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Identification of cc hot spots and risks in specific regions RRC FUMG
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Hot-spots & recent change
Identification of climate change hot spots and risks in specific regions, particularly Minas Gerais
PS Baker
R Ruiz
Belo Horitonte, 9th September 2013
How do we know what is happening? At the farm/district level?
• We know the climate is changing globally
• But we don’t know how this is manifesting itself at the local level – there are major regional variations
• We have climate maps that project future climate change – global, regional, some for coffee – up to 2050, 2100
• These are important for strategic understandings
• At a local level however these are not enough for extensionists and the many farmers who are facing difficulties now
• It’s a problem for the c&c initiative, which is trying to identify and prioritize risks
• We cannot help all farmers everywhere prepare for all possible CC risks
• We have to focus
• To objectively quantify the present climate/weather situation locally as much as possible
How do we know what is happening? At the farm/district level?
Example: E Africa projected to get wetter
• IPCC 2007 Projections for 2080-2099
But in reality it has been getting drier (Funk et al USGS)
Future rainfall is especially a problem
• We know it will get warmer
• But precipitation is much less certain for any given locality
– Wetter?
– Drier?
– Both (at different times of the year or longer period)?
• Very difficult to approach farmers about future flood risks if their recent experience is drought
Dealing with uncertainty
• What we need are accurate indications of how things have been changing in the recent past
• We use this as a guide to the present and the near future (and compare it with models)
• There is no ideal solution, but we believe it to be the best strategy
• But we have a practical problem
User-friendly historical weather data is mostly lacking!
• We need easy to understand maps that show coffee-relevant met. data
– E.g. to indicate zones getting drier
– E.g. zones where maximum temperatures are getting higher
• This sort of data does not exist – it’s a major failing – agrometeorology is not user-friendly
• So we are having to do it ourselves
• I.e.: turning data into info & knowledge
So we commissioned a study Ramiro Ruiz (Uni Belo Horizonte)
• Meteorological data used from 79 stations and 264 rain gauge locations, from 1960 – 2011
• Quality control procedures included: – Screening to identify erroneous data (e.g. Tmin > Tmax,
negative precipitation, etc.).
– Identification of temperature outliers using standard deviation thresholds.
– Statistical gap-filling of missing temperature data
– Homogeneity tests to detect data incontinuities
So we commissioned a study Ramiro Ruiz (Uni Belo Horizonte)
• Minas Gerais Jan-Mar rainfall (mm)
• 1961-1980
Rain mm
So we commissioned some work Ramiro Ruiz (Uni Belo Horizonte)
• Minas Gerais Jan-Mar rainfall (mm)
• 1981 – 2011: Getting drier in NE of Minas
Rain mm
MG – temperature
• Mean max temp for Sep- Nov (a critical period for flowering (get increasing flower abortion > 32°C)
T mean max
MG – temperature rises
• Mean max temp for Sep- Nov (a critical period for flowering (get increasing abortion > 32C)
T mean max
MG – temperature rises
• Mean max temp for Sep- Nov (a critical period for flowering (get increasing abortion > 32C)
• Getting hotter in north MG
T mean max
1995 coffee production
2011
For the first time…
• We have a simple visual way of seeing recent CC – and we think this is the best way to orient adaptation options
T mean max
Absolute maximum temperatures (Tmax) Statistically significant increases over MG
• Significant positive trends for the annual count of days with Tmax greater than 32oC (SU32).
• Stations at the southern region had a 5.56 (± 2.9) days per decade increase
• Zona da Mata (2.35 ± 1.8 days per decade ) at Caratinga and Viçosa). Filled triangle = significant
increase in Tmax
Daily temperature range Has been linked to coffee quality
• DTR = Monthly mean difference between Tmax and Tmin
• A mixed picture, but going up in Sul de Minas
Filled red triangles = significant increases
Signs of heavier rainfall events in parts of SW MG
• R50mm: annual count of days when precipitation greater than 50mm
Filled red triangles = significant increases
Annual water deficit in Minas Gerais 1960-1985 and 1986-2011 periods
1960 -1985
Annual water deficit in Minas Gerais 1960-1985 and 1986-2011 periods
1986 -2011
Mean annual water deficit by region in 1960-1985 and 1986-2011 periods
-40.4 mm -51.2 mm
-85.8 mm -103.1 mm
-183.5 mm -249.1 mm
-195.8 mm -270.5 mm
Summary
• This practical, user-friendly but science-based approach can give us some insight into local, recent climate change
• Especially where it coincides with model projections, it gives us considerable confidence to develop long-term strategies and help farmers make the right adaptation decisions (short to long term)
• We think this is the best way to guide us about what tools to use and where
• It is an approach that we would like to develop in all coffee-growing countries