Inferences on weather extremes and weather-related disasters: a review of statistical methods

Visser, Hubregt J.; Petersen, Arthur C.

doi:10.5194/cp-8-265-2012

Cited by 27 publications

(23 citation statements)

References 86 publications

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“…POT, BM, and RP estimates, show varying results in terms of the seasonal distribution of heavy precipitation events in the Vosges Mountains area. This is in agreement with Visser and Petersen () who stated that the selection of method might fundamentally influence the results of an analysis of precipitation extremes. Furthermore, the definition of heavy precipitation events is inevitable and crucial for studies dealing with extreme rainfall.…”

Section: Resultssupporting

confidence: 92%

Seasonality of mean and heavy precipitation in the area of the Vosges Mountains: dependence on the selection criterion

Minářová

Müller

Clappier

2016

Intl Journal of Climatology

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The seasonal distribution of mean precipitation and heavy rainfalls during 1960–2013 was analysed based on daily precipitation totals from 168 rain gauging stations in the Vosges Mountains area, north‐eastern France. Concerning mean precipitation, an ancient Hrudička's index designed as a half‐time of precipitation during a year, surprisingly well expresses the seasonality of precipitation and its clear correlation with the mean annual totals in the studied region. The annual course of mean precipitation leads to a distinction of four groups of stations with respect to the position of stations: MT, mountainous stations with maxima of precipitation in winter and an overall highest mean annual totals; LSp, stations situated on leeward slopes of the Vosges Mountains with two maxima of precipitation (primary in winter and secondary in summer); URP, leeward stations located in the Upper Rhine River Plain with the most humid summer season, and the lowest mean annual totals; WSd, windward stations not influenced by the Vosges Mountains, with relatively evenly distributed precipitation, and slight maxima in autumn. For the heavy precipitation, 1–10‐days totals have been considered to be ‘heavy’ subsequent to applying the three common methods – peaks over threshold (POT), block maxima (BM), and return period estimates based on generalized extreme value distribution. Varying criteria have been employed. The BM method for annual maxima indicates that the heavy rainfall generally occurs during the most humid season although it can also occur anytime during the year. The POT and return period estimates methods reveal that the seasonality of extremes is threshold‐dependent and that probably the threshold sensitivity is also related to the degree of orographic influence – higher occurrence of summer events in the lee while lesser occurrence of winter events in mountains, at higher threshold and shorter duration of event.

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Section: Resultssupporting

confidence: 92%

Seasonality of mean and heavy precipitation in the area of the Vosges Mountains: dependence on the selection criterion

Minářová

Müller

Clappier

2016

Intl Journal of Climatology

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“…Model results and comparison to observed data. (a) Subsurface warming is forced by increasing the ground surface temperature (the upper boundary of the model) in accordance with the long‐term trend (red line) inferred from annual average surface air temperatures representative for the central part of the Netherlands including the Veluwe area (van der Schrier et al, ; Visser & Petersen, ). Model simulations of the sensitivity to vertical groundwater flow of the inflection point depth in the TD profile in time for (b) homogeneous thermal properties (scenario I) in an aquifer composed of sandy material (yellow), and (c) when thermal properties are heterogeneous as a result of the presence of clayey (blue) units in an otherwise sand‐dominated aquifer (scenario II).…”

Section: Discussionsupporting

confidence: 63%

Tracking the Subsurface Signal of Decadal Climate Warming to Quantify Vertical Groundwater Flow Rates

Bense

Kurylyk

2017

Geophysical Research Letters

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Sustained ground surface warming on a decadal time scale leads to an inversion of thermal gradients in the upper tens of meters. The magnitude and direction of vertical groundwater flow should influence the propagation of this warming signal, but direct field observations of this phenomenon are rare. Comparison of temperature-depth profiles in boreholes in the Veluwe area, Netherlands, collected in 1978-1982 and 2016 provided such direct measurement. We used these repeated profiles to track the downward propagation rate of the depth at which the thermal gradient is zero. Numerical modeling of the migration of this thermal gradient "inflection point" yielded estimates of downward groundwater flow rates (0-0.24 m a −1) that generally concurred with known hydrogeological conditions in the area. We conclude that analysis of inflection point depths in temperature-depth profiles impacted by surface warming provides a largely untapped opportunity to inform sustainable groundwater management plans that rely on accurate estimates of long-term vertical groundwater fluxes.

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“…Our research is motivated by the fact that the selection method can substantially influence the results of a study (Visser and Petersen, 2012). In accordance with Diaz and Murnane (2008), we differentiate between short-term weather events (e.g., heavy rainfall) and longer-lived climate events (e.g., extra wet season).…”

Section: Introductionmentioning

confidence: 99%

Event-adjusted evaluation of weather and climate extremes

Müller

Kašpar

2014

Nat. Hazards Earth Syst. Sci.

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Abstract.After an overview of existing methods, we present a novel method of "event-adjusted" evaluation of extremeness of weather and climate events. It is based on optimization of both the considered area and the time duration for every event. The method consists of three steps: (i) estimation of return periods of a representative variable at individual sites, performed separately for various time windows; (ii) spatial interpolation of the point return period data; and (iii) searching the area and the time window in which the extremeness of the event was maximum. The extremeness is quantified as the common logarithm of the spatial geometric mean of the return periods multiplied by the radius of a circle of the same area as the one over which the geometric mean is taken. The maximum product is referred to as the weather extremity index (WEI). Two precipitation events, which affected the Czech Republic in May and in August 2010, were evaluated by the WEI for illustration. Validation of the method on sufficiently long data series is still needed. Moreover, the WEI is generally applicable regardless of the studied phenomenon (heavy rains, heat waves, windstorms, etc.). This makes it possible to study various weather and climate extremes from the viewpoint of possible recent and future changes in their frequency, seasonal distribution, and circulation conditions accompanying them.

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Inferences on weather extremes and weather-related disasters: a review of statistical methods

Cited by 27 publications

References 86 publications

Seasonality of mean and heavy precipitation in the area of the Vosges Mountains: dependence on the selection criterion

Seasonality of mean and heavy precipitation in the area of the Vosges Mountains: dependence on the selection criterion

Tracking the Subsurface Signal of Decadal Climate Warming to Quantify Vertical Groundwater Flow Rates

Event-adjusted evaluation of weather and climate extremes

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