SUMMER SCHOOL: CLIMATE CHANGES IN THE MEDITERRANEAN AREA Maurizio Maugeri Istituto di Fisica Generale Applicata – via Celoria 16 – Milano Istituto di Scienze.
Presentation on theme: "Tarragona – November 28th, 2007"— Presentation transcript:
1 Tarragona – November 28th, 2007 DATA AND METADATA FOR THE CENTRAL PART OF THE MEDITERRANEAN BASIN: LESSONS FROM THE CLIMAGRI PROJECTMaurizio MaugeriIstituto di Fisica Generale Applicata – via Celoria 16 – MilanoIstituto di Scienze dell'Atmosfera e del Clima – via Gobetti BolognaTarragona – November 28th, 2007
2 Italy has a very important role in the development of meteorological observations Invention of some of the most important meteorological instruments (thermometer, barometer).Establishment of the first network of observations (rete del Cimento, set up by Galileo’s scholars).The strong Italian presence in the development of meteorological observations is also testified by six stations that have been in operation since the eighteenth century (Bologna, Milan, Rome, Padua, Palermo and Turin) and other 15 stations where observations started in the first half of the nineteenth century (Aosta, Florence, Genoa, Ivrea, Locorotondo, Mantua, Naples, Parma, Pavia, Perugia, Trento, Trieste, Udine, Urbino and Venice).
3 As a consequence, a heritage of data of enormous value has been accumulated in Italy over the last three centuries
4 This heritage has been known for a long time and many attempts have been made to collect data into a meteorological archive…..Cantù V. and Narducci P. (1967) Lunghe serie di osservazioni meteorologiche. Rivista di Meteorologia Aeronautica, Anno XXVII, n. 2,Eredia F. (1908) Le precipitazioni atmosferiche in Italia dal 1880 al In: Annali dell'Ufficio Centrale di Meteorologia. Serie II, Vol. XXVII, anno 1905, Rome.Eredia F. (1919) Osservazioni pluviometriche raccolate a tutto l'anno 1915 dal R. Ufficio Centrale di Meteorologia e Geodinamica. Ministero dei Lavori Pubblici, Rome.Eredia F. (1925) Osservazioni pluviometriche raccolate nel quinquennio dal R. Ufficio Centrale di Meteorologia e Geodinamica. Ministero dei Lavori Pubblici, Rome.Mennella C Il Clima d'Italia. Napoli: Fratelli Conti Editori, 724 pp.Millosevich (1882) Sulla distribuzione della pioggia in Italia. In: Annali dell'Ufficio Centrale di Meteorologia. Serie II, Vol. III, anno 1881, Rome.Millosevich (1885) Appendice alla memoria sulla pioggia in Italia. In: Annali dell'Ufficio Centrale di Meteorologia. Serie II, Vol. V, anno 1883, Rome.Narducci, P., 1991: Bibliografia Climatologica Italiana, Consiglio Nazionale dei Geometri, Roma.
5 … however, in spite of the huge heritage of data and even if most records were subjected to some sort of analysis, until a few years ago only a small fraction of Italian data was available in computer readable formArchivio delle serie secolari UCEA - Anzaldi C., Mirri L. and Trevisan V., 1980: Archivio Storico delle osservazioni meteorologiche, Pubblicazione CNR AQ/5/27, Roma.
6 Within this context, a number of projects where set up in Italy in the last 5 to 10 years to recovery as much as possible secular meteorological recordsThe activities can be clustered in two general classesProjects concerning single stationsHigh temporal resolution, complete metadata documentation, etc…Projects concerning national/regional networksLower temporal resolution, less metadata, etc…
7 …there is a lot of still unexploited information… Projects concerning single stations are particularly important for the records beginnig in the 18th centuryMilan: a 10-year project developedby Osservatorio Astronomico diMilano-Brera and Milan Universityallowed to recovery metadata anddaily T, P, R recordsPadova: as for Milan but activitiesperformed by Istituto di Scienzedell'Atmosfera e del Clima – sectionof PadovaTorino: as for Milan and Padovabut activities performed by SocietàMeteorologica ItalianaPalermo: recovery started later on;The activities are performed by Os.Astronomico. Available: metadataand daily R and T records.Bologna: as for Milan, Padova andTorino for the data after Stillin progress for the 18th century dataRoma: as for Milan, Padova andTorino for the data after Onlymonthly data for the 18th century…there is a lot of still unexploited information…Cloudiness, sunshine, vapour pressure, wind, etc…
8 Projects concerning national/regional networks Second part of the 1990s: the CNR project “Reconstruction of the past climate in the Mediterranean area” allowed the UCEA secular series data set to be updated, completed, and revised. In spite of significant improvements, the new data set had the fundamental limitation of very poor metadata availability. Moreover, the number of stations was still too low. So homogenisation could not be performed.Around 2000 a new research programme was established. It was initially developed within a national project (CLIMAGRI), then an extension of the activities was performed within some other projects.Thanks to the availability of resources from more projects and to additional results from other projects, the initial goal of homogenising the existing records was extended and the construction of a completely new and larger set of data and metadata was also planned.
