices, biofuel prices, etc
ETEM-GENEVA
Proposition of workplan (1/3)
Step 1: Harmonize the different technology databases. => October
Step 2: Focus on energy prices. => December
TIAM-WORLD
Trends of energy prices are computed
endogenously in TIAM-WORLD (dual prices)
?
TIMES-SWITZ.
ETEM-GENEVA
TIMES-SWITZ. determines domestic electric
prices, biofuel prices, etc
Proposition of workplan (2/3)
Step 3: Implement a python code to automize the transfer of data
between different models. => January
Step 4: Extend the code to other types of data exchanges: =>
February
• CO2 prices
• Impose penetration of new technologies computed by
higher level models.
• Impacts of CC, adaptation measures, etc.
Step 5: If relevant, write a BFG compliance code and integrate this
linkage into the CIAS platform. => April
Proposition of workplan (3/3)
Step 6: Develop uncertainty analysis to assess the impacts of
different uncertain data/parameters: => April
•
•
•
•
•
Linkage data (energy prices)
Acceptability of renewable deployment (wind farms)
Impact of climate change (availability of power plants,
heating and cooling demands, etc)
Political decision (nuclear plant shutdown)
Efficiency and cost of new technologies (clean and
renewable)
Approach 1: Stochastic programming
• Posit the existence and the knowledge of a probability distribution.
• Approximate the distribution to generate a tractable model
• Event tree of moderate size for stochastic programming.
• Computable probabilities and expectations for chance
constrained programming.
Approach 2: Robust optimization
• Starts with a simplified non probabilistic model of the
uncertainty (Uncertainty set).
• Looks for solutions that remain feasible for all events in the
uncertainty
•
•
The optimization model is tractable (linear or conicquadratic).
No probability assumption but it exists strong results on
lower bounds on the probability of constraint
satisfaction.
Approach 2: Robust optimization
Example of results for transport sector.
Determinist
Robust
Use RO and SP for robust analysis in other WPs
•
Task 3-4: Propagation of uncertainty and multi-module feedback analyses
« Our approach will consist of … robust optimization … »
=> Apply RO in the oracle based approach (PLASIM-ENTS / TIAM-WORLD) to
coefficients of the PLASIM-ENTS emulator function.
•
Task 8-3: Uncertainty analysis.
« Stochastic analysis and robust programming will be applied to quantify …»
 Redundant work with Task 9-2 ???
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
Update : ClimGen [V1.20] C.Wallace, T. Osborn, M. Salmon
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] NetCDF output
NetCDF3
NetCDF4
ascii
Spec setting:
Output
001
ascii only
003
NetCDF3 only
004
NetCDF4 only
013
ascii & NetCDF3
014
ascii & NetCDF4
034
NetCDF3 & NetCDF4
134
everything!
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] NetCDF output
NetCDF3
v
NetCDF4
NetCDF4: 160Mb
ascii: 540Mb
NetCDF3: 940Mb
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] GENIE_EM coupling.
GENIE_EM
output
ClimGen v1.20
Other ERMITAGE
modules..
LPJmL (and
beyond)
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] GENIE_EM coupling.
GENIE_EM
output
- 5  by 5 
- DJF,MAM,JJA,SON
genie_cplr.f90
ClimGen v1.20
- 0.5  by 0.5 
- J ...... D
/climgen/changes/GENIE_EM/
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] GENIE_EM coupling: Naming convention.
GENIE_EM_000_000000_20102100.tmp
GENIE_EM
parameter tag
scenario identifier
tmp_chgGENIEEM00000000020102100_20052096ann_monthly_reglandboxes___.climgen
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] GENIE_EM coupling: functionality.
- variables: .tmp, .pre, .cld, .wet
- time slice: 2005 to 2104
- space: 0.5 x 0.5 grid
- combination with CRU TS baselines is additive:
scenario = eA + cru_tsB + obs_iyv
or...
scenario = eA
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] GENIE_EM Scenarios are changes from 19952004
do we: CRU_TS (19952004 – 19611990) + GENIE_EM ?
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] GENIE_EM precip anomalies, 2050s RCP4.5
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] CRU_TS 19952004 anoms T
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
ClimGen [V1.20] GENIE_EM anoms 2100 RCP4.5
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces):
Update : Daily Disaggregation of Precipitation
Objective: Daily precipitation generation capability on
CIAS/ClimGen Grid [0.5 by 0.5]
Monthly precip
(mm)
Monthly # wet
days
Daily pre
LPJmL
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sciences, UEA,
UK.
craig.wallace@uea.ac.uk
Major advancement is to use the gamma distribtution ...
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sci, UEA, UK.
craig.wallace@uea.ac.uk
Gamma shape values used in new scheme ‘CRU_DDS’
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sci, UEA, UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces): CRU_DDS status
Functional, outside of CIAS.
/CRU_DDS.f90
/anc/....
/out/.....
