Changes of snow cover in Poland

The present paper examines variability of characteristics of snow cover (snow cover depth, number of days with snow cover and dates of beginning and end of snow cover) in Poland. The study makes use of a set of 43 long time series of observation records from the stations in Poland, from 1952 to 2013. To describe temporal changes in snow cover characteristics, the intervals of 1952–1990 and of 1991–2013 are compared and trends in analysed data are sought (e.g., using the Mann–Kendall test). Observed behaviour of time series of snow-related variables is complex and not easy to interpret, for instance because of the location of the research area in the zone of transitional moderate climate, where strong variability of climate events is one of the main attributes. A statistical link between the North Atlantic Oscillation (NAO) index and the snow cover depth, as well as the number of snow cover days is found.     

Changes in daily temperature and precipitation extremes in the Yellow River Basin, China

Spatiotemporal changes in climatic extremes in the Yellow River Basin from 1959 to 2008 were investigated on the basis of a suite of 27 climatic indices derived from daily temperature and precipitation data from 75 meteorological stations with the help of the Mann–Kendall test, linear regression method and GIS technique. Furthermore, the changes in the probability distribution of the extreme indices were examined. The results indicate: (1) The whole basin is dominated by significant increase in the frequency of warm days and warm nights, and dominated by significant decrease in the frequency of cold days and cold nights. Although trends in absolute temperature indices show less spatial coherence compared with that in the percentile-based temperature indices, overall increasing trends can be found in Max Tmax (TXx), Min Tmax (TXn), Max Tmin (TNx) and Min Tmin (TNn). (2) Although the spatial patterns and the number of stations with significant changes for threshold and duration temperature indices are also not identical, general positive trends in warm indices (i.e., summer days (SU25), tropical nights (TR20), warm spell duration indicator and growing season length) and negative trends in cold indices (i.e., frost days, ice days and cold spell duration indicator) can be found in the basin. Annual nighttime temperature has increased at a faster rate than that in daytime temperature, leading to obvious decrease in diurnal temperature range. (3) The changes in precipitation indices are much weaker and less spatially coherent compared with these of temperature indices. For all precipitation indices, only few stations are characterized by significantly change in extreme precipitation, and their spatial patterns are always characterized by irregular and insignificant positive and negative changes. However, generally, changes in precipitation extremes present drying trends, although most of the changes are insignificant. (4) Results at seasonal scale show that warming trends occur for all seasons, particularly in winter. Different from that in other three seasons, general positive trends in max 1-day precipitation (Rx1DAY) and max 5-day precipitation (Rx5DAY) are found in winter. Analysis of changes in probability distributions of indices for 1959–1983 and 1984–2008 indicate a remarkable shift toward warmer condition and a less pronounced tendency toward drier condition during the past decades. The results can provide beneficial reference to water resource and eco-environment management strategies in the Yellow River Basin for associated policymakers and stakeholders.     

Seasonal temperature extremes in Potsdam

The awareness of global warming is well established and results from the observations made on thousands of stations. This paper complements the large-scale results by examining a long time-series of high-quality temperature data from the Secular Meteorological Station in Potsdam, where observation records over the last 117 years, i.e., from January 1893 are available. Tendencies of change in seasonal temperature-related climate extremes are demonstrated. “Cold” extremes have become less frequent and less severe than in the past, while “warm” extremes have become more frequent and more severe. Moreover, the interval of the occurrence of frost has been decreasing, while the interval of the occurrence of hot days has been increasing. However, many changes are not statistically significant, since the variability of temperature indices at the Potsdam station has been very strong.     

