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“Phenology – the timing of seasonal activities of animals and plants – is perhaps the simplest process in which to track changes in the ecology of species in response to climate change” (IPCC 2007). PEP725, the Pan-European Phenological Database, is thought as a European research infrastructure to promote and facilitate phenological research. Its main objective is to build up and maintain a European-wide phenological database with an open, unrestricted data access for science, research and education. So far, 20 European meteorological services and 6 partners from different phenological network operators have joined PEP725. The PEP725 phenological data base (www.pep725.eu) now offers close to 13 million phenological observations, essentially starting with 1951, comprising more than 200 species and 69 growing stages based on the BBCH scale. The data base grows with about 100000 additional observations per year. Having accepted the PEP725 data policy and finished the registration, the data can be downloaded according to various criteria, e.g. by a specific plant or all data from one country.To date (January 2023) we could count at least 115 peer - reviewed publications based on the PEP725, 17 of them published in Nature and one in Science. It appears that new avenues are entered in plant phenological research. Since remote sensing technology has been making big leaps forward with improved instruments and increasing resolution, Land Surface Phenology (LSP) is exploring its capabilities, especially experimenting with new and improved methods to correlate LSP with Ground Phenology (GP). A small but very active community continues to produce high quality research on plant physiological mechanisms and their relation with the atmospheric environment. Prominent appears the increase in the number of atmospheric variables, which have been related with plant phenology, for instance atmospheric brightening, light pollution, humidity, wind, day-time versus night-time trends. Strong interdisciplinarity combined with an increasing range of topics characterise the recent developments in phenological research. Just to cite a few: phenology in a future climate, agrometeorological questions, the role of plant energy budget, climate warming and fruit phenology, winter warming versus spring phenology, drought effects on phenology, carbon cycle, temperature sensitivity of various phenological phases and many more.Download statistics and the rapidly growing number of PEP725 based publications demonstrate the great demand and potential of the PEP725 phenological data set, which urgently needs development including a facilitated access, gridded versions and near real time products to attract a greater range of users.Finally, we would invite all, who have already used PEP725, to give us feedback!!! (markus.ungersboeck@geosphere.at; helfried.scheifinger@geosphere.at)Reference: Intergovernmental Panel on Climate Change (IPCC). 2007. Climate Change 2007: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK.

A paper published in Global Change Biology in 2006 revealed that phenological responses in 1971-2000 matched the warming pattern in Europe, but a lack of chilling and adaptation in farming may have reversed these findings. Therefore, for 1951-2018 in a corresponding data set, we determined changes as linear trends and analysed their variation by plant traits/groups, across season and time as well as their attribution to warming following IPCC methodology. Although spring and summer phases in wild plants advanced less (maximum advances in 1978-2007), more (~90%) and more significant (~60%) negative trends were present, being stronger in early spring, at higher elevations, but smaller for nonwoody insect-pollinated species. These trends were strongly attributable to winter and spring warming. Findings for crop spring phases were similar, but were less pronounced. There were clearer and attributable signs for a delayed senescence in response to winter and spring warming. These changes resulted in a longer growing season, but a constant generative period in wild plants and a shortened one in agricultural crops. Phenology determined by farmers' decisions differed noticeably from the purely climatic driven phases with smaller percentages of advancing (~75%) trends, but farmers' spring activities were the only group with reinforced advancement, suggesting adaptation. Trends in farmers' spring and summer activities were very likely/likely associated with the warming pattern. In contrast, the advance in autumn farming phases was significantly associated with below average summer warming. Thus, under ongoing climate change with decreased chilling the advancing phenology in spring and summer is still attributable to warming; even the farmers' activities in these seasons mirror, to a lesser extent, the warming. Our findings point to adaptation to climate change in agriculture and reveal diverse implications for terrestrial ecosystems; the strong attribution supports the necessary mediation of warming impacts to the general public.

Habitat fragmentation is one of the drivers for amphibian population declines globally. Especially in industrialized countries roads disrupt the seasonal migration of amphibians between hibernation and reproduction sites, often ending in roadkills. Thus, a timely installing of temporary mitigation measures is important for amphibian conservation. We wanted to find out if plant phenology can be a proxy in advance to determine the start of amphibian migration, since both phenomena are triggered by temperature. We analysed data of 3751 amphibian and 7818 plant phenology observations from citizen science projects in Austria between 2000 and 2018. Using robust regression modelling we compared the migration of common toads (Bufo bufo) and common frogs (Rana temporaria) with the phenology of five tree, one shrub, and one herb species. Results showed close associations between the migration of common frogs and phenological phases of European larch, goat willow and apricot. Models based on goat willow predict migration of common frog to occur 21 days after flowering, when flowering was observed on 60th day of year; apricot based models predict migration to occur 1 day after flowering, observed on the 75th day of year. Common toads showed weaker associations with plant phenology than common frogs. Our findings suggest that plant phenology can be used to determine the onset of temporary mitigation measures for certain amphibian species to prevent roadkills.

