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11 IMSC Session Program Anthropogenic influence on long return period daily temperature extremes at regional scales Friday - Parallel Session 6 Francis W. Zwiers, Xuebin Zhang and Yang Feng Climate Research Division, Environment Canada, Toronto, Canada Observed annual extreme temperatures, namely annual maximum daily maximum (TXx) and minimum (TNx) temperatures and annual minimum daily maximum (TXn) and minimum (TNn) temperatures, are compared with those from climate simulations of multiple model ensembles with historical anthropogenic (ANT) forcing and with combined anthropogenic and natural external forcings (ALL) for the period 1961- 2000 at both global and regional scales using a technique that allows us to infer changes in long return period extreme temperatures. We fit generalized extreme value (GEV) distributions to the observed extreme temperatures using a time-evolving pattern of location parameters obtained from model simulated extreme temperatures under ANT or ALL forcing. Evaluation of the parameters of the fitted GEV distributions shows that both ANT and ALL influence can be detected in TNx, TNn, TXn, and TXx at the global scale over the land areas for which there are observations, and also regionally over many large land areas, with detection in more regions in TNx. We therefore conclude that the influence of anthropogenic forcing has had a detectable influence on extreme temperatures that have impacts on human society and natural systems at global and regional scales. External influence is estimated to have resulted in large changes in the likelihood of extreme annual maximum and minimum daily temperatures. Globally, waiting times for events that were expected to recurred once every 20 years in the 1960s are now estimated to exceed 30 years for extreme annual minimum daily maximum temperature and 35 years for extreme annual minimum daily minimum temperature, and to have decreased to less than 10 or 15 years for annual maximum daily minimum and daily maximum temperatures respectively. Abstracts 353
11 IMSC Session Program Spatial characteristics of gridded Swiss temperature trends: Local and large-scale influences Friday - Parallel Session 6 Paulo Ceppi, Simon C. Scherrer and C. Appenzeller Climate Services, Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland Temperature is an essential variable in monitoring the impact of global climate change. Here we perform a detailed regional trend analysis of Swiss Alpine temperatures in the period 1959 to 2008 using a newly available gridded data set based on homogenised observations from 91 MeteoSwiss stations. The aim is to quantify possible large-scale and local-scale contributions to the local trends. It is shown that the yearly trends are all positive and highly significant, with an average warming rate of 0.35 °C/decade, consistent with results from earlier studies. The values show fairly little spatial variability, with 90% of all gridpoint trends between 0.30 and 0.39 °C/decade. This indicates that the warming in Switzerland has exceeded the NH extratropical mean trend by a factor of 1.6 over the last 50 years. On a seasonal scale, the analysis also reveals overall positive temperature trends, but seasonal and spatial variability are pronounced. The weakest trends (mostly insignificant at the 5% level) are observed in autumn (SON, 0.17 °C/decade on average) and early summer features the strongest warming rates, peaking at 0.48 °C/decade in May-June-July. A pronounced altitude dependence is found from late summer to early winter (ASO to NDJ), where the trends decrease with elevation. We investigate the impact of large-scale versus local-scale influences on seasonallyaveraged temperatures using a regression model with atmospheric circulation patterns and northern hemispheric temperatures as explanatory variables. The analysis reveals that 45 (summer) to 80% (winter) of the interannual variability of Swiss gridpoint temperatures can be explained by largescale influences. In spring, summer and autumn, a fraction of up to 20% of the temperature trends remains unexplained by the model. In spring, a positive trend anomaly close to the zero-degree isotherm is not detected by our model, while the largest unexplained trend magnitudes are found at low elevations in autumn and winter. Our results suggest that snow-albedo feedback effects might be responsible for the unexplained 10% higher spring trends near the altitude of the zero degree isotherm and snow line. In autumn, the observed decrease in mist and fog frequency may be a key process explaining the 20% higher Swiss autumn temperature trends at low elevations. Changes in soil-atmosphere interactions could explain part of the difference between observed and modelled trends in summer. For the unexplained lower than modelled temperature trends in late winter at low altitudes the physical mechanisms remain to be determined. Abstracts 354
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