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Heraklion, June 25, 2019
C. Tsompanidis, T. Lolos, A. Sakalis *, E. Vlahantoni, E. Ieremiadi, D.A. Sarigiannis, A. Gotti, E. Scoccimarro
Regional Climate Change Adaptation Planning:
Methodological Approach on Future Projections and
Vulnerability Assessment in accordance with the
5th IPCC Assessment Report
2nd International ADAPTtoCLIMATE Conference
IPCC
• The Intergovernmental Panel on Climate Change (IPCC) was established in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP) to assess climate change based on the latest science
• IPCC reports cover the scientific, technical and socio-economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential impacts and options for adaptation and mitigation
• The IPCC provides an internationally accepted authority on climate change, producing reports which have the agreement of leading climate scientists and the consensus of participating governments
2Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report2
IPCC 5th Assessment Report
3Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
2046-2065 2081-2100
Scenari
oMean Range Mean Range
Global Mean Temperature Change (oC)
RCP2.6 1,0 0,4 - 1,6 1,0 0,3 - 1,7RCP4.5 1,4 0,9 - 2,0 1,8 1,1 - 2,6RCP6.0 1,3 0,8 - 1,8 2,2 1,4 - 3,1RCP8.5 2,0 1,4 - 2,6 3,7 2,6 - 4,8
Global Mean Sea Level Rise
(m)
RCP2.6 0,24 0,17 - 0,32 0,40 0,26 - 0,55RCP4.5 0,26 0,19 - 0,33 0,47 0,32 - 0,63RCP6.0 0,25 0,18 - 0,32 0,48 0,33 - 0,63RCP8.5 0,30 0,22 - 0,38 0,63 0,45 - 0,82
• IPCC issued its 5th Assessment Report in 2014. According to the Report, anthropogenic greenhouse gas emissions are mainly caused due to population size, economic activity, lifestyle, energy consumption, land use patterns, technology and climate policy
• The Representative Concentration Pathways (RCPs), which were created to describe these factors, evaluate four different 21st century pathways for greenhouse gas emissions, atmospheric concentrations, air pollutant emissions and land use.
• RCPs include a rigorous mitigation scenario (RCP2.6), two intermediate scenarios (RCP4.5 and RCP6.0) and a very high greenhouse gas emissions (RCP8.5) scenario
• The scenarios are named on the basis of the change in energy intensity in 2100, in relation to the pre-industrial period (2.6, 4.5, 6.0 and 8.5 W/m2 respectively).
CORDEX downscaling effort based on Regional Climate Models (RCMs) running with boundary conditions provided by General Circulation Models (GCMs)
Euro-CORDEX Horizontal resolution
ranging from 50 to 15 km (EUR-11 domain)
Coordinated Regional Downscaling Experiment sponsored by the World Climate Research Programme
14 CORDEX Domains defined
EURO-CORDEX the European branch of the international CORDEX initiative organize an internationally coordinated framework to produce ensemble climate simulations based on multiple dynamical and empirical-statistical downscaling models forced by multiple global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5)
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
4
Global Scale: General Circulation Models GCMsFully coupled atmosphere-ocean GCMs are used to simulate past and future climate at the global scale, under different radiative forcing conditions. Under the Coupled Model Intercomparison Project (CMIP5 is the last one used for the 5th IPCC Assessment Report) different future radiative path are Considered (i.e. RCP4.5, RCP8.5 and RCP2.6).
Regional Scale: Regional Models (RCMs) forced by GCMsTo downscale to a higher resolution, Atmosphere onlyRegional Models are used.The atmospheric radiative forcing is the same as for GCMs.Also, boundary conditions for the RCM are Provided by GCMs.
The Euro-CORDEX (http://www.euro-cordex.net/) Coordinated Downscaling Experiment provides a multimodel ensemble of climate scenarios available at the 11 km horizontal resolution (EUR-11).
Projection of extreme precipitation
[% change]
Additional refinement to few km
Projection of extreme precipitation
GC
MR
CM
Downscaling process
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
5
6
Atmospheric model Orography
Downscaling to about 11 km as horizontal resolution
11 km as Horiz. Res.
