Climatologically based warning system against meteorological hazards and weather extremes: the example for Poland

Ustrnul, Zbigniew; Wypych, Agnieszka; Henek, Ewelina; Maciejewski, Michał; Bochenek, Bogdan

doi:10.1007/s11069-015-1673-2

Cited by 13 publications

(7 citation statements)

References 15 publications

(11 reference statements)

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“…Regarding precipitation extremes, they are usually detected by maximum daily totals P 1 at any individual rain gauge (Ustrnul et al, 2015) or by areal precipitation means A d during d days, for example, for d = 2 days (Konrad, 2001). The first approach is commonly used in the Czech Republic: Štekl et al (2001) analyzed days during the period of 1876-2000 when a daily total reached at least 150 mm anywhere in the Czech Republic.…”

Section: Comparison With Standard Indicesmentioning

confidence: 99%

Novel indices for the comparison of precipitation extremes and floods: an example from the Czech territory

Müller

Kašpar

Valeriánová

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. This paper presents three indices for evaluation of hydrometeorological extremes, considering them as areal precipitation events and trans-basin floods. In contrast to common precipitation indices, the weather extremity index (WEI) reflects not only the highest precipitation amounts at individual gauges but also the rarity of the amounts, the size of the affected area, and the duration of the event. Furthermore, the aspect of precipitation seasonality was considered when defining the weather abnormality index (WAI), which enables the detection of precipitation extremes throughout the year. The precipitation indices are complemented with the flood extremity index (FEI) employing peak discharge data. A unified design of the three indices, based on return periods of station data, enables one to compare easily interannual and seasonal distributions of precipitation extremes and large floods.The indices were employed in evaluation of 50 hydrometeorological extremes of each type (extreme precipitation events, seasonally abnormal precipitation events, and large floods) during the period 1961-2010 in the Czech Republic. A preliminary study of discrepancies among historic values of the indices indicated that variations in the frequency and/or magnitude of floods can generally be due not only to variations in the magnitude of precipitation events but also to variations in their seasonal distribution and other factors, primarily the antecedent saturation.

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Section: Comparison With Standard Indicesmentioning

confidence: 99%

Novel indices for the comparison of precipitation extremes and floods: an example from the Czech territory

Müller

Kašpar

Valeriánová

et al. 2015

Hydrol. Earth Syst. Sci.

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“…The method proposed in this study uses a Regional Climate Model to yield regularly distributed gridded data and to assimilate them into algorithms describing favourable meteorological conditions for each given weather phenomenon. The algorithms have been previously validated on both observational and modelled weather data (WYPYCH et al 2014;USTRNUL et al 2015). The resulting FMC maps exhibit an adequate quality of prediction.…”

Section: Discussionmentioning

confidence: 99%

Geospatial Predictive Modelling for Climate Mapping of Selected Severe Weather Phenomena Over Poland: A Methodological Approach

Walawender

Ustrnul

2016

Pure Appl. Geophys.

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The main purpose of the study is to introduce methods for mapping the spatial distribution of the occurrence of selected atmospheric phenomena (thunderstorms, fog, glaze and rime) over Poland from 1966 to 2010 (45 years). Limited in situ observations as well the discontinuous and location-dependent nature of these phenomena make traditional interpolation inappropriate. Spatially continuous maps were created with the use of geospatial predictive modelling techniques. For each given phenomenon, an algorithm identifying its favourable meteorological and environmental conditions was created on the basis of observations recorded at 61 weather stations in Poland. Annual frequency maps presenting the probability of a day with a thunderstorm, fog, glaze or rime were created with the use of a modelled, gridded dataset by implementing predefined algorithms. Relevant explanatory variables were derived from NCEP/NCAR reanalysis and downscaled with the use of a Regional Climate Model. The resulting maps of favourable meteorological conditions were found to be valuable and representative on the country scale but at different correlation (r) strength against in situ data (from r = 0.84 for thunderstorms to r = 0.15 for fog). A weak correlation between gridded estimates of fog occurrence and observations data indicated the very local nature of this phenomenon. For this reason, additional environmental predictors of fog occurrence were also examined. Topographic parameters derived from the SRTM elevation model and reclassified CORINE Land Cover data were used as the external, explanatory variables for the multiple linear regression kriging used to obtain the final map. The regression model explained 89 % of annual frequency of fog variability in the study area. Regression residuals were interpolated via simple kriging.

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“…In addition to individual recipients, project stakeholders are also to be responsible for spatial planning and flood protection planning. This mainly concerns the regional water management boards responsible for protecting areas at risk of flooding before they are populated in a way which hinders protection [20,21,22].…”

Section: Methodsmentioning

confidence: 99%

Challenges in Implementing Sendai Framework for Disaster Risk Reduction in Poland

Goniewicz

Burkle

2019

IJERPH

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Currently, weather conditions and extreme weather are becoming more frequent and more intense. Along with climate change, the vulnerability of society and individual regions to the risk of various types of threats also increases. The objectives of “The Sendai Framework for Disaster Risk Reduction 2015–2030”, are the first global political frameworks of the United Nations program designed for the period post-2015. The original priority objectives of the Framework are: Understanding disaster risk, strengthening disaster risk governance to manage disaster risk, investing in disaster risk reduction for resilience, and enhancing disaster preparedness for effective response, and to “Build Back Better” in recovery, rehabilitation, and reconstruction. The provisions contained in the document are an essential step towards building global political coherence with an apparent reference to health, development, and climate change. The article is briefly reporting current Disaster Risk Reduction related programs and policies in Poland, contributions as part of The Sendai Framework for Disaster Risk Reduction implementation, and its challenges.

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Climatologically based warning system against meteorological hazards and weather extremes: the example for Poland

Cited by 13 publications

References 15 publications

Novel indices for the comparison of precipitation extremes and floods: an example from the Czech territory

Novel indices for the comparison of precipitation extremes and floods: an example from the Czech territory

Geospatial Predictive Modelling for Climate Mapping of Selected Severe Weather Phenomena Over Poland: A Methodological Approach

Challenges in Implementing Sendai Framework for Disaster Risk Reduction in Poland

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