/CRU_DDS.f90
run.spec
Outfiles:
writes annually per GCM.
e.g. 1 yr of ‘standard’ ClimGen data --> 157Mb
ERMITAGE MEETING: Potsdam. 24 – 27.9.2012
Craig Wallace, Climatic Research Unit, School of Env Sci, UEA, UK.
craig.wallace@uea.ac.uk
WP9: Downscaling (Global to Local Interfaces): CRU_DDS status
Simulations.
Runs complete [Spt. 2012]:
•2001 – 2100, RCP2.6 18 x GCMs
•2001 – 2100, RCP8.5 18 x GCMs
•1958 – 2002 Observed CRUTS_3.00
CLIMASCOPE
FORD 13 pages
CIAS-Live
Overview & Update
Paul Slavin
The University of Manchester
September 2012
Overview
• Interface description syntax
• Knits together elements of CIAS-Live
Interfac
e
Interface
Description
Data
Source
Visualisatio
n
CIAS-Live Infrastructure
• XML interface description
• Defines the view presented in the Browser
Interfac
e
XML
WSGI
Parser
Browse
r
JavaScript
Template
s
Interface Definition Syntax
<choice id="emissions" datatype="int">
<description>Choice of emissions scenario</description>
<item description="Emission type 1" value="1"/>
<item description="Emission type 2" value="2"/>
<item description="Emission type 3" value="3"/>
<target type="model"><model modelID="CIAS_db" modelName="db_read" epName="run" id="1"/></target>
</choice>
Specifies a radio group with appropriate behaviour:
Data Sources
<xyPlot id="Temptime">
<description>Temperature as a function of time</description>
<x label="Years">
<source type="file" depends="CIAS_database">
<file datatype="int" format="ascii" name="years.out"/>
</source>
</x> continued...
•
•
Results in automatic creation of a
visualisation using the specified data
source.
"Data source" entirely flexible:
File, DB, Function return, AJAX call...
Summary
• Interface definition syntax
• Flexible specification of parameters and
representations of output
Transparent construction of UI
o Transparent connection of data sources
o
• Extensible in response to user feedback
CIAS: A hands-on demonstration
Sudipta Goswami
Potsdam (26/09/2012)
New Couplings
• New versions of CLIMGEN
• PLASIM-ENTS Emulator
• PLASIM-ENTS-CLIMGEN-LPJmL Emulator
What is involved...
• Cater for individual styles:
– Language
– Operating System
– Environment
– I/O routines
• BFG takes care of the first three items
• We tackle the I/O issue
• Routines for passing data between modules
• Routines for converting this data into the native
format of the modules
• Removing hard links within the code
• Separating large input datasets from the source
code
• Typically issues get identified at this stage and the
whole cycle of development of the coupling code
goes through a number of iterations.
• So....
PLASIM-ENTS
emulator and
ERMITAGE
couplings
2005 to 2105
Radiative forcing pathway (CO2e)
& CO2 concentration pathway
CO2e Tchebyshev coeffs TC1e, TC2e, TC3e
CO2 Tchebyshev coeffs TC1a, TC2a, TC3a
10 spatio-temporal EOFs
PC emulation
Linear regression
Evaporation
Emulate climate: ten output time slices
Decadal averages centered on
1/1/2010 to 1/1/2100
188-member emulated ensemble
Seasonal fields at T21 (~5°) resolution
Precipitation
Cloud cover
SAT
SAT variability
HDD/CDD
TIAM
hydropower
CLIMGEN
GEMINI
health impacts
GEMINI
energy demands
TIAM
energy demands
LPJmL_em
GEMINI crop
impacts
©Phil Holden
New Couplings
• New versions of CLIMGEN
• PLASIM-ENTS Emulator
• PLASIM-ENTS-CLIMGEN-LPJmL Emulator
• BFG2 upgrade completed on test portal
• Next in line: PLASIM-ENTS(Emu)-GEMINI
1. Setting up a simple run
• Select a coupling
• Press the ‘Create’ button
• Give the experiment a name (and description –
optional)
• Select a module
• Select a parameter
• Change the value of the selected parameter
• Hit the ‘Execute’ button
BFG Update
Paul Slavin
The University of Manchester
September 2012
BFG Python
Model A
PYTHON
BFG
Model B
FORTRAN
BFG Code Generator
Type
translation
Object and Symbol
Management
Python C-API
Python Virtual Machine
BFG Python Features
•
•
•
•
•
•
•
•
•
•
•
Transparent calling of Python methods from foreign
languages
Transparent type translation
Transparent module loading
Transparent object instantiation and caching
Reference-counting - memory parsimony
Full Numpy support
Native execution speeds
Exception handling, or throwing
Value and pointer based returns
PythonPath management
All happens at runtime
BFG Python Implementation
•
Code links against BFGpython API library
•
BFG2Main.f90 unchanged: invokes C-linkage wrapper functions
•
BFGpython offers a single function as interface to Python modules
o Variadic function which accepts parameter string (cf. printf() )
o ANSI C va_args() function parses parameter string
o Translates input into form suitable for Python C-API
PyArg_VaParse()
•
•
Native Python pre-execution environment setup, post-execution
finalisation
No ctypes
BFG Python Integration
Metadata
Composition
Deployment
BFG Parsing to per-language templates
Compiler & Linker
options
Coupled
Executable(s)
Makefile generation
BFG Python Summary
•
•
•
Python facilities adequate to support real-world couplings
Deployed for GeminiGENIEem, TiamGENIEem and (mostly)
MagpieRemind
Extensible framework for addition of further features
o Model idiosyncrasies require only modular extension to BFG
o Model-specific derived types likewise
Dissemination groups
 Strategy (D2-2) M24
 Public
 Sci/tech community
 Stakeholders
 SH analysts / policy users / KT people
Strategy elements
 Peer-reviewed high-impact / other
 Outreach pubs innov article
 Vids
 SH mtgs 1-1
 Brussels wkshop
 Other meetings (industry / community)
 Web tools site/CIAS/climascope
 Online social networks
 Briefing notes
• COUPLINGS
Outputs
 Knowledge gaps
 Nutrient limits energy for water (Kevin)
 Hot topics?
