Methods for Exploring Spatial and Temporal Variability of Extreme Events in Climate Data

Coelho, Caio A. S.; Ferro, Christopher A. T.; Stephenson, David B.; Steinskog, Dag Johan

doi:10.1175/2007jcli1781.1

Cited by 89 publications

(60 citation statements)

References 32 publications

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“…Thus, the POT approach is indeed more appropriate. While the POT method has been applied for studying temperature extremes in different regions of the world (Burgueño et al, 2002;Nogaj et al, 2006;Coelho et al, 2007;Ghil et al, 2011), to our knowledge, it has never been used to analyze the statistics of temperature extremes in Sindh. Thanks to the properties of universality of the GPD distribution (Lucarini et al, 2016), the POT approach can in principle provide reliable estimates of return periods and also the return levels (RLs) for time ranges longer than what is actually observed.…”

Section: Introductionmentioning

confidence: 99%

Return levels of temperature extremes in southern Pakistan

Zahid¹,

Blender²,

Lucarini

et al. 2017

Earth Syst. Dynam.

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Abstract. Southern Pakistan (Sindh) is one of the hottest regions in the world and is highly vulnerable to temperature extremes. In order to improve rural and urban planning, it is useful to gather information about the recurrence of temperature extremes. In this work, return levels of the daily maximum temperature T max are estimated, as well as the daily maximum wet-bulb temperature TW max extremes. We adopt the peaks over threshold (POT) method, which has not yet been used for similar studies in this region. Two main datasets are analyzed: temperatures observed at nine meteorological stations in southern Pakistan from 1980 to 2013, and the ERA-Interim (ECMWF reanalysis) data for the nearest corresponding locations. The analysis provides the 2-, 5-, 10-, 25-, 50-, and 100-year return levels (RLs) of temperature extremes. The 90 % quantile is found to be a suitable threshold for all stations. We find that the RLs of the observed T max are above 50 • C at northern stations and above 45 • C at the southern stations. The RLs of the observed TW max exceed 35 • C in the region, which is considered as a limit of survivability. The RLs estimated from the ERA-Interim data are lower by 3 to 5 • C than the RLs assessed for the nine meteorological stations. A simple bias correction applied to ERA-Interim data improves the RLs remarkably, yet discrepancies are still present. The results have potential implications for the risk assessment of extreme temperatures in Sindh.

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Section: Introductionmentioning

confidence: 99%

Return levels of temperature extremes in southern Pakistan

Zahid¹,

Blender²,

Lucarini

et al. 2017

Earth Syst. Dynam.

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“…Thus, the dynamic timing threshold is adopted to avoid disadvantageous factors and ensure the reasonability of threshold selection. The dynamic threshold is defined as (Coelho et al, 2008) …”

Section: Methodsmentioning

confidence: 99%

“…Use log σ to ensure the scale parameters positive and set the scale parameters as bilinear function to smooth its space (Coelho et al, 2008).…”

Section: Methodsmentioning

confidence: 99%

Effects of regional warming on extreme monthly low temperatures distribution in China

Zhou¹,

Wan²,

Feng³

et al. 2010

Intl Journal of Climatology

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Using generalised Pareto distribution (GPD) function, the regional characteristic of extreme monthly low temperatures (EMLT) distribution during 1960-2007 in China is studied, and the potential impact of climate warming on EMLT regions in China is analysed. The results show that EMLT space distribution has latitudinal difference in China. Higher-value EMLT events are likely to happen in northeastern and southwestern China, while EMLT variability and occurrence probability of high-value EMLT events are less in the Yangtze and Huaihe River basin and the coast of southern China. The study indicates that climate warming impacts EMLT, and EMLT distribution responds to the climate warming over most areas of China.

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“…For this study the GP distribution is chosen as it has been shown to fit meteorological data well (e.g. M11, also Coelho et al, 2008).…”

Section: Extreme Variability Of the Vortexmentioning

confidence: 99%

The nature of Arctic polar vortices in chemistry–climate models

Mitchell

Charlton‐Perez

Gray

et al. 2012

Quart J Royal Meteoro Soc

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† The contributions of these authors were written in the course of their employment at the Met Office, UK, and are published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.The structure of the Arctic stratospheric polar vortex in three chemistry-climate models (CCMs) taken from the CCMVal-2 intercomparison is examined using zonal mean and geometric-based methods. The geometric methods are employed by taking 2D moments of potential vorticity fields that are representative of the polar vortices in each of the models. This allows the vortex area, centroid location and ellipticity to be determined, as well as a measure of vortex filamentation. The first part of the study uses these diagnostics to examine how well the mean state, variability and extreme variability of the polar vortices are represented in CCMs compared to ERA-40 reanalysis data, and in particular for the UMUKCA-METO, NIWA-SOCOL and CCSR/NIES models. The second part of the study assesses how the vortices are predicted to change in terms of the frequency of sudden stratospheric warmings and their general structure over the period 1960-2100.In general, it is found that the vortices are climatologically too far poleward in the CCMs and produce too few large-scale filamentation events. Only a small increase is observed in the frequency of sudden stratospheric warming events from the mean of the CCMVal-2 models, but the distribution of extreme variability throughout the winter period is shown to change towards the end of the twentyfirst century.

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Methods for Exploring Spatial and Temporal Variability of Extreme Events in Climate Data

Cited by 89 publications

References 32 publications

Return levels of temperature extremes in southern Pakistan

Return levels of temperature extremes in southern Pakistan

Effects of regional warming on extreme monthly low temperatures distribution in China

The nature of Arctic polar vortices in chemistry–climate models

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