CLIVALP

Klimawandel Thematik

Abk.

CLIVALP

Themenbereich

Klimawandel, Klimafolgenforschung

Status

Abgeschlossenes FWF Projekt, P 15076-N06

Zusammenfassung

Die Alpenregion mit ihrem nahezu einzigartigen Potenzial an Klimadaten bezüglich Länge, räumlicher Auflösung und vertikaler Erstreckung, eignet sich hervorragend, Forschung über Klimavariabilität und Klimaschwankungen durchzuführen. Das Projekt CLIVALP – CLImate Variability Studies in the ALPine Region“- nützte dieses bisher nicht ausreichend beachtete Potential unter dem Motto „aus der Vergangenheit für die Zukunft lernen. Die im Rahmen des Projekts geschaffene HISTALP Datenbank (Klimadatenbank für die Alpenregion für historische instrumentelle multi-elementare Zeitreihen) ermöglichte bereits eine Reihe von Studien in diesem Sinne, stellt aber auch für die Zukunft eine bisher nicht existierende Datenbasis in monatlicher Auflösung für Klima- und Klimafolgenforschung dar. Mit Hilfe von 72 Luftdruck-, 131 Temperatur-, 192 Niederschlags-, 55 Sonnenscheindauer und 66 Bewölkungszeitreihen ermöglicht HISTALP die Betrachtung des Klimas und seiner Variabilität als Einheit – als Zusammenspiel mehrerer Klimaparameter. Die längsten Luftdruck- und Temperaturreihen reichen bis 1760 zurück, jene des Niederschlages bis 1800. Somit reicht HISTALP bis in die „frühinstrumentelle Klimaperiode“ zurück.

CLIVALP brachte auch neue Erkenntnisse bezüglich möglicher zukünftiger Änderungen im Sinne der Klimafolgenforschung. Sensitivitätsanalysen wurden explizit für die Änderung der Frosthäufigkeit als Folge einer mittleren Temperaturänderung über nicht lineare Beziehungen aufgezeigt. Eine zukünftige Temperaturzunahme von 1 Grad C würde jährlich um bis zu 15 Tage weniger Frost bedeuten, regionale Unterschiede und ein überlagerter Jahresgang lassen aber keine Pauschalaussagen zu. In Österreich am stärksten betroffen wären im Winter die Niederungen vom Innviertel, entlang der Donau bis zum Weinviertel sowie das Grazer Becken. Aber auch im Sommer würde es eine beträchtliche Frostreduktion geben, allerdings wären dann nur die hochalpinen Regionen betroffen.

Die mehr als 200jährigen HISTALP Zeitreihen gestatten es darüber hinaus, mit Hilfe objektiver Verfahren längere Perioden mit signifikanten klimatischen Abweichungen herauszufiltern. Diese „auffälligen Perioden“ bilden sich als unübersehbare Folgen der Klimaänderung ab, und beeinflussen etwa Gesellschaft, Landwirtschaft und schlagen sich auch in sichtbaren Landschaftsveränderungen nieder. So etwa im Zustand der hochalpinen Gletscher. HISTALP Daten erlauben es, Gletschervorstöße bzw. Gletscherrückzüge durch die Variabilität von Lufttemperatur, Niederschlag, Sonnenscheindauer und Bewölkung zu erklären.

Als ein weiteres wichtiges Ergebnis von CLIVALP kann sein Beitrag zum Verstehen einzelner Effekte externer Antriebe auf das europäische bzw. alpine Klima gewertet werden, durch Kombination von HISTALP Daten mit Ensemble Simulationen durchgeführt mit Hilfe eines gekoppelten GCM, angetrieben durch verschiedene externe Parameter. Diese hochwertigen und kostenintensiven Simulationen wurden vom GKSS-Forschungszentrum Geesthacht (BRD) zur Verfügung gestellt. Für diese „auffälligen Perioden“ konnten anhand der Simulationen die Temperaturverhältnisse zufriedenstellend reproduziert werden, verschiedene Zirkulationsmuster konnten für die entweder zu warmen oder zu kühlen Perioden erkannt werden. Die erzielten Resultate stehen in gutem Zusammenhang mit unserem Verständnis der atmosphärischen Zirkulation.

