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Prewhitening has been used to eliminate the influence of serial correlation on the Mann‐Kendall (MK) test in trend‐detection studies of hydrological time series. However, its ability to accomplish such a task has not been well documented. This study investigates this issue by Monte Carlo simulation. Simulated time series consist of a linear trend and a lag 1 autoregressive (AR(1)) process with a noise. Simulation results demonstrate that when trend exists in a time series, the effect of positive/negative serial correlation on the MK test is dependent upon sample size, magnitude of serial correlation, and magnitude of trend. When sample size and magnitude of trend are large enough, serial correlation no longer significantly affects the MK test statistics. Removal of positive AR(1) from time series by prewhitening will remove a portion of trend and hence reduces the possibility of rejecting the null hypothesis while it might be false. Contrarily, removal of negative AR(1) by prewhitening will inflate trend and leads to an increase in the possibility of rejecting the null hypothesis while it might be true. Therefore, prewhitening is not suitable for eliminating the effect of serial correlation on the MK test when trend exists within a time series.

Framed within the Copernicus Climate Change Service (C3S) of the European Commission, the European Centre for Medium-Range Weather Forecasts (ECMWF) is producing an enhanced global dataset for the land component of the fifth generation of European ReAnalysis (ERA5), hereafter referred to as ERA5-Land. Once completed, the period covered will span from 1950 to the present, with continuous updates to support land monitoring applications. ERA5-Land describes the evolution of the water and energy cycles over land in a consistent manner over the production period, which, among others, could be used to analyse trends and anomalies. This is achieved through global high-resolution numerical integrations of the ECMWF land surface model driven by the downscaled meteorological forcing from the ERA5 climate reanalysis, including an elevation correction for the thermodynamic near-surface state. ERA5-Land shares with ERA5 most of the parameterizations that guarantees the use of the state-of-the-art land surface modelling applied to numerical weather prediction (NWP) models. A main advantage of ERA5-Land compared to ERA5 and the older ERA-Interim is the horizontal resolution, which is enhanced globally to 9 km compared to 31 km (ERA5) or 80 km (ERA-Interim), whereas the temporal resolution is hourly as in ERA5. Evaluation against independent in situ observations and global model or satellite-based reference datasets shows the added value of ERA5-Land in the description of the hydrological cycle, in particular with enhanced soil moisture and lake description, and an overall better agreement of river discharge estimations with available observations. However, ERA5-Land snow depth fields present a mixed performance when compared to those of ERA5, depending on geographical location and altitude. The description of the energy cycle shows comparable results with ERA5. Nevertheless, ERA5-Land reduces the global averaged root mean square error of the skin temperature, taking as reference MODIS data, mainly due to the contribution of coastal points where spatial resolution is important. Since January 2020, the ERA5-Land period available has extended from January 1981 to the near present, with a 2- to 3-month delay with respect to real time. The segment prior to 1981 is in production, aiming for a release of the whole dataset in summer/autumn 2021. The high spatial and temporal resolution of ERA5-Land, its extended period, and the consistency of the fields produced makes it a valuable dataset to support hydrological studies, to initialize NWP and climate models, and to support diverse applications dealing with water resource, land, and environmental management. The full ERA5-Land hourly (Muñoz-Sabater, 2019a) and monthly (Muñoz-Sabater, 2019b) averaged datasets presented in this paper are available through the C3S Climate Data Store at https://doi.org/10.24381/cds.e2161bac and https://doi.org/10.24381/cds.68d2bb30, respectively.

Abstract Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis which, once completed, will embody a detailed record of the global atmosphere, land surface and ocean waves from 1950 onwards. This new reanalysis replaces the ERA‐Interim reanalysis (spanning 1979 onwards) which was started in 2006. ERA5 is based on the Integrated Forecasting System (IFS) Cy41r2 which was operational in 2016. ERA5 thus benefits from a decade of developments in model physics, core dynamics and data assimilation. In addition to a significantly enhanced horizontal resolution of 31 km, compared to 80 km for ERA‐Interim, ERA5 has hourly output throughout, and an uncertainty estimate from an ensemble (3‐hourly at half the horizontal resolution). This paper describes the general set‐up of ERA5, as well as a basic evaluation of characteristics and performance, with a focus on the dataset from 1979 onwards which is currently publicly available. Re‐forecasts from ERA5 analyses show a gain of up to one day in skill with respect to ERA‐Interim. Comparison with radiosonde and PILOT data prior to assimilation shows an improved fit for temperature, wind and humidity in the troposphere, but not the stratosphere. A comparison with independent buoy data shows a much improved fit for ocean wave height. The uncertainty estimate reflects the evolution of the observing systems used in ERA5. The enhanced temporal and spatial resolution allows for a detailed evolution of weather systems. For precipitation, global‐mean correlation with monthly‐mean GPCP data is increased from 67% to 77%. In general, low‐frequency variability is found to be well represented and from 10 hPa downwards general patterns of anomalies in temperature match those from the ERA‐Interim, MERRA‐2 and JRA‐55 reanalyses.