Boundary conditions for RCMs are provided by General Circulation Models
Regional Climate Models (RCMs) involved
EURO-CORDEX – CoordinatedDownscaling Experiment - EuropeanDomain (http://www.euro-cordex.net/)
European branch of the international CORDEX initiative, which is a program sponsored by the World Climate Research Program (WRCP)
Five regional climate Models used.
Under two different CMIP5 (5th Coupled Model Intercomparison Project defined to support the 5th IPCC Assessment Report (AR-5) emission scenarios for the XXI century : RCP8.5, RCP4.5 and RCP2.6 up to year 2100.
Delivery of climate data and indicators
Model nameDriving GCM
Institute
CCLM4MPI-M-ESM-LR
Consortium for Small‐scale Modelling (COSMO)
KNMI-RACMO22E
ICHEC-EC-EARTH
Royal Netherlands Meteorological Institute
INERIS-WRF331F
IPSL-CM5A-MR
IPSL (Institut Pierre Simon Laplace) and INERIS (Institut National de l Environnement industriel et des RISques)
CNRM-CCLM4
CNRM-CM5 Consortium for Small‐scale Modelling (COSMO)
REMO2009MIP-M-ESM-LR
Max Plank Institute
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Climate Change Modeling
Climate data availability at the EU level
The Euro-CORDEX (http://www.euro-cordex.net/)
Coordinated Downscaling Experiment provides
A multimodel ensemble of climate scenarios
available at the 11 km horizontal resolution (EUR-11).
Based on CORDEX-EUR11 Regional Climate model results, we collected daily data covering the period 2005-2100 under the RCP8.5, RCP4.5 and RCP2.6 scenarios over the European region from 4 Regional Climate Models for the following variables:Field Description
Acronym
Vertical level
Field Unit
Precipitation pr Surface [Kgm-2s-1]
Surface relative humidity hurs surface [%]
Surface solar radiation rsds surface [W/m2]
Wind module sfcWind 10 meter [m/s]
Wind module max sfcWindmax 10 meter [Pa]
zonal wind speed uas 10 meter [m/s]
meridional wind speed vas 10 meter [m/s]
2 meter Temperature tas 2 meter [K]
2 meter Air Temperature max tasmax 2 meter [K]
2 meter Air Temperature min tasmin 2 meter [K]
Number of tropical nights Ecatr surface
Number of wet days Ecaid surface
Number of ice days Ecarr1 surface
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
7
Regional EURO-CORDEX models
To calculate the basic climate indices and apply them to the methodology, we used a set of modes so as to optimize the result and reduce the error. The following EURO-CORDEX models were used:
• CNRM_CCLM4: Group of simulations developed by the Center National de Recherches Météorologiques of France. Data were produced in a daily step and include a reference period (historical data) as well as future projections up to 2100 for RCP4.5 and RCP8.5 scenarios.
• EC-EARTH_KNMI: Group of simulations fully coupled Atmospheric-Ocean model developed by twenty-two research Organizations from ten European countries under the lead of Koninklijk Nederlands Meteorologisch Instituut of the Netherlands. Data were generated on a daily basis and include a reference period (historical data) and future projections up to 2100 for RCP2.6, RCP4.5 and RCP8.5 scenarios.
• IPSL_WRF331F: Group of simulations, developed by the Institut Pierre Simon Laplace of France. Data were produced in a daily step and include a reference period (historical data) and future projections up to 2100 for RCP4.5 and RCP8.5 scenarios.
• MPI_CCLM4: Group of simulations, developed by the Max Planck Institute for Meteorology in Germany. Data were generated on a daily basis and include a reference period (historical data) and future projections up to 2100 for RCP4.5 and RCP8.5 scenarios.
• MPI_REMO_2009: Group of simulations, developed by the Max Planck Institute for Meteorology in Germany. The atmospheric model is coupled to three different hydrologic models and three ocean models. Data were generated in a daily step and include a reference period (historical data) and future projections up to 2100 for RCP2.6 scenario.
8Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
A/A Climate IndexReference Period
(1986-2005)
RCP2.6 RCP4.5 RCP8.5
2011-2030 2031-2050 2081-2100 2011-2030 2031-2050 2081-2100 2011-2030 2031-2050 2081-2100
1 Mean temperature (daily)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
2 Minimum temperature (daily)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
3 Maximum temperature (daily)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
4 Mean wind (daily)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
5 Maximum wind (daily)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
6 Precipitation (daily) EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI
7 Relative humidity (daily)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F
EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F
8 Ice days (annual)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
9 Tropical nights (annual)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
10 Wet days (annual)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
EC-EARTH_KNMI EC-EARTH_KNMI EC-EARTH_KNMI
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
11 Solar radiation (daily)
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
CNRM_CCLM4,
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_CCLM4
12 Snowfall (daily)
EC-EARTH_KNMI,
IPSL_WRF331F,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
MPI_REMO2009
EC-EARTH_KNMI,
IPSL_WRF331F
EC-EARTH_KNMI,
IPSL_WRF331F
EC-EARTH_KNMI,
IPSL_WRF331F
EC-EARTH_KNMI,
IPSL_WRF331F
EC-EARTH_KNMI,
IPSL_WRF331F
EC-EARTH_KNMI,
IPSL_WRF331F
13 Sea level rise (annual) - AR5_SLRAR5_SLR
AR5_SLR AR5_SLR AR5_SLR AR5_SLR AR5_SLR AR5_SLR AR5_SLR
9Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Management of climatic data
The steps followed to downscale and manage each climate index were:
• Generation of climate data with an equivalent step through the downscaling process of GCMs to RCMs
• Conversion of climate data into NC files (software libraries and self-describing machine-independent data)
• Conversion of NC files to Microsoft Excel data in order to be easily manageable in Microsoft Windows environment
• Set up of all Microsoft Excel files in the three time horizons (short-term, medium-term and long-term) and the historical data (reference period)
• Data quality control (errors, grid size etc.)
• Calculation of data produced to investigate the values of indices and the climatic phenomena in all different time horizons and scenarios. Data calculations were performed using the following tools:• Pivot tables in Microsoft Excel• SQL commands through Microsoft Access• Python coding and object-oriented calculations in ArcGIS Pro
The process was carried out to derive thirteen main climate indices, while the last step was carried out for other fifty-seven (57) indices.
10Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
A regional climate change adaptation plan structure
Definition of the economy sectors and geographical
areas expected to be mostly affected by climate change
Definition of the economy sectors and geographical
areas expected to be mostly affected by climate change
• Estimation of possible cost of implementing measures and actions
• Potential stakeholders and implementation bodies
• Project implementation indicators
• Estimation of possible cost of implementing measures and actions
• Potential stakeholders and implementation bodies
• Project implementation indicators
• Vulnerability assessment
• Quantification of the vulnerability
• Vulnerability assessment
• Quantification of the vulnerability
Investigation of available technologies and
adaptation policies by sector
Investigation of available technologies and
adaptation policies by sector
Hierarchical selection of
measures and actions per sector
Hierarchical selection of
measures and actions per sector
Evaluation of the projected climate indices
change
Evaluation of the projected climate indices
change
Agriculture Forestry Biodiversity and
ecosystems Fisheries and
aquaculture Water resources Coastal areas Tourism Energy demand Transport infrastructure Health Urban environment Mining industry Culture Insurance sector
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
11
Climate indices used
The list of the thirteen (13) basic climate indices is presented below. In parenthesis the data availability and the unit of calculation are reported:
• Mean temperature (daily, oC)
• Minimum temperature (daily, oC)
• Maximum temperature (daily, oC)
• Mean wind (daily, m/s)
• Maximum wind (daily, m/s)
• Mean precipitation (daily, mm)
• Mean relative humidity (daily, %)
• Ice days (annually, days)
• Tropical nights (annually, days)
• Wet days (annually, days)
• Mean solar radiation (daily,W/m2)
• Mean snowfall (daily, mm)
• Sea level rise (annually, cm)
The fifty-seven (57) supporting indices were derived from these basic indices to evaluate climate phenomena like heatwaves, floods, storms, cold periods, drought, comfort and seasonal changes.
12Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Supporting climate indices
13Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
14Μεταβολή αριθμού ημερών ανά έτος με ελάχιστη θερμοκρασία < 0οC
(νυχτερινός παγετός - night frost)d/y
15 Μεταβολή βαθμοημερών θέρμανσης ανά έτος (Heating Degree Days - HDD) dd/y
16 Μεταβολή αριθμού ημερών χειμώνα με ελάχιστη θερμοκρασία < - 5 oC d/per
17 Μεταβολή αριθμού ημερών άνοιξης με ελάχιστη θερμοκρασία < 0 oC d/per
18 Μεταβολή μέγιστης διάρκειας (ημέρες) με ελάχιστη θερμοκρασία < 0 oC d/per
19 Μεταβολή αριθμού ημερών ανά έτος με μέγιστη θερμοκρασία > 35 oC d/y
20 Μεταβολή αριθμού ημερών ανά έτος με μέγιστη θερμοκρασία > 37 oC d/y
21 Μεταβολή βαθμοημερών ψύξης ανά έτος (Cooling Degree Days - CDD) dd/y
22 Μεταβολή αριθμού ημερών καλοκαιριού με μέγιστη θερμοκρασία > 37 oC d/per
23 Μεταβολή αριθμού ημερών άνοιξης με μέγιστη θερμοκρασία > 30 oC d/per
24 Μεταβολή μέγιστης διάρκειας (ημέρες) με μέγιστη θερμοκρασία > 37 oC d/per
25 Μεταβολή βαθμοημερών ανάπτυξης (Growth Degree Days – GDD) dd/y
26 Μεταβολή αριθμού ημερών ανά έτος με μέση ένταση ανέμου < 3 beaufort d/y
27 Μεταβολή αριθμού ημερών ανά έτος με μέση ένταση ανέμου > 6 beaufort d/y
28 Μεταβολή αριθμού ημερών ανά έτος με μέγιστη ένταση ανέμου < 4 beaufort d/y
29 Μεταβολή αριθμού ημερών ανά έτος με μέγιστη ένταση ανέμου από 4 έως 7 beaufort d/y
30 Μεταβολή αριθμού ημερών ανά έτος με μέγιστη ένταση ανέμου > 7 beaufort d/y
31 Μεταβολή αριθμού ημερών ανά έτος με ημερήσια βροχόπτωση < 1 mm (ξηρές μέρες) d/y
32 Μεταβολή αριθμού ημερών ανά έτος με ημερήσια βροχόπτωση > 2 mm (αποδοτική βροχόπτωση) d/y
33 Μεταβολή αριθμού ημερών ανά έτος με ημερήσια βροχόπτωση >10 mm (βαριά βροχόπτωση) d/y
34Μεταβολή αριθμού ημερών ανά έτος με ημερήσια βροχόπτωση > 20 mm (ακραία
βροχόπτωση)d/y
35 Μεταβολή μέγιστης διάρκειας (συνεχόμενες ημέρες) με βροχόπτωση > 1 mm (υγρή περίοδος) d
36Μεταβολή μέσης ημερήσιας βροχόπτωσης κατά τη μέγιστη διάρκεια (συνεχόμενες ημέρες) με
βροχόπτωση > 1 mm (υγρή περίοδος)mm/d
37 Μεταβολή μέγιστης διάρκειας συνεχόμενων ημερών ξηρασίας (βροχόπτωση < 1 mm) d/per
38 Μεταβολή μέσης καλοκαιρινής βροχόπτωσης ανά έτος mm/y
39 Μεταβολή μέσης χειμερινής βροχόπτωσης ανά έτος mm/y
40Μεταβολή αριθμού ημερών ανά έτος με δείκτη δυσφορίας (distress index) < 24 (ημέρες όπου μικρό
ποσοστό του πληθυσμού (< 50%) νιώθει δυσφορία)d/y
41Μεταβολή αριθμού ημερών ανά έτος με δείκτη δυσφορίας (distress index) 24 - 29 (ημέρες όπου
μεγάλο ποσοστό του πληθυσμού (50 – 75%) νιώθει δυσφορία)d/y
42Μεταβολή αριθμού ημερών ανά έτος με δείκτη δυσφορίας (distress index) > 29 (ημέρες όπου όλος ο
πληθυσμός νιώθει δυσφορία – πιθανότητα κήρυξης κατάστασης έκτακτης ιατρικής ανάγκης)d/y
43 Μεταβολή αριθμού ημερών χιονόπτωσης ανά έτος d/y
44Μεταβολή αριθμού ημερών ανά έτος με δείκτη κινδύνου πυρκαγιάς Angstrom (Angstrom Index) <2
(ημέρες όπου η εμφάνιση πυρκαγιάς είναι πολύ πιθανή)d/y
45Μεταβολή αριθμού ημερών ανά έτος με δείκτη κινδύνου πυρκαγιάς Angstrom (Angstrom Index) 2 –
2,5 (ημέρες με ευνοϊκές συνθήκες για εμφάνιση πυρκαγιάς)d/y
46Μεταβολή αριθμού ημερών ανά έτος με δείκτη κινδύνου πυρκαγιάς Angstrom (Angstrom Index) 2,5 –
4 (ημέρες με δυσμενείς συνθήκες για εμφάνιση πυρκαγιάς)d/y
47Μεταβολή αριθμού ημερών ανά έτος με δείκτη κινδύνου πυρκαγιάς Angstrom (Angstrom Index) > 4
(ημέρες όπου η εμφάνιση πυρκαγιάς είναι μη πιθανή)d/y
48 Μεταβολή μέγιστης διάρκειας συνεχόμενων ημερών με βροχόπτωση > 10 mm (ισχυρή βροχόπτωση) d/per
