Jana Sillmann

Extreme Cold Winter Temperatures in Europe under the Influence of North Atlantic Atmospheric Blocking

North Atlantic atmospheric blocking conditions explain part of the winter climate variability in Europe, being associated with anomalous cold winter temperatures. In this study, the generalized extreme value (GEV) distribution isfitted tomonthlyminimaof Europeanwinter6-hourlyminimumtemperatures fromthe ECHAM5/MPI-OM global climate model simulations and the ECMWF reanalysis product known as ERA40, with an indicator for atmospheric blocking conditions being used as covariate. It is demonstrated that relating the location and scale parameter of the GEV distribution to atmospheric blocking improves the fit to extreme minimum temperatures in large areas of Europe. The climate model simulations agree reasonably with ERA-40 in the present climate (1961‐2000). Under the influence of atmospheric blocking, a decrease in the 0.95th quantiles of extreme minimum temperatures can be distinguished. This cooling effect of atmospheric blocking is, however, diminished in future climate simulations because of a shift in blocking location, and thus reduces the chances of very cold winters in northeastern parts of Europe.

Magnitude of extreme heat waves in present climate and their projection in a warming world

An extreme heat wave occurred in Russia in the summer of 2010. It had serious impacts on humans and natural ecosystems, it was the strongest recorded globally in recent decades and exceeded in amplitude and spatial extent the previous hottest European summer in 2003. Earlier studies have not succeeded in comparing the magnitude of heat waves across continents and in time. This study introduces a new Heat Wave Magnitude Index that can be compared over space and time. The index is based on the analysis of daily maximum temperature in order to classify the strongest heat waves that occurred worldwide during the three study periods 1980–1990, 1991–2001, and 2002–2012. In addition, multimodel ensemble outputs from the Coupled Model Intercomparison Project Phase 5 are used to project future occurrence and severity of heat waves, under different Representative Concentration Pathways, adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5). Results show that the percentage of global area affected by heat waves has increased in recent decades. Moreover, model predictions reveal an increase in the probability of occurrence of extreme and very extreme heat waves in the coming years, in particular, by the end of this century, under the most severe IPCC AR5 scenario, events of the same severity as that in Russia in the summer of 2010 will become the norm and are projected to occur as often as every 2 years for regions such as southern Europe, North America, South America, Africa, and Indonesia.

Top ten European heatwaves since 1950 and their occurrence in the coming decades

The Russian heatwave in 2010 killed tens of thousands of people, and was by far the worst event in Europe since at least 1950, according to recent studies and a novel universal heatwave index capturing both the duration and magnitude of heatwaves. Here, by taking an improved version of this index, namely the heat wave magnitude index daily, we rank the top ten European heatwaves that occurred in the period 1950–2014, and show the spatial distribution of the magnitude of the most recent heatwave in summer 2015. We demonstrate that all these events had a strong impact reported in historical newspapers. We further reveal that the 1972 heatwave in Finland had a comparable spatial extent and magnitude as the European heatwave of 2003, considered the second strongest heatwave of the observational era. In the next two decades (2021–2040), regional climate projections suggest that Europe experiences an enhanced probability for heatwaves comparable to or greater than the magnitude, extent and duration of the Russian heatwave in 2010. We demonstrate that the probability of experiencing a major European heatwave in the coming decades is higher in RCP8.5 than RCP4.5 even though global mean temperature projections do not differ substantially. This calls for a proactive vulnerability assessment in Europe in support of formulating heatwave adaptation strategies to reduce the adverse impacts of heatwaves.

Consistency of Temperature and Precipitation Extremes across Various Global Gridded In Situ and Reanalysis Datasets

AbstractChanges in climate extremes are often monitored using global gridded datasets of climate extremes based on in situ observations or reanalysis data. This study assesses the consistency of temperature and precipitation extremes between these datasets. Both the temporal evolution and spatial patterns of annual extremes of daily values are compared across multiple global gridded datasets of in situ observations and reanalyses to make inferences on the robustness of the obtained results.While normalized time series generally compare well, the actual values of annual extremes of daily data differ systematically across the different datasets. This is partly related to different computational approaches when calculating the gridded fields of climate extremes. There is strong agreement between extreme temperatures in the different in situ–based datasets. Larger differences are found for temperature extremes from the reanalyses, particularly during the presatellite era, indicating that reanalyses are most c...

A multimodel examination of climate extremes in an idealized geoengineering experiment

Temperature and precipitation extremes are examined in the Geoengineering Model Intercomparison Project experiment G1, wherein an instantaneous quadrupling of CO2 from its preindustrial control value is offset by a commensurate reduction in solar irradiance. Compared to the preindustrial climate, changes in climate extremes under G1 are generally much smaller than under 4 × CO2 alone. However, it is also the case that extremes of temperature and precipitation in G1 differ significantly from those under preindustrial conditions. Probability density functions of standardized anomalies of monthly surface temperature T and precipitation P in G1 exhibit an extension of the high-T tail over land, of the low-T tail over ocean, and a shift of P to drier conditions. Using daily model output, we analyzed the frequency of extreme events, such as the coldest night (TNn), warmest day (TXx), and maximum 5 day precipitation amount, and also duration indicators such as cold and warm spells and consecutive dry days. The strong heating at northern high latitudes simulated under 4 × CO2 is much alleviated in G1, but significant warming remains, particularly for TNn compared to TXx. Internal feedbacks lead to regional increases in absorbed solar radiation at the surface, increasing temperatures over Northern Hemisphere land in summer. Conversely, significant cooling occurs over the tropical oceans, increasing cold spell duration there. Globally, G1 is more effective in reducing changes in temperature extremes compared to precipitation extremes and for reducing changes in precipitation extremes versus means but somewhat less effective at reducing changes in temperature extremes compared to means.