Phenology is the study of the seasonal timing of life cycle events. The Belgian botanist Charles Morren introduced the term in 1853, which is a combination of two Greek words, φαίνω, which means to show, to bring to light, make to appear, and λόγος, which means study, discourse, or reasoning. The global change discussion has stimulated phenological research, which as a consequence greatly advanced as science and evolved to one of the main climate impact indicators. Many of the earliest systematic efforts to collect phenological observations took place in countries sharing the Alps, most of which are still operating phenological networks. These phenological data sets are generally freely available to researchers, and numerous essential contributions to the topic of phenology and climate have been built on those data sets. Plant physiological processes underlying the ability of the plants to adapt to the year-to-year variability of the climate still constitutes largely a black box. Since the experiments of René Antoine Ferchault de Reaumur in the 18th century, it is known that temperature constitutes the main environmental driver of the seasonal development of the mid- to high-latitude plants. Second to temperature, day length governs the seasonal cycle of some species as an additional factor. Therefore, temperature-driven phenological models are able to simulate the year-to-year variability of phenological entry dates accurately enough for various applications, such as climate change impact research or numerical pollen forecast models, where the beginning of flowering of some plants is linked with the release of allergic pollen into the atmosphere. Large-scale circulation patterns, like the North Atlantic Oscillation, determine the frequency and intensity of warm and cold spells and decadal temperature trends over Europe. Combined anthropogenic and natural forcings explain the advance of spring phenology over the last 50 years, which is also clearly discernible in the area of the Alps. The early phenological spring starts in Western Europe, whereas later in the season it makes progress with a stronger southerly component across the Alps. The combined temporal and spatial trends have been studied along elevational gradients. Trends toward earlier entry dates are stronger at higher elevations, which indicates that the elevational phenological gradient has weakened since the mid-20th century. Similarly, the vegetation response to temperature is observed to decrease when moving from high to low latitudes. In contrast, the temporal response of plant phenology to increasing temperatures is less clear. Some works indeed demonstrate a decreasing temperature sensitivity with increasing temperature, which is explained as a result of a reduced winter chilling that delays spring phenology or of a limiting effect due to a shorter photoperiod. Other works report no change of temporal temperature sensitivity with increasing temperatures. Indigenous midlatitude vegetation is able to withstand large temperature variations during winter and spring. The safety margin between last frost events, budding, and leaf emergence was found to be uniform across elevations and taxa, except for beech trees. The probability of freezing damage to natural vegetation is almost nil, but late frost risk constitutes a real threat to fruit growers. The ratio of phenological and last frost trends is ambiguous. An increase or decrease in frost risk depends on regions, elevations, and species. Vegetation at high altitudes is exposed to a harsh climate with a long-lasting snow cover, low temperatures, and a short growing season. Snowmelt is a necessary but insufficient requirement for the start of the growing season, which has to be supplemented by plant-specific temperature sums to activate the growth of most alpine and subalpine species. The seasonal cycle has to be completed within a short time. Advances in remote sensing technology have provided access to high-resolution landscape scale phenological information. Especially in remote areas, like the Alps, in situ observations could be supplemented by satellite observations. Observations from both methods, I -situ and remote sensing, have been applied to describe spring vegetation dynamics, but the correlation between these data sets have typically been weak because of differences in temporal and spatial scales and resolutions. A successfully combined description of the seasonal vegetation cycle is still lacking. The area of the European Alps offers a wealth of long chronicles, containing historical phenological observations some of which have been extracted and digitized. Grape harvest dates belong to the most readily available historical phenological observations, which have helped reconstruct summer temperatures as far back as the 15th century.

“Phenology – the timing of seasonal activities of animals and plants – is perhaps the simplest process in which to track changes in the ecology of species in response to climate change” (IPCC 2007).PEP725, the Pan-European Phenological Database, is a European research infrastructure to promote and facilitate phenological research. Its main objective is to build up and maintain a European-wide phenological database with an open, unrestricted data access for science, research and education. So far, 20 European meteorological services and 6 partners from different phenological network operators have joined PEP725.The PEP725 phenological data base (www.pep725.eu) now offers more than 12 million phenological observations, all of them classified according to the so called BBCH scale. The first datasets in PEP725 date back to 1868; however, there are only a few observations available until 1950. Having accepted the PEP725 data policy and finished the registration, the data download is quick and easy and can be done according to various criteria, e.g., by a specific plant or all data from one country. The integration of new data sets for future partners is also easy to perform due to the flexible structure of the PEP725 database as well as the classification of the observed plants via the so-called gss format (genus, species and subspecies).PEP725 is funded by EUMETNET, the network of European meteorological services, ZAMG, who is the acting host for PEP, and the Austrian ministry of education, science and research.The phenological data set has been growing by about 100000 observations per year. Also the number of user registrations has continually been increasing, amounting to 305 new users and more than 28000 downloads in 2020. The greatest number of users are found in China, followed by Germany and the US. To date we could count 78 reviewed publications based on the PEP725 data set with 18 in 2020 and a total of 9 published in Nature and one in Science.The data base statistics demonstrate the great demand and potential of the PEP725 phenological data set, which urgently needs development including a facilitated access, gridded versions and near real time products to attract a greater range of users.

