department of geography and environmental science ... · the recurring crises in west africa •...

Department of Geography and environmental science

Department of Meteorologyp gy

Weathering theWeathering the droughtgStrategies for adaptation under extreme risk and uncertainty

© University of Reading 2008 www.reading.ac.ukOctober 2, 2012

uncertainty

A thought• Seasonal and sub-seasonal prediction and climate

change research has long been dominated by top-d d li f i f ti ith “f f id ldown delivery of information with “far from ideal packaging” (Tall et al., 2012)Thi t h ll• This presents a challenge.

• Given the complex interactions between climate, f flivelihoods and vulnerability and the confines of

institutions (or lack of), how can locally appropriate d t ti l b t i l th t fl t l ladaptation plans be put in place that reflect local

experiences and impacts?

Strategies for Adaptation Under Extreme Risk and Uncertainty 2

Climate change: a wicked problem

FoodFood security

Water security

Social protection


How will rainfall patterns change by 2050?

Sahel rainfall index

Our understanding of the processes governing tropical rainfall is insufficient to predict with certainty a trend f ith i

Biasutti et al J Clim (2008)

of either sign.

Strategies for Adaptation Under Extreme Risk and Uncertainty

Biasutti et al., J. Clim. (2008)

4

C i l d fConvection triggered on soil moisture gradient: signature of surface forced circulation

Convective response to land surface

Land Surface Temperature Anomalies

Convection triggered on soil moisture gradient: signature of surface-forced circulation. Soil moisture can feedback on regional circulations.

Blue contours: LSTA

Wet features

From Chris Taylor CEH

Strategies for Adaptation Under Extreme Risk and UncertaintyHigh resolution visible (1km) MSG

From Chris Taylor, CEHTaylor et al. (2009)

Chain of models: Cascade of uncertaintyGCM

Ensemble

DownscalingT, P, Wind, Solar…

Applications Model eg.

Hydro Model

Sub-daily scale e.g. watershed scale

Operations Model

Climate characteristics, water shed features

Utility Planning e.g. water

e.g. Reservoir output, distribution and demand


Adaptation

Chain of models: Cascade of uncertainty

Ensemble size = 51, climate size = 450Forecast start reference is 01/04/12Prob(most likely category of precipitation)

<---- below lower tercile

0°N

30°S

30°N

0°E30°E

70..100%60..70%

50..60%40..50%

other

Ensemble size = 51, climate size = 450Forecast start reference is 01/04/12Prob(most likely category of precipitation)

<---- below lower tercile

0°N

30°S

30°N

0°E30°E

70..100%60..70%

50..60%40..50%

other

JAS 201

above upper tercile ---->

0°N30°S

30°N

60°E90°E

40..50%50..60%

60..70%70..100%

JAS 201


0°N30°S

30°N

60°E90°E

40..50%50..60%

60..70%70..100%

1000’s to 100’s Km

1000’s to 100’s Km

1000’s to 100’s m1000’s to 100’s m


1000’s to 100’s cm1000’s to 100’s cm

Chain of models: Cascade of uncertaintyff f• Met office seasonal forecasts

compared with outcomes, 1992-2011. Years marked in bold performed particularly poorly.

• “Placebo or pacifier”, ZiloreMumba, previously Head of Forecasting for ACMADForecasting for ACMAD


From Cornforth, 2012 (Table 1)

The recurring crises in West Africa f• West Africa represents a

textbook example of the devastating impacts of a g phighly variable climate prone to episodes of extreme

tevents. • Africa depends predominantly

on climate for its livelihoodon climate for its livelihood and yet has low resilience and lacks adequate i f ti hi h t binformation on which to base coping strategies.


Growing evidence that the frequency and extent of droughts have increased as a result of human induced climate change (IPCC, SREX report, Nov 2011) Medium confidence of more intense and longer droughts in some regions, particularly in southern Europe and West Africa.

“Drought is predictable and does not happen overnight. Therefore it should not claim lives nor lead to famine, which results when drought couples with policy failure or governance breakdown or both.”

Luc Gnacadja, Exec Secretary, UN Convention to Combat Desertification 2011Desertification, 2011


IPCC projections into the future


What are the important risks and tradeoffs?

Weather-related event

Affected Died

Flood 19 939 000 9 642

Drought/Famine

110 956 000 4 453

Wi d t 5 687 000 1 335Windstorms 5 687 000 1 335

Extreme Temps 8 000 147

TOTAL 136 590 000 15 713

Numbers of people affected by extreme weather-related events in Africa 1993-2003

TOTAL 136 590 000 15 713

2003EM-DAT data set, Centre for Research on the Epidemiology of Disasters, University of Louvain, Bel. (Conway 2009)


How to manage risk? Work with uncertainty?

Early warning? Early action?

(b)(a)

Famine Early Warning Network (FEWS) estimated food security outlooks for (a) July-September 2012 for West Africa; and (b) January-March 2011 (issued 31 January 2011) for East Africa, when ‘Extremely Food Insecure’ conditions already prevailed over


y y pthe Greater Horn of Africa.