Statistics of extremes in hydrology

The statistics of extremes have played an important role in engineering practice for water resources design and management. How recent developments in the statistical theory of extreme values can be applied to improve the rigor of hydrologic applications and to make such analyses more physically meaningful is the central theme of this paper. Such methodological developments primarily relate to maximum likelihood estimation in the presence of covariates, in combination with either the block maxima or peaks over threshold approaches. Topics that are treated include trends in hydrologic extremes, with the anticipated intensification of the hydrologic cycle as part of global climate change. In an attempt to link downscaling (i.e., relating large-scale atmosphere–ocean circulation to smaller-scale hydrologic variables) with the statistics of extremes, statistical downscaling of hydrologic extremes is considered. Future challenges are reviewed, such as the development of more rigorous statistical methodology for regional analysis of extremes, as well as the extension of Bayesian methods to more fully quantify uncertainty in extremal estimation. Examples include precipitation and streamflow extremes, as well as economic damage associated with such extreme events, with consideration of trends and dependence on patterns in atmosphere–ocean circulation (e.g., El Niño phenomenon).     

Entropy estimation of hydrological extremes

The method of Relative Entropy with Fractile constraints (REF method) is explained and applied to model extreme compound hydrological phenomena, such as extreme sea levels under storm conditions. Also presented is a simple method of Tail Entropy Approximation (TEA), which amounts to a correction of traditional statistical estimates for extreme observations.Distribution assumptions are necessary but downplayed in the REF method, relegating the prior distribution to the role of an extrapolation function. The estimates are objective in an information-theoretical sense. They also satisfy a strict requirement of self-consistency that is generally not satisfied by standard statistical methods: invariance under monotonic transformations of the random variable.Historical records of storm surge levels in the Netherlands and annual maximum tidal heights for Sheerness, UK, are used as examples. Comparison is made with distributions obtained using other methods.It is concluded that the tail entropy approximation provides simple, objective estimates of extremes in the tail beyond the range of observations.     

Spectral density regression for bivariate extremes

We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods.     

Detection of trends in hydrological extremes for Canadian watersheds

The potential impacts of climate change can alter the risk to critical infrastructure resulting from changes to the frequency and magnitude of extreme events. As well, the natural environment is affected by the hydrologic regime, and changes in high flows or low flows can have negative impacts on ecosystems. This article examines the detection of trends in extreme hydrological events, both high and low flow events, for streamflow gauging stations in Canada. The trend analysis involves the application of the Mann–Kendall non‐parametric test. A bootstrap resampling process has been used to determine the field significance of the trend results. A total of 68 gauging stations having a nominal record length of at least 50 years are analysed for two analysis periods of 50 and 40 years. The database of Canadian rivers investigated represents a diversity of hydrological conditions encompassing different extreme flow generating processes and reflects a national scale analysis of trends. The results reveal more trends than would be expected to occur by chance for most of the measures of extreme flow characteristics. Annual and spring maximum flows show decreasing trends in flow magnitude and decreasing trends in event timing (earlier events). Low flow magnitudes exhibit both decreasing and increasing trends. Copyright © 2010 John Wiley & Sons, Ltd.     

Nonstationary extreme value analysis of temperature extremes in China

In a changing climate, the common assumption of stationarity of climate extremes has been increasingly challenged, raising the need to incorporate non-stationarity in extreme value modeling. In this study, quantile regression is used to identify the trends of annual temperature extremes and their correlations with two large climate patterns, the western Pacific subtropical high (WPSH) and the Arctic Oscillation (AO) at 357 stations in China. Statistical significant positive trends and correlations between warm (or cold) temperature extremes and WPSH (or AO) have been detected at most stations. The influence of WPSH on warm extremes is significant in southern China, while the AO mainly affects the cold extremes in northern and eastern China. Then, annual temperature extremes are fitted to generalized extreme value (GEV) distributions with time-varying parameters. The summer (or winter) mean daily maximum (or minimum) temperatures and two climate indices, the WPSH index and the AO index, are chosen as covariates. In total, 16 candidate GEV distribution models are constructed, and the best fitting model with the lowest Bayesian information criterion (BIC) is selected. The 20-year return levels of annual warm (or cold) extremes in the period 1961–1980 and 1991–2010 are computed and compared. The changes of 20-year return levels of annual warm and cold extremes are jointly determined by trend and distributional changes of annual temperature extremes. Analysis of large scale atmospheric circulation changes indicate that a strengthening anticyclonic circulation and increasing geopotential height in recent decades may have contributed to the changes in temperature extremes in China.     