International audience; Vegetation phenology obtained from time series of remote sensing data is relevant for a range of ecological applications. The freely available Sentinel-2 imagery at a 10 m spatial resolution with a similar to 5-day repeat cycle provides an opportunity to map vegetation phenology at an unprecedented fine spatial scale. To facilitate the production of a Europe-wide Copernicus Land Monitoring Sentinel-2 based phenology dataset, we design and evaluate a framework based on a comprehensive set of ground observations, including eddy covariance gross primary production (GPP), PhenoCam green chromatic coordinate (GCC), and phenology phases from the Pan-European Phenological database (PEP725). We test three vegetation indices (VI) - the normalized difference vegetation index (NDVI), the two-band enhanced vegetation index (EVI2), and the plant phenology index (PPI) - regarding their capability to track the seasonal trajectories of GPP and GCC and their performance in reflecting spatial variabilities of the corresponding GPP and GCC phenometrics, i.e., start of season (SOS) and end of season (EOS). We find that for GPP phenology, PPI performs the best, in particular for evergreen coniferous forest areas where the seasonal variations in leaf area are small and snow is prevalent during wintertime. Results are inconclusive for GCC phenology, for which no index is consistently better than the others. When comparing to PEP725 phenology phases, PPI and EVI2 perform better than NDVI regarding the spatial correlation and consistency (i.e., lower standard deviation). We also link VI phenometrics at various amplitude thresholds to the PEP725 phenophases and find that PPI SOS at 25% and PPI EOS at 15% provide the best matches with the ground-observed phenological stages. Finally, we demonstrate that applying bidirectional reflectance distribution function correction to Sentinel-2 reflectance is a step that can be excluded for phenology mapping in Europe.

Operational pollen monitoring networks have developed across Europe, and the world more generally, in response to the increasing prevalence of pollen allergy and asthma. Routine pollen observations are in large part currently still based on time-intensive manual techniques developed in the 1950s. These methods suffer from low temporal resolution and long delays in data availability. Recent technological developments are revolutionising the field making real-time high-temporal resolution measurements possible. This paper describes the rationale behind the EUMETNET AutoPollen programme, which aims to develop a prototype automatic pollen monitoring network across Europe. We provide a brief description of the current state-of-the-art, then an overview of new technologies, and finally the main tasks of the AutoPollen programme.

During 1971-2000 phenological responses of wild species in spring and summer matched the warming pattern in Europe, whereas timing of farming activities as well as autumnal leaf colouring did not mirror climate change to the same extent (Menzel et al. GCB 2006). These findings were a backbone of the corresponding global attribution study of the IPCC AR4 (Rosenzweig et al. 2007, 2008). Two decades of warming later, however, new phenological findings suggest that especially a lack of chilling and / or increasing influence of photoperiod may have lowered the phenological temperature response and that adaptation in agricultural management is taking place. We therefore updated the GCB 2006 study by asking three questions: What drives the inherent variation of trends? Can we now detect a warming signal in “false” agricultural (i.e. those being directly or indirectly determined by farmers’ management) and autumn phases? Is there still an attributable warming signal in phenology?The complete phenological dataset of Germany, Austria and Switzerland (1951-2018, ~97.000 times series, corresponding to 96.3% of PEP725 data) was analysed. We determined linear trends, studied their variation by plant traits / phenogroups, across season and time, and followed IPCC methodology for attributing phenological changes to warming patterns.For spring and summer phases of wild plants we found more (significantly) advancing trends (~90% and ~60% sign.) which were stronger in early spring, at higher elevations, but smaller for non-woody insect-pollinated species. Although mean trend strength decreased, changes in spring were strongly attributable to warming in spring and winter. We had similar but less strong findings for agricultural crops in these seasons. In contrast only ~75% of phenological phases set by farmers’ decisions were advancing, however this was the only phenological group for which the mean advance increased, indicating adaptation. Equally trends in farming phases in spring and summer were attributable to warming in winter and summer, respectively. Leaf coloring and fall was now predominantly delayed (57%) which was attributable to winter and spring warming, too.Thus, this update of the GCB2006 study demonstrates that there is still a significant and attributable phenological change pattern in Europe, in which number of (significant) trends pointing into the direction of warming increased, but mean trend strength mostly decreased, probably due to a lack of chilling and smaller forcing trends. More attention should be paid to the inherent variability of trends with traits / species groups, season and time triggering divers (e.g. ecological) consequences of these phenological shifts. Still existing differences between the generative period of crops and wild species as well as between the farming season and the general growing season call for more research in this area.

