A method for deriving a future temporal spectrum of heavy precipitation on the basis of weather patterns in low mountain ranges

Franke, Johannes; Bernhofer, Christian

doi:10.1002/met.149

Cited by 9 publications

(17 citation statements)

References 16 publications

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“…Although it is rather difficult to predict future extreme precipitation events based on climate projections, trend analyses carried out in this region point to a likely increase of heavy rains, in terms of both intensity and the probability of their occurrence (Franke and Bernhofer 2009). …”

Section: Heavy Rain Impacts On Buildingsmentioning

confidence: 99%

Heavy rainfall: An underestimated environmental risk for buildings?

et al. 2016

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Abstract. Although impacts of heavy rain on buildings in urban areas are often extensive, the public usually underestimates the negative consequences of that environmental risk compared e.g. to storm or hail events. However, the intensification of extreme weather events due to climate change as well as the rising physical vulnerability of assets are going to trigger the increase of impacts on the built environment. Heavy rain events are often highly localised that makes it difficult to estimate their probability and magnitude accurately. High intensity rain affects buildings both directly as well as indirectly.First, engineering surveys have already proven the broad variety and high physical vulnerability of building constructions that are directly and frequently affected by invading water during heavy rainfall events: flat roofs, roof terraces and balconies, connections between steep roofs and other building parts, soil-covered slabs of underground parking, soil-contacted basement walls and bottom plates as well as windows and external doors. It became evident that most damage is avoidable if exposed constructions become more resilient. Nevertheless, any adaptations require expertise on the demanding damage processes in order to explore deficiencies and to reduce physical vulnerability of building constructions exposed to heavy rainfall. In response to that challenge, the paper describes an engineering approach for the systematic classification of physical vulnerability criteria based on empirical research. A developed classification scheme allows the ex-ante examination of typical failure modes and the evaluation of negative consequences of heavy rainfall at individual building level. The topic is of high relevance, because the classification scheme may act as a capable tool for the prospective planning of adaptations towards more resilient buildings.Second, heavy rain may result in urban pluvial flooding due to sewer overflow that cause severe damage to buildings. A comprehensive study of the impacts and the consequences in Dresden (Germany), presented in the paper, revealed that the potential risks of flooding from sewers due to hydraulic overload can be estimated on building scale using the model approach IVART (Integrated Spatial Vulnerability and Risk Assessment Tool). Modelling results provide the basis to quantify the effectiveness and efficiency of flood resilience technologies.

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Section: Heavy Rain Impacts On Buildingsmentioning

confidence: 99%

Heavy rainfall: An underestimated environmental risk for buildings?

et al. 2016

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“…It is therefore assumed that the disaggregation of past or projected rainfall would imprint the scaling behaviour observed during the parameterization period on the target time slice, expecting that the scaling properties remain stationary between both periods. Since the climate system is in fact highly nonstationary, with short-term fluctuations and long-term trends (Rapp, 2000) and the resulting changes in the frequency and intensity of heavy precipitation events (Franke et al, 2004;Franke and Bernhofer, 2009), it can be argued that the parameters of a disaggregation model could be not transferable to different climatic periods. Considering the Wernersbach Table 2.…”

Section: Coupling Of Generator Parameters To a Climate Signalmentioning

confidence: 99%

“…It is worth noting that while the frequency of the CPs may change between time slices, the relationship between MRC parameters and CPs is assumed to be invariant in time. A similar method has already been successfully employed for the derivation of a future temporal spectrum of heavy precipitation by Franke and Bernhofer (2009).…”

Section: Parameterizationmentioning

confidence: 99%

Circulation pattern based parameterization of a multiplicative random cascade for disaggregation of observed and projected daily rainfall time series

Lisniak

Franke

Bernhofer

2013

Hydrol. Earth Syst. Sci.