3

Bild 13

3 Or difference picture of the crises? link to seasonal forecast?Emily Boyd; 2012-09-28

Skillful forecasting insufficientSkillful forecasting insufficient

Ensemble sForecast staProb(moECMWF

0°N

30°S

30°N

7 size = 51, climate size = 450art reference is 01/04/12ost likely category of prF Seasonal Forecast<---- be

0°E0°E

0..100%60..70%

50..60 recipitation)

elow lower tercile a

30°E

30°E

%40..50%

other


60°E

60°E

40..50%50..60%

60

JAS 2012System 4

0°N30°S

30°N

90°E

90°E

0..70%70..100%

• 2012 season very wetBut reality is that, 1-15 days


y yout to seasonal forecasting

14

Result is often poor uptake • From talk by Bruce Hewitson, CSIAG (2011)


What actions?• Practical seasonal forecasting that circumnavigates

the current modeling difficulties (errors due to physics, b ti l ti ) i l i tobservations, resolution) is an early warning system

that provides people with information quickly and in a form that even largely illiterate populations canform that even largely illiterate populations can understand. Bottom up approaches• Bottom-up approaches

– Rainwatch in Niger (drought, sub-seasonal to seasonal)seasonal)

– Red Cross in Senegal (flood, extreme event)


Rainwatch in Niger

• Rainwatch is an automated rainfall auto ated a amonitoring system that ingests year-to-date station data on a daily basisC t ff ti i t t d

(a)

• Cost effective integrated solutions real-time monitoring of 2011 rainymonitoring of 2011 rainy season in Niger via the Rainwatch project Fig.6 Rainwatch culmulative precipitation

for Niamy (Niger) for 2011

(b)


for Niamy (Niger) for 2011

Boyd, Cornforth, Lamb, Brouder et al. submitted, Nature Reports Climate Change

Rainwatch contribution in AfricaEarly warning can beEarly warning can beEarly warning can be

be based on nowcasting

monitoring, visual and useful to decision

Early warning can be be based on nowcasting

monitoring, visual and useful to decision

K i di id l ithK i di id l ith

useful to decision maker (defined by

Niger Met services)

useful to decision maker (defined by

Niger Met services)

Time frames areTime frames areKey individual with vision and personal

commitment

Key individual with vision and personal

commitment

Time frames are significant long-term

engagement in the region

Time frames are significant long-term

engagement in the region

Monitoring and dissemination by Rainwatch of key

Monitoring and dissemination by Rainwatch of key y

variables (i.e. rainfall, soil moisture,

atmospheric dust), significant to regional

livelihoods and as

yvariables (i.e. rainfall,

soil moisture, atmospheric dust),

significant to regional livelihoods and as


indicators of climatic variability

indicators of climatic variability

Red Cross early warning in Senegal• Exchange activities are

coordinated by the Senegalese Red Cross and gfocus on providing flood alerts to vulnerable

iticommunities• Community volunteers as

climate information relays,climate information relays, links national level and timing of activities


Red Cross model contribution in Africa

• Key individual who links across boundaries withacross boundaries with institutions, key individual/Transcended language barriers

• Effective communication of weather as basis to build uponweather as basis to build upon e.g. channels that were previously unknown, starting from the application side

• Time frames significant Red Cross are facilitating the


Cross are facilitating the process

20

What are the key characteristicsof this bottom up forecast system?of this bottom up forecast system?

• Cost-effective innovative solutionsT h i l i li it• Technical simplicity

• Use of local indicators• Polycentric levels of cooperation• Polycentric levels of cooperation• Ease of upscaling• “Help Africa to help itself” (Tarhule Lamb et al 2003) andHelp Africa to help itself (Tarhule, Lamb et al., 2003) and

achieve more effective, equitable and sustainable outcomes at multiple levels

• Caveat that there will always be some level of opportunism, i.e. governance is never perfect (Toonen, 2010 cf Ostrom2010)’


2010) .

21

Oxfam’s polycentric model of resilience

Boyd, Cornforth, Lamb, Brouderet al. submitted (2012)Nature - Climate Change


What are the features of success?1. A key individual (node) who has vision to energise

long-term engagement and understands influential i t i th t k tpoints in the network governance system

2. Effective communication of current weather3. Time frames are significant because the processes

for building resilience and sustainability can take between 5-20 years to develop


Looking forwardsThe time is ripe for nations to move forward with the development of a pro-active, risk-based national drought policy WMO Secretary General Michel Jarraud:policy - WMO Secretary-General, Michel Jarraud:

Institutions must establish practical innovations toInstitutions must establish practical innovations to anticipate impending crises:• Identifying rainfall deficits through long-term• Identifying rainfall deficits through long-term

monitoring and timely communication of user-relevant information

• Access to relevant and reliable forecasts and the ability of stakeholders to act on that information.


Transferability of lessons?


Setting the scenef f• Insecure sources of food + water (70%, thermal tolerance, few

days, little irrigation, v vulnerable to small changes in rainfall patterns)

• Knock-on threats to security and infrastructure - DarfurKnock on threats to security and infrastructure Darfur conflict, East Africa 2009.


• Adverse impacts on health - direct and indirect - more vector borne diseases eg. dengue, malaria rise in Ethiopian highlands, 0.5C1980) ->

Looking forwards• Research into the predictability of coupled ocean-

atmospheres is relatively new and exciting – many real li ti f thi h i l di l it ti iapplications for this research, including exploitation in

the development of seasonal forecasting systemsR h l d b l l• Research on seasonal and sub-seasonal scale predictions must fit in with WMO climate services framework and be defined by African stakeholder needframework and be defined by African stakeholder need for locally appropriate adaptation outcomes


What are the important risks and tradeoffs?

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