An important consequence of climate change is the impact on the seasonal cycle of vegetation flora and fauna. Although it is generally understood that anthropogenic mechanisms play a major role in the warming trend of the climate and that the timing of such phases, especially spring timing events, depends largely on the temperature, the link has yet to be quantitatively shown for different kind of areas on a regional scale, due to high intrinsic noise. In this study, an end-to-end analysis to external forcings was carried out, linking the earlier timing of phenological spring timing events to changed climate conditions (increasing temperature) and this change in the environment to anthropogenic forcing, for the region of interest: Germany. Besides a large ensemble originating from six different General Circulation Models (GCMs), driven with various kinds of forcings, the E-OBS data set was used as observational reference for near-surface air temperature and the PEP725 for phenological observations. The latter contains over 100 different phenological phases, from which - after quality checking - 12 phases are evaluated. To overcome the scale differences, a quantile mapping bias correction approach was used to downscale the GCM data. The generation of simulated phenological time series was done with a temperature-day-sum model, which had to be calibrated and optimised beforehand. The signal-to-noise ratio was increased by generating samples of 50-year running trends, which make up the basis for the statistical evaluation. U-values from the Mann-Whitney U-Test represent the foundation, on which the null hypothesis for detection, that the observed changes can be explained with naturally forced climate conditions only, was tested. Based thereupon, a newly defined consistency factor was constructed, which allowed the assessment of anthropogenic impact on phenological phases. Observed changes in phenological phases were successfully attributed to anthropogenic impacts.

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 “Establishing a European phenological data platform for climatological applications” working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

The Alpine stations Zugspitze, Hohenpeissenberg, Sonnblick, Jungfraujoch and Mt. Krvavec contribute to the Global Atmosphere Watch Programme (GAW) of the World Meteorological Organization (WMO). The aim of GAW is the surveillance of the large-scale chemical composition of the atmosphere. Thus, the detection of air pollutant transport from regional sources is of particular interest. In this paper, the origin of NOx (measured with a photo-converter), CO and O3 at the four Alpine GAW stations is studied by trajectory residence time statistics. Although these methods originated during the early 1980s, no comprehensive study of different atmospheric trace gases measured simultaneously at several background observatories in the Alps was conducted up to present. The main NOx source regions detected by the trajectory statistics are the northwest of Europe and the region covering East Germany, Czech Republic and southeast Poland, whereas the main CO source areas are the central, north eastern and eastern parts of Europe with some gradient from low to high latitudes. Subsiding air masses from west and southwest are relatively poor in NOx and CO. The statistics for ozone show strong seasonal effects. Near ground air masses are poor in ozone in winter but rich in ozone in summer. The main source for high ozone concentration in winter is air masses that subside from higher elevations, often enhanced by foehn effects at Hohenpeissenberg. During summer, the Mediterranean constitutes an important additional source for high ozone concentrations. Especially during winter, large differences between Hohenpeissenberg and the higher elevated stations are found. Hohenpeissenberg is frequently within the inversion, whereas the higher elevated stations are above the inversion. Jungfraujoch is the only station where the statistics detect an influence of air rich in CO and NOx from the Po Basin.

A number of works have been trying to validate various trajectory statistical methods (TSMs), mostly through subjective comparison with known sources. Here in a more comprehensive and quantitative approach three trajectory statistical methods (potential source contribution function (PSCF), concentration field method (CF), and redistributed concentration field method (RCF)) were subjected to two validation approaches: validation with virtual and real sources under idealised conditions, where the effects of dispersion and removal of the trace substance are excluded, and comparisons with the EMEP SO2 emission inventory under realistic conditions. The best performance was achieved in an idealised situation with about 78% common spatial variance between the EMEP emission inventory and the trajectory statistical reconstruction of the EMEP emission inventory with the RCF method, whereas the real world experiments for SO2 on an European scale resulted in a much lower performance with 33% common spatial variance between the EMEP SO2 emission inventory and the trajectory statistical reconstruction with the PSCF method. The experiments suggest that the limitation of the accuracy and spatial range of TSMs are rooted in the simplified transport process described just by trajectory paths. If one links these limitations with the concept of the mean residence time of the considered trace substance, a temporal and spatial scope can be deduced, within which the effect of the simplification of the transport process is restricted and useful information can be expected from TSMs. The lower values of the mean residence time for SO2 range from 9 to 17 h, which were deduced from the decay approach, where an exponential decay, respectively, removal of SO2 was built into the trajectory statistical procedure. The values derived from the optimum real world validation experiment place the upper range of the mean residence time to about 60 h or 2.5 days. Both figures are within the range of mean residence times for SO2 cited in literature. Through the validation experiments of this work the rule of thumb, not to trust TSMs beyond the mean residence time of the substance, has become palpable. Nevertheless TSMs and related methods are computationally fast procedures, which deliver first hints on potential source areas, if applied within the frame of the mean residence time of the considered substance.

