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Institution

MeteoSwiss

GovernmentZurich, Switzerland
About: MeteoSwiss is a government organization based out in Zurich, Switzerland. It is known for research contribution in the topics: Climate change & Environmental science. The organization has 364 authors who have published 926 publications receiving 47176 citations. The organization is also known as: Federal Office of Meteorology and Climatology & Central Meteorological Institute.


Papers
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Journal ArticleDOI
22 Jan 2004-Nature
TL;DR: It is found that an event like that of summer 2003 is statistically extremely unlikely, even when the observed warming is taken into account, and it is proposed that a regime with an increased variability of temperatures (in addition to increases in mean temperature) may be able to account for summer 2003.
Abstract: Instrumental observations1,2 and reconstructions3,4 of global and hemispheric temperature evolution reveal a pronounced warming during the past ∼150 years. One expression of this warming is the observed increase in the occurrence of heatwaves5,6. Conceptually this increase is understood as a shift of the statistical distribution towards warmer temperatures, while changes in the width of the distribution are often considered small7. Here we show that this framework fails to explain the record-breaking central European summer temperatures in 2003, although it is consistent with observations from previous years. We find that an event like that of summer 2003 is statistically extremely unlikely, even when the observed warming is taken into account. We propose that a regime with an increased variability of temperatures (in addition to increases in mean temperature) may be able to account for summer 2003. To test this proposal, we simulate possible future European climate with a regional climate model in a scenario with increased atmospheric greenhouse-gas concentrations, and find that temperature variability increases by up to 100%, with maximum changes in central and eastern Europe.

2,660 citations

Journal ArticleDOI
TL;DR: In this article, the authors 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) and concluded that previously published results of phenological changes were not biased by reporting or publication predisposition.
Abstract: 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

2,457 citations

Journal ArticleDOI
TL;DR: The European Climate Assessment (ECA) dataset as discussed by the authors is a dataset of daily resolution climatic time series that has been compiled for the European climate assessment (ECA), which consists of 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East.
Abstract: We present a dataset of daily resolution climatic time series that has been compiled for the European Climate Assessment (ECA). As of December 2001, this ECA dataset comprises 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East. Almost all series cover the standard normal period 1961–90, and about 50% extends back to at least 1925. Part of the dataset (90%) is made available for climate research on CDROM and through the Internet (at http://www.knmi.nl/samenw/eca). A comparison of the ECA dataset with existing gridded datasets, having monthly resolution, shows that correlation coefficients between ECA stations and nearest land grid boxes between 1946 and 1999 are higher than 0.8 for 93% of the temperature series and for 51% of the precipitation series. The overall trends in the ECA dataset are of comparable magnitude to those in the gridded datasets. The potential of the ECA dataset for climate studies is demonstrated in two examples. In the first example, it is shown that the winter (October–March) warming in Europe in the 1976–99 period is accompanied by a positive trend in the number of warm-spell days at most stations, but not by a negative trend in the number of cold-spell days. Instead, the number of cold-spell days increases over Europe. In the second example, it is shown for winter precipitation between 1946 and 1999 that positive trends in the mean amount per wet day prevail in areas that are getting drier and wetter. Because of its daily resolution, the ECA dataset enables a variety of empirical climate studies, including detailed analyses of changes in the occurrence of extremes in relation to changes in mean temperature and total precipitation. Copyright  2002 Royal Meteorological Society.

1,523 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated how ModelPredictive control and weatherpredictions can increase the energy efficiency in Integrated Room Automation (IRA) while respecting occupant comfort.

1,070 citations

Journal ArticleDOI
TL;DR: In this article, a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers.
Abstract: Floods, wildfires, heatwaves and droughts often result from a combination of interacting physical processes across multiple spatial and temporal scales. The combination of processes (climate drivers and hazards) leading to a significant impact is referred to as a ‘compound event’. Traditional risk assessment methods typically only consider one driver and/or hazard at a time, potentially leading to underestimation of risk, as the processes that cause extreme events often interact and are spatially and/or temporally dependent. Here we show how a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers, who need to work closely together to understand these complex events.

960 citations


Authors

Showing all 398 results

NameH-indexPapersCitations
Thomas Peter6928014500
Mathias W. Rotach451437975
Isabelle Bey457412082
Sven Kotlarski38926123
Christof Appenzeller37707791
Christoph Frei366110391
Laurent Vuilleumier351374308
Wolfgang A. Müller35963183
Urs Germann31993430
Mark A. Liniger30625606
Rolf Philipona30783691
Martin Hirschi30547417
René Stübi28772692
Cornelia Schwierz27473234
Christoph Spirig26431992
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202367
202261
202180
202086
201996
201878