Non-stationary extreme models and a climatic application

In this paper, we study extreme values of non-stationary climatic phenomena. In the usually considered stationary case, the modelling of extremes is only based on the behaviour of the tails of the distribution of the remainder of the data set. In the non-stationary case though, it seems reasonable to assume that the temporal dynamics of the entire data set and that of extremes are closely related and thus all the available information about this link should be used in statistical studies of these events. We try to study how centered and normalized data which are closer to stationary data than the observation allows easier statistical analysis and to understand if we are very far from a hypothesis stating that the extreme events of centered and normed data follow a stationary distribution. The location and scale parameters used for this transformation (the central field), as well as extreme parameters obtained for the transformed data enable us to retrieve the trends in extreme events of the initial data set. Through non-parametric statistical methods, we thus compare a model directly built on the extreme events and a model reconstructed from estimations of the trends of the location and scale parameters of the entire data set and stationary extremes obtained from the centered and normed data set. In case of a correct reconstruction, we can clearly state that variations of the characteristics of extremes are well explained by the central field. Through these analyses we bring arguments to choose constant shape parameters of extreme distributions. We show that for the frequency of the moments of high threshold excesses (or for the mean of annual extremes), the general dynamics explains a large part of the trends on frequency of extreme events. The conclusion is less obvious for the amplitudes of threshold exceedances (or the variance of annual extremes) – especially for cold temperatures, partly justified by the statistical tools used, which require further analyses on the variability definition

Is there a trend in extremely high river temperature for the next decades? A case study for France

International audienceAfter 2003's summer heat wave, Electricité de France created a global plan called "heat wave-dryness". In this context, the present study tries to estimate high river temperatures for the next decades, taking into account climatic and anthropogenic evolutions. To do it, a specific methodology based on Extreme Value Theory (EVT) is applied. In particular, a trend analysis of water temperature data is done and included in EVT used. The studied river temperatures consist of mean daily temperatures for 27 years measured near the French power plants (between 1977 and 2003), with four series for the Rhône river, four for the Loire river and a few for other rivers. There are also three series of mean daily temperatures computed by a numerical model. For each series, we have applied statistical extreme value modelling. Because of thermal inertia, the Generalized Extreme Value (GEV) distribution is corrected by the medium cluster length, which represents thermal inertia of water during extremely hot events. The µ and s parameters of the GEV distributions are taken as polynomial or continuous piecewise linear functions of time. The best functions for µ and s parameters are chosen using Akaike criterion based on likelihood and some physical checking. For all series, the trend is positive for µ and not significant for s, over the last 27 years. However, we cannot assign this evolution only to the climatic change for the Rhône river because the river temperature is the resultant of several causes: hydraulic or atmospheric, natural or related to the human activity. For the other rivers, the trend for µ could be assigned to the climatic change more clearly. Furthermore, the sample is too short to provide reliable return levels estimations for return periods exceeding thirty years. Still, quantitative return levels could be compared with physical models for example

Creating a proof-of-concept climate service to assess future renewable energy mixes in Europe: an overview of the C3S ECEM project

The EU Copernicus Climate Change Service (C3S) European Climatic Energy Mixes (ECEM) has produced, in close collaboration with prospective users, a proof-of-concept climate service, or Demonstrator, designed to enable the energy industry and policy makers assess how well different energy supply mixes in Europe will meet demand, over different time horizons (from seasonal to long-term decadal planning), focusing on the role climate has on the mixes. The concept of C3S ECEM, its methodology and some results are presented here. The first part focuses on the construction of reference data sets for climate variables based on the ERA-Interim reanalysis. Subsequently, energy variables were created by transforming the bias-adjusted climate variables using a combination of statistical and physically-based models. A comprehensive set of measured energy supply and demand data was also collected, in order to assess the robustness of the conversion to energy variables. Climate and energy data have been produced both for the historical period (1979–2016) and for future projections (from 1981 to 2100, to also include a past reference period, but focusing on the 30 year period 2035–2065). The skill of current seasonal forecast systems for climate and energy variables has also been assessed. The C3S ECEM project was designed to provide ample opportunities for stakeholders to convey their needs and expectations, and assist in the development of a suitable Demonstrator. This is the tool that collects the output produced by C3S ECEM and presents it in a user-friendly and interactive format, and it therefore constitutes the essence of the C3S ECEM proof-of-concept climate service

The price of mobility

This paper addresses the question concerning the price of geographic mobility in various labour market and migration scenarios. Pivotal points are expected mobility premiums which are sufficient to tip the scales in favour of moving to a geographically distinct location. These premiums are first derived within a theoretical model, accounting not only for location-specific amenity levels or labour market conditions, but also for heterogeneous personality traits and preferences. Derived hypotheses demonstrate that—in presence of heterogeneous psychic costs or adjustment capabilities—expected mobility premiums can remain distinctly positive even in an unemployment scenario. Furthermore, adjustment capabilities are to a large extent related to earlier mobility experiences, implying that labour mobility is partially learnable

Changes in northern hemisphere temperature variability shaped by regional warming patterns

Global warming involves changes not only in the mean atmospheric temperature, but also in its variability and extremes. Here we use a feature-tracking technique to investigate the dynamical contribution to temperature anomalies in the northern hemisphere in CMIP5 climate-change simulations. We develop a simple theory to explain how temperature variance and skewness changes are generated dynamically from mean temperature gradient changes, and demonstrate the crucial role of regional warming patterns in shaping the distinct response of cold and warm anomalies. We also show that skewness changes must be taken into account, in addition to variance changes, in order to correctly capture the projected temperature variability response. These changes in variability may impact humans, agriculture and animals, as they experience not only a warmer mean climate, but also a new likelihood of temperature anomalies within that climate

Checklist of the caddisfly family Rhyacophilidae (Insecta: Trichoptera) in India

The present checklist covers the fauna of the Trichopteran family Rhyacophilidae Stephens, 1836. Based on extensive surveys done during 2003–2019 and previous species records, we find that the family Rhyacophilidae is represented by two genera and 184 species in India. The genus Rhyacophila Pictet contains 165 species in India while the genus Himalopsyche Banks contains 19 described species. The Indian Himalayan region is inhabited by more species than the rest of India

An Advanced Numerical Model of Gear Tooth Loading from Backlash and Profile Errors

This study demonstrates the early transient dynamic loading on teeth within a fixed-axis gear transmission arising from backlash and geometric manufacturing errors by utilizing a non-linear multi-body dynamics software model. Selection of the non-linear contact parameters such as the stiffness, force exponent, damping, and friction coefficients are presented for a practical transmission. Backlash between gear teeth which is essential to provide better lubrication on tooth surfaces and to eliminate interference is included as a defect and a necessary part of transmission design. Torsional vibration is shown to cause teeth separation and double-sided impacts in unloaded and lightly loaded gearing drives. Vibration and impact force distinctions between backlash and combinations of transmission errors are demonstrated under different initial velocities and load conditions. Additionally, the loading dynamics of a crank-slider mechanism with two-stage gear driving train is analyzed. The backlash and manufacturing errors in the first stage of the gear train are distinct from those of the second stage. By analyzing the signal at a location between the two stages, the mutually affected impact forces are observed from different gear pairs, a phenomenon not observed from single pair of gears

Two new species of the genus Eubasilissa Martynov (Trichoptera: Phryganeidae) from the Indian Himalaya

Parey, Sajad H., Saini, Malkiat S. (2012): Two new species of the genus Eubasilissa Martynov (Trichoptera: Phryganeidae) from the Indian Himalaya. Zootaxa 3403: 61-68, DOI: 10.5281/zenodo.28185