Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes

Sørup, Hjalte Jomo Danielsen; Georgiadis, Stylianos; Gregersen, Ida Bülow; Arnbjerg‐Nielsen, Karsten

doi:10.5194/hess-21-345-2017

Cited by 13 publications

(5 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, no correction is applied to GCM precipitation projections. Instead, the relative change between the historical and scenario simulations of the GCM is used to calculate a change factor that can then be applied to the observed time series (Sunyer et al, 2012(Sunyer et al, , 2015. The method applied to the precipitation P of day t in month m Table 1.…”

Section: Change Factor Of Mean (Cfm) Methodsmentioning

confidence: 99%

Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Tabari

Paz

Buekenhout

et al. 2021

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. General circulation models (GCMs) are the primary tools for evaluating the possible impacts of climate change; however, their results are coarse in temporal and spatial dimensions. In addition, they often show systematic biases compared to observations. Downscaling and bias correction of climate model outputs is thus required for local applications. Apart from the computationally intensive strategy of dynamical downscaling, statistical downscaling offers a relatively straightforward solution by establishing relationships between small- and large-scale variables. This study compares four statistical downscaling methods of bias correction (BC), the change factor of mean (CFM), quantile perturbation (QP) and an event-based weather generator (WG) to assess climate change impact on drought by the end of the 21st century (2071–2100) relative to a baseline period of 1971–2000 for the weather station of Uccle located in Belgium. A set of drought-related aspects is analysed, i.e. dry day frequency, dry spell duration and total precipitation. The downscaling is applied to a 28-member ensemble of Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs, each forced by four future scenarios of SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5. A 25-member ensemble of CanESM5 GCM is also used to assess the significance of the climate change signals in comparison to the internal variability in the climate. A performance comparison of the downscaling methods reveals that the QP method outperforms the others in reproducing the magnitude and monthly pattern of the observed indicators. While all methods show a good agreement on downscaling total precipitation, their results differ quite largely for the frequency and length of dry spells. Using the downscaling methods, dry day frequency is projected to increase significantly in the summer months, with a relative change of up to 19 % for SSP5–8.5. At the same time, total precipitation is projected to decrease significantly by up to 33 % in these months. Total precipitation also significantly increases in winter, as it is driven by a significant intensification of extreme precipitation rather than a dry day frequency change. Lastly, extreme dry spells are projected to increase in length by up to 9 %.

show abstract

Section: Change Factor Of Mean (Cfm) Methodsmentioning

confidence: 99%

Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Tabari

Paz

Buekenhout

et al. 2021

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…The author showed that synthetic but high-resolution time series could be used to assess the probability distribution of the variables and predict short-term operation rules and hydropower generation, which are crucial for securing WRM. The climate change impacts on these time series were also considered in recent studies (Pereira-Cardenal et al 2014;Sørup et al 2017). Sechi et al (2019) used the stochastic quasi-gradient method to optimize and simulate a pumping system's often conflicting water deficit and energy consumption.…”

Section: Reservoirs and Hydropower Plantsmentioning

confidence: 99%

Nordic contributions to stochastic methods in hydrology

et al. 2022

View full text Add to dashboard Cite

The paper presents prominent Nordic contributions to stochastic methods in hydrology and water resources during the previous 50 years. The development in methods from analysis of stationary and independent hydrological events to include non-stationarity, risk analysis, big data, operational research and climate change impacts is hereby demonstrated. The paper is divided into four main sections covering flood frequency and drought analyses, assessment of rainfall extremes, stochastic approaches to water resources management and approaches to climate change and adaptation efforts. It is intended as a review paper referring to a rich selection of internationally published papers authored by Nordic hydrologists or hydrologists from abroad working in a Nordic country or in cooperation with Nordic hydrologists. Emerging trends in needs and methodologies are highlighted in the conclusions.

show abstract

“…Furthermore, they define several classes of dry spell lengths (Table 4), based on the percentiles of dry spell length calculated using the historical period of the study. Dry spells are not to be confused with the terms dry events (Willems, 2013;Willems and Vrac, 2011) or inter-events (Sørup et al, 2017;Thorndahl et al, 2017) used in the SDMs. This is due to the definition of dry spells comprising consecutive dry days (≥ 2 days).…”

Section: Research Indicatorsmentioning

confidence: 99%

Comparison of statistical downscaling methods for climate change impact analysis on drought

Tabari

Buekenhout

Willems

2020

Preprint

View full text Add to dashboard Cite

Abstract. General circulation models (GCMs) are the primary tools to evaluate the possible impacts of climate change; however, their results are coarse in temporal and spatial dimensions. In addition, they often show systematic biases compared to observations. Downscaling and bias correction of climate model outputs is thus required for local applications. Besides the computationally intensive strategy of dynamical downscaling, statistical downscaling offers a relatively straightforward solution by establishing relationships between small and large scale variables. This study compares four statistical downscaling methods (SDMs) of bias correction (BC), change factor of mean (CFM), quantile perturbation (QP) and event based weather generator (EBWG) to assess climate change impact on drought by the end of the 21st century (2071–2100) relative to a baseline period of 1971–2000. A set of drought related aspects is analysed: dry day frequency, dry spell duration and total precipitation. The downscaling is applied to a 14-member ensemble of CMIP6 GCMs, each powered by four future scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. A 25-member ensemble of CanESM5 GCM is also used to assess the significance of the climate change signals in comparison to the internal variability of the climate. While all methods show a good agreement on downscaling total precipitation, the CFM method fails to downscale dry day frequency well. The QP method outperforms the others in downscaling dry spells. Using this method, dry day frequency is projected to increase significantly in the summer months, with relative changes of up to 20.4 % in the worst-case climate change scenario. At the same time, total precipitation is projected to decrease significantly by up to 41.9 % in these months. Lastly, extreme dry spells are projected to increase in length by up to 7.4 %.

show abstract

Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes

Cited by 13 publications

References 39 publications

Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought

Nordic contributions to stochastic methods in hydrology

Comparison of statistical downscaling methods for climate change impact analysis on drought

Contact Info

Product

Resources

About