1 / 1

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

Action ES0601 “HOME” ADVANCES IN HO MOGENISATION ME THODS OF CLIMATE SERIES. Participating countries: 26 european countries+ 2 non-COST: Andorra, Australia Chair of the Action: Olivier MESTRE, FR, olivier.mestre@meteo.fr COST Science Officer: Carine PETIT, cpetit@cost.esf.org.

Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Action ES0601 “HOME” ADVANCES IN HOMOGENISATION METHODS OF CLIMATE SERIES • Participating countries: 26 european countries+ 2 non-COST: Andorra, Australia • Chair of the Action: Olivier MESTRE, FR, olivier.mestre@meteo.fr • COST Science Officer: Carine PETIT, cpetit@cost.esf.org homogenization.org 1910  2008 • 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). 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 2 • WG 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. Raw series ▼ Homogenised series • Working Group 3 • WG 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 4 • WG 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. Objectives: 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 • Working Group 5 • WG leader: To be defined • SOFTWARE 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

More Related