Articles | Volume 14, issue 12
https://doi.org/10.5194/essd-14-5287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-5287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region
Campus Alpin (IMK-IFU), Karlsruhe Institute of Technology, Kreuzeckbahnstraße 19, 82467 Garmisch-Partenkirchen, Germany
Andreas Wagner
Institute of Geography (IGUA), University of Augsburg, Alter Postweg 118, 86159 Augsburg, Germany
Bettina Kamm
Institute of Photogrammetry and Remote Sensing (IPF), Karlsruhe Institute of Technology, Englerstr. 7, 76131 Karlsruhe, Germany
Endrit Shehaj
Institute of Geodesy and Photogrammetry, ETH Zurich, Robert-Gnehm-Weg 15, 8093 Zurich, Switzerland
Andreas Schenk
Institute of Photogrammetry and Remote Sensing (IPF), Karlsruhe Institute of Technology, Englerstr. 7, 76131 Karlsruhe, Germany
Peng Yuan
Geodetic Institute (GIK), Karlsruhe Institute of Technology, Englerstr. 7, 76131 Karlsruhe, Germany
Alain Geiger
Institute of Geodesy and Photogrammetry, ETH Zurich, Robert-Gnehm-Weg 15, 8093 Zurich, Switzerland
Gregor Moeller
Institute of Geodesy and Photogrammetry, ETH Zurich, Robert-Gnehm-Weg 15, 8093 Zurich, Switzerland
Bernhard Heck
Geodetic Institute (GIK), Karlsruhe Institute of Technology, Englerstr. 7, 76131 Karlsruhe, Germany
Stefan Hinz
Institute of Photogrammetry and Remote Sensing (IPF), Karlsruhe Institute of Technology, Englerstr. 7, 76131 Karlsruhe, Germany
Hansjörg Kutterer
Geodetic Institute (GIK), Karlsruhe Institute of Technology, Englerstr. 7, 76131 Karlsruhe, Germany
Harald Kunstmann
Campus Alpin (IMK-IFU), Karlsruhe Institute of Technology, Kreuzeckbahnstraße 19, 82467 Garmisch-Partenkirchen, Germany
Institute of Geography (IGUA), University of Augsburg, Alter Postweg 118, 86159 Augsburg, Germany
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Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743, https://doi.org/10.5194/essd-15-723-2023, https://doi.org/10.5194/essd-15-723-2023, 2023
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We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 22, 3875–3895, https://doi.org/10.5194/nhess-22-3875-2022, https://doi.org/10.5194/nhess-22-3875-2022, 2022
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Matthias Aichinger-Rosenberger, Elmar Brockmann, Laura Crocetti, Benedikt Soja, and Gregor Moeller
Atmos. Meas. Tech., 15, 5821–5839, https://doi.org/10.5194/amt-15-5821-2022, https://doi.org/10.5194/amt-15-5821-2022, 2022
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Maik Heistermann, Heye Bogena, Till Francke, Andreas Güntner, Jannis Jakobi, Daniel Rasche, Martin Schrön, Veronika Döpper, Benjamin Fersch, Jannis Groh, Amol Patil, Thomas Pütz, Marvin Reich, Steffen Zacharias, Carmen Zengerle, and Sascha Oswald
Earth Syst. Sci. Data, 14, 2501–2519, https://doi.org/10.5194/essd-14-2501-2022, https://doi.org/10.5194/essd-14-2501-2022, 2022
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S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-7-2022, https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-7-2022, 2022
M. Rebmeister, A. Schenk, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 341–348, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-341-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-341-2022, 2022
S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022, https://doi.org/10.5194/isprs-annals-V-1-2022-7-2022, 2022
A. Michel, W. Gross, S. Hinz, and W. Middelmann
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 291–298, https://doi.org/10.5194/isprs-annals-V-2-2022-291-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-291-2022, 2022
M. Evers, A. Thiele, H. Hammer, and S. Hinz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 107–114, https://doi.org/10.5194/isprs-annals-V-3-2022-107-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-107-2022, 2022
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
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Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
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In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2021, 7–7, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-7-2021, https://doi.org/10.5194/isprs-archives-XLIII-B1-2021-7-2021, 2021
M. Evers, A. Thiele, H. Hammer, E. Cadario, K. Schulz, and S. Hinz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 147–154, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-147-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-147-2021, 2021
S. Hinz, R. Q. Feitosa, M. Weinmann, and B. Jutzi
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2021, 7–7, https://doi.org/10.5194/isprs-annals-V-1-2021-7-2021, https://doi.org/10.5194/isprs-annals-V-1-2021-7-2021, 2021
Christof Lorenz, Tanja C. Portele, Patrick Laux, and Harald Kunstmann
Earth Syst. Sci. Data, 13, 2701–2722, https://doi.org/10.5194/essd-13-2701-2021, https://doi.org/10.5194/essd-13-2701-2021, 2021
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Short summary
Semi-arid regions depend on the freshwater resources from the rainy seasons as they are crucial for ensuring security for drinking water, food and electricity. Thus, forecasting the conditions for the next season is crucial for proactive water management. We hence present a seasonal forecast product for four semi-arid domains in Iran, Brazil, Sudan/Ethiopia and Ecuador/Peru. It provides a benchmark for seasonal forecasts and, finally, a crucial contribution for improved disaster preparedness.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
N. Mazroob Semnani, M. Breunig, M. Al-Doori, A. Heck, P. Kuper, and H. Kutterer
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 485–492, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-485-2020, https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-485-2020, 2020
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Short summary
In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was...
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