Land surface hydrology controls runoff production and the associated transport of sediments, and a wide variety of anthropogenic organic chemicals, and nutrients from upland landscape areas and hillslopes to streams and other water bodies. Based on interactions between landscape characteristics and precipitation inputs, watersheds respond differently to different climatic inputs (e.g. precipitation and solar radiation). This study compares the hydrologic responses of the MidAtlantic watersheds, and identifies the landscape and climatic descriptors that control those responses. Our approach was to select representative watersheds from the Mid-Atlantic region, group the watersheds by physiographic province and ecoregion, and then collect landscape, climate, and hydrologic response descriptor data for each selected watershed. For example, we extracted extensive landscape descriptor data from soil, land use and land cover, and digital elevation model geographic information system (GIS) databases. After sufficient data was collected, we conducted a variety of studies to determine how different landscape and climatic descriptors influence the hydrologic response of Mid-Atlantic watersheds. This report is comprised of four main parts. Part I describes the selection of the representative study watersheds and the determination of representative physical landscape descriptors for each watershed using geographic information system analysis tools. Part II characterizes the climate and associated hydrologic responses of the study watersheds. To select climate descriptors that are good predictors of hydrologic response, we examined a large number of candidate descriptors. Based on our examination, we selected dryness index and mean monthly rainfall as the best hydrologic response predictors. In Part II, we also present the results of our study hydrologic response comparisons of the study watersheds using a water balance approach. The water balance approach was based on comparisons of precipitation, streamflow, and evapotranspiration at annual, monthly, and daily time scales. These comparisons revealed that elevation and latitudinal position strongly influence hydrologic response. The results also showed that mountainous watersheds of the Appalachian Plateau, Ridge and Valley, and Blue Ridge Physiographic Provinces have more streamflow and less evapotranspiration than watersheds located in the Piedmont Province, and that snowmelt contributes a large portion of streamflow. Part III presents relationships we derived between landscape-climatic descriptors and the hydrologic response descriptors. Flow duration indices (Q1...Q95) were used to represent the hydrologic responses of the study watersheds. In Part III, we also present comparisons of the hydrologic responses of the study watersheds at high flow condition, represented by the Q1 index, medium flow condition represented by the Q50 index, and low flow condition represented by the Q95 index. These comparisons revealed that: the Appalachian Plateau, ridge-dominated Ridge and Valley, and Blue Ridge watersheds have the highest Q1 and Q50 indices; the valley-dominated Ridge and Valley watersheds have the lowest Q50 index, and the Piedmont watersheds have the lowest Q1 index and a relatively high Q95 index. Finally, Part IV discusses some of the implications of the study results for watershed management. We also present applications of the research for hydrologic modeling and watershed assessment.

Faisant partie d'un numéro spécial sur l'histoire des communautés de la MRC des Chenaux, ce texte examine le statut de "capitale du petit poisson des chenaux" des Péradiens en prenant comme point de départ l'éboulis de Saint-Alban, survenu en 1894. (Empreintes, Revue d'histoire de la Mauricie et du Centre-du-Québec, vol.5 (1), p.12-16).

UNDRR report published to mark the International Day for Disaster Risk Reduction on October 13, 2020, confirms how extreme weather events have come to dominate the disaster landscape in the 21st century.

According to our survey about climate risk perceptions, institutional investors believe climate risks have financial implications for their portfolio firms and that these risks, particularly regulatory risks, already have begun to materialize. Many of the investors, especially the long-term, larger, and ESG-oriented ones, consider risk management and engagement, rather than divestment, to be the better approach for addressing climate risks. Although surveyed investors believe that some equity valuations do not fully reflect climate risks, their perceived overvaluations are not large.