9 The new dataset of Italian secular records Meteorological variablesAir Temperature (minimum, mean, maximum)PrecipitationAir PressureCloud CoverOther dataTemporal resolutionDaily/Monthly
14 The new Italian dataset: other variables … the activities are still in progress (e.g. EU project ALP-IMP). They concern air pressure, cloud cover, humidity and snow…AIR PRESSURE(secular records)CLOUD COVER(secular records)HUMIDITY (i.e. dry / wet temperatures)daily data2 recordsSNOW (HS: snow at ground; HN: fresh snow)daily / monthly dataAbout 15 records of northern ItalyPERIOD:All variables available in digital formatItalian Air Force data-set.
16 The new Italian dataset: metadata Metadata collection was performed with two main objectives:to understand the evolution of the Italian meteorological networkto reconstruct the “history” of all the stations of the data-set.The research on the history of the single stations was performed both by analysing a large amount of grey literature and by means of the UCEA archive.All information was summarized in a card for each data series.Each card is divided into three parts. In the first part all the information obtained from the literature is reported. In the second part there are abstracts from the epistolary correspondence between the stations and the Central Office. In the third part the sources of the data used to construct the record are summarized.For full details; see CLIMAGRI project WEB site (www.climagri.it)
17 The new Italian dataset: quality and homogeneity issuesThe problem: the real climate signal, that we try to reconstruct studying long (secular) records of meteorological data, is generally hidden behind non-climatic noise caused by station relocation, changes in instruments, changes in observing times, observers, and observing regulations, algorithms for the calculation of means and so on. climatic time series should not be used for climate research without a clear knowledge about the state of the data in terms of quality and homogeneity.
18 QualityClassification of the institutions (Observatory, high school, etc…) Data sources (hand-written original observations; year books; pre existing data sets, etc…) Time resolution (yearly, monthly, daily, etc…) Comparison with other records
19 “Signals” in the records of meteorological data HomogeneityClimate variationsMeasuring problems“Signals” in the records of meteorological dataMeasuring problemsRelocationsInstrumental errors (changes of the instruments and/orrecalibrations)Observation methodsScreeningsChanges in the environment around the station
20 The problem is not easy to manage Meteorological series can be tested for homogeneity andhomogenised both by direct and indirect methodologies.The first approach is based on objective information thatcan be extracted from the station history or from someother sources, the latter uses statistical methods,generally based on comparison with other series.Both direct and indirect methodologies have severe limits
21 Direct methodologies are not easy to use as: 1) it is generally very difficult to recover complete information on the history of the observations (metadata); 2) even if available, metadata hardly give quantitative estimates of the inhomogeneities in the measures. Also indirect methodologies have important deficits: 1) they require some hypothesis about the data (e.g. homogeneous signals over the same region); 2) inhomogeneities and errors are present in all meteorological series, and so it is often difficult to decide where to apply corrections and, when the results are not clear there is a high risk of applying subjective corrections.
22 How to overcome the intrinsic limit of indirect homogenisation methods is, at present, still an open question.The possibilities range from homogenising all suspect periods, to correcting the series only if the results of the statistical methods are very clear and also supported by metadata.
23 So, at present, an universal approach to manage the problem is lacking. Our approach:Collecting as much metadata as possible;Performing a first homogenisation by means of direct methologies;3) Performing final homogenisation by means ofindirect methologies
24 Basic problem: what is to correct? a) All the periods given by statistical methodsb) Only the periods for which there is evidence in metadataThe problem is openOur methodology:Wide use of statistical methodsCritical analysis on the light of metadataThe CLIMAGRI project
25 Important open question: trends critically depend on the methods used to homogenise the data North Italy long-term temperature evolution (filtered curves) in the period according to Brunetti et al. (2000) and Boehm et al. (2001).Adapted from: Brunetti, M., Buffoni, L., Maugeri, M., Nanni, T., 2000: Trends of minimum and maximum daily temperatures in Italy from 1865 to Theor. Appl. Climatol., 66, and Böhm, R., Auer, I., Brunetti, M., Maugeri, M., Nanni, T., Schöner W., 2001: Regional Temperature Variability in the European Alps from homogenised instrumental time series. Int. J. Climatol., 21,
26 Important open question: trends critically depend on the methods used to homogenise the data Long-term evolution of summer temperatures in the period according to Auer et al. (2007) and Brunetti et al. (2006).