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Abstract. The use of multiplicative random cascades (MRCs) for temporal rainfall disaggregation has been extensively studied in the past. MRCs are appealing for rainfall disaggregation due to their formal simplicity and the possibility to extract the model parameters directly from observed high resolution rainfall data. These parameters, however, represent the rainfall characteristics of the observation period. Since rainfall characteristics of different time slices are changing due to climate variability, we propose a parameterization approach for MRCs to adjust the parameters according to past (observed) or future (projected) time series. This is done on the basis of circulation patterns (CPs) by extracting a distinct MRC parameterization from high resolution rainfall data, as observed on days governed by each individual CP. The parameterization approach is tested by comparing the statistical properties of disaggregated rainfall time series of two time slices, 1969-1979 and 1989-1999, to the results obtained by two other disaggregation methods (a conceptually similar MRC without CP-based parameterization and a recombination approach) and to the statistical properties of observed hourly rainfall data. In this context, all three approaches use rainfall data of the time slice 1989-1999 for parameterization. We found that the inclusion of CPs into the parameterization of a MRC yields hourly time series that better reproduce the properties of observed rainfall in time slice [1989][1990][1991][1992][1993][1994][1995][1996][1997][1998][1999], as compared to the simple MRC. Despite similar results of both MRCs in the validation period of 1969-1979, we can conclude that the CP-based parameterization approach is applicable for temporal rainfall disaggregation in time slices distinct from the parameterization period. This approach accounts for changes in rainfall characteristics due to changes in the frequency of occurrence of the CPs and allows generating hourly rainfall from daily data, as often provided by a statistical downscaling of global climate change.

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“…The method was modified by adaptation to area-specific characteristics for this purpose. This means that correction depended on a station-related wind protection class and an elevation-related threshold temperature to distinguish between kinds of precipitation (Franke et al, 2006). The parameterization of the trigonometric regionalization approach is based on hourly measured values of precipitation, wind speed and wind direction in the 1997-2003 growing seasons that were simultaneously recorded at all gauging locations as a matter of principle.…”

Section: Datamentioning

confidence: 99%

Application of a trigonometric approach to the regionalization of precipitation for a complex small‐scale terrain in a GIS environment

Franke

Häntzschel²,

Goldberg

et al. 2008

Meteorological Applications

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ABSTRACT:To regionalize precipitation on a small-scale, complex, low mountain range terrain, trigonometric relationships were constructed in a geographical information system (GIS) environment using a digital elevation model (DEM). The large-scale orographic effect and small-scale windward and leeward effects on precipitation were recorded and quantified using a grid-based combination of a terrain vector (slope angle, aspect) with a wind vector (wind direction, speed). This was based on the parameterization of a longer-term wind-precipitation distribution. Both effects were mapped for the meso-scale Weißeritz River catchment in the Ore Mountains of Germany, using an estimate of spatially distributed slope precipitation. It was shown that the small-scale windward and leeward effects modify the larger-scale orographic effect spatially. It was determined that both the amount and the phase of the small-scale windward and leeward effect correlates with the height above sea level. During the 1971-2003 growing seasons the amount of precipitation increased by 4% per 100 m, and for the 1971-2000 statistically heavy precipitation (SHP) (duration: 24 h, return period: 100 years) the increase was 1% per 100 m. The phase shift occurred because the main wind veered south-west to west to north-west with elevation increase, and it was more pronounced for mean than for heavy precipitation. Spatial slope precipitation was estimated to be within the 390-715 mm range for mean adjusted precipitation and 100-140 mm for SHP. The maximum of the windward and leeward effect on precipitation amounts to ±25% of fallen precipitation.

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A method for deriving a future temporal spectrum of heavy precipitation on the basis of weather patterns in low mountain ranges

Cited by 9 publications

References 16 publications

Heavy rainfall: An underestimated environmental risk for buildings?

Heavy rainfall: An underestimated environmental risk for buildings?

Circulation pattern based parameterization of a multiplicative random cascade for disaggregation of observed and projected daily rainfall time series

Application of a trigonometric approach to the regionalization of precipitation for a complex small‐scale terrain in a GIS environment

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