Analyzing climate change risks and vulnerabilities

1. Least Developed Countries Expert Group (LEG)
Regional training workshop on NAPs for the Pacific region
10 to 13 July 2017
Nadi, Fiji
Analyzing climate change risks
- constructing climate scenarios

2. Introductory slide
 One of the essential functions for the NAPs is to put in place robust
systems at the national level for “analysing climate data and assessing
vulnerabilities to climate change and identifying adaptation options
at the sector, subnational, national and other appropriate levels”
 Detailed and relevant assessments are critical to underpin the
identification of adaptation actions to be undertaken, as well as to
monitor the progress towards reducing vulnerability to climate change
risks
 Depending on the nature and level of risk, a country will be able to decide
upon the most appropriate measures for adapting particular systems

3. Changes in the climate – the global picture
Source: Climate Lab Book (2017). Climate spirals. Available at <http://www.climate-lab-book.ac.uk/spirals>. Accessed 20
February 2017

4. Defining climate scenarios
 A plausible and often simplified representation of the future climate,
based on an internally consistent set of climatological relationships that
has been constructed for explicit use in investigating the potential
consequences of anthropogenic climate change, often serving as input to
impact models
 Climate projections often serve as the raw material for constructing
climate scenarios, but climate scenarios usually require additional
information such as the observed current climate
 A climate change scenario is the difference between a climate scenario
and the current climate
Source: Figure TS-15 in Stocker et al., 2013: Technical Summary. In: Climate Change 2013: The Physical Science Basis.
Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker,
T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA.

5. Risk of climate-related impacts
Source: Figure SPM.1 in IPCC, 2014: Summary for policymakers. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and
Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R.
Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S.
MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1-32.

6. Types of climate scenarios
 Incremental scenarios
 Assume a realistic incremental change in climate over time
 e.g. decline of summer rains by 5% per decade
 Analogue scenarios
 Spatial - projecting climate of one location from another
 Temporal - reconstruction of past climate
 Climate model based scenarios
 Mathematical representation of the climate system
 Coupled Atmosphere-Ocean Climate Models
 Dynamically downscaled AOGCMs
 Statistically downscaled AOGCMs

7. (a) previous sequential approach; (b) parallel approach. Numbers indicate analytical
steps (2a and 2b proceed concurrently). Arrows indicate transfers of information
(solid), selection of RCPs (dashed), and integration of information and feedbacks
(dotted). Source: Moss et al. (2008).
Approaches to the development of global scenarios

8. Generating climate scenarios using climate models
Climate models
 Mathematical representation of the climate system based on the physical,
chemical and biological properties of its components, their interactions
and feedback processes, and accounting for some of its known properties
 Coupled Atmosphere–Ocean General Circulation Models (AOGCMs)
provide a representation of the climate system that is near or at the most
comprehensive end of the spectrum currently available
 There are two levels or hierarchy:
 General Circulation Models providing information at global scale –
they have coarse resolution (250 – 600 km over land)
 Regional Climate Models providing information at regional scale –
have higher resolution (~ 50km and less)

9. Generating climate scenarios using climate models
 Depict the climate using
a three dimensional grid
over the globe;
 Horizontal resolution of
between 250 and 600
km;
 10 to 20 vertical layers in
the atmosphere and
sometimes as many as
30 layers in the oceans.
General circulation models
Source: http://www.ipcc-data.org/guidelines/pages/gcm_guide.html

10. Generating climate scenarios using climate models
Regional Climate Models
 Involve dynamically downscaling GCM data
 Run at continental scale with boundary conditions from GCMs
 Good for investigating variability

11. Generating climate scenarios using climate models
Statistical downscaling
 Steps
 Construction of relationships between local climate variables (e.g.
surface air temperature and precipitation) and large-scale predictors
(e.g., pressure fields)
 Application of the relationships to the largescale climate variables from
the GCMs to estimate corresponding local and regional characteristics
 Assumptions
 High quality large-scale and local data being available for a sufficiently
long period to establish robust relationships in the current climate
 Relationships which are derived from recent climate being relevant in a
future climate

12. Generating climate scenarios using climate models
Regional Climate Models
 Involve dynamically downscaling GCM data
 Run at continental scale with boundary conditions from GCMs
 Good for investigating variability

13.  A number of national and regional centres house climate data and
scenarios. Examples in the region include:
 PACCSAP
 Regional data and scenarios can also be accessed from global projects:
 e.g. CORDEX
 A WCRP project to generate regional climate change
projections
for all terrestrial regions of the global for AR5 and beyond
 Domains for the region: South Asia, East Asia, Central Asia,
Australasia
Accessing climate data and scenarios from existing sources

14. Annual projected temperature change relative to 1986–2005
Excerpt from Fig 24-2: Hijioka, Y., E. Lin, J.J. Pereira, R.T. Corlett, X. Cui, G.E. Insarov, R.D. Lasco, E. Lindgren, and A. Surjan, 2014: Asia. In: Climate Change
2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee, K.L. Ebi,Y.O . Estrada, R.C. Genova, B.
Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA, pp. 1327-1370.
Northern Pacific Southern Pacific
 Median projected regional increase is in the range 0.5°C
to 0.9°C by 2100 compared to 1986–2005

15. Annual projected precipitation change relative to 1986–2005
Excerpt from Fig 24-2: Hijioka, Y., E. Lin, J.J. Pereira, R.T. Corlett, X. Cui, G.E. Insarov, R.D. Lasco, E. Lindgren, and A. Surjan, 2014: Asia. In: Climate Change
2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee, K.L. Ebi,Y.O . Estrada, R.C. Genova, B.
Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York,
NY, USA, pp. 1327-1370.
Northern Pacific Southern Pacific

