18 Sep 2020
| 18 Sep 2020
FAIR: a project to realize a user-friendly exchange of open weather data
Christopher W. Frank
CISS TDI GmbH, Sinzig, Germany
Frank Kaspar
Deutscher Wetterdienst, Offenbach, Germany
Jan D. Keller
Deutscher Wetterdienst, Offenbach, Germany
Hans-Ertel-Centre for Weather Research, Climate Monitoring and Diagnostics, Germany
Till Adams
terrestris GmbH & Co. KG, Bonn, Germany
mundialis GmbH & Co. KG, Bonn, Germany
Miriam Felkers
BayWa r.e. Wind GmbH, München, Germany
Bernd Fischer
CISS TDI GmbH, Sinzig, Germany
Marcus Handte
Universität Duisburg-Essen, Networked Embedded Systems, Essen, Germany
Pedro José Marrón
Universität Duisburg-Essen, Networked Embedded Systems, Essen, Germany
Hinrich Paulsen
terrestris GmbH & Co. KG, Bonn, Germany
mundialis GmbH & Co. KG, Bonn, Germany
Markus Neteler
mundialis GmbH & Co. KG, Bonn, Germany
Jochen Schiewe
HafenCity Universität Hamburg, Lab for Geoinformatics and Geovisualization (g2lab), Hamburg, Germany
Marvin Schuchert
KME Karlsuhe Marketing und Event GmbH, Karlsruhe, Germany
Christian Nickel
YellowMap AG, Karlsruhe, Germany
Richard Wacker
YellowMap AG, Karlsruhe, Germany
Richard Figura
CORRESPONDING AUTHOR
CISS TDI GmbH, Sinzig, Germany
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Johannes Meuer, Laurens M. Bouwer, Frank Kaspar, Roman Lehmann, Wolfgang Karl, Thomas Ludwig, and Christopher Kadow
EGUsphere, https://doi.org/10.5194/egusphere-2024-1392, https://doi.org/10.5194/egusphere-2024-1392, 2024
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Our study focuses on filling in missing precipitation data using an advanced neural network model. Traditional methods for estimating missing climate information often struggle in large regions where data is scarce. Our solution, which incorporates recent advances in machine learning, captures the intricate patterns of precipitation over time, especially during extreme weather events. Our model shows good performance in reconstructing large regions of missing rainfall radar data.
Abhay Devasthale, Sandra Andersson, Erik Engström, Frank Kaspar, Jörg Trentmann, Anke Duguay-Tetzlaff, Jan Fokke Meirink, Erik Kjellström, Tomas Landelius, Manu Anna Thomas, and Karl-Göran Karlsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-1805, https://doi.org/10.5194/egusphere-2024-1805, 2024
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Using the satellite-based climate data record CLARA-A3 spanning 1982–2020 and ERA5 reanalysis, we present climate regimes that are favourable or unfavourable for solar energy applications. We show that the favourable climate regimes are emerging over much of Europe during spring and early summer for solar energy exploitation.
Thomas Spangehl, Michael Borsche, Deborah Niermann, Frank Kaspar, Semjon Schimanke, Susanne Brienen, Thomas Möller, and Maren Brast
Adv. Sci. Res., 20, 109–128, https://doi.org/10.5194/asr-20-109-2023, https://doi.org/10.5194/asr-20-109-2023, 2023
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The quality of the global reanalysis ERA5, the regional reanalysis COSMO-REA6 and a successor version (R6G2), the new Copernicus European Regional Re-Analysis (CERRA) and a regional downscaling simulation with COSMO-CLM (HoKliSim-De) is assessed for offshore wind farm planning in the German Exclusive Economic Zone (EEZ) of the North Sea. The quality is assessed using in-situ wind measurements at the research platform FINO1 and satellite-based data of the near-surface wind speed as reference.
