Stefan Muthers

Tambora 1815 as a test case for high impact volcanic eruptions: Earth system effects

The eruption of Tambora (Indonesia) in April 1815 had substantial effects on global climate and led to the ‘Year Without a Summer’ of 1816 in Europe and North America. Although a tragic event—tens of thousands of people lost their lives—the eruption also was an ‘experiment of nature’ from which science has learned until today. The aim of this study is to summarize our current understanding of the Tambora eruption and its effects on climate as expressed in early instrumental observations, climate proxies and geological evidence, climate reconstructions, and model simulations. Progress has been made with respect to our understanding of the eruption process and estimated amount of SO2 injected into the atmosphere, although large uncertainties still exist with respect to altitude and hemispheric distribution of Tambora aerosols. With respect to climate effects, the global and Northern Hemispheric cooling are well constrained by proxies whereas there is no strong signal in Southern Hemisphere proxies. Newly recovered early instrumental information for Western Europe and parts of North America, regions with particularly strong climate effects, allow Tamboras effect on the weather systems to be addressed. Climate models respond to prescribed Tambora‐like forcing with a strengthening of the wintertime stratospheric polar vortex, global cooling and a slowdown of the water cycle, weakening of the summer monsoon circulations, a strengthening of the Atlantic Meridional Overturning Circulation, and a decrease of atmospheric CO2. Combining observations, climate proxies, and model simulations for the case of Tambora, a better understanding of climate processes has emerged. WIREs Clim Change 2016, 7:569–589. doi: 10.1002/wcc.407 This article is categorized under: 1 Paleoclimates and Current Trends > Paleoclimate

A glossary for biometeorology

Here we present, for the first time, a glossary of biometeorological terms. The glossary aims to address the need for a reliable source of biometeorological definitions, thereby facilitating communication and mutual understanding in this rapidly expanding field. A total of 171 terms are defined, with reference to 234 citations. It is anticipated that the glossary will be revisited in coming years, updating terms and adding new terms, as appropriate. The glossary is intended to provide a useful resource to the biometeorology community, and to this end, readers are encouraged to contact the lead author to suggest additional terms for inclusion in later versions of the glossary as a result of new and emerging developments in the field.

The role of cold stress in predicting extra cardiovascular and respiratory admissions

Although several studies have examined effects of air temperature and/or other meteorological variables separately on disease rates, the relationship of meteorological variables and human disease is, in fact, rather complex in the “real-world” [1,2] including the number of potential variables to be considered and their weighting. In other words, 1 °C of air temperature difference in a warm climate may not necessarily mean the same in a cold climate across regions on Earth [3,4]. Why some seasonality was observed in certain regions at certain times only is likely due in part to the imprecise weather estimation from mean, maximum, or minimum air temperature or the definition of study catchments or time period to be included.

Application and comparison of UTCI and PET in temperate climate conditions

the assessment of the thermal bioclimate is based on the human energy balance and derived indices such as Physiologically equivalent temperature (Pet) or Universal thermal Climate index (UtCi). these two indices were compared over a period of ten year based on hourly data in a middle european city with a temperate climate. the analysis performed shows that the differences obtained result from the different thermophysiological settings of clothing insulation. for conditions with extremely high vapour pressure values, UtCi yields higher values than Pet, which could describe the thermophysiological stress more appropriately.

Assessment of tourism and recreation destinations under climate change conditions in Austria

To urism and recreation are important economic factors which are directly connected to weather and climate of a specific destination. Based on the observation network of the Central Institute of Meteorology and Geodynamics of Austria (ZAMG), data of 37 stations has been collected and analysed for tourism and recreation purposes. The analysis was based on long term data sets which were processed in relevant ways for tourism and recreation, resulting in frequency diagrams of Physiologically Equivalent Temperature (PET) and precipitation. Additionally, we prepared the results according to the demands of tourism and recreation authorities and industry using the Climate-Tourism/Transfer-Information-Scheme (CTIS). Applying data from the regional climate models REMO and CLM we can provide information on future climate conditions in Austria’s recreation areas. We chose two different time slices (2021–2050, 2071–2100) and IPCC emission scenarios (A1B, B1). The data was processed based on the threshold factors which are included in the CTIS (e.g. thermal comfort, heat stress, cold stress, sunshine, etc.). For the time slice 2021–2050 only moderate changes can be expected. But for 2071–2100 one can observe a distinct decrease of cold stress and the skiing potential. On the other hand, moderate increases of thermal comfort, heat stress, sultriness and sunshine are expected. No tendencies can be seen in precipitation and wind conditions.

Stratospheric age of air variations between 1600 and 2100

The current understanding of preindustrial stratospheric age of air (AoA), its variability, and the potential natural forcing imprint on AoA is very limited. Here we assess the influence of natural and anthropogenic forcings on AoA using ensemble simulations for the period 1600 to 2100 and sensitivity simulations for different forcings. The results show that from 1900 to 2100, CO₂ and ozone-depleting substances are the dominant drivers of AoA variability. With respect to natural forcings, volcanic eruptions cause the largest AoA variations on time scales of several years, reducing the age in the middle and upper stratosphere and increasing the age below. The effect of the solar forcing on AoA is small and dominated by multidecadal total solar irradiance variations, which correlate negatively with AoA. Additionally, a very weak positive relationship driven by ultraviolett variations is found, which is dominant for the 11 year cycle of solar variability.

Use of beanplots in applied climatology A comparison with boxplots

Boxplots have been a widely used technique for descriptive statistics for many years. They have the advantage of being easy to compute and displaying five important values that summarize the data under investigation. However, earlier studies revealed some problems in the interpretation of boxplots by non-scientific observers; besides with todays computation possibilities, more information can be displayed in the same space. Therefore an alternative to the boxplot, the beanplot according to KA M PSTRA, 2008, is presented by means of some typical example from climatological research.

Decadal to multi-decadal scale variability of Indian summer monsoon rainfall in the coupled ocean-atmosphere-chemistry climate model SOCOL-MPIOM

The present study is an effort to deepen the understanding of Indian summer monsoon rainfall (ISMR) on decadal to multi-decadal timescales. We use ensemble simulations for the period AD 1600–2000 carried out by the coupled Atmosphere-Ocean-Chemistry-Climate Model (AOCCM) SOCOL-MPIOM. Firstly, the SOCOL-MPIOM is evaluated using observational and reanalyses datasets. The model is able to realistically simulate the ISMR as well as relevant patterns of sea surface temperature and atmospheric circulation. Further, the influence of Atlantic Multi-decadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) variability on ISMR is realistically simulated. Secondly, we investigate the impact of internal climate variability and external climate forcings on ISMR on decadal to multi-decadal timescales over the past 400 years. The results show that AMO, PDO, and Total Solar Irradiance (TSI) play a considerable role in controlling the wet and dry decades of ISMR. Resembling observational findings most of the dry decades of ISMR occur during a negative phase of AMO and a simultaneous positive phase of PDO. The observational and simulated datasets reveal that on decadal to multi-decadal timescales the ISMR has consistent negative correlation with PDO whereas its correlation with AMO and TSI is not stationary over time.