49Μεταβολή μέσης ημερήσιας βροχόπτωσης κατά την μέγιστη διάρκεια συνεχόμενων ημερών με
βροχόπτωση > 10 mm (ισχυρή βροχόπτωση)mm/d
50 Μεταβολή μέσης μέγιστης βροχόπτωσης 48ώρου ανά έτος mm
51 Μεταβολή μέσης μέγιστης βροχόπτωσης τριών ημερών mm
52 Μεταβολή μέσης μέγιστης βροχόπτωσης πέντε ημερών mm
53Μεταβολή αριθμού ημερών με τιμή βροχόπτωσης > 95ο εκατοστημόριο της περιόδου αναφοράς
(ημέρες με πολύ βαριά βροχόπτωση)d/y
54Μεταβολή δείκτη ημερήσιας έντασης βροχόπτωσης (daily
intensity index) ανά έτοςmm/d
55Μεταβολή αριθμού θερινών ημερών (summer days) (μέγιστη
θερμοκρασία > 25 oC)d/y
56Μεταβολή αριθμού ημερών ανά έτος με δείκτη humidex
(humidex index) > 38 (ημέρες με μεγάλη δυσφορία)d/y
57
Μεταβολή αριθμού ημερών ανά έτος με δείκτη κινδύνου πυρκαγιάς Angstrom (Angstrom Index) < 2,5 (ημέρες όπου η
εμφάνιση πυρκαγιάς είναι πολύ πιθανή και οι συνθήκες εμφάνισης ευνοϊκές)
d/y
58Μεταβολή αριθμού ημερών ανά έτος με μέγιστη ένταση ανέμου >
6 beaufortd/y
59 Μεταβολή μέσης θερμοκρασίας χειμώνα oC
60Μεταβολή μέσης μέγιστης θερινής βροχόπτωσης 48ώρου ανά
έτοςmm
61Μεταβολή αριθμού καλοκαιρινών ημερών ανά έτος με μέγιστη
ένταση ανέμου > 6 beaufortd/y
62 Ποσοστιαία μεταβολή μέσης ετήσιας βροχόπτωσης %
63 Ποσοστιαία μεταβολή μέσης ετήσιας χιονόπτωσης %
64Ποσοστιαία μεταβολή μέσης μέγιστης βροχόπτωσης 48ώρου ανά
έτος%
65Ποσοστιαία μεταβολή μέσης μέγιστης βροχόπτωσης 24ώρου ανά
έτος%
66 Μεταβολή μέσης μέγιστης θερμοκρασίας καλοκαιριού oC
67Μεταβολή αριθμού ημερών χειμώνα ανά έτος με μέγιστη ένταση
ανέμου > 6 beaufortd/y
68Μεταβολή αριθμού ημερών χειμώνα ανά έτος με μέση ένταση
ανέμου > 5 beaufortd/y
69Μεταβολή αριθμού ημερών ανά έτος με μέση ένταση ανέμου > 6
beaufort κατά την αντιπυρική περίοδο (Μάϊος – Οκτώβριος)d/y
70Μεταβολή αριθμού ημερών καλοκαιριού ανά έτος με βροχόπτωση
> 10 mm (ισχυρή βροχόπτωση)d/y
Definitions
Exposure: The nature and extent to which a system is exposed to significant climate fluctuations
Sensitivity: The extent to which a system is affected, either negatively or positively, by the associated climate index. The results may be direct or indirect
Impact: Consequences of climate change to natural or human ecosystems. As far as adaptation is concerned, one can distinguish between potential and expected impacts
Adaptive capacity: The ability of a natural or human system to adapt to climate change (including climate variability and extreme conditions) to mitigate possible damage, exploit any positive impacts, or cope with the consequences
Vulnerability: The extent to which a system is vulnerable or unable to cope with the adverse effects of climate change. Vulnerability is a function of the nature, magnitude and rate of climate change in which a system is exposed, its sensitivity and its adaptive capacity
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
14
Vulnerability assessment
Based on the previous slide, vulnerability can be expressed as:
Vulnerability = (Sensitivity x Exposure) – Adaptive capacity
However, in the context of this methodology, vulnerability has been assessed without taking into account the ability to adapt to climate change (the worst-case scenario). Therefore, the vulnerability formula used would become:
Vulnerability = Sensitivity x Exposure
The following steps were taken in order to assess the vulnerability of the various sectors and geographical areas of the Region to climate change:
• Selection of the sectors for which vulnerability analysis will be performed
• Selection of the most suitable climate indices to measure the impact of each climate component on each sector
• Sensitivity evaluation for each sector to climate change. Evaluation of Sensitivity index.
• Exposure calculation for each sector to climate change. Evaluation of Exposure index.
• Vulnerability assessment for each sector and geographic area
15Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Components of climate change
The components of climate change for which the vulnerability analysis was carried out are were the following:
• Temperature rise
• Drought
• Strong winds
• Heatwaves
• Frost invasion
• Heavy precipitation – Floods
• Snowfall
• Sea level rise
16Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Sectors of anthropogenic and natural environment under evaluation
• Agriculture,
• Forests,
• Reforested areas,
• Biodiversity and ecosystems,
• Fisheries and aquaculture,
• Water resources,
• Coastal areas,
• Rivers (floods),
• Ski related tourism,
• Summer tourism,
• Energy demand,
• Land transport,
• Ports,
• Airports,
• Public health,
• Urban environment and
• Cultural environment
17Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Sensitivity and exposure analysisSensitivity analysis. The aim of this step was to assess the sensitivity expected for each sector to the different components of climate change. Sensitivity assessment was done taking into consideration relative estimates reported in Greek and international literature using the following scale:
• Zero (negligible) sensitivity: 0
• Slight sensitivity: 1
• Moderate sensitivity: 2
• High sensitivity: 3
• Very high sensitivity: 4
Exposure analysis. Changes in the climate indices were assessed in the context of this study. These changes describe the extent of exposure to the climate change components. The degree of exposure was calculated for each point in the grid of the study area using the following scale:
• Zero (negligible) exposure: 0
• Slight exposure: 1
• Moderate exposure: 2
• High exposure: 3
• Very high exposure: 4
Scales of sensitivity and exposure analysis are then divided by four (4) in order to provide the rate of sensitivity and exposure, respectively.
18Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Vulnerability assessment
In the context of the current study vulnerability is evaluated without taking into account the adaptive capacity to climate change (worst case). Therefore, vulnerability depends on sensitivity and exposure to climate change. Vulnerability to climate change is performed for every climatic component separately and the expression of vulnerability follows the scale reported in the following Table.
19Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Boundaries Vulnerability description
<= 0.25 Negligible
0.26 – 0.50 Low
0.51 – 1.00 Medium
1.01 – 1.50 High
> 1.50 Very high (extreme)
Vulnerability assessment was undertaken with two different approaches: Geographic vulnerability: Investigates the geographic areas for
each sector that are most vulnerable to climate change (e.g. coastal agricultural areas of Zacharo municipality have high vulnerability in the scenario RCP8.5 in the period 2081-2100). In this case, vulnerability is calculated only for the grid points that belong to the sector under investigation.