Climate extremes in South Western Siberia: past and future

In this study, the temporal and spatial trends of ten climate extreme indices were computed based on observed daily precipitation and on daily maximum and minimum temperatures at 26 weather stations in South Western Siberia during the period 1969–2011 and, based on projected daily maximum and minimum temperatures, during 2021–2050. The Mann–Kendall test was employed to analyze the temporal trend and a combination of multiple linear regressions and semivariogram functions were used to evaluate the regional spatial trends and the local spatial variability of climate extremes, respectively. The results show that the temperature-based climate extremes increase at a 0.05 significance level while none of the precipitation-based climate extremes did. Spatially, dominant gradients are observed along latitude: The northern taiga vegetation zone experiences a colder and wetter climate while the southern forest steppe zone is drier and hotter. Over time, a tendency towards homogenization of the regional climate is observed through a decrease of the spatial variability for most climate extreme indices. In the future, the most intense changes are anticipated for the bio-climate indicators “growing season length” and “growing degree days” in the north, while the warming indicators, “warm day” and “warm night” are expected to be high to the south.     

Stratigraphy of Fossil Pigments as a Guide to the Environmental Changes of the Kortowskie Lake,Poland

A 294 cm long sediment core is divided into 1 cm disks at intervals of 7 cm. The disks are pollen-stratigraphically dated. At the same time, the pigment content is determined by two-dimensional thin-layer chromatography. The pigments were determined spectrophotometrically between 200 and 800 nm, six pigments having been identified, whereas in the chromatograms 13… 36 spots are found. Chlorophyll conversion products as well as epiphasic and hypophasic carotenoids were determined by liquid adsorption. The greatest variety was found with the pigments in the Atlantic period, the minimum of diversity lies in the Subboreal period. The concentration of the chlorophyll derivatives decreases with the age of sediments, whereas the carotenoids have maxima in the Atlantic and Subatlantic periods. On the basis of the ratio of chlorophyll derivatives to carotenoids and of the ratio of epiphasic carotenoids to hypophasic ones, the trophic state of the lake between oligotrophic and eutrophic as well as the relative share of autochthonous and allochthonous feed of matter to the sediment can be represented well.     

Bayesian posterior predictive return levels for environmental extremes

A key aim of most extreme value analyses is the estimation of the r-year return level; the wind speed, or sea-surge, or rainfall level (for example), we might expect to see once (on average) every r years. There are compelling arguments for working within the Bayesian setting here, not least the natural extension to prediction via the posterior predictive distribution. Indeed, for practitioners the posterior predictive return level has been cited as perhaps the most useful point summary from a Bayesian analysis of extremes, and yet little is known of the properties of this statistic. In this paper, we attempt to assess the performance of predictive return levels relative to their estimative counterparts obtained directly from the return level posterior distribution; in particular, we make comparisons with the return level posterior mean, mode and 95% credible upper bound. Differences between the predictive return level and standard summaries from the return level posterior distribution, for wind speed extremes observed in the UK, motivates this work. A large scale simulation study then reveals the superiority of the predictive return level over the other posterior summaries in many cases of practical interest.     

Testing exponentiality against NBUE distributions with an application in environmental extremes

The test for exponentiality of a dataset in terms of a specific aging property constitutes an interesting problem in reliability analysis. To this end, a wide variety of tests are proposed in the literature. In this paper, the excess-wealth function is recalled and new asymptotic properties are studied. By using the characterization of the exponential distribution based on the excess-wealth function, a new exponentiality test is proposed. Through simulation techniques, it is shown that this new test works well on small sample sizes. The exact null distribution and normality asymptotic is also obtained for the statistic proposed. This test and a new empirical graph based on the excess-wealth function are applied to extreme-value examples.     