Observed and simulated temperature extremes during the recent warming hiatus

The discrepancy between recent observed and simulated trends in global mean surface temperature has provoked a debate about possible causes and implications for future climate change projections. However, little has been said in this discussion about observed and simulated trends in global temperature extremes. Here we assess trend patterns in temperature extremes and evaluate the consistency between observed and simulated temperature extremes over the past four decades (1971–2010) in comparison to the recent 15 years (1996–2010). We consider the coldest night and warmest day in a year in the observational dataset HadEX2 and in the current generation of global climate models (CMIP5). In general, the observed trends fall within the simulated range of trends, with better consistency for the longer period. Spatial trend patterns differ for the warm and cold extremes, with the warm extremes showing continuous positive trends across the globe and the cold extremes exhibiting a coherent cooling pattern across the Northern Hemisphere mid-latitudes that has emerged in the recent 15 years and is not reproduced by the models. This regional inconsistency between models and observations might be a key to understanding the recent hiatus in global mean temperature warming.

When will unusual heat waves become normal in a warming Africa

Africa is one of the most vulnerable continents to climate change. In the upcoming decades the occurrence of longer, hotter and more frequent heat waves could have a strong impact on human mortality and crop production. Here, by applying the heat wave magnitude index daily to temperature reanalysis data, we quantify the magnitude and the spatial extent of the most extreme heat waves experienced in Africa between 1979 and October 2015 across different seasons. Results show that in the recent years Africa experienced hotter, longer and more extent heat waves than in the last two decades of the 20th century. In the future, 50% of regional climateprojections suggest that heat waves that are unusual under present climate conditions will occur on a regular basis by 2040 under the most severe IPCC AR5 scenario (i.e. RCP8.5).

Synoptic and meteorological drivers of extreme ozone concentrations over Europe

The present work assesses the relationship between local and synoptic meteorological conditions and surface ozone concentration over Europe in spring and summer months, during the period 1998–2012 using a new interpolated data set of observed surface ozone concentrations over the European domain. Along with local meteorological conditions, the influence of large-scale atmospheric circulation on surface ozone is addressed through a set of airflow indices computed with a novel implementation of a grid-by-grid weather type classification across Europe. Drivers of surface ozone over the full distribution of maximum daily 8 h average values are investigated, along with drivers of the extreme high percentiles and exceedances or air quality guideline thresholds. Three different regression techniques are applied: multiple linear regression to assess the drivers of maximum daily ozone, logistic regression to assess the probability of threshold exceedances and quantile regression to estimate the meteorological influence on extreme values, as represented by the 95th percentile. The relative importance of the input parameters (predictors) is assessed by a backward stepwise regression procedure that allows the identification of the most important predictors in each model. Spatial patterns of model performance exhibit distinct variations between regions. The inclusion of the ozone persistence is particularly relevant over southern Europe. In general, the best model performance is found over central Europe, where the maximum temperature plays an important role as a driver of maximum daily ozone as well as its extreme values, especially during warmer months.

PDRMIP: A Precipitation Driver and Response Model Intercomparison Project—Protocol and Preliminary Results

As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of inter-model differences unaccounted for. Individual drivers of climate change initially alter the energy budget of the atmosphere leading to distinct rapid adjustments involving changes in precipitation. Differences in how these rapid adjustment processes manifest themselves within models are likely to explain a large fraction of the present model spread and needs better quantifications to improve precipitation predictions. Here, we introduce the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where a set of idealized experiments designed to understand the role of different climate forcing mechanisms were performed by a large set of climate models. PDRMIP focuses on understanding how precipitation changes relating to rapid adjustments and slower responses to climate forcings are represented across models. Initial results show that rapid adjustments account for large regional differences in hydrological sensitivity across multiple drivers. The PDRMIP results are expected to dramatically improve our understanding of the causes of the present diversity in future climate projections.

The Influence of Atmospheric Blocking on Extreme Winter Minimum Temperatures in North America

AbstractRegional climate models (RCMs) are the primary source of high-resolution climate projections, and it is of crucial importance to evaluate their ability to simulate extreme events under current climate conditions. Many extreme events are influenced by circulation features that occur outside, or on the edges of, RCM domains. Thus, it is of interest to know whether such dynamically controlled aspects of extremes are well represented by RCMs. This study assesses the relationship between upstream blocking and cold temperature extremes over North America in observations, reanalysis products (ERA-Interim and NARR), and RCMs (CanRCM4, CRCM5, HIRHAM5, and RCA4). Generalized extreme value distributions were fitted to winter minimum temperature (TNn) incorporating blocking frequency (BF) as a covariate, which is shown to have a significant influence on TNn. The magnitude of blocking influence in the RCMs is consistent with observations, but the spatial extent varies. CRCM5 and HIRHAM5 reproduce the pattern o...