COSTOC Olivier MestreMétéo-FranceFrance Ingebor AuerZAMGAustria Enric AguilarU. Rovirat i VirgiliSpain Paul Della-MartaMeteoSwissSwitzerland Vesselin AlexandrovNIMHBulgaria Sylvie JourdainMétéo-FranceFrance ADVANCES IN HOMOGENISATION METHODS OF CLIMATE SERIES: AN INTEGRATED APPROACH

COSTOC Homogenisation : WHY? Exemple of PAU-UZEIN temperatures Juin 1912 PAU-LESCAR (EN)2005 PAU-UZEIN (AERO)

COSTOC Station Silistra

COSTOC Station Dobrich

COSTOC Anomalies of annual minimum temperature in Kjustendil (raw data)

COSTOC Raw series of annual Maximum Temperatures (TX) PAU-UZEIN

COSTOC Homogenisation of Pau Maximum Temperatures « before »« after »

COSTOC Decomposition of climatological series

COSTOC 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

COSTOC Two problems DETECTION OF SHIFTS CORRECTION OF SHIFTS

COSTOC Many solutions ! DETECTION Visual, Craddock test, Student t-test, Likelihood ratio test (SNHT), Potter test, Bayesian procedures, Local contrast test, Pettitt test, penalized likelihood, MASH… CORRECTION Composite reference series, interpolated reference series, multiple non-homogeneous series (MASH), ANOVA (Mestre)…

COSTOC Statistical problems Related to detection power and level of the procedures, which are the best ones? Related to correction how to ensure unbiased corrections?

COSTOC 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?

COSTOC 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

COSTOC 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.

COSTOC 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

COSTOC Is this ambitious? YES

COSTOC 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

COSTOC Is this TOO Ambitious? NO

COSTOC 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

COSTOC Structure of the proposal Working groups WG1 inventory WG3 Correction WG2 Detection WG4 Daily values WG5 Implement Benchmark Report Method Final report Software

COSTOC Dissemination plan Mailing list: Web site: domain name « homogenisation.org » is available, with free software and documentation Publications Workshops Training sessions (ENM)

COSTOC 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

COSTOC Benefits Links to European projects : CIRCE, MACE, ECA&D… Economical impacts: risk assessment (extremes: insurance companies) Calibration of weather derivatives

COSTOC 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

COSTOC Conclusion Many procedures Few intercomparisons Daily data correction has to be developed  Need of a COST concerted Action