This document provides guidance on using climate data to inform adaptation strategies. It discusses key concepts like climate variability and change. The objectives are to assess different climate data sources, communicate future changes accounting for uncertainty, and evaluate adaptation options under different climate futures. Principles discussed include framing the question, understanding past/present climate, and that uncertainty cannot be avoided. A range of climate data sources are presented, from recorded data to global and downscaled models. Uncertainty from different sources is compounded and does not preclude adaptation. The Philippines example shows temperature increases are clear while rainfall projections vary between models. Exercises guide applying the concepts to assess data sources and identify robust adaptation options.

1. Climate Analysis: using data to
inform adaptation strategies.
Climate Adaptation training in the Philippines – SEI Oxford and SEI Asia
November 12-13, 2013

2. Learning Objectives
• By the end of this session participants will be able to:
- Assess the strengths and weaknesses of several
different types of climate data.
- Develop clear messages on future changes in climate
which account for uncertainty.
- Critically evaluate the strengths and weaknesses of
different adaptation options in regard to different possible
climate futures.

3. Some definitions
Source southwestclimate.org
• Climate Variability:
Variations in the
mean state of the
climate – natural
variability always
exists (e.g. wetter
years, drier years).
• Climate Change:
Anthropogenic climate
change is a significant
and persistent change
in the average
conditions or extremes
of a region.

4. Some Definitions
• Two ways we can deal with a changing climate:
• Attempt to minimise how much change will occur, by reducing
emissions (mitigation)
• Attempt to minimise the negative effects of climate change
(adaptation)
• Sometimes we can do both at once:
- e.g. Conservation agriculture can increase farm water availability at
the same time as reducing emissions.
For more on adaptation-mitigation synergies
seehttp://weadapt.org/initiative/synergies-between-adaptation-andmitigation

5. Principles
• The data needed depends on the question (so frame the
question well first).
• Using multiple sources of information will provide a
better understanding of the issue.
• Always understand the past and the present before
looking to the future.
• Uncertainty can’t be avoided; there is a range of
plausible futures
• Climate change is the not the only issue (deforestation,
population growth, intensive agriculture. . .)

6. Frame the Question
• Who? Different groups will be vulnerable in different
ways.
• Where? The location and spatial scale are key. Are we
interested in changes at a national scale, to inform
policy? Or are we trying to implement adaptation in a
small rural community?
• What? Are there specific areas we are interested in, for
example how climate change might affect the growing
season for different crops?
• The more specific we can make the question, the easier
it will be to identify the specific changes in climate which
we need to understand (e.g. onset of the rainy season,
or maximum temperatures).

7. Understand the Context
• What is the current climate like – variability, seasonality.
• Are there cyclical patterns which affect the climate – e.g.
El Niño causing droughts.
• Is there evidence that the climate has been changing?
• Are there other factors which are important in these
changes? e.g. a decrease in water availability may also
be due to land-use change.

8. Climate Models
• A model is a representation of the
real world, it is not an exact copy
• Projections vs Predictions.
• We do not know which model is
‘best’; fit to historical climate is not
necessarily an indicator of quality
of projection
• Climate is a complex system –
there are a range of plausible
future states

9. Data and Uncertainty
300km GCM resolution
50km RCM resolution
Downscaled data around Dumaguete
• Different types of data (recorded, observed, global
models, downscaled models).
• Good for different things; understand pros and cons.
• No single model is ‘best’ – look at projections from a
range of regionally appropriate models.

10. Data and Uncertainty
• Downscaling –
can be dynamic
or statistical
• Important in an
island context!

11. Data and Uncertainty
Rainfall changes Mataram Station from 10 models
Cascade of uncertainty (Wilby and Dessai 2010)
• Many different sources of uncertainty, which get amplified!

12. Dumaguete
• There will always be uncertainty – we can’t predict the
future.
• For some locations and some changes we can be more
confident than others.
• Uncertainty doesn’t mean we can’t do anything to adapt.

13. Philippines
• For the Philippines we have a mixed picture:
- Temperatures are clear; there will be increases
- Sea-Level rise is clear; we will have increases
- Certain impacts can be clear – e.g. there will be
problems from coastal erosion and storm surges, there is
likely to be coral bleaching and die-off.
- Rainfall changes are less certain: generally we may see
increases in Luzon and Visayas, and decreases in
Visayas, but different models vary. . .
- Greater intensity though.

14. Typhoons
• No evidence for changes in intensity or frequency of
typhoons in Pacific (historical record poor!)
• No change in frequency of typhoons in Philippines –
however, damage increasing (PAGASA)
• Projections: Uncertainty, but wind speed and rainfall
intensity likely to increase, frequency same or decrease.
• Unclear how tracks will change.

15. Typhoons
Source: PAGASA

16. Robust Choices
• Key is to choose adaptation options which are no/lowregret, and start by addressing current vulnerability:
- Create a plausible list of adaptation options (which are
socially acceptable).
- Based on data create a plausible list of future climate
scenarios (e.g. earlier start to rains, warmer, more
intense rainfall).
- Are the adaptation options negatively affected by
possible future changes?
- Which choices are least affected by differences between
scenarios?

17. Useful Data Sources
• CSAG Climate Information
Portal:http://cip.csag.uct.ac.za/webclient2/app/
• World Bank Climate Portal:
http://sdwebx.worldbank.org/climateportal/index.cfm?page=co
untry_historical_climate&ThisRegion=Asia&ThisCCode=IDN
• weADAPT: http://weadapt.org/placemarks/maps/weatherstation/37891
• UK Met Office Indonesia profile:
http://www.metoffice.gov.uk/media/pdf/8/f/Indonesia.pdf
• GTZ Adaptation to climate change on Lombok:
http://www.paklim.org/wpcontent/uploads/downloads/2011/05/Risk-and-AdaptationAssessment-to-Climate-Change-in-Lombok-Island.pdf

18. Exercise 1: Assessing data
• For Lombok identify 1 source of information on historical climate,
and 2 different sources of information about future climate. Assess
the following:
• What has been the historical change in rainfall and temperature?
• For 2050, what do the projections say about:
-
Annual rainfall
Average temperatures
The timing of the rainy season
-
What do the different data sources agree on?
What do they disagree on?
Are there differences between historical trends and future
projections?
Write down 2 key messages about the future climate you would be
confident in using in your work.
-

19. Exercise 2: Robust adaptation
• Choose 1 stakeholder group from your case study
• Based on results from the vulnerability assessment, write
down a list of possible adaptation options.
• Using different data sources develop 3 possible
scenarios of how the climate might change.
• For each adaptation option identified score them 1-5 for
each scenario, based on how sensitive they are to the
changes (where 1 is not affected and 5 is very affected).
• How do the adaptation options compare? Are there
options which perform well under all 3 scenarios?
• What other non-climatic changes might influence how
well the adaptation options perform?