climate change adaptation in northern ethiopia
DESCRIPTION
Presented by Polly Ericksen at the Stakeholders’ Workshop on Enhancing Communities’ Adaptive Capacity to Climate Change Induced Water Scarcity in Kabe Watershed, South Wollo Zone, Wollo University, Dessie, Ethiopia, 24-25 November 2011.TRANSCRIPT
Climate Change Adaptation in Northern Ethiopia
Polly Ericksen (ILRI)
Stakeholders’ Workshop on Enhancing Communities’ Adaptive Capacity to Climate Change Induced Water Scarcity in Kabe Watershed, South Wollo Zone
Wollo University, Dessie, Ethiopia, 24-25 November 2011
Climate variability already a constant
• East Africa characterized by high CV rainfall annually and seasonally
• Evidence in N. Ethiopia farmers abandoning belg crops
• Droughts and water stress affect both livestock and crops
• Bi-modal distribution means seasonal distribution more important than annual averages
Recent Climate Trends in East Africa
Temperature
• Mean annual temperature increased by 1.0°C since 1960• Most rapid in March-May (0.29°C per decade)• Slowest in June-September (0.19°C per decade)
• Increasing frequency of hot days, and more frequent hot nights• Number of ‘hot’ days per year increased by since 1960 (especially in
March-May)• Number of ‘hot’ nights per year increased especially in September-
November
Rainfall
• Met station data show no statistically significant trends since 1960
• More rainfall occurring in heavy events
Climate Change
Image of the Future
Image of the Future
Climate Change Scenarios
Downscaling GCMs for impact / exposure analysis
• Use ensembles of “equally-likely” combinations of climate model + emissions scenario mean response and s.e. of response
• Downscale spatially, from 2° lat-long grids to a more useful resolution (e.g. 9-km grids)
• Downscale temporally from long-term climatology to characteristic daily weather data
Use MarkSim as a GCM downscaler: difference interpolation + stochastic downscaling + weather typing
Generate exposure indicators based on daily data
Future Climate Trends in East Africa
Different climate models project different trendsTemperature• Mean annual temperature may increase 1.0 - 2.8°C by the 2060s, and 1.3 -5.5°C by the 2090s• Models agree on increases in frequency of ‘hot’ days and nights• Models agree on decreases in frequency of ‘cold’ days and nights (these essentially disappear by the 2090s)
Precipitation• Most models indicate increases in annual rainfall in northern part of EA (up to 48% by the 2090s), and more in heavy events• Projected increases largest in October-December (up to 49 m per month) but this depends upon El Niño. Possible drying in June to August.
Changes in variability• Variability projected to increase, butare few details• Wide disagreement in projected changes in El Niño events (and hence OND)
Changes in maximum temperature
Changes in growing periods
Climate change exposure: changes in rain per rainfall event
Ericksen et al, 2011
Adaptation to climate change
• More than just buffering against vulnerability • Shifting strategies in face of changes (with no
precedent) but continuing to develop• Climate “smart” agriculture
– Resilience to shocks– Greater resource use efficiency
• Also, avoidance of negative feedbacks or “mal-adaptation”, including increased inequity
Adaptive capacity
• More forward looking and pro-active than coping
• Ability to change or reorganize strategies to diminish risk and prepare for new ones
• Depends upon– Resources and ability to access and use them– Removal of external constraints to adapt – Free flow of information
Adaptation research priorities• What are people’s NEEDS for rainfall to
support their livelihoods?• What innovations can we support NOW?• Support “no regrets” options• Constraints on adaptive capacity.. E.g.
• Lack of safety nets• Markets • Land tenure
• SCENARIOS as a planning tool
SCENARIO STORY LINES Millennium Ecosystem Assessment
Source: Millennium Ecosystem Assessment (2006)
Order from Strength
Adapting Mosaic
Global Orchestration
TechnoGarden
Globalization Regionalization
World DevelopmentEn
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Proa
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