Pan-European groundwater to atmosphere terrestrial systems climatology from a physically consistent simulation

Furusho, Carina; Goergen, Klaus; Hartick, Carl; Kulkarni, Ketan; Keune, Jessica; Kollet, Stefan

doi:10.1038/s41597-019-0328-7

Cited by 40 publications

(51 citation statements)

References 41 publications

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“…The TSMP simulation results, especially anomalies, show high agreement with in situ and satellite observations (i.e., E-OBS v19 and GRACE datasets), as presented in Furusho-Percot et al, (2019). We had a sentence in our manuscript (Line 200-204) to…”

Section: Cross-wavelet Transform Are Also Used To Analyze the Responsmentioning

confidence: 74%

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Ma¹

2020

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Section: Cross-wavelet Transform Are Also Used To Analyze the Responsmentioning

confidence: 74%

“…Printer-friendly version Discussion paper address your concern about the performance of TSMP, and the reader is referred to related references [e.g., Furusho-Percot et al, (2019)] for detailed information.…”

Section: Hessdmentioning

confidence: 99%

Comment_responses_referee2_Ma_et_al

Ma¹

2020

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“…Please contract Yueling Ma at y.ma@fz-juelich.de. The TSMP-G2A data set is available online at https://doi.org/10.17616/R31NJMH3 (Furusho-Percot et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…and abbreviations, coordinates, and climatologic information. The climatology is represented by regional averages and standard deviations of yearly averaged data derived from the TSMP-G2A data set(Furusho-Percot et al, 2019) from the years 1996 to 2016, except for Sw of which data are only available from the years 2003 to 2010. The TSMP-G2A data set consists of daily averaged simulation results from the Terrestrial Systems Modeling Platform (TSMP) over Europe, using the grid definition from the COordinated Regional Downscaling Experiment (CORDEX) framework with a spatial resolution of 0.11° (12.5 km, EUR-11).…”

mentioning

confidence: 99%

“…The TSMP-G2A data set consists of daily averaged simulation results from the Terrestrial Systems Modeling Platform (TSMP) over Europe, using the grid definition from the COordinated Regional Downscaling Experiment (CORDEX) framework with a spatial resolution of 0.11° (12.5 km, EUR-11). TSMP is a fully coupled atmosphere-land-surface-subsurface modeling system, giving a physically consistent representation of the terrestrial water and energy cycle from the groundwater via the land surface to the top of the atmosphere(Keune et al, 2016;Furusho-Percot et al, 2019). TSMP has been successfully applied in many studies to simulate the terrestrial hydrological processes, e.g.,Shrestha et al (2014),Kurtz et al (2016),Sulis et al (2018) andKeune et al (2019).…”

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confidence: 99%

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Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe

Ma¹,

Montzka²,

Bayat³

et al. 2020

Preprint

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Abstract. Many European countries mainly rely on groundwater for domestic water use. Due to a scarcity of near real-time water table depth (wtd) observations, establishing a spatially consistent groundwater monitoring system at the continental scale is a challenge. Hence, it is necessary to develop alternative methods to estimate wtd anomalies (wtda) using other hydrometeorological observations routinely available near real-time. In this work, we explore the potential of Long Short-Term Memory (LSTM) networks to produce monthly wtda, using monthly precipitation anomalies (pra) as input. LSTM networks are a special category of artificial neural networks, useful in detecting a long-term dependency within sequences, in our case time series, which is expected in the relationship between pra and wtda. To set up the methodology, spatio-temporally continuous data were obtained from daily terrestrial simulations (hereafter termed the TSMP-G2A data set) with a spatial resolution of 0.11°, ranging from the year 1996 to 2016. They were separated into a training set (1996–2012), a validation set (2013–2014), and a test set (2015–2016) to establish local networks at selected pixels across Europe. The modeled wtda maps from LSTM networks agreed well with TSMP-G2A wtda maps in 2003 and 2015 constituting drought years over Europe. Moreover, we categorized test performances of the networks based on yearly averaged wtd, evapotranspiration (ET), soil moisture (θ), snow water equivalent (Sw), and soil type (St) and dominant plant functional type (PFT). Superior test performance was found at the pixels with wtd 200 mm, θ > 0.15 m3 m−3 and Sw

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Regionale Klimamodellierung

Rechid,

Breil,

Jacob

et al. 2023

Klimawandel in Deutschland

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ZusammenfassungRegionalisierungen von globalen Klimaprojektionen liefern räumlich detaillierte Informationen zu den Auswirkungen globaler Klimaänderungen auf einzelne Regionen, welche als Basis für die Forschung zu Klimafolgen, Vulnerabilität und Anpassungsoptionen dienen. Die Vielfalt der dafür eingesetzten regionalen Klimamodelle wird vorgestellt. Dabei widmet sich das Kapitel ebenso den methodischen Ansätzen, Herausforderungen und neuen Entwicklungen der regionalen Klimamodellierung und der Validierung der einzelnen Modelle, wie auch der Interpretation und Darstellung der Modellergebnisse, die zur Berücksichtigung von Unsicherheiten in Bandbreiten zu fassen sind. Dargestellt werden Ergebnisse regionaler Klimasimulationen basierend auf dem neuesten Stand des EURO-CORDEX Ensemble, der Schwerpunkt liegt auf Temperatur und Niederschlag.

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Pan-European groundwater to atmosphere terrestrial systems climatology from a physically consistent simulation

Cited by 40 publications

References 41 publications

Comment_responses_referee2_Ma_et_al

Comment_responses_referee2_Ma_et_al

Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe

Regionale Klimamodellierung

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