Katharina Lengfeld, Paul Voit, Frank Kaspar, and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 23, 1227–1232, https://doi.org/10.5194/nhess-23-1227-2023, https://doi.org/10.5194/nhess-23-1227-2023, 2023
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Estimating the severity of a rainfall event based on the damage caused is easy but highly depends on the affected region. A less biased measure for the extremeness of an event is its rarity combined with its spatial extent. In this brief communication, we investigate the sensitivity of such measures to the underlying dataset and highlight the importance of considering multiple spatial and temporal scales using the devastating rainfall event in July 2021 in central Europe as an example.
Alberto Caldas-Alvarez, Markus Augenstein, Georgy Ayzel, Klemens Barfus, Ribu Cherian, Lisa Dillenardt, Felix Fauer, Hendrik Feldmann, Maik Heistermann, Alexia Karwat, Frank Kaspar, Heidi Kreibich, Etor Emanuel Lucio-Eceiza, Edmund P. Meredith, Susanna Mohr, Deborah Niermann, Stephan Pfahl, Florian Ruff, Henning W. Rust, Lukas Schoppa, Thomas Schwitalla, Stella Steidl, Annegret H. Thieken, Jordis S. Tradowsky, Volker Wulfmeyer, and Johannes Quaas
Nat. Hazards Earth Syst. Sci., 22, 3701–3724, https://doi.org/10.5194/nhess-22-3701-2022, https://doi.org/10.5194/nhess-22-3701-2022, 2022
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In a warming climate, extreme precipitation events are becoming more frequent. To advance our knowledge on such phenomena, we present a multidisciplinary analysis of a selected case study that took place on 29 June 2017 in the Berlin metropolitan area. Our analysis provides evidence of the extremeness of the case from the atmospheric and the impacts perspectives as well as new insights on the physical mechanisms of the event at the meteorological and climate scales.
Sebastian Brune and Jan D. Keller
Wind Energ. Sci., 7, 1905–1918, https://doi.org/10.5194/wes-7-1905-2022, https://doi.org/10.5194/wes-7-1905-2022, 2022
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A post-processing of the wind speed of the regional reanalysis COSMO-REA6 in Central Europe is performed based on a combined physical and statistical approach. The physical basis is provided by downscaling wind speeds with the help of a diagnostic wind model, which reduces the horizontal grid point spacing by a factor of 8. The statistical correction using a neural network based on different variables of the reanalysis leads to an improvement of 30 % in RMSE compared to COSMO-REA6.
P. Löwe and M. Neteler
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W1-2022, 287–293, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-287-2022, https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-287-2022, 2022
Martin Knura and Jochen Schiewe
Proc. Int. Cartogr. Assoc., 4, 60, https://doi.org/10.5194/ica-proc-4-60-2021, https://doi.org/10.5194/ica-proc-4-60-2021, 2021
Jonas Luft and Jochen Schiewe
Proc. Int. Cartogr. Assoc., 4, 69, https://doi.org/10.5194/ica-proc-4-69-2021, https://doi.org/10.5194/ica-proc-4-69-2021, 2021
Jochen Schiewe
Proc. Int. Cartogr. Assoc., 4, 95, https://doi.org/10.5194/ica-proc-4-95-2021, https://doi.org/10.5194/ica-proc-4-95-2021, 2021
Sebastian Brune, Jan D. Keller, and Sabrina Wahl
Adv. Sci. Res., 18, 115–126, https://doi.org/10.5194/asr-18-115-2021, https://doi.org/10.5194/asr-18-115-2021, 2021
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Correct estimates of wind speed between 60 and 200 m above ground are of great interest for the renewable energy sector. Observed wind speeds are compared to three different reanalyses. ERA5 and COSMO-REA6 outperform MERRA-2 at offshore, flat and hilly sites. Over land, ERA5 models nighttime wind speed better than COSMO-REA6 due to better representation of the low level jet through higher vertical resolution, a more comprehensive data assimilation scheme, and/or the more recent model version.
