Abstract. The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum 3 s wind-gust footprints for 50 the most extreme winter windstorms to hit Europe in period 1979–2012. is intended be a valuable resource both academia industries such as (re)insurance, example allowing users characterise European storms, validate climate catastrophe models. Several severity indices were investigated find which could best represent list known high-loss (severe) storms....

Generalized additive model (GAM) forms offer a flexible approach to capturing marginal variation. Such are used here represent distributional variation in extreme values and presented terms of spatio-temporal variation, which is often evident environmental processes. A two-stage procedure proposed that identifies as exceedances high threshold, defined fixed quantile estimated by regression. Excesses the threshold modelled with generalized Pareto distribution (GPD). GAM adopted for GPD...

This article introduces the R package evgam. The provides functions for fitting extreme value distributions. These include generalized and Pareto former can also be fitted through a point process representation. Package evgam supports quantile regression via asymmetric Laplace distribution, which useful estimating high thresholds, sometimes used to discriminate between non-extreme values. main addition of is let distribution parameters have additive model forms, smoothness objectively...

Climate services must provide robust estimates of future changes to precipitation extremes inform flood risk management and assess the resilience existing urban drainage systems in a changing climate. We use an ensemble convection-permitting UK climate projections, UKCP Local estimate return levels 1–24 h extremes, combining state-of-the-art spatial statistical modelling. produce low, central high level uplifts at 5 km resolution across UK. On average UK, 30y 1 24 is projected increase by...

Societal Impact Statement The UK Plant Health Risk Register (PHRR) has so far identified 581 Pests and Diseases (PPDs) that could invade the United Kingdom affect 74 tree species. combined effects of multiple invasions on trees are little understood seldom considered. We estimate future invasion rates losses from PHRR risk scores using historical data. project potentially severe to ecologically economically important species like oak, apple, poplar pine due impacts PPDs. Our analysis...

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent Pareto marginal distribution parameters while Student's t-process captures spatial dependence gives continuous-space event simulations. Efficiency of the simulation method allows many years data (typically over 10 000) to be obtained at relatively little computational cost. This makes viable forming module catastrophe...

Abstract There is a pressing need for simple and reliable risk transfer mechanisms that can pay out quickly after natural disasters without delays caused by loss estimation, the long historical claims records. One such approach, known as parametric insurance, pays when key hazard variable exceeds predetermined threshold. However, this approach to catastrophe risk, based on making deterministic binary predictions of occurrence, susceptible basis (mismatch between payouts realized losses). A...

Point processes are a natural class of models for representing occurrences various types hazard event. Flexibly implementing such is often hindered by intractable likelihood forms. Consequently, the rates point tend to be reduced parametric forms, or discretised give data readily modelled “count‐per‐unit” type. This work proposes generalised additive model forms process rates. The resulting low‐rank spatiotemporal representations rates, coupled with Laplace approximation, makes restricted...

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This article introduces the R package evgam. The provides functions for fitting extreme value distributions. These include generalized and Pareto former can also be fitted through a point process representation. evgam supports quantile regression via asymmetric Laplace distribution, which useful estimating high thresholds, sometimes used to discriminate between non-extreme values. main addition of is let distribution parameters have additive model forms, objectively estimated using Laplace's...

Abstract. The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum three-second wind-gust footprints for 50 the most extreme winter windstorms to hit Europe over 1979–2012. is intended be a valuable resource both academia industries such as (re)insurance, example allowing users characterise European storms, validate climate catastrophe models. Several severity indices were investigated find which could best represent list known high loss (severe) storms....

There are many situations when modelling environmental phenomena for which it is not appropriate to assume a stationary dependence structure. \cite{sampson1992} proposed an approach allowing nonstationarity in based on deformed space: coordinates from original geographic "$G$" space mapped new dispersion "$D$" reasonable assumption. achieve this with two deformation functions, chosen as thin plate splines, each representing how one of the $D$-space relates $G$-space coordinates. This works...

Abstract Environmental hazard events such as extra‐tropical cyclones or windstorms that develop in the North Atlantic can cause severe societal damage. is quantified by footprint, a spatial area describing potential However, environmental hazards are never directly observed, so estimation of footprint for any given event primarily reliant on station observations (e.g., wind speed case windstorm event) and physical model hindcasts. Both data sources indirect measurements true here we present...

We calibrate a Natural History Model, which is class of computer simulator used in the health industry, and here has been to characterise bowel cancer incidence for UK. The tracks development sample people, its output mostly stratifies occurrence by patient age type. Its relies on 25 unknown inputs, we are required calibrate. In order do this must address that not only count data, but it also stochastic, due simulation procedure. cannot feasibly achieve calibration using Monte Carlo methods...

We present a framework for inference spatial processes that have actual values imperfectly represented by data. Environmental as fields, either at fixed time points, or aggregated over periods, are studied. Data from both measurements and simulations performed complex computer models used to infer of the fields. Methods geostatistics statistical emulation explicitly capture discrepancies between field's simulated values. A geostatistical model captures discrepancy: difference in structure An...

Gaussian processes (GP) are a popular and powerful tool for spatial modelling of data, especially data that quantify environmental processes. However, in stationary form, whether covariance is isotropic or anisotropic, GPs may lack the flexibility to capture dependence across continuous process, large domains. The deform package aims provide users with user-friendly R functions fitting visualization nonstationary Users can choose nonstationarity either deformation approach Sampson Guttorp...

This paper introduces a method for spatial interpolation of extreme values, and in particular targets the case which conventional data, resulting from measurement example, are available at only few locations. To overcome this data supplemented with output computer simulator. For environmental applications, such as rainfall we study here, simulator could be regional climate model. Annual maxima studied assumed to follow generalised value (GEV) distribution dependence is accommodated between...