Increasing volatility of reconstructed Morava River warm-season flow, Czech Republic

Study region

The Morava River basin, Czech Republic, Danube Basin, Central Europe.

Study focus

Hydrological summer extremes represent a prominent natural hazard in Central Europe. River low flows constrain transport and water supply for agriculture, industry and society, and flood events are known to cause material damage and human loss. However, understanding changes in the frequency and magnitude of hydrological extremes is associated with great uncertainty due to the limited number of gauge observations. Here, we compile a tree-ring network to reconstruct the July-September baseflow variability of the Morava River from 1745 to 2018 CE. An ensemble of reconstructions was produced to assess the impact of calibration period length and trend on the long-term mean of reconstruction estimates. The final estimates represent the first baseflow reconstruction based on tree rings from the European continent. Simulated flows and historical documentation provide quantitative and qualitative validation of estimates prior to the 20th century.

New hydrological insights for the region

The reconstructions indicate an increased variability of warm-season flow during the past 100 years, with the most extreme high and low flows occurring after the start of instrumental observations. When analyzing the entire reconstruction, the negative trend in baseflow displayed by gauges across the basin after 1960 is not unprecedented. We conjecture that even lower flows could likely occur in the future considering that pre-instrumental trends were not primarily driven by rising temperature (and the evaporative demand) in contrast to the recent trends.

On automatic bias reduction for extreme expectile estimation

Expectiles induce a law-invariant risk measure that has recently gained popularity in actuarial and financial risk management applications. Unlike quantiles or the quantile-based Expected Shortfall, the expectile risk measure is coherent and elicitable. The estimation of extreme expectiles in the heavy-tailed framework, which is reasonable for extreme financial or actuarial risk management, is not without difficulties; currently available estimators of extreme expectiles are typically biased and hence may show poor finite-sample performance even in fairly large samples. We focus here on the construction of bias-reduced extreme expectile estimators for heavy-tailed distributions. The rationale for our construction hinges on a careful investigation of the asymptotic proportionality relationship between extreme expectiles and their quantile counterparts, as well as of the extrapolation formula motivated by the heavy-tailed context. We accurately quantify and estimate the bias incurred by the use of these relationships when constructing extreme expectile estimators. This motivates the introduction of classes of bias-reduced estimators whose asymptotic properties are rigorously shown, and whose finite-sample properties are assessed on a simulation study and three samples of real data from economics, insurance and finance.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11222-022-10118-x.

Erratic Asian summer monsoon 2020: COVID-19 lockdown initiatives possible cause for these episodes?

The summer (June through September) monsoon 2020 has been very erratic with episodes of heavy and devastating rains, landslides and catastrophic winds over South Asia (India, Pakistan, Nepal, Bangladesh), East Asia (China, Korea, and Japan), and Southeast Asia (Singapore, Thailand, Vietnam, Laos, Cambodia, Philippines, Indonesia). The withdrawal of the summer monsoon over India was delayed by 2 weeks. The monsoon season over East Asia has been the longest. China recorded a Dam burst in the twentieth century. Furthermore, the Korean Peninsula has experienced back-to-back severe tropical cyclones. Could the lockdown activities initiate to control the COVID-19 spread a possible cause for these major episodes? The strict enforcement of the lockdown regulations has led to a considerable reduction of air pollutants-dust and aerosols throughout the world. A recent study based on satellites and merged products has documented a statistically significant mean reduction of about 20, 8, and 50% in nitrogen dioxide, Aerosol Optical Depth (AOD) and PM_2.5 concentrations, respectively over the megacities across the globe. Our analysis reveals a considerable reduction of about 20% in AOD over South as well as over East Asia, more-over East Asia than over South Asia. The reduced aerosols have impacted the strength of the incoming solar radiation as evidenced by enhanced warming, more-over the land than the oceans. The differential warming over the land and the ocean has resulted in the amplification of the meridional ocean-land thermal contrast and strengthening of the monsoon flow. These intense features have supported the surplus transport of moisture from the oceans towards the main lands. Some similarity between the anomalous rainfall pattern and the anomalous AOD pattern is discernable. In particular, the enhancement of rainfall, the reduction in AOD and the surface temperature warming match very well over two regions one over West-Central India and the other over the Yangzte River Valley. Results further reveal that the heavy rains over the Yangzte River Valley could be associated with the preceding reduced aerosols, while the heavy rains over West-Central India could be associated with reduced aerosols and also due to the surface temperature warming.