 Bioenergy 10% EU target 5% this week
 Water-energy, groundwater, shale gas, CCS
 (both water-energy) permafrost (uncertainty)
 geoengineering
 Sustainability indicators
Publication ideas (summary)
•
•
•
•
•
•
Impacts (price, availability) on agriculture and crops
Avoided deforestation
Constraining CO2 fertilisation
Climate macro-economic damages & feedbacks
Groundwater constraints on development
Uncertainty and sensitivity from emulators (crops,
economics)
• Climate-energy feedbacks (heating & cooling, power
plants, bioenergy)
ERMITAGE
Enhancing Robustness and Model
Integration for the Assessment
of Global Environmental change
SECOND ANNUAL MEETING
AND
WORKSHOP
MANAGEMENT AND COORDINATION
Achievements
• Deliverables first 18 months:
– D2.1 (Report of WS1), D4.1 (BFG2 metadata standards),
D5.1 (Provision of climate data), D6.1 (Climate-economy
interface), D3.1 (GENIE emulator), D4.2 (ERMITAGE Portal,
initial version), D5.2 (Crop and water impacts), D10.1
(Calibration of IEA models), D11.1 (Scenario generation
mechanism)
• Periodic report: 31/07/12
• First review: 19/09/12
Website
http://ermitage.cs.man.ac.uk/
Twitter
JISCMail
www.jiscmail.ac.uk
Next tasks
•
Short term:
– 30/09/12: D6.2 (Damage cost functions)
– 31/11/12: D2.2 (Dissemination report ); D3.2 (Emulation and coupling
report); D9.1 (Downscaling for adaptation)
•
Long term:
– 31/05/13: D6.3 (Stochastic simulations); D7.1 (Macro-economy agriculture
link. Sensitivity and scenario analysis); D8.1 (Uncertainty analyses in TIAM);
D9.2 (Energy model hierarchy output); D10.2 (Analysis of fair burden sharing)
– 31/07/13: D11.2 (Harmonised policy scenarios)
•
End of the project:
– 31/11/13: D4.3 (ERMITAGE Portal, final version); D5.3 (Effects of land-use
emissions); D7.2 (Sensitivity and scenario analysis)
– 31/01/14: Second periodic report; Final report.
Dissemination
• Monthly reminders:
– Publications/events in the current month
– To be provided a few days before!
• Acknowledgements in papers:
The research leading to these results has received
funding from the Seventh Framework Programme
(FP7/2007-2013) under grant agreement n° 265170
• Involving stakeholders. Not easy…some good reasons
to do it:
– Written in the DoW
– Money allocated for it, funded 100%
ERMITAGE
Enhancing Robustness and Model
Integration for the Assessment
of Global Environmental change
SECOND ANNUAL MEETING
AND
WORKSHOP
THANK YOU!
Proposed Publications ideas/notes
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
Dieter: impacts paper, LPJmL (subm almost)
Permafrost paper (soon)
Rachel: avoided deforestation, spatially explicit version of her existing paper,
but using coupling Magicc_ClimGEN_LPJ_Magicc ?
LUC simulations with GENIE (done)
GEMINIe3-GENIE based paper
RCP based LPJ impacts, using ERMITAGE ClimGEN data. (D5-2 still possible)
Delphine: model comparison, LPJmL and PEGASUS (early 2013 impact
uncertainty)
Coupling loop (i.e. Magicc6_ClimGEN_ LPJmL_MagPIE_TIAM/REMIND) (needs
work?)
Groundwater simulations LPJmL + DDS + sensitivity (IPCC deadline)
LPJmL – MAgPIE + GW
GENIE pattern scaler: compare with GCM based pattern scaler. Paper either if
results similar or contrasting, through to LPJ
GENIE-LPJmL emulator is a basis for publications, CO2 fertilisation vs
respiration / Permafrost?
Proposed Publications ctd.
13.
14.
15.
16.
17.
18.
Smart grids (done, Fred)
Economic emulation
remind-magpie coupling
BFG-CIAS infrastructure paper (Rupert)
Energy system impacts (Maryse)
Alain handbook article + paper?