Temperature extremes reduce seagrass growth and induce mortality

Extreme heating (up to 43 °C measured from five-year temperature records) occurs in shallow coastal seagrass meadows of the Great Barrier Reef at low tide. We measured effective quantum yield (_?PSII${?}_{\text{PSII}}$), growth, senescence and mortality in four tropical seagrasses to experimental short-duration (2.5 h) spikes in water temperature to 35 °C, 40 °C and 43 °C, for 6 days followed by one day at ambient temperature. Increasing temperature to 35 °C had positive effects on _?PSII${?}_{\text{PSII}}$ (the magnitude varied between days and was highly correlated with PPFD), with no effects on growth or mortality. 40 °C represented a critical threshold as there were strong species differences and there was a large impact on growth and mortality. At 43 °C there was complete mortality after 2–3 days. These findings indicate that increasing duration (more days in a row) of thermal events above 40 °C is likely to affect the ecological function of tropical seagrass meadows.     

Temporal and spatial variations in hydro-climatic extremes in the Lake Victoria basin

A study was carried out to investigate variability in long term hydro-climatic extremes in the Lake Victoria basin, East Africa. The study aimed at determining whether the long term historical changes in frequency and magnitude of hydro-climatic extremes are statistically significant, to give more light on the differentiation of climate variability from climate change. Long term extremes for 22 rainfall and 10 river flow gauge stations were examined. The hydro-climatic extremes were aggregated at levels from daily, decadal, to monthly scales defined for two wet seasons in the area, the long rainy season extending from March to May (MAM) and the short rainy season extending from October to December (OND), and time slices of 10 years using a sliding window approach. An empirical statistical technique based on Quantile Perturbation Method (QPM) was used. Quantile perturbations that represent empirical changes for precipitation and river flow extremes were derived. Significant decreasing trends in precipitation were observed in the 1930s, 1970s and 1980s, while significant increasing trends were common in the 1960s, late 1980s, and 1990s to the most recent years (2000–2006). In general, significant trends were dominant in the OND compared to MAM season for precipitation and river flow extremes. Results indicated further that there are differences in geographic location of significant trends in the hydro-climatic variables investigated implying that impacts are not spatially coherent. Areas with significant trends appeared to be concentrated in the North to North eastern parts compared to those in the southern parts of the basin.     

Stormy geomorphology: geomorphic contributions in an age of climate extremes

The increasing frequency and/or severity of extreme climate events are becoming increasingly apparent over multi‐decadal timescales at the global scale, albeit with relatively low scientific confidence. At the regional scale, scientific confidence in the future trends of extreme event likelihood is stronger, although the trends are spatially variable. Confidence in these extreme climate risks is muddied by the confounding effects of internal landscape system dynamics and external forcing factors such as changes in land use and river and coastal engineering. Geomorphology is a critical discipline in disentangling climate change impacts from other controlling factors, thereby contributing to debates over societal adaptation to extreme events. We review four main geomorphic contributions to flood and storm science. First, we show how palaeogeomorphological and current process studies can extend the historical flood record while also unraveling the complex interactions between internal geomorphic dynamics, human impacts and changes in climate regimes. A key outcome will be improved quantification of flood probabilities and the hazard dimension of flood risk. Second, we present evidence showing how antecedent geomorphological and climate parameters can alter the risk and magnitude of landscape change caused by extreme events. Third, we show that geomorphic processes can both mediate and increase the geomorphological impacts of extreme events, influencing societal risk. Fourthly, we show the potential of managing flood and storm risk through the geomorphic system, both near‐term (next 50 years) and longer‐term. We recommend that key methods of managing flooding and erosion will be more effective if risk assessments include palaeodata, if geomorphological science is used to underpin nature‐based management approaches, and if land‐use management addresses changes in geomorphic process regimes that extreme events can trigger. We argue that adopting geomorphologically‐grounded adaptation strategies will enable society to develop more resilient, less vulnerable socio‐geomorphological systems fit for an age of climate extremes. © 2016 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Assessment of hydrological extremes in the Kamo River Basin,Japan