Sectoral vulnerability: Investigates the sectors that are most vulnerable to climate change and to which priority should be given to measures and actions (e.g. the water resources sector is highly vulnerable in the short-term horizon in the adverse scenario). In this case, the sectoral vulnerability is the average vulnerability value of the grid points that correspond to geographic areas of the sector.
A case study in Greece
Climate indices projection (1)Results from the evaluation and analysis of seventy (70) climate indices showed that the climate will become warmer and drier in the coming decades with a significant reduction in rainfall and snowfall and an increase in the frequency of extreme weather events (mainly droughts, floods and heatwaves). A climate index that will also affect significantly the area is the sea level rise. Briefly the main climate changes projected from the RCP’s evaluation are presented below.
• Average temperature in the Region of Western Greece is expected to increase in all scenarios and time periods examined.
• Average temperature rise is expected to range from 0.45 oC (RCP2.6, 2011 – 2030) to 3.92 oC (RCP8.5, 2081 – 2100).
• By the end of the 21st century average temperature in the Region will be kept below 2 oC, in all periods of the stringent (RCP 2.6) and the intermediate scenario (RCP 4.5), however temperature rise will follow the corresponding global projections reaching 3.92 oC for RCP8.5 scenario.
• Maximum summer temperatures are expected to rise above the average temperature (4.51 oC, RCP8.5, 2081-2100). The biggest increase is expected in the municipalities of Amfilochia, Agrinio and Thermo.
• Average winter temperature is expected to increase, with the Kalavryta municipality showing the highest increase (3.80 oC, RCP8.5, 2081-2100).
• Energy demand for cooling is expected to increase in all scenarios and time horizons considered, on the contrary with the energy demand for heating which is expected to decrease.
21Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Climate indices projection (2)• The number of days with an event of fire likely to occur will increase by about 20
days in the adverse scenario (RCP 8,5) between 2081 and 2100.
• Precipitation is expected to gradually decrease in the stringent and worst-case scenarios. Regional Units of Ileia as well as the municipalities of Kalavryta, Erymanthos and West Achaia appear to be facing the biggest problem.
• Similarly, the number of wet days in the year is expected to decrease gradually
• Continuous days without precipitation are expected to increase by about 33 days in the adverse scenario, in the time horizon 2081 – 2100.
• The biggest drought problems are expected to be encountered by the municipalities of Aitoloakarnania and the municipality of Patra.
• In terms of wind speed no significant changes are expected compared with the reference period.
• The number of days where the maximum temperature exceeds 35 oC is expected to increase in the long-term horizon by about 16 days in the worst-case scenario with respect to the reference period.
22Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Climate indices projection (3)• Even higher is expected to be the number of days with minimum temperature over 20 oC
(tropical nights) in the coming decades. The average increase ranges from eight (8) days (in the favorable and intermediate scenario in 2011-2030) to fifty-six (56) days (in the worst-case scenario, 2081-2100).
• Changes in temperature (combined with changes in humidity) are expected to increase the number of days in the years in which there will be great discomfort for the population.
• The number of days in the year with heavy precipitation, which may be associated with flood events is expected to increase in all scenarios and time periods. The highest increase is expected in the short term, even in the most favorable scenario (+ 20.85 days).
• Cold invasions (number of days with minimum daily temperature below 0 oC) will decrease in all future scenarios. After 2080 the reduction is expected to reach up to minus 15.43 days in the worst-case scenario.
• Correspondingly snowfall is expected to decline in the intermediate and adverse scenario. In the period 2081-2100 this reduction is expected to reach up to 81% in the unfavorable scenario
• Amount of snowfall and the number of days with snowfall will decrease. In the period 2081-2100 days of snowfall will decrease by about 6 times in comparison with the unfavorable scenario.