Prolonged Siberian heat of 2020 almost impossible without human influence

Over the first half of 2020, Siberia experienced the warmest period from January to June since records began and on the 20th of June the weather station at Verkhoyansk reported 38 °C, the highest daily maximum temperature recorded north of the Arctic Circle. We present a multi-model, multi-method analysis on how anthropogenic climate change affected the probability of these events occurring using both observational datasets and a large collection of climate models, including state-of-the-art higher-resolution simulations designed for attribution and many from the latest generation of coupled ocean-atmosphere models, CMIP6. Conscious that the impacts of heatwaves can span large differences in spatial and temporal scales, we focus on two measures of the extreme Siberian heat of 2020: January to June mean temperatures over a large Siberian region and maximum daily temperatures in the vicinity of the town of Verkhoyansk. We show that human-induced climate change has dramatically increased the probability of occurrence and magnitude of extremes in both of these (with lower confidence for the probability for Verkhoyansk) and that without human influence the temperatures widely experienced in Siberia in the first half of 2020 would have been practically impossible.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10584-021-03052-w.

Modelling the epidemic extremities of dengue transmissions in Thailand

Significant health risks arise in Thailand from dengue but little work has been conducted to quantify the extremities of dengue outbreaks - where health systems are likely to be most stretched. In this paper, we detail the utility of tools derived from extreme value theory (EVT) in modelling the extremes in dengue case counts observed during outbreaks using 25 years of province level dengue case count data in Thailand from 1993 to 2018. We assess the validity of the EVT toolkit by comparing them against 8 competing benchmarks. The inhomogeneous point process representation (IPP) was found to perform best on 5 in and out of sample criterion such as parameter stability, distributional characteristics and out of sample coverage. Lastly, by using the IPP to infer future extreme dengue events, IPP found stark differences at the province level in the mean level of dengue case counts that is expected to be exceeded over the next 10 years. The IPP model also found that high probability that dengue extreme events will reach levels above and beyond the observed historical maximums. EVT shows considerable potential in aiding health planners for the risk management of dengue. The results in this paper can be easily translatable to any infectious disease observed over a long period.

Future projections of record-breaking sea surface temperature and cyanobacteria bloom events in the Baltic Sea

Aiming to inform both marine management and the public, coupled environmental-climate scenario simulations for the future Baltic Sea are analyzed. The projections are performed under two greenhouse gas concentration scenarios (medium and high-end) and three nutrient load scenarios spanning the range of plausible socio-economic pathways. Assuming an optimistic scenario with perfect implementation of the Baltic Sea Action Plan (BSAP), the projections suggest that the achievement of Good Environmental Status will take at least a few more decades. However, for the perception of the attractiveness of beach recreational sites, extreme events such as tropical nights, record-breaking sea surface temperature (SST), and cyanobacteria blooms may be more important than mean ecosystem indicators. Our projections suggest that the incidence of record-breaking summer SSTs will increase significantly. Under the BSAP, record-breaking cyanobacteria blooms will no longer occur in the future, but may reappear at the end of the century in a business-as-usual nutrient load scenario.

Record breaking achievements by spiders and the scientists who study them

Organismal biology has been steadily losing fashion in both formal education and scientific research. Simultaneous with this is an observable decrease in the connection between humans, their environment, and the organisms with which they share the planet. Nonetheless, we propose that organismal biology can facilitate scientific observation, discovery, research, and engagement, especially when the organisms of focus are ubiquitous and charismatic animals such as spiders. Despite being often feared, spiders are mysterious and intriguing, offering a useful foundation for the effective teaching and learning of scientific concepts and processes. In order to provide an entryway for teachers and students-as well as scientists themselves-into the biology of spiders, we compiled a list of 99 record breaking achievements by spiders (the "Spider World Records"). We chose a world-record style format, as this is known to be an effective way to intrigue readers of all ages. We highlighted, for example, the largest and smallest spiders, the largest prey eaten, the fastest runners, the highest fliers, the species with the longest sperm, the most venomous species, and many more. We hope that our compilation will inspire science educators to embrace the biology of spiders as a resource that engages students in science learning. By making these achievements accessible to non-arachnologists and arachnologists alike, we suggest that they could be used: (i) by educators to draw in students for science education, (ii) to highlight gaps in current organismal knowledge, and (iii) to suggest novel avenues for future research efforts. Our contribution is not meant to be comprehensive, but aims to raise public awareness on spiders, while also providing an initial database of their record breaking achievements.

