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

Training module on climate analysis (I)

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Page 1: Training module on climate analysis (I)

Climate Adaptation training in the Philippines – SEI Oxford and SEI Asia. November 12-13, 2013

Climate Analysis: using data to inform adaptation strategies.

Page 2: Training module on climate analysis (I)

• 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.

Learning Objectives

Page 3: Training module on climate analysis (I)

• 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.

Some definitions

Source southwestclimate.org

Page 4: Training module on climate analysis (I)

• 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-and-mitigation

Some Definitions

Page 5: Training module on climate analysis (I)

• 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. . .)

Principles

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• 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).

Frame the Question

Page 7: Training module on climate analysis (I)

• 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.

Understand the Context

Page 8: Training module on climate analysis (I)

• 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

Climate Models

Page 9: Training module on climate analysis (I)

• 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.

Data and Uncertainty

50km RCM resolution Downscaled data around Dumaguete 300km GCM resolution

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Data and Uncertainty

• Downscaling – can be dynamic or statistical

• Important in an island context!

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Data and Uncertainty

Rainfall changes Mataram Station from 10 models

• Many different sources of uncertainty, which get amplified!

Cascade of uncertainty (Wilby and Dessai 2010)

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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.

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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.

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• 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.

Typhoons

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Typhoons

Source: PAGASA

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• Key is to choose adaptation options which are no/low-regret, 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?

Robust Choices

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• CSAG Climate Information Portal:http://cip.csag.uct.ac.za/webclient2/app/

• World Bank Climate Portal: http://sdwebx.worldbank.org/climateportal/index.cfm?page=country_historical_climate&ThisRegion=Asia&ThisCCode=IDN

• weADAPT: http://weadapt.org/placemarks/maps/weather-station/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/wp-content/uploads/downloads/2011/05/Risk-and-Adaptation-Assessment-to-Climate-Change-in-Lombok-Island.pdf

Useful Data Sources

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• 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.

Exercise 1: Assessing data

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• 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?

Exercise 2: Robust adaptation