16. Source: Pacific Climate Change Science Climate Futures -
https://www.pacificclimatefutures.net/en/climate-futures/future-climate/

17. Applying climate scenarios in impact studies (example)
Assessment of global banana production and suitability under climate
change scenarios
Source: German Calberto, G., C. Staver and P. Siles. 2015. An assessment of global banana production and suitability
under climate change scenarios, In: Climate change and food systems: global assessments and implications for food
security and trade, Aziz Elbehri (editor). Food Agriculture Organization of the United Nations (FAO), Rome, 2015
Steps
 Using the current mean climate (mean monthly temperature and precipitation) to
classify areas according to a range of suitability criteria for banana production
 Areas not suitable for banana production were defined as areas having three or more
months with temperatures below 13°C
 Globally suitable areas were classified into tropical and subtropical banana production
areas
 Further subcategories were identified based on average annual temperature, total annual
rainfall and length of the dry season:
 Four categories of total annual rainfall <900 mm, 900-1500 mm, 1500-2500 mm and
>2500 mm
 Three categories of average annual temperature : 13-18 °C, 18-24 °C and >24 °C
 Two categories for length of dry season: three months or fewer with less than 60
mm of monthly rainfall (i.e. “dry”) and more than three dry months

18. Source: German Calberto, G., C. Staver and P. Siles. 2015. An assessment of global banana production and suitability
under climate change scenarios, In: Climate change and food systems: global assessments and implications for food
security and trade, Aziz Elbehri (editor). Food Agriculture Organization of the United Nations (FAO), Rome, 2015

19. Applying climate scenarios in impact studies (example)
Assessment of global banana production and suitability under climate
change scenarios
Source: German Calberto, G., C. Staver and P. Siles. 2015. An assessment of global banana production and suitability
under climate change scenarios, In: Climate change and food systems: global assessments and implications for food
security and trade, Aziz Elbehri (editor). Food Agriculture Organization of the United Nations (FAO), Rome, 2015
Steps
 Projections were done for 2030, 2050 and 2070, under the A2 scenario and the average
of 20 general circulation models

20. Source: German Calberto, G., C. Staver and P. Siles. 2015. An assessment of global banana production and suitability
under climate change scenarios, In: Climate change and food systems: global assessments and implications for food
security and trade, Aziz Elbehri (editor). Food Agriculture Organization of the United Nations (FAO), Rome, 2015
Distribution for climatic zones for banana suitability (Current)

21. Source: German Calberto, G., C. Staver and P. Siles. 2015. An assessment of global banana production and suitability
under climate change scenarios, In: Climate change and food systems: global assessments and implications for food
security and trade, Aziz Elbehri (editor). Food Agriculture Organization of the United Nations (FAO), Rome, 2015
Distribution for climatic zones for banana suitability (2050)

22. Applying climate scenarios in impact studies (example)
Findings
Source: German Calberto, G., C. Staver and P. Siles. 2015. An assessment of global banana production and suitability
under climate change scenarios, In: Climate change and food systems: global assessments and implications for food
security and trade, Aziz Elbehri (editor). Food Agriculture Organization of the United Nations (FAO), Rome, 2015
 Conditions globally will continue to be highly favourable for banana
production
 Even though increasing temperatures are not unfavourable for banana,
they may be unfavourable for perennial and annual crops with which
bananas are often grown
 Production cycles from planting to harvest will be shorter due to an
accelerated rate of leaf emission
 By 2070, projections indicate that certain areas in Africa and Asia will have
at least three months with average monthly temperatures above 35 °C,
conditions not suitable for banana production
 A large area of land will shift out of the unsuitably cold category in Asia

23. Important considerations (1/4)
Baseline climate data
• Helps to identify characteristics of the current climate regime such as
means, seasonal patters, trends, variability, extremes, etc.;
• Based on at least 30 years of observed data – see WMO climatological
standard normals
(http://www.wmo.int/pages/prog/wcp/wcdmp/GCDS_1.php);
• Current climatological standard normal period is 1961-1990
Map source: Malawi Department of Climate Change and Meteorological Services (2017). Climate of
Malawi. Available at http://www.metmalawi.com/climate/climate.php (Accessed 22 February 2017)

24. Important considerations (2/4)
Uncertainty
Sources
 Uncertainties in
future emissions
 Uncertainties in
future
concentrations
 Uncertainties in the
response of the
climate
The global goals under the Paris Agreement provide a basis for removing
the uncertainties in decision-making
Figure source: Preliminary Scenario MIP SSP for the Coupled Model Intercomparison Project 6, O’Neil et al,
GMD Discussion 2016, from Riahi, K., van Vuuren, D.P., Kriegler, E., Edmonds, J., O’Neill, B.C., et al.: The
Shared Socioeconomic Pathways: An Overview, Global Environmental Change (submitted), 2016.

25. Important considerations (3/4)
Global goals under the Paris Agreement a
Article 2.1(a)
“Holding the increase in the global average temperature to well below 2 °C
above pre-industrial levels and pursuing efforts to limit the temperature
increase to 1.5 °C above pre-industrial levels, recognizing that this would
significantly reduce the risks and impacts of climate change”
Article 7.1
Parties hereby establish the global goal on adaptation of enhancing
adaptive capacity, strengthening resilience and reducing vulnerability to
climate change, with a view to contributing to sustainable development and
ensuring an adequate adaptation response in the context of the temperature
goal referred to in Article 2
a Complete information on the Paris Agreement is available at http://unfccc.int/9485

26. Important considerations (4/4)
Resource requirements for generating climate scenarios
 Good technical capacity on the climate science
 Large computer resources
 Stable power supply
 Institutional support

27. Contact:
The Chair
Least Developed Countries Expert Group (LEG)
leghelp@unfccc.int