Sebastian Sippel

Beyond climatological extremes - assessing how the odds of hydrometeorological extreme events in South-East Europe change in a warming climate

With record breaking heat waves, dryness, and floods in several parts of the world in recent years the question arises whether and to what extent the hazard of hydrometeorological extreme weather events has changed, and if changes can be attributed to specific causes. The methodology of probabilistic event attribution allows to evaluate such potential changes in the occurence probabilities of particular types of extreme events. We show that such a probabilistic assessment not only provides information on changing hazards in hydrometerological events but also permits statements about multivariate combinations of hydrometeorological variables. Hence attribution studies could be targeted specifically towards relevant impacts in particular sectors, if different suitable multivariate proxies are used. We demonstrate our methodology by using combinations of temperature, precipitation and humidity in the large ensemble of climate simulations within the weather@home project in order to derive impact-relevant quantities such as a seasonal water balance and heat stress imposed on the human body. Finally, we estimate the hazard probabilities of those events in South-East Europe, a region that has recently experienced severe summer dryness (2012) in combination with multiple heat waves.

Quantifying changes in climate variability and extremes: Pitfalls and their overcoming

Hot temperature extremes have increased substantially in frequency and magnitude over past decades. A widely used approach to quantify this phenomenon is standardizing temperature data relative to the local mean and variability of a reference period. Here we demonstrate that this conventional procedure leads to exaggerated estimates of increasing temperature variability and extremes. For example, the occurrence of ‘2-sigma extremes’ would be overestimated by 48.2% compared to a given reference period of 30 years with time-invariant simulated Gaussian data. This corresponds to an increase from a 2.0% to 2.9% probability of such events. We derive an analytical correction revealing that these artifacts prevail in recent studies. Our analyses lead to a revision of earlier reports [e.g. Huntingford et al., 2013]: For instance we show that there is no evidence for a recent increase in normalized temperature variability. In conclusion, we provide an analytical pathway to describe changes in variability and extremes in climate observations and model simulations.

Ecosystem impacts of climate extremes crucially depend on the timing.

The year 1540 was unprecedented in centuries. It was dreadful, bright, and hot. Bright weather and heat... lasted for 29 weeks, in which rain fell on not more than 6 days. ... Meadows and forests were yellow from the heat, and the earth opened large cracks; at several locations, grapes and vine withered, many forests burned, fountains and springs dried out completely... (but) there was an abundance of corn and a lot of delicious wine.Translated from German, a contemporary witness describing the contrasting impacts of a megaheat and drought event of 1540 in Europe (1). The impacts of climate extremes have always been of crucial importance to human societies, but they also play a key role in affecting structure and functioning of ecosystems. Whether there are any impacts at all, and how these impacts manifest themselves, critically depends on the timing, magnitude, extent, and type of the climate anomaly. Although many studies have been undertaken to investigate the impacts of climate extremes on ecosystem functioning, attempts to build an overarching framework have had little success so far and many open questions remain (2). A study published in PNAS (3) provides new insights into the question of how impacts of climate extremes occurring during different periods of the year can interact and counteract each other. Wolf et al. (3) investigated the year 2012 and its impacts on terrestrial carbon fluxes in the continental United States, an extreme year in which a record warm spring was followed by a severely dry and hot summer (4, 5). The authors analyzed three independent streams of observational data and data-driven models, and demonstrated that losses in net carbon uptake during summer were largely offset by unusual carbon gains in spring caused by its record-exceeding warmth and early arrival. In this way, the … [↵][1]1To whom correspondence should be addressed. Email: ssippel{at}bgc-jena.mpg.de. [1]: #xref-corresp-1-1

Stakeholder Perspectives on the Attribution of Extreme Weather Events: An Explorative Enquiry

AbstractRecent extreme weather events and their impacts on societies have highlighted the need for timely adaptation to the changing odds of their occurrence. Such measures require appropriate information about likely changes in event frequency and magnitude on relevant spatiotemporal scales. However, to support robust climate information for decision-making, an effective communication between scientists and stakeholders is crucial. In this context, weather event attribution studies are increasingly raising attention beyond academic circles, although the understanding of how to take it beyond academia is still evolving. This paper presents the results of a study that involved in-depth interviews with stakeholders from a range of sectors about potential applications and the general usefulness of event attribution studies. A case study of the hot and dry summer 2012 in southeast Europe is used as a concrete example, with a focus on the applicability of attribution results across sectors. An analysis of the ...

Diagnosing the dynamics of observed and simulated ecosystem gross primary productivity with time causal information theory quantifiers

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.