Arianna Valmassoi and Jan D. Keller
Adv. Sci. Res., 18, 41–49, https://doi.org/10.5194/asr-18-41-2021, https://doi.org/10.5194/asr-18-41-2021, 2021
Frank Kaspar, Deborah Niermann, Michael Borsche, Stephanie Fiedler, Jan Keller, Roland Potthast, Thomas Rösch, Thomas Spangehl, and Birger Tinz
Adv. Sci. Res., 17, 115–128, https://doi.org/10.5194/asr-17-115-2020, https://doi.org/10.5194/asr-17-115-2020, 2020
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Reanalyses are long-term meteorological datasets that are based on numerical weather prediction models and the assimilation of historic observations. The regional model COSMO of Germany’s national meteorological service (Deutscher Wetterdienst) has been used to develop regional reanalyses with spatial resolution of up to 2 km. In this paper, we provide an overview of evaluation results and application examples at the European and national German level with a focus on renewable energy.
Lisa Hannak, Karsten Friedrich, Florian Imbery, and Frank Kaspar
Adv. Sci. Res., 16, 175–183, https://doi.org/10.5194/asr-16-175-2019, https://doi.org/10.5194/asr-16-175-2019, 2019
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In order to analyze the impact on long time series by the transition from manual to automatic sunshine duration devices, parallel measurements of German climate reference stations are used. The different measurement principles (glass sphere and photodiode) cause systematic differences between the observations. With a linear regression model (used to adjust the automatic measurements) we want to prevent breaks in long time series of daily sunshine duration.
Jochen Schiewe
Proc. Int. Cartogr. Assoc., 2, 114, https://doi.org/10.5194/ica-proc-2-114-2019, https://doi.org/10.5194/ica-proc-2-114-2019, 2019
Bonan Wei and Jochen Schiewe
Proc. Int. Cartogr. Assoc., 2, 144, https://doi.org/10.5194/ica-proc-2-144-2019, https://doi.org/10.5194/ica-proc-2-144-2019, 2019
Frank Kaspar, Michael Borsche, Uwe Pfeifroth, Jörg Trentmann, Jaqueline Drücke, and Paul Becker
Adv. Sci. Res., 16, 119–128, https://doi.org/10.5194/asr-16-119-2019, https://doi.org/10.5194/asr-16-119-2019, 2019
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In this study, we assess balancing effects between photovoltaics and wind energy. On average, the seasonal cycles complement each other in Germany as well as in Europe. The frequency of events with a risk of low electricity generation is analyzed. The results illustrate that the number of such events is reduced when offshore regions are included, or when a combined system of PV and wind energy is considered. A European-wide analysis also leads to a distinct reduction of such events.
Frank Kaspar, Frank Kratzenstein, and Andrea K. Kaiser-Weiss
Adv. Sci. Res., 16, 75–83, https://doi.org/10.5194/asr-16-75-2019, https://doi.org/10.5194/asr-16-75-2019, 2019
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During recent years, Germany’s national meteorological service has significantly expanded the open access to its climate observations. To improve the interactive and user-friendly access to the data, a new data portal has been developed. The portal serves a variety of user requirements that result from the broad range of applications of DWD’s climate data. The focus of the recent developments was on improved access to German station data.
J. Schiewe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 551–558, https://doi.org/10.5194/isprs-archives-XLII-4-551-2018, https://doi.org/10.5194/isprs-archives-XLII-4-551-2018, 2018
Dirk Burghardt, Wolfgang Nejdl, Jochen Schiewe, and Monika Sester
Proc. Int. Cartogr. Assoc., 1, 15, https://doi.org/10.5194/ica-proc-1-15-2018, https://doi.org/10.5194/ica-proc-1-15-2018, 2018
V. Andreo, M. Metz, M. Neteler, R. Rosà, M. Marcantonio, C. Billinis, A. Rizzoli, and A. Papa
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W2, 19–26, https://doi.org/10.5194/isprs-archives-XLII-4-W2-19-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W2-19-2017, 2017
Kai-Uwe Eiselt, Frank Kaspar, Thomas Mölg, Stefan Krähenmann, Rafael Posada, and Jens O. Riede
Adv. Sci. Res., 14, 163–173, https://doi.org/10.5194/asr-14-163-2017, https://doi.org/10.5194/asr-14-163-2017, 2017
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As one element of the SASSCAL initiative (a cooperation of Angola, Botswana, Namibia, Zambia, South Africa and Germany) networks of automatic weather stations have been installed or improved in Southern Africa. Here we compare interpolation methods for monthly minimum and maximum temperatures which were calculated from hourly measurements. The best interpolation results have been achieved combining multiple linear regression with three dimensional inverse distance weighted interpolation.