The Alpine region offers a unique potential of historical climate data regarding temporal lengths, spatial resolution, and vertical extension. This potential has not been exploited yet, hence CLIVALP – CLimate Variability studies in the ALPine region – took the initiative to make use of it guided by the watchword: “Learning from the Past for the Future”. The HISTALP database (Historical Instrumental Climatological Surface Time series for the Alpine region), which has been developed and systematically implied within CLIVALP, has already formed an ideal basis for investigations of climate and its variability and it will certainly continue to satisfy this concern in the future. It is a homogenized, multi-elemental database (72 series of air pressure, 131 of temperature, 192 of precipitation, 55 and 66 of sunshine and cloudiness, respectively) reaching back into the early instrumental period and allowing for a large range of studies concerning Alpine climate. The longest temperature and air pressure series extend back to 1760, precipitation to 1800, cloudiness into the 1840s and sunshine into the 1880s.

CLIVALP assessed potential future changes of climate impact parameters via non linear relationships with temperature. Such sensitivity studies were highlighted considering frost frequency as example. A future temperature increase, for instance, of 1 K translates into a decrease of frost days per year, which can be, depending on location and season, as high as 15 days. During winter, for example, low elevated regions from Innviertel along the Danube valley to the Weinviertel and southwards to the Grazer Becken exhibit highest sensitivity values of over six days of frost reduction. In summer the affected regions are along the Alpine chain raising the matter of permafrost etc.

More than two centuries of high quality climate data also allowed for the detection of multi-annual to decadal periods showing significant anomalies for a large fraction of records. Such periods, called ‘outstanding’ have an impact on society, agriculture and leave their marks in the scenery as e.g. glacier advances or retreats. Actually, HISTALP data were used to explain glacial changes by the variability of air temperature, precipitation, sunshine, and cloudiness.

CLIVALP also contributed to understanding the effect of external forcings on European/Alpine scale climate. This was achieved by combining HISTALP and ensemble simulations, carried out with a coupled General Circulation Model, driven by different external forcings. These high standard and expensive simulations were provided by the GKSS Research Centre, Geesthacht. Based on outstanding periods we analyzed atmospheric circulation of those simulations that satisfyingly reproduced surface temperature conditions. Thereby it was possible to address different circulation modes to different warm and cool phases of outstanding periods. Results are regarded as promising and in agreement with the physical undwinter aerstanding of atmospheric circulation. Due to the larger sample size findings for nd the year as a whole are found to be as more reliable than those for summer.

Projektziele

  • · eine multi-elementare Betrachtung der Klimavariabilität unter Verwendung homogenisierter Langzeitreihen mit monatlicher Auflösung, Erweiterung der in Vorprojekten (ALOCLIM, ALPCLIM) erarbeiteten Datensätze um die Elemente Luftdruck, Sonnenschein und Bewölkung.
  • · eine detaillierte Analyse markanter Zeitabschnitte mit ausgeprägten Abweichungen im Scale von fünf bis 20 Jahren zum langjährigen Mittel, z.B. die zu warmen 1980er und 1990er Jahre, das Temperaturmaximum um 1950, die maritim geprägte Zeit um 1910, die kontinentale Phase um 1890, die Trockenzeit um 1860, die vulkangesteuerten kühlen Sommer 1813 bis 1817, die Warmzeit um 1800.
  • · die Analyse räumlicher (horizontaler und vertikaler) Unterschiede sowie der räumlichen Repräsentativität der homogenisierten Klimareihen von Luftdruck, Sonnenscheindauer und Bewölkung.
  • · Studien zur Reaktion einzelner Klimaparameter wie Niederschlag, Schnee etc. bei veränderten Temperaturgegebenheiten.
  • · das Erkennen von Zirkulationsmustern, die für die langfristige Klimaentwicklung in den Alpen bestimmend sind, auf der Basis der homogenisierten Luftdruckzeitreihen über den Alpen und aus vier Gebieten im Norden und Süden, sowie Westen und Osten Europas.
  • · ein Vergleich der alpinen Gitterpunkte (berechnet aus räumlich feinauflösenden Datensätzen) mit existierenden globalen Datensätzen, die für die Alpen in den meisten Fällen nicht hochauflösend genug sind.