Global climate change impacts can already be tracked in many physical and biological systems; in particular, terrestrial ecosystems provide a consistent picture of observed changes. One of the preferred indicators is phenology, the science of natural recurring events, as their recorded dates provide a high-temporal resolution of ongoing changes. Thus, numerous analyses have demonstrated an earlier onset of spring events for mid and higher latitudes and a lengthening of the growing season. However, published single-site or single-species studies are particularly open to suspicion of being biased towards predominantly reporting climate change-induced impacts. No comprehensive study or meta-analysis has so far examined the possible lack of evidence for changes or shifts at sites where no temperature change is observed. We used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971–2000). Our results showed that 78% of all leafing, flowering and fruiting records advanced (30% significantly) and only 3% were significantly delayed, whereas the signal of leaf colouring/fall is ambiguous. We conclude that previously published results of phenological changes were not biased by reporting or publication predisposition: the average advance of spring/summer was 2.5 days decade � 1 in Europe. Our analysis of 254 mean national time series undoubtedly demonstrates that species’ phenology is responsive to temperature of the preceding

The year to year variability and trends of animal phenological phases (honey bee, cockchafer, 3 butterfly species, swallow and cuckoo) of the Austrian phenological observational network were related to each other and to mean monthly temperatures over the time period 1951-1998. Insect phases were well correlated with each other (r 2 = 0.4 to 0.6) and with temperature (r 2 = 0.25 to 0.55), whereas both bird phases were only well correlated with each other (r 2 = 0.57), but showed low common variance values with temperature and with other animal phases. The slope of the temperature-pheno regression, also termed as temperature sensitivity of the phenological phase, was high in the case of the insect phases (-3 to -5 days/°C), but low in the cases of both bird phases (about -1 days/°C). All animal phenological time series showed a trend towards later occurrence dates. The trends of the bird phases were even significant (p

In this study we set out to investigate the possibility of linking phenological phases throughout the vegetation cycle, as a local-scale biological phenomenon, directly with large-scale atmospheric variables via two different empirical downscaling techniques. In recent years a number of methods have been developed to transfer atmospheric information at coarse General Circulation Model's grid resolutions to local scales and individual points. Here multiple linear regression (MLR) and canonical correlation analysis (CCA) have been selected as downscaling methods. Different validation experiments (e.g. temporal cross-validation, split-sample tests) are used to test the performance of both approaches and compare them for time series of 17 phenological phases and air temperatures from Central Europe as microscale variables. A number of atmospheric variables over the North Atlantic and Europe are utilized as macroscale predictors. The period considered is 1951-1998. Temporal cross-validation reveals that the CCA model generally performs better than MLR, which explains 20%-50% of the phenological variances, whereas the CCA model shows a range from 40% to over 60% throughout most of the vegetation cycle. To show the validity of employing phenological observations for downscaling purposes both methods (MLR and CCA) are also applied to gridded local air temperature time series over Central Europe. In this case there is no obvious superiority of the CCA model over the MLR model. Both models show explained variances from 40% to over 70% in the temporal cross-validation experiment. The results of this study indicate that time series of phenological occurrence dates are very compatible with the needs of empirical downscaling originally developed of local-scale atmospheric variables.

¶Over large parts of the Northern Hemisphere’s continents temperature has been increasing during the last century. Particularly minimum temperatures show a more pronounced increase than maximum temperatures. Not only the phenological seasons, but also the potentially plant damaging late frost events are governed by the atmosphere. In case of a rise of minimum temperatures one would expect phenological phases and spring late frost events to occur earlier. In this work the question is elucidated whether plant phenology shifts at a higher or lower rate towards earlier occurrences than potential plant damaging events, like spring late frost events. Frost events based on the last occurrence of daily minimum temperatures below a certain threshold have been moving faster to earlier occurrence dates than phenological phases during the last decades at 50 climate stations in Central Europe. Trend values of frost time series range around −0.2 days/year and of phenological time series are between −0.2 and 0.0 days/year over the period from 1951–1997. ‘Corylus avellana beginning of pollination’ is the only one of the 13 phases considered here with a lower trend value of −0.28 days/year. Early phases are more adapted to below zero temperatures and therefore follow more closely the temperature variability. Later phases seem to have more reason to be concerned about possible late frost events and react more cautiously towards higher spring temperatures and earlier last frost dates. The risk of late frost damage for plants should have been lower during the last decade as compared to the previous decades.