The Role of Anthropogenic Warming in 2015 Central European Heat Waves

Summer 2015 in Europe. The summer 2015 in Europe was highly unusual, as persistent heat and dryness prevailed in large parts of the continent. In central and eastern Europe, a combination of record-low seasonal rainfall (Orth et al. 2016) and record-high monthly July/August temperatures were observed over an area stretching from France to western Russia (Supplemental Fig. S11.1). The anomalous temperatures were caused by a sequence of four intense heat waves that struck the region from the end of June to early September (e.g., Fig. 11.1a). It is precisely the few-day heat that causes problems with human health, especially when combined with high humidity (McGregor et al. 2010). We analyze seasonal maxima of 3-day mean temperature (Tair3d, max) and seasonal maxima of 3-day daily maximum wet bulb temperature (WBTX3d, max), a measure of human thermal discomfort that combines temperature and humidity and is a proxy for heat stress on the human body (Fischer and Knutti 2013; Sherwood and Huber 2010). The series of heat waves began with a strongly meandering jet stream, that is summertime “omegablocking” (Dole et al. 2011), and the advection of very warm subtropical air into central and western Europe (Supplemental Fig. S11.1). Later in the season, the jet stream was displaced to the north, so that stable high-pressure systems could prevail over central and eastern Europe bringing heat there. The first heat wave in early July was hence most pronounced in western parts of the continent, while south-central and east-central Europe experienced the highest temperatures in the subsequent heat waves later in the season (Fig. 11.1b). Anomalies in the hottest 3-day mean temperature reached up to +6°C relative to climatology (Figs. 11.1c,d), and temperature records were broken, including nationwide records (Kitzingen, Germany: 40.3°C; https://weather.com/news/climate/news/europe-heat-wave-poland-germany-czech-august-2015), various station records stretching from France to the Balkan countries and southern Sweden (www .meteofrance.fr/actua l ites/26913226-episode -de-tres-fortes-chaleurs-en-france), nighttime temperatures (Vienna, Austria: 26.9°C), record 3-day mean temperatures across central Europe (Fig. 11.1e), and inland water temperatures (e.g., Lake Constance). Europe experienced the hottest August ever recorded (NOAA 2016), and the entire summer season ranked third after the unusual summers of persistent heat in 2003 and 2010 with hotspots in France and western Russia, respectively (Barriopedro et al. 2011; Stott et al. 2004). This extraordinary sequence of events raises the question to what extent human-induced climate change played a role in short-term heat waves beyond natural climate variability. A potential anthropogenic contribution to the summer 2015 heat events had already been investigated in near–real time (www.climatecentral.org /europe-2015-heatwave-climate-change), and in the present paper we build upon and substantiate the previous analysis. We investigate two diagnostics (Tair3d, max and WBTX3d, max) at four locations in longterm station-based observational records and in a large ensemble of consistently bias-corrected regional climate model simulations.

Drought, Heat, and the Carbon Cycle: a Review

Purpose of the ReviewWeather and climate extremes substantially affect global- and regional-scale carbon (C) cycling, and thus spatially or temporally extended climatic extreme events jeopardize terrestrial ecosystem carbon sequestration. We illustrate the relevance of drought and/or heat events (“DHE”) for the carbon cycle and highlight underlying concepts and complex impact mechanisms. We review recent results, discuss current research needs and emerging research topics.Recent FindingsOur review covers topics critical to understanding, attributing and predicting the effects of DHE on the terrestrial carbon cycle: (1) ecophysiological impact mechanisms and mediating factors, (2) the role of timing, duration and dynamical effects through which DHE impacts on regional-scale carbon cycling are either attenuated or enhanced, and (3) large-scale atmospheric conditions under which DHE are likely to unfold and to affect the terrestrial carbon cycle. Recent research thus shows the need to view these events in a broader spatial and temporal perspective that extends assessments beyond local and concurrent C cycle impacts of DHE.SummaryNovel data streams, model (ensemble) simulations, and analyses allow to better understand carbon cycle impacts not only in response to their proximate drivers (drought, heat, etc.) but also attributing them to underlying changes in drivers and large-scale atmospheric conditions. These attribution-type analyses increasingly address and disentangle various sequences or dynamical interactions of events and their impacts, including compensating or amplifying effects on terrestrial carbon cycling.

Extreme heat-related mortality avoided under Paris Agreement goals

In key European cities, stabilizing climate warming at 1.5 °C would decrease extreme heat-related mortality by 15–22% per summer compared with stabilization at 2 °C.

Large‐Scale Droughts Responsible for Dramatic Reductions of Terrestrial Net Carbon Uptake Over North America in 2011 and 2012

This research is funded by National Key R&D Program of China (2016YFA0600202). C. Zhang is partially funded by the National Natural Science Foundation of China (grant 41601054).