Methodik

Alle CLIVALP Untersuchungen wurden anhand homogenisierter Klimazeitreihen, die die letzten 1 ½ bis 2 ½ Jahrhunderte überdecken, durchgeführt. Das Untersuchungsgebiet überdeckt die Alpen und seine Umgebung (Greater Alpine Region) im Bereich von etwa 4 bis 18 Grad E und 43 bis 49 Grad N.

Abwicklung

CLIVALP – under the philosophy of “Learning from the Past for the Future” contributed to the understanding of our past climate, to understand mechanisms of our recent climate by using historical data, and to estimate future climate developments via sensitivity functions. Therefore CLIVALP studies intended to investigate into regional Alpine climate features, into the sensitivity of climate parameters, into circulation patterns and into significant anomalies on a multi-annual to decadal time scale (special or outstanding periods).

The first few months (pre-project phase) were mainly devoted to systematic literature survey and first contacts to external project partners for data exchange and scientific collaboration. We soon came to know about the importance of the new developed HISTALP database – ensuring a combined acquisition and storing of data (original, homogenised) and metadata and avoiding different data versions from the various national and international project outcomes (e.g. Austrian ALOCLIM, EU funded ALP-CLIM, Italian Climagri and Reconstruction of the past climate in the Mediterranean area, Swiss NORM 90 and KLIMA90 etc.). In contrast to what has been proposed in the CLIVALP application form, we decided to update HISTALP every year, mainly to allow the inclusion of the latest weather events (e.g. flooding and heavy precipitation in summer 2002, heat waves and dry spells in summer 2003 etc.). HISTALP is entrusted in ZAMG’s care and will support scientific studies also in the future by means of:

  • · update of the existing data series by means of informal data exchange
  • · storage of new series (new elements, new stations) from future projects
  • · modification of HISTALP to allow handling for daily data as well

  • An essential not predictable support for CLIVALP came from the EU-funded project ALP-IMP (Multi-centennial climate variability in the Alps based on Instrumental data, Model simulations and Proxy data) in two aspects. The first one was a number of additional digitised data provided for HISTALP, the second one was the opportunity of collaboration with the Climatic Research Unit of the University of East Anglia (CRU).

    CLIVALP is indebted to GKSS (Institute for Coastal Research, GKSS Research Centre, Geesthacht, Germany) as well. Prof. Hans von Storch enabled and raised a cooperation between CLIVALP and the GKSS Research Centre.
  • HISTALP is a unique data set for the Greater Alpine Region (henceforce called GAR) with an extraordinary potential for climate and climate impact research. The area covered by HISTALP has an areal extent of approximately 724.000 km²,
     

    • · Reaching back until 1760, HISTALP is about 100 years longer than existing global datasets.
    • · It is a multiple data set covering a number of elements (air pressure, air temperature, precipitation, sunshine duration, cloudiness, and two humidity parameters for the eastern Alps)
    • · Its homogeneity has been attained by two approaches: mathematical testing and use of metadata
    • · Its spatial resolution exceeds those of global datasets
    • · It opens the possibility to investigate also in the vertical dimension of climate variability due series up to 3500 asl.

      A summarising table gives an overview of the numbers of available data, detected breaks, outliers and filled gaps.