We analyse how variations in the climatological growing season, defined by single-value thresholds of daily minimum and mean air temperature, mirror recent changes in plant phenological phases. In Germany (1951–2000, 41 climate stations), the dates of last spring frost Tmin 950 m a.s.l.) weaker trends are again generally observed. Copyright  2003 Royal Meteorological Society.

Regional risk assessments for the potential effects of climate change rely on plausible small-scale climate change scenario data. To bridge the gap between the coarse scale of general circulation models and the local scale of approximately 11 000 sample sites of the Austrian National Forest Inventory (AFI), a seasonally stratified statistical downscaling procedure was applied to a con- trol run and 2 transient experiments of ECHAM4/OPYC3, which are based on the trace gas only or trace gas plus sulphate scenario IPCC IS92a. We fitted multiple linear regression (MLR) models for the micro-scale monthly precipitation and temperature for each AFI point. The meteorological data at the AFI sites were obtained by interpolation of measurements from the dense network of Austrian weather stations for the period 1961-1995. The macro-scale predictors were principal components of monthly NCEP/NCAR reanalysis data (850 and 700 hPa geopotential height, 850 hPa temperature and 700 hPa relative humidity). The results show spatial and temporal heterogeneity for both tem- perature and precipitation. In case of temperature MLR leads to increases from +1.4 to +4.0oC (trace gas only integration) and from +1.1 to +2.9oC (trace gas plus sulphate integration) for a period of about 55 yr relative to the 1961-1995 climatology. The regionalized precipitation changes are both negative and positive. Values range from -44 to +26% (trace gas only integration) and from -29 to +26% (trace gas plus sulphate integration). As expected, the explained variability for temperature was higher than for precipitation and depended on the season. From a validation experiment for model calibration we conclude that MLR shows reliable results for temperature. Even in the case of precipitation the method seems to yield plausible results. Both temperature and precipitation were better reproduced for winter than for summer.

A data set of 17 phenological phases from Germany, Austria, Switzerland and Slovenia spanning the time period from 1951 to 1998 has been made available for analysis together with a gridded temperature data set (1° × 1° grid) and the North Atlantic Oscillation (NAO) index time series. The disturbances of the westerlies constitute the main atmospheric source for the temporal variability of phenological events in Europe. The trend, the standard deviation and the discontinuity of the phenological time series at the end of the 1980s can, to a great extent, be explained by the NAO. A number of factors modulate the influence of the NAO in time and space. The seasonal northward shift of the westerlies overlaps with the sequence of phenological spring phases, thereby gradually reducing its influence on the temporal variability of phenological events with progression of spring (temporal loss of influence). This temporal process is reflected by a pronounced decrease in trend and standard deviation values and common variability with the NAO with increasing year-day. The reduced influence of the NAO with increasing distance from the Atlantic coast is not only apparent in studies based on the data set of the International Phenological Gardens, but also in the data set of this study with a smaller spatial extent (large-scale loss of influence). The common variance between phenological and NAO time series displays a discontinuous drop from the European Atlantic coast towards the Alps. On a local and regional scale, mountainous terrain reduces the influence of the large-scale atmospheric flow from the Atlantic via a proposed ‘decoupling mechanism’. Valleys in mountainous terrain have the inclination to harbour temperature inversions over extended periods of time during the cold season, which isolate the valley climate from the large-scale atmospheric flow at higher altitudes. Most phenological stations reside at valley bottoms and are thus largely decoupled in their temporal variability from the influence of the westerly flow regime (local-scale loss of influence). This study corroborates an increasing number of similar investigations that find that vegetation does react in a sensitive way to variations of its atmospheric environment across various temporal and spatial scales. Copyright © 2002 Royal Meteorological Society.

The European phyto-phenological database of the EU 5th Framework project ‘POSITIVE’ facilitated an examination of the rate and spatial pattern of changes in spring phenology across Europe. This database was collected, evaluated and composed from different national databases of Eastern and Western Europe covering the time period 1951–1998. Results show that spring phases have advanced four weeks in Western and Central Europe, and have been delayed up to two weeks in Eastern Europe. Western European spring starts earlier because of the intensive flow of warmer Atlantic air masses; the Eastern part of Europe has a different phenological rhythm and trends, that can be explained by the influence of the Siberian high. The highest rate of significant ( p< 0.05) phenological change (−0. 3t o−0.4 days per year) occurs in the Western Europe and Baltic Sea regions for early spring phases of hazel and colts-foot. Spring phases of birch, apple and lilac, and summer phases, such as the flowering of linden, tend to occur earlier with an average rate of −0.1 to 0.3 days per year. Copyright  2002 Royal Meteorological Society.

