Action ES0601“HOME” ADVANCES IN HO MOGENISATION ME THODS OF CLIMATE SERIES

European Cooperation in the field of Scientific and Technical Research

COST is supported by the EU RTD Framework Programme

ESF provides the COST Officethrough an EC contract

ESSEM

www.cost.esf.orgAction ES0601 “HOME”

ADVANCES IN HOMOGENISATION METHODS OF CLIMATE SERIESParticipating countries: 26 european countries+ 2 non-COST: Andorra, Australia

Chair of the Action: Olivier MESTRE, FR, olivier.mestre@meteo.frCOST Science Officer: Carine PETIT, cpetit@cost.esf.org

The main objective of the Action is to achieve a general method for homogenising climate datasets

The method will be an improved synthesis of the most effective statistical procedures for detection and correction of Essential Climate Variables at different space and time scales_________________________________

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

Provide an evaluation of specific artificial changes, such as the impact of urban effect on temperature series for example

Relocations, changes in the instrumentation of the weather stations often have a large impact on the data quality

Homogenisation procedures aim at detect and correct the effect of such changes.

In this example, we present the impact of homogenisation of Pau maximum temperature series.

From 1880 to now, the series suffered from major changes, as illustrated on pictures, taken in 1910 and 2008. The resulting raw series is unreliable. An homogenisation procedures allowed to detect and correct changes in Pau series.

Working Group 1 WG leaders: Enric Aguilar (ES), Victor Venema (DE)INVENTORY OF EXISTING METHODS – CONSTITUTION OF A BENCHMARK DATASET

• Survey groups or individuals using homogenisation techniques. Search the literature. Classification of the methods according to: statistical nature, data requirements, time scope (annual, monthly, daily).

• Compilation of the Benchmark Dataset: catalogue of expected inhomogeneity situations, list of suitable real datasets, selection of real datasets, creation of simulated time series reproducing expected problems (surrogates).

Working Group 2WG leaders: Tamas Szentimrey (HU), Olivier Mestre (FR)DETECTION METHODS

• Creation of software to test the different detection methods. Test runs over the benchmark-dataset: simulated series, practical real cases, ranking of the methods.

• Detection principles, absolute vs relative methods, practical recommendations.

Working Group 5WG leader: To be definedSOFTWARE IMPLEMENTATION AND DISSEMINATION

• Implementation of “R” code of the selected methods.• Dissemination of the software, training schools organization.

Main Achievements:

At the end of 1st year of the Action

A detailed bibliography has been achieved

Benchmark dataset has been created, with both simulated and real cases

An intercomparison study of 22 detection procedures has been achieved

The impact of three different homogenisation procedures on Catalan temperature series has been achieved

A comparison of two daily correction procedures has started

homogenization.org

Objectives:

Working Group 3WG leader: Anders Grimvall (SW)CORRECTION METHODS (MONTHLY TO ANNUAL TIME SCALES)

• Evaluation and ranking of correction methods on benchmark dataset.• Formulation of practical recommendations for correction.

Working Group 4WG leader: Petr Stepanek (CZ)CORRECTION METHODS (DAILY TIME SCALE)

• Evaluation and ranking of correction methods on daily benchmark dataset.• Formulation of practical recommendations for correction of daily climate series.

1910 2008

Raw series

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Homogenised series