    HISTALP database

     

     

    air pressure

    temperature

    precipitation

    sunshine

    cloudiness

    all

     

    no. of series

    72

    131

    192

    55

    66

    516

    series

    available data

    10215

    19312

    26063

    7886

    7669

    71145

    years

    mean length of series

    141.9

    147.4

    135.7

    88.8

    119.5

    137.9

    years

    detected breaks

    256

    711

    966

    366

    234

    2533

    breaks

    mean homogeneous sub-interval

    31.1

    22.9

    22.7

    11.6

    26.3

    23.4

    years

    detected real outliers

    638

    4175

    529

     

     

     

    outliers

    filled gaps

    4217

    12392

    14927

    2011

    3513

    37060

    months

    mean gap rate

    3.4

    5.3

    4.8

    2.1

    3.8

    4.3

    %



    Besides the station mode data HISTALP contains grid data in a resolution of 1 deg. longitude and latitude for the elements air pressure, air temperature and precipitation. For all elements regional mean series have been calculated and made available. PCA analyses applied to all elements allowed to define homogeneous regions.

    Figure 1: Leading horizontal climatological sub-regions of the Greater Alpine Region . Thin lines: Results of PCA (based on single element monthly anomalies) for P01air pressure, T01 air temperature, R01precipitation, SU1 sunshine, N01 cloudiness. Bold lines: The CRS (coarse resolution) compromise allowing for intra-elemental comparisons based on equal sub-regions for each climate element

    Table 2: Long-term annual climate trends in the coarse resolution subregions of the Greater Alpine Region in two 100-years, four 50years- and two (recent) 25years subperiods. Trends have been calculated as linear regression coefficients, each box shows the trends in geographical order, bold figures mark 90% significance according to Mann-Kendall trend test, all values are decade-1 (mean trends in units "per decade")

    SENSITIVITY STUDIES: Since the late 19th century global mean surface temperature has increased by approximately 0.6°C (comp. Table 2), whereas in the Alpine region this increase has been approximately twice as large. To assess potential effects of temperature growth within the Alpine Region, CLIVALP investigated also the linkages of secondary elements to monthly mean temperature. Secondary climate elements are also referred to as ‘frequencies of weather events’ such as the number of frost days, ice days, summer days, hot days within one month or the proportion of solid precipitation in total precipitation. Relationships between secondary climate elements and temperature cannot be linear as the mentioned frequencies are limited between ‘no day and all days´, whereas temperature is much more variable. Hence, we had to apply functions that map a variable range of values onto a limited domain (0 to 1). This can be achieved by e.g. tangens hyperbolicus (tanh) which is characterised by three free parameters defining (1) the range of the limited element, (2) the shift along the x-axis of the primary element and (3) the steepness of the curve. Such tanh functions have been adjusted over the CLINO period (1961-1990) to a dense network of about 500 stations in GAR. With other words, for every month from January to December we used tanh plus temperature to model the second order elements. A number of validation procedures have been applied to determine the models´ skills, which were assessed as reasonable. Then, the sensitivity of the secondary climatic elements to temperature variations has been calculated via the first derivate with respect to temperature. This involves the cosinus hyperbolicus describing the sensitivity of the secondary element to a 1 Kelvin temperature change. In the case of the second order elements "number of frost days" and "share of solid precipitation" the tanh-models showed best performances.

    The models can be applied to single sites but also to whole temperature maps. If regions are characterized by a certain temperature-gradient (e.g. Po Valley) sensitivity can be formulated in dependence on altitude by converting temperature into altitude.

    Figure 2: Maps showing the sensitivity of the number of frost days to a temperature change of 1K in Austria based on CLINO (1961-1990). The left panel shows the winter season (DJF) and the right panel the summer season (JJA)

    In winter areas below 500 m will be most affected. There, a temperature increase of 1 K is translated via the models into an average reduction of seasonal frost days for more than 4 days. Areas from low mountain level show no strong dependence of sensitivity on a 1 K temperature increase and regions located in the vicinity of the highest peaks show no dependence on an increase of 1 K. In summer most parts of the country turn out to be insensitive to a prospected temperature increase. However, sensitivity at high elevated areas across the Alpine chain reaches maximal values, which has the potential to cause significant changes regarding vegetation and permafrost.

