Revisiting Swiss temperature trends 1959–2008

Ceppi, Paulo; Scherrer, Simon C.; Fischer, Andreas M.; Appenzeller, Christof

doi:10.1002/joc.2260

Cited by 156 publications

(125 citation statements)

References 30 publications

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“…This has been confirmed by (Rebetez and Reinhard 2011;Ceppi et al 2012). For precipitation, significant trends have only been found during the winter season in the period 1864 to 2000 (Begert et al 2005).…”

Section: Motivationsupporting

confidence: 53%

“…The snow-albedo feedback describes the enhanced warming with less snow due to a darker land surface and the connected increase in absorbed solar radiation at the surface (Im et al 2011). Thus, the warming is larger at higher altitudes, where the models predict a snow cover decrease in the future (Im et al 2011;Ceppi et al 2012;Kotlarski et al 2012a;Steger et al 2013). In summer, the warming in 2045-2074 and also 2070-2099 is about 1°C larger above 2,500 m asl as compared to the Swiss lowlands with altitudes between 400 and 800 m asl.…”

Section: Resultsmentioning

confidence: 99%

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Localized climate change scenarios of mean temperature and precipitation over Switzerland

et al. 2014

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There is a growing need of the climate change impact modeling and adaptation community to have more localized climate change scenario information available over complex topography such as in Switzerland. A gridded dataset of expected future climate change signals for seasonal averages of daily mean temperature and precipitation in Switzerland is presented. The basic scenarios are taken from the CH2011 initiative. In CH2011, a Bayesian framework was applied to obtain probabilistic scenarios for three regions within Switzerland. Here, the results for two additional Alpine sub-regions are presented. The regional estimates have then been downscaled onto a regular latitudelongitude grid with a resolution of 0.02°or roughly 2 km. The downscaling procedure is based on the spatial structure of the climate change signals as simulated by the underlying regional climate models and relies on a Kriging with external drift using height as auxiliary predictor. The considered emission scenarios are A1B, A2 and the mitigation scenario RCP3PD. The new dataset shows an expected warming of about 1 to 6°C until the end of the 21st century, strongly depending on the scenario and the lead time. Owing to a large vertical gradient, the warming is about 1°C stronger in the Alps than in the Swiss lowlands. In case of precipitation, the projection uncertainty is large and in most seasons precipitation can increase or decrease. In summer a distinct decrease of precipitation can be found, again strongly depending on the emission scenario.

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Section: Motivationsupporting

confidence: 53%

Section: Resultsmentioning

confidence: 99%

Localized climate change scenarios of mean temperature and precipitation over Switzerland

et al. 2014

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“…In-between is a transition zone with rather strong changes with elevation, which approximately corresponds to the mean elevation of the September-May zero-degree line in today's climate (e.g. Ceppi et al, 2012;MeteoSwiss, 2016). Individual simulations with large reductions in S mean , such as the RCA experiments, also project the strongest declines in S freq .…”

Section: Snowfall Projections For the Late 21st Centurymentioning

confidence: 99%

Future snowfall in the Alps: projections based on the EURO-CORDEX regional climate models

et al. 2018

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Abstract. Twenty-first century snowfall changes over the European Alps are assessed based on high-resolution regional climate model (RCM) data made available through the EURO-CORDEX initiative. Fourteen different combinations of global and regional climate models with a target resolution of 12 km and two different emission scenarios are considered. As raw snowfall amounts are not provided by all RCMs, a newly developed method to separate snowfall from total precipitation based on near-surface temperature conditions and accounting for subgrid-scale topographic variability is employed. The evaluation of the simulated snowfall amounts against an observation-based reference indicates the ability of RCMs to capture the main characteristics of the snowfall seasonal cycle and its elevation dependency but also reveals considerable positive biases especially at high elevations. These biases can partly be removed by the application of a dedicated RCM bias adjustment that separately considers temperature and precipitation biases.Snowfall projections reveal a robust signal of decreasing snowfall amounts over most parts of the Alps for both emission scenarios. Domain and multi-model mean decreases in mean September-May snowfall by the end of the century amount to −25 and −45 % for representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, respectively. Snowfall in low-lying areas in the Alpine forelands could be reduced by more than −80 %. These decreases are driven by the projected warming and are strongly connected to an important decrease in snowfall frequency and snowfall fraction and are also apparent for heavy snowfall events. In contrast, high-elevation regions could experience slight snowfall increases in midwinter for both emission scenarios despite the general decrease in the snowfall fraction. These increases in mean and heavy snowfall can be explained by a general increase in winter precipitation and by the fact that, with increasing temperatures, climatologically cold areas are shifted into a temperature interval which favours higher snowfall intensities. In general, percentage changes in snowfall indices are robust with respect to the RCM postprocessing strategy employed: similar results are obtained for raw, separated, and separated-bias-adjusted snowfall amounts. Absolute changes, however, can differ among these three methods.

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“…Since at low altitudes the snow pack is temperature limited (see Scherrer et al, 2004) this trend reversal seems to be linked to the 'plateauing' or even slightly decreasing temperature in Switzerland. Figure 10 shows the absolute mean winter (DJF) temperatures for three different altitude bands (400-500 m asl, 700-800 m asl and 1000-1100 m asl) in the period 1961-2010 using the gridded 2 km temperature data set introduced in Ceppi et al (2012). It shows that DJF temperatures have generally increased from values somewhat below 0 • C in the 1960s to values around or above 0 • C in the more recent time.…”

Section: Trend Analysis: Combining the Long Series With Other Snow Obmentioning

confidence: 99%

Snow variability in the Swiss Alps 1864–2009

Scherrer

Wüthrich

Croci-Maspoli

et al. 2013

Intl Journal of Climatology

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ABSTRACT:We present a climate analysis of nine unique Swiss Alpine new snow series that have been newly digitized. The stations cover different altitudes (450-1860 m asl) and all time series cover more than 100 years (one from 1864 to 2009). In addition, data from 71 stations for the last 50-80 years for new snow and snow depth are analysed to get a more complete picture of the Swiss Alpine snow variability. Important snow climate indicators such as new snow sums (NSS), maximum new snow (MAXNS) and days with snowfall (DWSF) are calculated and variability and trends analysed. Series of days with snow pack (DWSP) ≥ 1 cm are reconstructed with useful quality for six stations using the daily new snow, local temperature and precipitation data. Our results reveal large decadal variability with phases of low and high values for NSS, DWSF and DWSP. For most stations NSS, DWSF and DWSP show the lowest values recorded and unprecedented negative trends in the late 1980s and 1990s. For MAXNS, however, no clear trends and smaller decadal variability are found but very large MAXNS values (>60 cm) are missing since the year 2000. The fraction of NSS and DWSP in different seasons (autumn, winter and spring) has changed only slightly over the ∼150 year record. Some decreases most likely attributable to temperature changes in the last 50 years are found for spring, especially for NSS at low stations. Both the NSS and DWSP snow indicators show a trend reversal in most recent years (since 2000), especially at low and medium altitudes. This is consistent with the recent 'plateauing' (i.e. slight relative decrease) of mean winter temperature in Switzerland and illustrates how important decadal variability is in understanding the trends in key snow indicators.

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Revisiting Swiss temperature trends 1959–2008

Cited by 156 publications

References 30 publications

Localized climate change scenarios of mean temperature and precipitation over Switzerland

Localized climate change scenarios of mean temperature and precipitation over Switzerland

Future snowfall in the Alps: projections based on the EURO-CORDEX regional climate models

Snow variability in the Swiss Alps 1864–2009

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