CLIVALP
Klimawandel Thematik
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Abk. |
CLIVALP |
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Themenbereich |
Klimawandel, Klimafolgenforschung |
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Status |
Abgeschlossenes FWF Projekt, P 15076-N06 |
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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. |
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Projektziele |
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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. |
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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).
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,
HISTALP database
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)
summer (JJA)
year
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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