    Besides the above applications the models can be further used to reconstruct time series of secondary elements into the past. Up to now we have done this for ‘number of frost days’. Original series of frost days are generally about 100 years shorter than mean temperature series (as they require measurements of maximum-thermometers), they are inhomogeneous (which is true for all long-term raw climate time series) and there are no common approved methods available to generate homogeneous historical time series of frost days. In order to overcome this lack of we have applied the calibrated and validated tanh functions to the historical, homogenized HISTALP temperature data set and reconstructed the past Alpine frost variability.

    Figure 3: Time series of reconstructed frost days. (a) for Brno (CZ) for October to April, (b) panel for Sonnblick (A) for May to September.

    OUTSTANDING PERIODS were defined as significant climatic anomalies from de-trended long-term series on multi-annual to decadal timescales. Temperature, reaching back to 1760 was used to identify such outstanding periods. Ten of them, regarded as most prominent, were further investigated. In this investigation we have studied not only all classical seasons (winter, spring, summer and autumn) but moving seasons as well. Moving seasons are consisting of three successional months (e.g. February-March-April). Some of the outstanding periods are found in all seasons, exhibiting the same feature, while others show opposite behaviours during summer and winter. Few of them occur only during a couple of seasons.

    Table 3. List of outstanding periods and seasons within these periods are detected. Emphasis is put on winter (DJF), summer (JJA) and year (YAR). Additional information referring to Alpine glacier behaviour is included as well.

    winter (DJF)

     

     no

    from-to

     

    seasons that exhibit this feature

    1

    1760-1783

    cool

    all year round, but in general somewhat shorter

    2

    1790-1795

    warm

    weak, all year round and more pronounced in summer, several evidences that Alpine glaciers retreated

    5

    1860-1872

    warm

    all year round but weak during some seasons; pronounced glacier retreats from LIA maximum extents

    6

    1887-1895

    cool

    to be found from OND till JFM (minimum in DJF), many Alpine glaciers advanced

    7

    1910-1924

    warm

    warm from NDJ to JFM but cool from JJA to SON, advancing glaciers

    8

    1935-1951

    cool

    to be found from OND till JFM (JJA-ASO: warm); embedded into a period (approx. 1930-1960) characterized by strongly retreating glaciers

    9

    1957-1972

    cool

    from NDJ till MAM; during most of the other seasons this period lasts even longer, advancing glaciers

     

    1990-now

    warm

    almost all year round; strongly retreating glaciers


    summer (JJA)

     

     no

    from-to

     

    seasons that exhibit this feature

    1

    1760-1775

    cool

    all year round

    2

    1792-1807

    warm

    all year round; more pronounced during the warm season. several evidences that Alpine glaciers retreated

    3

    1810-1820

    cool

    period from MJJ till ASO; Alpine glaciers strongly advanced towards their LIA maximum event

    5

    1856-1873

    warm

    almost all year round; pronounced retreat from LIA maximum glacier extents

    7

    1911-1924

    cool

    from JJA to SON and warm in winter; advancing glaciers

    8

    1942-1951

    warm

    period from MAM to ASO but cool during winter (NDJ, DJF); embedded into a period of strong glacier retreats

    9

    1956-1985

    cool

    the full period is to be found from about MAM to JAS and shorter ones all year round; up to 70% of the Alpine glaciers advanced

     

    1900-now

    warm

    almost all year round; strongly retreating glaciers


    year

     


     no

    from-to

     

    seasons that exhibit this feature

    1

    1760-1787

    cool

    all year round; partly for a shorter period

    2

    1791-1806

    warm

    all year round; sometimes weakly pronounced, several evidences that Alpine glaciers retreated

    3

    1809-1817

    cool

    during the summer-seasons; advancing glaciers

    4

    1821-1830

    warm

    all year round but very weak in some seasons (DJF, JFM, MJJ); several glaciers still advancing towards their LIA maximum

    5

    1860-1873

    warm

    all year round, but weakest for JFM and JJA, retreating Alpine glaciers

    8

    1945-1950

    warm

    period mainly during the summer-seasond; glaciers were retreating during this period

