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Climate Forecasting Unit
Prediction of climate extreme
events at seasonal and
decadal time scale
Aida Pintó Biescas
Climate Forecasting Unit
Outline
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Introduction
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Methodology
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Data description
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Methods
•
Results
•
Future work
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Near term work
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Long term work
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Climate Forecasting Unit
Outline
•
Introduction
•
Methodology
–
Data description
–
Methods
•
Results
•
Future work
–
Near term work
–
Long term work
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Climate Forecasting Unit
Introduction
Scenarios described by the Intergovernmental Panel on Climate Change, IPCC
(Solomon et al., 2007), says that climate change will lead by the end of the
century to changes in the frequency and intensity of extreme events such as
tropical cyclones, heavy rainfall and droughts
Lack of information (when, where, frequency, intensity,…)
Need to forecast extreme events taking into account interannual variability and the impact of
the anthropogenic climate change
Analysis of the forecast quality of seasonal and decadal climate predictions
Predicting evolution of extreme event frequency, duration and intensity and application climate
forecast information in a climate services context Integrate climate information in
decision making processes.
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Climate Forecasting Unit
Introduction
Thesis main objective:
Provide a synthesis of the forecast quality of seasonal-to-decadal climate predictions for different
types of extreme climate events, performed with both global dynamical and statistical models
General objectives:
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To study the sources of predictability and the forecast quality using state-of-the art forecast
systems for extreme precipitation, temperature and drought events, and the frequency of North
Atlantic tropical cyclones , at seasonal-to-decadal time scales.
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Develop methods to communicate the results of the predictive climate forecast information, in the
context of a climate service for the insurance and renewable-energy sectors.
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Climate Forecasting Unit
Outline
•
Introduction
•
Methodology
–
Data description
–
Methods
•
Results
•
Future work
–
Near term work
–
Long term work
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Climate Forecasting Unit
Methodology
MODEL DATA: ENSEMBLES prediction system
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Atmospheric data from daily seasonal hindcasts of the ENSEMBLES Stream 2
experiment.
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Precipitation and temperature daily data for five models contributing to the multimodel:
- ECMWF's IFS/HOPE
- UK Met Office's HadGEM2
- Météo-France's ARPEGE/OPA
- INGV's ECHAM5/OPA
- ifM Kiel's ECHAM5/OM1
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9 members each
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Seasonal forecasts (hindcasts) starting every year since 1960 until 2005 for four
different start dates (the first of February, May, August and November)
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Climate Forecasting Unit
Methodology
REFERENCE DATA:
ECMWF Interim Re-analysis (ERA Interim) Daily Atmospheric Data Sets
•Daily gridded reanalysis dataset for precipitation and near surface temperature.
•Period 1979-Now (uploaded monthly)
•Resolution 0.75º x 0.75º
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Methodology
Climate Forecasting Unit
IPCC 2001 definition of extreme event:
“An extreme weather event is an event that is rare within its statistical reference
distribution at a particular place. Definitions of "rare" vary, but an extreme weather
event would normally be as rare or rarer than the 10th or 90th percentile.”
Extreme indices:
• 90th and 10th percentile for Tº and P
• Days of extreme precipitation/temperature  nº
of days with precipitation/temperature > 90th
percentile of the seasonal climatology
• Frost days (nº of days with Tº< 0ºC )
Annual , seasonal and monthly analysis
for:
• All globe
• Single regions
• Reproduction of important extreme past events
• Heavy precipitation days (nº of days with
P>10mm/day)
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Climate Forecasting Unit
Methodology
Current work:
- Generating netCDF files with R for the extreme indices obtained. Variables: Precipitation and
near-surface temperature.
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For observations
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For all the 5 systems from ENSEMBLES
- Objective: Open the files with CFU_load to make the calculations, using common diagnostics
tools:
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Climatologies for both model and observations
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Correlations between model-observations
- For different systems
- For different star dates and forecast times
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Study of single regions and periods:
- Warm season  August: Floods, droughts and heat waves
- Cold season  Winter time: Floods, droughts and cold waves
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Climate Forecasting Unit
Outline
•
Introduction
•
Methodology
–
Data description
–
Methods
•
Results
•
Future work
–
Near term work
–
Long term work
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Climate Forecasting Unit
Results
Preliminary results
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Results
Climate Forecasting Unit
Preliminary results
ºC
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Climate Forecasting Unit
Outline
•
Introduction
•
Methodology
–
Data description
–
Methods
•
Results
•
Future work
–
Near term work
–
Long term work
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Climate Forecasting Unit
Future work
Near term work
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Verification of the results obtained so far using different verification tools
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Continue working on the ENSEMBLES data, adapting and optimizing scripts to be able to deal
with all the variables needed for the analysis of extreme events
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Formulation of probability forecasts for extreme precipitation and temperature and assessment
of their forecast quality.
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Prepare the structure of an article to document the expected results and a one-page
introduction to this paper with the necessary bibliography.
Long term work
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Preparation of promotional material that describes the basis of seasonal and decadal climate
prediction and its potential applications in the insurance sector.
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Submit to a scientific journal a first publication with the results obtained so far on the prediction
of extreme seasonal precipitation and temperature.
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Downloading new data from wind and repeat the same steps done for precipitation and
temperature.
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Definition of a North Atlantic tropical-cyclone frequency methodology based on large-scale
parameters and formulation of probability forecasts of the North Atlantic tropical cyclone
frequency.
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Climate Forecasting Unit
Thanks
Gràcies
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