A suite of extreme indices derived from daily precipitation and streamflow was analysed to assess changes in the hydrological extremes from 1951 to 2012 in the Kamo River Basin. The evaluated indices included annual maximum 1-day and 5-day precipitation (RX1day, RX5day), consecutive dry days (CDD), annual maximum 1-day and 5-day streamflow (SX1day, SX5day), and consecutive low-flow days (CDS). Sen’s slope estimator and two versions of the Mann-Kendall test were used to detect trends in the indices. Also, frequency distributions of the indices were analysed separately for two periods: 1951–1981 and 1982–2012. The results indicate that quantiles of the rainfall indices corresponding to the 100-year return period have decreased in recent years, and the streamflow indices had similar patterns. Although consecutive no rainfall days represented by 100-year CDD decreased, continuous low-flow days represented by 100-year CDS increased. This pattern change is likely associated with the increase in temperature during this period.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR E. Gargouri     

The Great Flood of 1997 in Poland

Abstract

The flood that occurred in summer 1997 in Poland, affecting the drainage basins of the Odra and the Vistula, caused 54 fatalities and material losses of the order of billions of US$. The flood struck a large part of the country and caused inundation of 665 000 ha of land. The number of evacuees was 162 thousand. The rhetoric commonly used in Poland refers to the Great Flood of 1997 as an event whose scale exceeded all imagination about the possible size of the disaster. Indeed, historic maxima of river stage and flow rate were considerably exceeded. From the hydrological point of view, this flood was a very rare event, with a return period in some river cross-sections of the order of a thousand years and more. As this natural disaster, striking a dynamically developing country-in-transition, attracted much international interest, a holistic view of it is presented. Attempts to answer the questions: “Could the disaster have been avoided?” and “What lessons can be learnt from the flood?” are also made.     

Single station and regional analysis of daily rainfall extremes

A peaks over threshold (POT) method of analysing daily rainfall values is developed using a Poisson process of occurrences and a generalised Pareto distribution (GPD) for the exceedances. The parameters of the GPD are estimated by the method of probability weighted moments (PWM) and a method of combining the individual estimates to define a regional curve is proposed.     

Numerical modeling of space-time wave extremes using WAVEWATCH III

A novel implementation of parameters estimating the space-time wave extremes within the spectral wave model WAVEWATCH III (WW3) is presented. The new output parameters, available in WW3 version 5.16, rely on the theoretical model of Fedele (J Phys Oceanogr 42(9):1601-1615, 2012) extended by Benetazzo et al. (J Phys Oceanogr 45(9):2261–2275, 2015) to estimate the maximum second-order nonlinear crest height over a given space-time region. In order to assess the wave height associated to the maximum crest height and the maximum wave height (generally different in a broad-band stormy sea state), the linear quasi-determinism theory of Boccotti (2000) is considered. The new WW3 implementation is tested by simulating sea states and space-time extremes over the Mediterranean Sea (forced by the wind fields produced by the COSMO-ME atmospheric model). Model simulations are compared to space-time wave maxima observed on March 10th, 2014, in the northern Adriatic Sea (Italy), by a stereo camera system installed on-board the “Acqua Alta” oceanographic tower. Results show that modeled space-time extremes are in general agreement with observations. Differences are mostly ascribed to the accuracy of the wind forcing and, to a lesser extent, to the approximations introduced in the space-time extremes parameterizations. Model estimates are expected to be even more accurate over areas larger than the mean wavelength (for instance, the model grid size).