    9

    1956-1985

    cool

    all year round, most pronounced in summer glaciers were advancing

     

    1991-now

    warm

    all year round; strongly retreating glaciers


    Four outstanding periods lie within the early instrumental period. It is our understanding that these periods are detected here for the first time on the basis of a high quality dataset (HISTALP). Two of them in the very early period (2, 3) follow each other in direct succession. The former (around 1800) with high spring-summer temperatures is still a subject under discussion among instrumental- and proxy climatologists. It was followed by a sudden temperature decrease in the 1810s, which we regard as the most extreme "sudden climate event’ ever since 1760, which is also known as the ‘Volcanic Years without Summers". The deterioration of climate during this period has caused severe impacts on crop yield and massive glacier advances. Similarly, the following OPs had specific impacts on society and environment for which those on glaciers are exemplarily discussed in this study. Concerning the ongoing debate on climate the cooling in the 1960s and 1970s (strongest in summer) appears of special interest. During that time a widespread discussion about a possible and disastrous future cooling took place in the media. Although the scientific community was already aware of the future warming to be caused by the anthropogenic release of greenhouse gases into the atmosphere, the transport of this message to the public clearly failed in those decades.

    ATMOSPHERIC CIRCULATION was simulated by a coupled Atmosphere-Ocean General Circulation Model ECHO-G. Colleagues at the GKSS research centre have carried out multi century ensemble simulations at the German High Performance Computing Centre for Climate- and Earth System Research (DKRZ). The ensemble members correspond to differently forced AOGCM runs (e.g. volcanic forcing, greenhouse gas forcing, etc. ‘on or off’). These high standard and expensive simulations were an unexpected input to the project, that significantly increased the scientific output of CLIVALP. We extracted the North Atlantic/European sector from these simulations, which captures the most important atmospheric phenomena regarding climate within GAR and analyzed the circulation objectively by means of Rotated Empirical Orthogonal Functions (REOFs). It was found that circulation patterns corresponding to differently forced simulations are quite similar but the time coefficients, showing the patterns appearance in time, are quite diverse. This is regarded to reflect the effect of different external forcings on atmospheric circulation and therefrom gives rise to an assessment of external forcings onto the appearance of the previously and independently detected OPs. In doing so we selected for all outstanding periods those ECHO-G simulations, that reasonably reflect the observed surface temperature behaviour, and calculated the corresponding contributions of the circulations patterns. This approach allows to attach different circulation patterns to outstanding warm or cool European conditions.

    Circulation at a yearly time scale is mainly dominated by winter conditions. This is well known and was actually found in the REOF-circulation patterns as well. So, winter and the year as a whole were joined together, whereby the sample size is enhanced (and the statistical findings are more reliable). Findings assign a pronounced zonal airflow, advection of subtropical air and air mass transport from northern North Atlantic to warm conditions in Europe, while blockings over Central Europe are attached to cool conditions. This is in line with the physical understanding of the atmospheric processes and is likely to show the ability of ECHO-G to consistently simulate European-scale temperature and circulation over the North Atlantic-European sector during outstanding periods.

    This assignment of differently forced simulations to outstanding periods may be used as well to relate forcings to regional scale impacts. Summers of the 1810s may serve as an example. We found that simulations that do account for volcanic activities show low temperatures compared to the surrounding period - in accordance with observations (HISTALP). The only ensemble member that does not reproduce cool conditions is the one driven without volcanic forcings. This suggests that volcanic activities were responsible for the cool European summers of the 1810s. Findings derived for summer are clearly more indistinct. In contrary to winter and the whole year, which is dominated by large scale atmospheric processes, summer exhibits processes that are in general smaller in space and shorter in duration. This is well known and can be seen by the objective analysis of the summer-circulation over the North Atlantic European sector. Because of this fact and the small sample size on which conclusions are based, findings for summer should not be overrated.

    Projektbeginn 03.2002

    Projektende 08.2005

    Quelle: ZAMG

     

     

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