Frank Kaspar, Lisa Hannak, and Klaus-Jürgen Schreiber
Adv. Sci. Res., 13, 163–171, https://doi.org/10.5194/asr-13-163-2016, https://doi.org/10.5194/asr-13-163-2016, 2016
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Germany's national meteorological service (DWD) operates a network of so-called climate reference stations. At these stations parallel measurements are performed in order to allow the comparison of manual and automatic observations. We present an analysis of parallel measurements of temperature at 2 m height. It is shown that the automation of stations did not cause an artificial increase in the series of daily mean temperature. A bias occurs for maximum temperature in specific configurations.
Michael Borsche, Andrea K. Kaiser-Weiss, and Frank Kaspar
Adv. Sci. Res., 13, 151–161, https://doi.org/10.5194/asr-13-151-2016, https://doi.org/10.5194/asr-13-151-2016, 2016
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Wind speeds derived from the regional reanalysis COSMO-REA6 and from two global reanalyses of ECMWF (ERA-Interim and ERA-20C) have been compared to tower measurements covering heights from 10 m up to 140 m, located in the North Sea, in The Netherlands, and in Northeast Germany. In general, the monthly and hourly mean values of COSMO-REA6 are at least as close to the measurements as the global reanalyses, and in the correlation of daily means an added value of COSMO-REA6 is found.
Rafael Posada, Domingos Nascimento, Francisco Osvaldo S. Neto, Jens Riede, and Frank Kaspar
Adv. Sci. Res., 13, 97–105, https://doi.org/10.5194/asr-13-97-2016, https://doi.org/10.5194/asr-13-97-2016, 2016
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To respond to the challenges of climate change, Angola, Botswana, Germany, Namibia, South Africa and Zambia have initiated the regional competence centre SASSCAL. As part of the initiative, Deutscher Wetterdienst (DWD) cooperates with the meteorological services of Angola, Botswana and Zambia to improve the management of climate data. First results of the cooperation between DWD and the Angolan Meteorological Services (INAMET) are presented in order to provide hints for comparable activities.
M. Borsche, A. K. Kaiser-Weiss, P. Undén, and F. Kaspar
Adv. Sci. Res., 12, 207–218, https://doi.org/10.5194/asr-12-207-2015, https://doi.org/10.5194/asr-12-207-2015, 2015
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Within the European Union’s seventh Framework Programme project Uncertainties in Ensembles of Regional Re-Analyses (UERRA), ensembles of RRAs covering the European area are produced and their uncertainties are quantified. In this study, we discuss different methods for quantifying the uncertainty of RRAs in order to answer the question to which extent the smaller scale information (or resulting statistics) provided by the RRAs can be relied on.
A. K. Kaiser-Weiss, F. Kaspar, V. Heene, M. Borsche, D. G. H. Tan, P. Poli, A. Obregon, and H. Gregow
Adv. Sci. Res., 12, 187–198, https://doi.org/10.5194/asr-12-187-2015, https://doi.org/10.5194/asr-12-187-2015, 2015
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Wind speed measured at the German stations correlate well with reanalysis fields. Monthly means from two global reanalyses (ERA-20C, ERA-Interim) and one regional reanalysis (COSMO-REA6) were analysed and correlate well for the majority of the German stations. Thus we conclude that the monthly and seasonal anomalies recorded at these stations can be understood as representative for a spatial area comparable to the resolution of the reanalyses, at least for the recent years.