Attributing extreme fire risk in Western Canada to human emissions

Canada is expected to see an increase in fire risk under future climate projections. Large fires, such as that near Fort McMurray, Alberta in 2016, can be devastating to the communities affected. Understanding the role of human emissions in the occurrence of such extreme fire events can lend insight into how these events might change in the future. An event attribution framework is used to quantify the influence of anthropogenic forcings on extreme fire risk in the current climate of a western Canada region. Fourteen metrics from the Canadian Forest Fire Danger Rating System are used to define the extreme fire seasons. For the majority of these metrics and during the current decade, the combined effect of anthropogenic and natural forcing is estimated to have made extreme fire risk events in the region 1.5 to 6 times as likely compared to a climate that would have been with natural forcings alone.

Comparing regional precipitation and temperature extremes in climate model and reanalysis products

A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.

Decadal-Scale Forecasting of Climate Drivers for Marine Applications

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales.

Multilevel quantile function modeling with application to birth outcomes

Infants born preterm or small for gestational age have elevated rates of morbidity and mortality. Using birth certificate records in Texas from 2002 to 2004 and Environmental Protection Agency air pollution estimates, we relate the quantile functions of birth weight and gestational age to ozone exposure and multiple predictors, including parental age, race, and education level. We introduce a semi-parametric Bayesian quantile approach that models the full quantile function rather than just a few quantile levels. Our multilevel quantile function model establishes relationships between birth weight and the predictors separately for each week of gestational age and between gestational age and the predictors separately across Texas Public Health Regions. We permit these relationships to vary nonlinearly across gestational age, spatial domain and quantile level and we unite them in a hierarchical model via a basis expansion on the regression coefficients that preserves interpretability. Very low birth weight is a primary concern, so we leverage extreme value theory to supplement our model in the tail of the distribution. Gestational ages are recorded in completed weeks of gestation (integer-valued), so we present methodology for modeling quantile functions of discrete response data. In a simulation study we show that pooling information across gestational age and quantile level substantially reduces MSE of predictor effects. We find that ozone is negatively associated with the lower tail of gestational age in south Texas and across the distribution of birth weight for high gestational ages. Our methods are available in the R package BSquare.

Precipitation Extremes Under Climate Change

The response of precipitation extremes to climate change is considered using results from theory, modeling, and observations, with a focus on the physical factors that control the response. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate. However, the sensitivity of precipitation extremes to warming remains uncertain when convection is important, and it may be higher in the tropics than the extratropics. Several physical contributions govern the response of precipitation extremes. The thermodynamic contribution is robust and well understood, but theoretical understanding of the microphysical and dynamical contributions is still being developed. Orographic precipitation extremes and snowfall extremes respond differently from other precipitation extremes and require particular attention. Outstanding research challenges include the influence of mesoscale convective organization, the dependence on the duration considered, and the need to better constrain the sensitivity of tropical precipitation extremes to warming.

21st century climate change in the European Alps--a review

Reliable estimates of future climate change in the Alps are relevant for large parts of the European society. At the same time, the complex Alpine region poses considerable challenges to climate models, which translate to uncertainties in the climate projections. Against this background, the present study reviews the state-of-knowledge about 21st century climate change in the Alps based on existing literature and additional analyses. In particular, it explicitly considers the reliability and uncertainty of climate projections. Results show that besides Alpine temperatures, also precipitation, global radiation, relative humidity, and closely related impacts like floods, droughts, snow cover, and natural hazards will be affected by global warming. Under the A1B emission scenario, about 0.25 °C warming per decade until the mid of the 21st century and accelerated 0.36 °C warming per decade in the second half of the century is expected. Warming will probably be associated with changes in the seasonality of precipitation, global radiation, and relative humidity, and more intense precipitation extremes and flooding potential in the colder part of the year. The conditions of currently record breaking warm or hot winter or summer seasons, respectively, may become normal at the end of the 21st century, and there is indication for droughts to become more severe in the future. Snow cover is expected to drastically decrease below 1500-2000 m and natural hazards related to glacier and permafrost retreat are expected to become more frequent. Such changes in climatic parameters and related quantities will have considerable impact on ecosystems and society and will challenge their adaptive capabilities.