In spite of its limitations the combination of routine meteorological data and meteorological pre-processors is an efficient approach to provide gridded fields of turbulence scaling parameters for routine ATD (Atmospheric Transport and Dispersion) modelling. Height detrended inverse distance weighting is introduced to calculate the necessary 2D fields of global radiation, temperature, humidity, cloud cover and air pressure to feed the pre-processor. Cross validation of the interpolation scheme shows that the spatial interpolation method is superior to the more common extrapolation in case of complex terrain. In a further validation the impact of the interpolation respectively extrapolation errors on the results of the pre-processor is investigated. It turns out that the pre-processor is not very sensitive to variations in input data. This suggests that in case of flat areas or in case the ATD modelling problem is not influenced by topographical features, one could achieve good results without investing into the development and adaptation of spatial interpolation procedures of basic atmospheric variables, which serve as pre-processor input. If the dispersion process is influenced by topographical features, one should invest into a spatial interpolation procedure. Because temperature is an essential variable for modelling chemical reactions in the atmosphere, a 3D interpolation scheme for temperature has been adapted from literature and found to behave plausibly.

Two simple approaches for assessing global radiation in complex terrain are tested and compared. A parameterisation scheme for global radiation based on cloud cover observations was compared with interpolation of measured global radiation values from the Austrian climate observation network. Interpolation appears to be a useful method for a station density which has been available after 1992 in Austria (about 1000 km2/station). In that case interpolation is superior to parameterisation. The quality of interpolated data quickly drops with height and for elevations above 1500 m neither method delivers useful results.

The section about monitoring covers the development of phenological networks, remote sensing of the season cycle of the vegetation, the emergence of the science of aerobiology and, more specifically, aeropalynology, pollen sampling instruments, pollen counting techniques, applications of aeropalynology in agriculture and the European Pollen Information System. Three data sources are directly related with aeropalynology: phenological observations, pollen counts and remote sensing of the vegetation activity. The main future challenge is the assimilation of these data streams into numerical pollen forecast systems. Over the last decades consistent monitoring efforts of various national networks have created a wealth of pollen concentration time series. These constitute a nearly untouched treasure, which is still to be exploited to investigate questions concerning pollen emission, transport and deposition. New monitoring methods allow measuring the allergen content in pollen. Results from research on the allergen content in pollen are expected to increase the quality of the operational pollen forecasts.In the modelling section the concepts of a variety of process-based phenological models are sketched. Process-based models appear to exhaust the noisy information contained in commonly available observational phenological and pollen data sets. Any additional parameterisations do not to improve model quality substantially. Observation-based models, like regression models, time series models and computational intelligence methods are also briefly described. Numerical pollen forecast systems are especially challenging. The question, which of the models, regression or process-based models is superior, cannot yet be answered.

For environmental meteorological studies it is often crucial to have access to a weather pattern classification scheme, which also includes information about the source area and the path of an air parcel. Besides the fact that most weather pattern classifications lack objectivity, only a few are applicable to environmental questions. Thus a new approach was persued in this work to obtain the desired information. Isobaric backward trajectories, calculated twice daily over a period of three and a half years ending in the Eastern Alps were sorted into nine typical clusters by a clustering technique described in Dorling at al. (1992). Relating the classification with selected meteorological and chemical parameters of the atmosphere measured at various Austrian sites the method was found to yield meaningful results

The reflectivity of the 22 km x 24 km region surrounding Sonnblick Observatory near Salzburg, Austria (3104-m altitude, 47.05 degrees N, 12.95 degrees E), was calculated with a three-dimensional albedo model. The average albedo of the region was calculated at 305 and 380 nm for different solar zenith angles, ground reflectances, and solar azimuth angles. To determine geometrical effects, we first carried out the simulations without taking account of the effects of the atmosphere. The ratio to the reflectivity of a corresponding flat surface area (area with the same ground characteristics) was always less than 1 and showed a decrease with increasing solar zenith angle and with diminishing ground reflectance. Even when the ground reflectance was 100%, the average albedo was less than 1. The effect of the atmosphere was then taken into consideration in these calculations and was found to diminish the reflected components. This diminishing effect was compensated for, however, by the scattered irradiance. Finally, simulations of real conditions (nonhomogeneous ground reflectivities) were performed for different snow lines in the Sonnblick region. The average albedos obtained when all the surroundings were covered with snow were 0.32-0.63 with low solar zenith angles and 0.38-0.77 with a 40 degrees solar zenith angle.

