Long term variations of extreme rainfall in Denmark and southern Sweden

Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan; Arnbjerg‐Nielsen, Karsten

doi:10.1007/s00382-014-2276-4

Cited by 35 publications

(29 citation statements)

References 24 publications

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“…Using Danish rainfall data on a daily scale Gregersen et al (2014a) have been able to identify multidecadal climate oscillations (Ntegeka and Willems, 2008;Willems, 2013a) as well as climate-related changes in precipitation patterns over the past 140 years. Nevertheless, since this paper is based on evidently shorter rainfall series, it is assumed that no significant trends or climate changes in this period are present.…”

Section: Datamentioning

confidence: 99%

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

Thorndahl

Andersen²,

Larsen³

2017

Hydrol. Earth Syst. Sci.

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Abstract. Continuous and long rainfall series are a necessity in rural and urban hydrology for analysis and design purposes. Local historical point rainfall series often cover several decades, which makes it possible to estimate rainfall means at different timescales, and to assess return periods of extreme events. Due to climate change, however, these series are most likely not representative of future rainfall. There is therefore a demand for climate-projected long rainfall series, which can represent a specific region and rainfall pattern as well as fulfil requirements of long rainfall series which includes climate changes projected to a specific future period. This paper presents a framework for resampling of historical point rainfall series in order to generate synthetic rainfall series, which has the same statistical properties as an original series. Using a number of key target predictions for the future climate, such as winter and summer precipitation, and representation of extreme events, the resampled historical series are projected to represent rainfall properties in a future climate. Climate-projected rainfall series are simulated by brute force randomization of model parameters, which leads to a large number of projected series. In order to evaluate and select the rainfall series with matching statistical properties as the key target projections, an extensive evaluation procedure is developed.

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Section: Datamentioning

confidence: 99%

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

Thorndahl

Andersen²,

Larsen³

2017

Hydrol. Earth Syst. Sci.

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“…They provide valuable information to decision-making within design and analysis of urban water infrastructure, both for quantifying uncertainty and for studying non-stationary behaviour (e.g. Ntegeka and Willems, 2008;Madsen et al, 2009;Willems, 2013a, b;Gregersen et al, 2014). When using single site rain gauges for large catchments, simple areal reduction factors (ARFs) can be applied to account for the spatial distribution of extremes (e.g.…”

Section: General Statistical and Hydrometeorological Characterizationmentioning

confidence: 99%

Weather radar rainfall data in urban hydrology

Thorndahl

Einfalt

Willems

et al. 2017

Hydrol. Earth Syst. Sci.

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158

108

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Abstract. Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

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“…This is because the Poison-cluster model is only parameterized on a monthly basis to reflect monthly variability. Larger scale internal variability may be significant as shown by Willems (2013) and Gregersen et al (2015) who identified multi-decadal oscillations in precipitation extremes. Advances in reflecting internal climate variability by the NSRP model at least on an inter-annual scale has made by Fatichi et al (2011).…”

Section: Climate Model and Sampling Uncertaintymentioning

confidence: 92%