Abstract As losses from extreme weather events grow, many governments are looking to privatize the financing and incentivization of climate adaptation through insurance markets. In a pure market approach to insurance for extreme weather events, individuals become responsible for ensuring they are adequately covered for risks to their own properties, and governments no longer contribute funds to post‐disaster recovery. Theoretically, insurance premiums signal the level of risk faced by each household, and incentivize homeowners to invest in adaptive action, such as retrofitting, or drainage work, to reduce premiums. Where risk is considered too high by insurance markets, housing is devalued, in theory leading to retreat from risky areas. In this review article, we evaluate the suitability of private insurance as a mechanism for climate adaptation at a household and community level. We find a mismatch between social understandings of responsibility for climate risks, and the technocratic, market‐based home insurance products offered by private insurance markets. We suggest that by constructing increasingly individualized, technical, and calculative evaluations of risk, market‐based models of insurance for extreme weather events erode the solidaristic and collective discourses and practices that support adaptive behavior. This article is categorized under: Vulnerability and Adaptation to Climate Change > Institutions for Adaptation

Information on the size of academic search engines and bibliographic databases (ASEBDs) is often outdated or entirely unavailable. Hence, it is difficult to assess the scope of specific databases, such as Google Scholar. While scientometric studies have estimated ASEBD sizes before, the methods employed were able to compare only a few databases. Consequently, there is no up-to-date comparative information on the sizes of popular ASEBDs. This study aims to fill this blind spot by providing a comparative picture of 12 of the most commonly used ASEBDs. In doing so, we build on and refine previous scientometric research by counting query hit data as an indicator of the number of accessible records. Iterative query optimization makes it possible to identify a maximum number of hits for most ASEBDs. The results were validated in terms of their capacity to assess database size by comparing them with official information on database sizes or previous scientometric studies. The queries used here are replicable, so size information can be updated quickly. The findings provide first-time size estimates of ProQuest and EbscoHost and indicate that Google Scholar’s size might have been underestimated so far by more than 50%. By our estimation Google Scholar, with 389 million records, is currently the most comprehensive academic search engine.

In undertaking what we believe is the first national-scale study of its kind, we provide methodologically transparent, statistically robust insights into associations and potential unfolding effects of house and contents under-insurance. We identify new dimensions in the complex relationship between householders and insurance, including the salience of interpersonal – and likely institutional – trust. Under-insurance is (re)produced along socio-economic and geographical lines, with those of lower socio-economic status or living in cities more likely to be under-insured. Should a disaster strike, such communities are likely to suffer further disadvantage, especially if governments continue to shift the responsibility for risk onto households. Our findings support the observation that insurance can contribute to increasing socio-economic urban polarisation in light of natural disasters. We conclude by considering how under-insurance may contribute to growing urban social stratification, as well as how it may produce situated ethical and political responses that exceed neoliberal aspirations.

Abstract The COST‐731 action is focused on uncertainty propagation in hydrometeorologica l forecasting chains. Goals and activities of the action Working Group 2 are presented. Five foci for discussion and research have been identified: (1) understand uncertainties, (2) exploring, designing and comparing methodologies for the use of uncertainty in hydrological models, (3) providing feedback on sensitivity to data and forecast providers, (4) transferring methodologies among the different communities involved and (5) setting up test‐beds and perform proof‐of‐concepts. Current examples of different perspectives on uncertainty propagation are presented. Copyright © 2010 Royal Meteorological Society

1. This review is presented as a broad synthesis of riverine landscape diversity, beginning with an account of the variety of landscape elements contained within river corridors. Landscape dynamics within river corridors are then examined in the context of landscape evolution, ecological succession and turnover rates of landscape elements. This is followed by an overview of the role of connectivity and ends with a riverine landscape perspective of biodiversity. 2. River corridors in the natural state are characterised by a diverse array of landscape elements, including surface waters (a gradient of lotic and lentic waterbodies), the fluvial stygoscape (alluvial aquifers), riparian systems (alluvial forests, marshes, meadows) and geomorphic features (bars and islands, ridges and swales, levees and terraces, fans and deltas, fringing floodplains, wood debris deposits and channel networks). 3. Fluvial action (erosion, transport, deposition) is the predominant agent of landscape evolution and also constitutes the natural disturbance regime primarily responsible for sustaining a high level of landscape diversity in river corridors. Although individual landscape features may exhibit high turnover, largely as a function of the interactions between fluvial dynamics and successional phenomena, their relative abundance in the river corridor tends to remain constant over ecological time. 4. Hydrological connectivity, the exchange of matter, energy and biota via the aqueous medium, plays a major though poorly understood role in sustaining riverine landscape diversity. Rigorous investigations of connectivity in diverse river systems should provide considerable insight into landscape‐level functional processes. 5. The species pool in riverine landscapes is derived from terrestrial and aquatic communities inhabiting diverse lotic, lentic, riparian and groundwater habitats arrayed across spatio‐temporal gradients. Natural disturbance regimes are responsible for both expanding the resource gradient in riverine landscapes as well as for constraining competitive exclusion. 6. Riverine landscapes provide an ideal setting for investigating how complex interactions between disturbance and productivity structure species diversity patterns.