• Sea level will rise in the future. The maximum rise will range from 9 cm (in 2011-2030, regardless of the scenario) to 55 cm (in 2081-2100 for the worst-case scenario)
23Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Temperature
24Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Time horizon
Mean temperature change in relation with the reference period
RCP 2.6 RCP 4.5 RCP 8.5
2011-2030 0,45 0,54 0,642031-2050 0,91 0,97 1,232081-2100 0,70 1,82 3,92
Time horizon
Minimum temperature change in relation with the reference periodRCP 2.6 RCP 4.5 RCP 8.5
2011-2030 0,46 0,54 0,642031-2050 0,84 0,96 1,222081-2100 0,72 1,82 3,91
Time horizon
Maximum temperature change in relation with the reference periodRCP 2.6 RCP 4.5 RCP 8.5
2011-2030 0,39 0,54 0,652031-2050 1,00 0,98 1,242081-2100 0,64 1,84 3,97
Temperature
25
RCP 4.5
RCP 2.6
RCP 8.5
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Sea Level Rise
26
RCP 4.5
RCP 2.6
RCP 8.5
2011-2030 2031-2050 2081-21000,00
0,10
0,20
0,30
0,40
0,50
0,60
Maximum sea level rise for each RCP scenario and time horizon in relation with the reference period
RCP 2.6 RCP 4.5 RCP 8.5
Sea level rise
(m)
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Vulnerability projection – RCP 2.6
• In the short term horizon the great majority of sectors showed from negligible to low vulnerability to climate change. The sectors of coastal areas, rivers, urban and cultural environment show medium vulnerability.
• In the medium term horizon vulnerability to climate change varies between low / negligible to medium. Medium vulnerability is expected for the agriculture, reforested areas, biodiversity – ecosystems, water resources, rivers, urban and cultural environment sectors.
• In the long term horizon water resources sector showed high vulnerability. Agriculture, forests, reforested areas, biodiversity – ecosystems and rivers sectors showed medium vulnerability. Other sectors showed low or negligible vulnerability to climate change.
• There are no sectors showing very high vulnerability in any of the time horizons. Water resources sector, seems to be the most vulnerable to climate change with high vulnerability levels in the long-term time horizon.
• Fisheries – aquaculture, tourism, energy demand, transport and public health sectors, scored the lowest vulnerability and appear to be more resilient to climate change.
27Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Vulnerability projection – RCP 4.5• In the short term horizon the great majority of sectors showed low vulnerability to
climate change. Agriculture, biodiversity – ecosystems, water resources, rivers, urban and cultural environment sectors show medium vulnerability.
• In the medium term horizon vulnerability to climate change varied between low / negligible to medium. Water resources sectors is expected to face high vulnerability, while agriculture, biodiversity – ecosystems, rivers, ski related tourism, urban and cultural environment sectors showed medium vulnerability to climate change.
• In the long term horizon water resources sector showed the highest vulnerability. Agriculture, reforested areas, biodiversity – ecosystems, fisheries and aquaculture, tourism, urban and cultural environment sectors are expected to have medium vulnerability. The others sectors showed low or negligible vulnerability to climate change.
• There are no sectors showing very high vulnerability to climate change in any time horizon. The water resources sector appeared to be the most vulnerable to climate change with high vulnerability in the medium and long-term time horizon.
• Forests, summer tourism, energy demand, transport and public health sectors scored the lowest vulnerability and appeared to be more resilient to climate change.
28Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Vulnerability projection – RCP 8.5
• In the short term horizon the great majority of sectors showed low or medium vulnerability to climate change. Forests, energy demand and ports sectors had negligible vulnerability. Agriculture, biodiversity – ecosystems, fisheries – aquaculture, water resources, coastal areas, rivers, urban and cultural environment sectors showed medium vulnerability.
• In the medium term horizon, transportation and health showed low vulnerability to climate change. Water resources sector is expected to face very high vulnerability and the ski related tourism high. Others sectors showed medium vulnerability to climate change.
• In the long term horizon agriculture, biodiversity – ecosystems, water resources and tourism (both forms) sectors are expected to face very high vulnerability. Moreover, forests, energy demand and cultural environment sectors are expected to face high vulnerability. Others sectors showed medium vulnerability, with the exception of ports which appeared to show the best adaptation to climate change with low vulnerability levels.
29Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Vulnerability of agriculture
30
RCP 4.5
RCP 2.6
RCP 8.5
Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
Thank you for your attention!
31Regional Climate Change Adaptation Planning: Methodological Approach on Future Projections and Vulnerability Assessment in accordance with the 5th IPCC Assessment Report
