COSTOC-2006-32 Olivier MestreMétéo-FranceFrance Ingebor AuerZAMGAustria Enric AguilarU. Rovirat i...
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Transcript of COSTOC-2006-32 Olivier MestreMétéo-FranceFrance Ingebor AuerZAMGAustria Enric AguilarU. Rovirat i...
![Page 1: COSTOC-2006-32 Olivier MestreMétéo-FranceFrance Ingebor AuerZAMGAustria Enric AguilarU. Rovirat i VirgiliSpain Paul Della-MartaMeteoSwissSwitzerland Vesselin.](https://reader036.fdocuments.net/reader036/viewer/2022081603/56649e9f5503460f94ba2015/html5/thumbnails/1.jpg)
COSTOC-2006-32
Olivier Mestre Météo-France FranceIngebor Auer ZAMG AustriaEnric Aguilar U. Rovirat i Virgili SpainPaul Della-Marta MeteoSwiss SwitzerlandVesselin Alexandrov NIMH BulgariaSylvie Jourdain Météo-France France
ADVANCES IN HOMOGENISATION METHODS OF CLIMATE SERIES:
AN INTEGRATED APPROACH
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COSTOC-2006-32
Homogenisation : WHY?Exemple of PAU-UZEIN temperatures
• Juin 1912 PAU-LESCAR (EN) • 2005 PAU-UZEIN (AERO)
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COSTOC-2006-32 Station SilistraStation Silistra
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COSTOC-2006-32 Station DobrichStation Dobrich
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COSTOC-2006-32
Anomalies of annual minimum temperature in Anomalies of annual minimum temperature in Kjustendil (raw data)Kjustendil (raw data)
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COSTOC-2006-32
Raw series of annual Maximum Temperatures (TX) PAU-UZEIN
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COSTOC-2006-32
Homogenisation of Pau Maximum Temperatures
• « before » • « after »
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COSTOC-2006-32
Decomposition of climatological seriesDecomposition of climatological series
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COSTOC-2006-32
Usual method: relative homogeneity
PRINCIPLE : removing the climatic signal to put into evidence artificial shifts in the series
minus
Tested series
Reference series
COMPARISON
series
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COSTOC-2006-32
Two problems
• DETECTION OF SHIFTS
• CORRECTION OF SHIFTS
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COSTOC-2006-32
Many solutions !
• DETECTIONVisual, Craddock test, Student t-test, Likelihood ratio test (SNHT), Potter test, Bayesian procedures, Local contrast test, Pettitt test, penalized likelihood, MASH…
• CORRECTIONComposite reference series, interpolated reference series, multiple non-homogeneous series (MASH), ANOVA (Mestre)…
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COSTOC-2006-32
Statistical problems
• Related to detection
power and level of the procedures, which are the best ones?
• Related to correction
how to ensure unbiased corrections?
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COSTOC-2006-32
Practical problems
• Data requirements, depending on parameters: spatial correlation
• Nature of correction: raw monthly estimated coefficients, annual coefficients?
• What about close shifts?• What about gaps?• Trust metadata or statistics?• Trust relative homogenisation or parallel measurements?
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COSTOC-2006-32
Why COST?
• Many procedures, many authors, that might lead to different results
• Few intercomparisons
COST is an ideal platform for the exchange of experiences, harmonisation of approaches and
the development of joint methods
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COSTOC-2006-32
Objectives
To achieve a general method for homogenising climate and environmental datasets
• Provide practical rules for the implementation of homogenisation.
• Provide tools for comparison and evaluation of different methods.
• Analyse the strengths and weaknesses of the methods for different applications.
• Provide methods for evaluating uncertainties resulting from homogenisation.
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COSTOC-2006-32
Scientific Program
• Inventory of existing detection and correction methods• Compilation of a benchmark dataset to be used across the
Action• Selection, comparison and evaluation of existing detection
methods• Selection, comparison and evaluation of existing
correction methods• Documentation of practical recommendations• Selection, comparison and evaluation of existing
correction methods for daily data• Presentation and release of the new common method
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COSTOC-2006-32
Is this ambitious?
YES
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COSTOC-2006-32
Why ?
• Because we want to make a synthesis of the most appropriate methods, based on objective comparisons and sharing of practical experiences
• Because we feel that the corresponding software has to be released – just editing recommandations would be useless
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COSTOC-2006-32
Is this TOO Ambitious?
NO
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COSTOC-2006-32
Why ?
• We have a clear view of what has to be done• Benchmark dataset conception (simulated and
real cases)• Coding and testing the procedures is rather easy,
and may be done by students• To test real cases and edit practical
recommandations, we get together highly trained climatologists
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COSTOC-2006-32
Structure of the proposal
• Working groups
WG1inventory
WG3Correction
WG2Detection
WG4Daily values
WG5Implement
Benchmark
Benchmark
Benchmark
Report
Report
Report
Report
Report
Method
Final report
Software
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COSTOC-2006-32
Dissemination plan
• Mailing list: [email protected]
• Web site: domain name « homogenisation.org » is available, with free software and documentation
• Publications
• Workshops
• Training sessions (ENM)
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COSTOC-2006-32
Benefits
• Standardisation of homogenisation procedures in Europe
• Results of climate studies based on homogenised series could be easily compared
• Provide a benchmark dataset that can be used to test future methods
• Significant advances in daily data homogenisation• All this will result in an increased confidence in
European (and global) assessments of mean and extreme Climate Change
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COSTOC-2006-32
Benefits
• Links to European projects : CIRCE, MACE, ECA&D…
• Economical impacts: risk assessment (extremes: insurance companies)
• Calibration of weather derivatives
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COSTOC-2006-32
Participants
• From 17 countries
• Around 60 participants– 60% plan to participate actively to the Action– 40% are mainly interested by the results– 45% may have students working on the Action
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COSTOC-2006-32
Conclusion
• Many procedures
• Few intercomparisons
• Daily data correction has to be developed
Need of a COST concerted Action