An open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST v0.1.1)

Förster, Kristian; Hanzer, Florian; Winter, Benjamin; Marke, Thomas; Strasser, Ulrich

doi:10.5194/gmd-9-2315-2016

Cited by 48 publications

(29 citation statements)

References 34 publications

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“…Since WaSiM is more complex than HBV with respect to computational needs, a different strategy for model calibration was chosen. As the number of both adjustable parameters and iterations is limited due to limited computational resources, a lexicographical approach was set up for model calibration (Gelleszun et al, 2017). In this way, the optimization of parameters is divided into subsequent steps that are associated with different processes.…”

Section: (B) Wasimmentioning

confidence: 99%

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Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence?

Müller-Thomy

Wallner²,

Förster

2018

Hydrol. Earth Syst. Sci.

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Abstract. In this study, the influence of disaggregated rainfall products with different degrees of spatial consistence on rainfall–runoff modeling results is analyzed for three mesoscale catchments in Lower Saxony, Germany. For the disaggregation of daily rainfall time series into hourly values, a multiplicative random cascade model is applied. The disaggregation is applied on a station by station basis without consideration of surrounding stations; hence subsequent steps are then required to implement spatial consistence. Spatial consistence is represented here by three bivariate spatial rainfall characteristics that complement each other. A resampling algorithm and a parallelization approach are evaluated against the disaggregated time series without any subsequent steps. With respect to rainfall, clear differences between these three approaches can be identified regarding bivariate spatial rainfall characteristics, areal rainfall intensities and extreme values. The resampled time series lead to the best agreement with the observed ones. Using these different rainfall products as input to hydrological modeling, we hypothesize that derived runoff statistics – with emphasis on seasonal extreme values – are subject to similar differences as well. However, an impact on the extreme values' statistics of the hydrological simulations forced by different rainfall approaches cannot be detected. Several modifications of the study design using rainfall–runoff models with and without parameter calibration or using different rain gauge densities lead to similar results in runoff statistics. Only if the spatially highly resolved rainfall–runoff WaSiM model is applied instead of the semi-distributed HBV-IWW model can slight differences regarding the seasonal peak flows be identified. Hence, the hypothesis formulated before is rejected in this case study. These findings suggest that (i) simple model structures might compensate for deficiencies in spatial representativeness through parameterization and (ii) highly resolved hydrological models benefit from improved spatial modeling of rainfall.

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Section: (B) Wasimmentioning

confidence: 99%

“…From the Braunlage climate station, time series of temperature, relative air humidity and wind speed are available with an hourly resolution. Global radiation was only available on a daily basis, but has been disaggregated to hourly values using an approach as in Förster et al (2016).…”

mentioning

confidence: 99%

Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence?

Müller-Thomy

Wallner²,

Förster

2018

Hydrol. Earth Syst. Sci.

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“…As the EURO-CORDEX simulations were however only available in daily temporal resolution, an additional processing step was necessary. This step was performed with the open-source temporal disaggregation tool MELODIST (Förster et al, 2016). MELODIST provides simple, empirical disaggregation routines for the sub-daily disaggregation of daily point-scale data for the variables air temperature, precipitation, relative humidity, solar radiation, and wind speed.…”

Section: Temporal Downscaling Of Rcm Datamentioning

confidence: 99%

Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach

Hanzer

Förster

Nemec

et al. 2018

Hydrol. Earth Syst. Sci.

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123

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Abstract.A physically based hydroclimatological model (AMUNDSEN) is used to assess future climate change impacts on the cryosphere and hydrology of the Ötztal Alps (Austria) until 2100. The model is run in 100 m spatial and 3 h temporal resolution using in total 31 downscaled, bias-corrected, and temporally disaggregated EURO-CORDEX climate projections for the representative concentration pathways (RCPs) 2.6, 4.5, and 8.5 scenarios as forcing data, making this -to date -the most detailed study for this region in terms of process representation and range of considered climate projections. Changes in snow coverage, glacierization, and hydrological regimes are discussed both for a larger area encompassing the Ötztal Alps (1850 km 2 , 862-3770 m a.s.l.) as well as for seven catchments in the area with varying size (11-165 km 2 ) and glacierization (24-77 %).Results show generally declining snow amounts with moderate decreases (0-20 % depending on the emission scenario) of mean annual snow water equivalent in high elevations (> 2500 m a.s.l.) until the end of the century. The largest decreases, amounting to up to 25-80 %, are projected to occur in elevations below 1500 m a.s.l. Glaciers in the region will continue to retreat strongly, leaving only 4-20 % of the initial (as of 2006) ice volume left by 2100. Total and summer (JJA) runoff will change little during the early 21st century with simulated decreases (compared to 1997-2006) of up to 11 % (total) and 13 % (summer) depending on catchment and scenario, whereas runoff volumes decrease by up to 39 % (total) and 47 % (summer) towards the end of the century (2071-2100), accompanied by a shift in peak flows from July towards June.

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“…Different land use types have been taken into account by using an average land use and wind speed are available with an hourly resolution. Global radiation was only available on a daily basis, but has been 5 disaggregated to hourly values using an approach as per Förster et al (2016).…”

Section: Climate Datamentioning

confidence: 99%

Rainfall disaggregation for hydrological modeling: Is there a need for spatial consistence?

Müller¹,

Wallner²,

Förster³

et al. 2017

Preprint

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Abstract.In this investigation, the influence of disaggregated rainfall data sets with different degrees of spatial consistence on rainfall runoff modeling results is analyzed for three meso-scale catchments in Lower Saxony, Germany. For the disaggregation of daily rainfall time series into hourly values a multiplicative random cascade model is applied. The disaggregation is applied on a per station basis without consideration of surrounding stations, hence subsequent steps are then required to implement 15 spatial consistence. Spatial consistence is here represented by three bivariate spatial rainfall characteristics, complementing each other. A resampling algorithm and a parallelization approach are evaluated against the disaggregated time series without any subsequent steps. With respect to rainfall, clear differences between these three approaches can be identified regarding bivariate spatial rainfall characteristics, areal rainfall intensities and extreme values. The resampled time series lead to the best agreement with the observed ones. Using these different rainfall data sets as input to hydrological modeling, 20 we hypothesize that derived runoff statistics are subject to similar differences as well. However, an impact on the runoff statistics summer and winter peak flows, monthly average discharge and flow duration curve of the simulated runoff time series cannot be detected. Several modifications of the investigation using rainfall runoff models with and without parameter calibration or using different rain gauge densities lead to similar results in runoff statistics. Only if the spatially highly resolved rainfall-runoff WaSiM-model is applied instead of the semi-distributed HBV-IWW-model, slight differences 25 regarding the seasonal peak flows can be identified. Hence, the hypothesis formulated before is rejected in this case study. These findings suggest that (i) simple model structures might compensate for deficiencies in spatial representativeness through parameterization and (ii) highly resolved hydrological models benefit from improved spatial modeling of rainfall.Hydrol. Earth Syst. Sci. Discuss., https://doi

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An open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST v0.1.1)

Cited by 48 publications

References 34 publications

Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence?

Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence?

Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach

Rainfall disaggregation for hydrological modeling: Is there a need for spatial consistence?

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