F. Kaspar, J. Helmschrot, A. Mhanda, M. Butale, W. de Clercq, J. K. Kanyanga, F. O. S. Neto, S. Kruger, M. Castro Matsheka, G. Muche, T. Hillmann, K. Josenhans, R. Posada, J. Riede, M. Seely, C. Ribeiro, P. Kenabatho, R. Vogt, and N. Jürgens
Adv. Sci. Res., 12, 171–177, https://doi.org/10.5194/asr-12-171-2015, https://doi.org/10.5194/asr-12-171-2015, 2015
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One task of the “Southern African Science Service Centre for Climate Change and Adaptive Land Management” (www.sasscal.org) is the provision of climate data for Southern Africa. Extension and improvements of observational networks in Angola, Botswana, Namibia, Zambia and South Africa are supported. This effort is complemented by an improvement of climate data management at national weather authorities, capacity building activities and an extension of the data bases with historical climate data.
H. Gregow, P. Poli, H. M. Mäkelä, K. Jylhä, A. K. Kaiser-Weiss, A. Obregon, D. G. H. Tan, S. Kekki, and F. Kaspar
Adv. Sci. Res., 12, 63–67, https://doi.org/10.5194/asr-12-63-2015, https://doi.org/10.5194/asr-12-63-2015, 2015
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Many users of climate information are unaware of the availability of reanalysis feedback data and input observations, and uptake of feedback data is rather low. The most important factors limiting the use of this data is that the users feel that there is no easy interface to get the data or they do not find it at all. The relevant communities should invest resources to develop tools and provide training to bridge the gap between current capabilities and comprehensive exploitation of the data.
F. Kaspar, B. Tinz, H. Mächel, and L. Gates
Adv. Sci. Res., 12, 57–61, https://doi.org/10.5194/asr-12-57-2015, https://doi.org/10.5194/asr-12-57-2015, 2015
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Germany’s national meteorological service (Deutscher Wetterdienst, DWD) houses in Offenbach and Hamburg huge archives of historical handwritten journals of weather observations. They comprise not only observations from Germany, but also of the oceans and land stations in many parts of the world. DWD works on the digitisation and quality control of these archives. The paper presents the current status.
F. Kaspar, K. Zimmermann, and C. Polte-Rudolf
Adv. Sci. Res., 11, 93–99, https://doi.org/10.5194/asr-11-93-2014, https://doi.org/10.5194/asr-11-93-2014, 2014
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Plant phenology is the study of periodically recurring patterns of growth and development of plants during the year. First plant phenological observations have been performed in Germany already in the 18th century. Today, Germany’s national meteorological service (Deutscher Wetterdienst, DWD) maintains a dense phenological observation network and a database with phenological observations.
J. D. Keller and A. Hense
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npgd-1-1509-2014, https://doi.org/10.5194/npgd-1-1509-2014, 2014
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F. Kaspar, G. Müller-Westermeier, E. Penda, H. Mächel, K. Zimmermann, A. Kaiser-Weiss, and T. Deutschländer
Adv. Sci. Res., 10, 99–106, https://doi.org/10.5194/asr-10-99-2013, https://doi.org/10.5194/asr-10-99-2013, 2013
K.-G. Karlsson, A. Riihelä, R. Müller, J. F. Meirink, J. Sedlar, M. Stengel, M. Lockhoff, J. Trentmann, F. Kaspar, R. Hollmann, and E. Wolters
Atmos. Chem. Phys., 13, 5351–5367, https://doi.org/10.5194/acp-13-5351-2013, https://doi.org/10.5194/acp-13-5351-2013, 2013
A. Riihelä, T. Manninen, V. Laine, K. Andersson, and F. Kaspar
Atmos. Chem. Phys., 13, 3743–3762, https://doi.org/10.5194/acp-13-3743-2013, https://doi.org/10.5194/acp-13-3743-2013, 2013
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Short summary
Access to high quality weather and climate data is crucial for a wide range of societal and economic issues. It allows optimising industrial processes with respect to efficiency. The goal of the research project FAIR is to simplify the information exchange between the DWD and economical players. This paper summarizes the results of the requirement analysis of three use cases and presents the deduced technical architecture and FAIR services aiming at a user-friendly exchange of weather data.
Access to high quality weather and climate data is crucial for a wide range of societal and...