The paper evaluates long-term seasonal variations of the deuterium excess (d-excess = delta(2)H - 8. delta(18)O) in precipitation of stations located north and south of the main ridge of the Austrian Alps. It demonstrates that sub-cloud evaporation during precipitation and continental moisture recycling are local, respectively, regional processes controlling these variations. In general, sub-cloud evaporation decreases and moisture recycling increases the d-excess. Therefore, evaluation of d-excess variations in terms of moisture recycling, the main aim of this paper, includes determination of the effect of sub-cloud evaporation. Since sub-cloud evaporation is governed by saturation deficit and distance between cloud base and the ground, its effect on the d-excess is expected to be lower at mountain than at lowland/valley stations. To determine quantitatively this difference, we examined long-term seasonal d-excess variations measured at three selected mountain and adjoining valley stations. The altitude differences between mountain and valley stations ranged from 470 to 1665 m. Adapting the 'falling water drop' model by Stewart [J. Geophys. Res., 80(9), 1133-1146 (1975).], we estimated that the long-term average of sub-cloud evaporation at the selected mountain stations (altitudes between about 1600 and 2250 m.a.s.l.) is less than 1 % of the precipitation and causes a decrease of the d-excess of less than 2 per thousand. For the selected valley stations, the corresponding evaporated fraction is at maximum 7 % and the difference in d-excess ranges up to 8 per thousand. The estimated d-excess differences have been used to correct the measured long-term d-excess values at the selected stations. Finally, the corresponding fraction of water vapour has been estimated that recycled by evaporation of surface water including soil water from the ground. For the two mountain stations Patscherkofel and Feuerkogel, which are located north of the main ridge of the Alps, the maximum seasonal change of the corrected d-excess (July/August) has been estimated to be between 5 and 6 per thousand, and the corresponding recycled fraction between 2.5-3 % of the local precipitation. It has been found that the estimated recycled fractions are in good agreement with values derived from other approaches.

Operational model forecasts of ozone concentrations are compared to the observations of about 150 air quality stations in Austria. Evaluations of the last three summers revealed that exceedances of the information threshold could be predicted quite well by the model. Investigation of a heat period in summer 2006 indicates possible sources of precursors. The Lagrangian particle model LASAT (www.janicke.de) is used additionally to the chemical model CAMx (www.camx.com) to show the dispersion of the plumes of stacks with high emissions of NOx in the vicinity of Vienna. For two months in summer 2007 sensitivity studies with different input parameters were performed. Model runs with different parameterisations for the vertical diffusion coefficient (Kv) are conducted and experiments with different values of the minimum values of Kv in the lower levels show the influence of this parameter on the nocturnal ozone decrease for different sites. Different model runs with variable boundary conditions at the top of the modelling domain as well as variable total ozone column data are performed.

Recently the study of plant and animal phenological observations has contributed much to understand the sensitivity of biosphere to the variability of its atmospheric environment. This study is based on time series of 3 bird phenological phases (‘first barn swallow’, ‘first cuckoo call’ and ‘all swallows have left’) from the archive of the Central Institute for Meteorology and Geodynamics in Vienna, which have been collected at 65 Austrian stations from 1951 – 1999. In contrast to many European countries the arrival times of barn swallow and the cuckoo have predominantly been moving to later dates in Austria. A preliminary analysis points towards dryer conditions in the sub - saharan winter quarters as possible cause for a later departure from the African winter quarters to Europe. About a third of the year to year variability of both spring bird phases can be explained by temperature and wind conditions on the migration route and local temperature.

The methodological framework of a large-scale risk assessment for Austrian forests under scenarios of climatic change is presented. A recently developed 3D-patch model is initialized with ground-true soil and vegetation data from sample plots of the Austrian Forest Inventory (AFI). Temperature and precipitation data of the current climate are interpolated from a network of more than 600 weather stations to the sample plots of the AFI. Vegetation development is simulated under current climate (‘control run’) and under climate change scenarios starting from today's forest composition and structure. Similarity of species composition and accumulated biomass between these two runs at various points in time were used as assessment criteria. An additive preference function which is based on Saaty’s AHP is employed to synthesize these criteria to an overall index of the adaptation potential of current forests to a changing climate. The presented methodology is demonstrated for a small sample from the Austrian Forest Inventory. The forest model successfully simulated equilibrium species composition under current climatic conditions spatially explicit in a heterogenous landscape based on ground-true data. At none of the simulated sites an abrupt forest dieback did occur due to climate change impacts. However, substantial changes occured with regard to species composition of the potential natural vegetation (PNV).