Interactive open access to climate  observations from Germany

Kaspar, Frank; Kratzenstein, Frank; Kaiser-Weiss, Andrea

doi:10.5194/asr-16-75-2019

Cited by 8 publications

(6 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Planning of wind farms -With the FAIR services, we plan to make the high-resolution reanalysis products COSMO-REA6 (Bollmeyer et al, 2015) and COSMO-REA2 (Wahl et al, 2017) of DWD easily accessible to the wind sector. Previous studies show a high quality of these data sets for wind applications (Kaspar et al, 2020), but a user-friendly platform for that community does not yet exist. Thus, relevant wind estimates and other weather data at the specific sites and heights will be made available via a data portal and downloadable in the required data format CSV.…”

Section: Planned End-to-end Chainsmentioning

confidence: 99%

“…DWD is aware of existing issues with this approach such as weak visibility of data products in the directory tree or technical obstacles (especially for non-meteorological users) due to the heterogenity of data formats. Therefore, DWD implemented the new CDC data portal (Kaspar et al, 2019) as a first step towards a more user-friendly provisioning of meteorological data. This portal allows access to a subset of the data located on the server via an interactive web interface.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

FAIR: a project to realize a user-friendly exchange of open weather data

Frank¹,

Kaspar

Keller

et al. 2020

Adv. Sci. Res.

Self Cite

View full text Add to dashboard Cite

Abstract. Access to high quality weather and climate data is crucial for a wide range of societal and economic issues. It allows optimising industrial processes, supports the identification of potential risks related to climate change or allows the development of corresponding adaptation and mitigation strategies. Although such data is freely available through Germany’s national meteorological service DWD (Deutscher Wetterdienst) since 2017, the application potential in industry and society has certainly not yet been fully unlocked. Major obstacles are the complexity of the raw data, as well as missing tools for their simple integration into existing industrial applications. The goal of the research project FAIR is to simplify the information exchange between the DWD and economical players. In order to reach this goal a requirement analysis with end-users of weather data from three different sectors was conducted. A central requirement regarding the site assessment of wind plants is quick and easy access to historical wind-series at specific sites. Preferably downloadable in formats like CSV or via an API. Event planning partners are interested in a quick access to health relevant weather information at their event location, and the E-mobility sector in temperature data along planned routes. In this paper, we summarize the results of the requirement analysis and present the deduced technical architecture and FAIR services aiming at a user-friendly exchange of weather data.

show abstract

Section: Planned End-to-end Chainsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FAIR: a project to realize a user-friendly exchange of open weather data

Frank¹,

Kaspar

Keller

et al. 2020

Adv. Sci. Res.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The high-performance raster data management system contains geodata time series, which are managed locally and made analysisready via OGC-compliant web services (Web Mapping Services and Web Coverage Services). This includes, for example, meteorological time series provided by the German weather service (DWD,"Deutscher Wetterdienst") and phenological time series (Kaspar et al 2019;Möller et al 2020).…”

Section: Jki's Demilitarized Zonementioning

confidence: 99%

A paradigm shift towards decentralized cloud-integrated spatial data infrastructures: Lessons learned and solutions provided for public authorities

Beyer¹,

Brandt²,

Schmidt³

et al. 2023

Preprint

View full text Add to dashboard Cite

Digital transformation is a key to turn public authorities into organisations that make decisions based on data-driven insights. The use of big geodata can enable public authorities to tackle complex sustainability issues. However, the efficient management of large amounts of geodata through implementing viable data infrastructures represents a major challenge for public authorities. In this article, we propose a decentralized, cloud-integrated spatial data infrastructure (SDI) to meet the needs of public authorities mandated to provide data services based on earth observation (EO) imagery. We describe the SDI setup and integration of the EO cloud platform \cde, drawing on the specific SDI implementation at a federal, agricultural authority in Germany. Two practical applications are illustrated, underpinning the added value of a cloud-integrated SDI. We elaborate on lessons learned from SDI implementation by summarizing four key findings that may facilitate effective SDI establishment and use, namely i) the need for an organizational strategy, ii) identifying stakeholders, including their participatory roles, iii) long-term financial and human resource planning, and iv) the implementation of a data governance framework. The SDI proposed, serves as blueprint for public authorities aiding them on their path to become providers of data services, leveraging the potential of big geodata, including EO imagery.

show abstract

“…Significant correlation coefficients indicate a negative relationship between these two parameters. For the analysis the R-functions "cor" and "cor.test" are used (based on methods described in Kendall, 1938Kendall, , 1945Hollander and Wolfe, 1973;Best and Roberts, 1975;Becker et al, 1988). The day length is also correlated.…”

Section: Differences In Daily Sunshine Durationmentioning

confidence: 99%

Comparison of manual and automatic daily sunshine duration measurements at German climate reference stations

et al. 2019

Self Cite

View full text Add to dashboard Cite

Abstract. Precise quantification of climate change depends on long time series of meteorological variables. Such time series should be as homogeneous as possible but some changes of measurement conditions cannot be prevented. At German climate reference stations, parallel measurements are used to analyze the effects of changes in measurement systems for example for the transition from manual to automatic instruments. These parallel measurements aim to identify measurement uncertainties and to analyze the comparability of measurement systems to investigate the homogeneity. In this study, we investigate daily sunshine duration. Traditionally, manual measurements of daily sunshine duration are taken with Campbell-Stokes sunshine recorders. For automatic measurements the SONIe or SCAPP instrument is used. The different measurement principles (glass sphere and photodiode) cause systematic differences between the observations. During summer, values for manual observations are larger especially in case of frequent alternations between sunny and cloudy conditions. Furthermore, the standard deviation of the differences between the two measurement systems is larger during summer because of the greater day length. To adjust the automatic measurements a linear regression model is suggested based on parallel measurements from 13 climate reference stations in Germany. To validate the regression coefficients, a leave-one-out cross validation was performed (by leaving out data of individual stations). The regression coefficients (derived from different sets of stations) are similar, thereby indicating a robust data set for the estimation of the linear model. With this method we want to prevent breaks in long time series of daily sunshine duration caused by the transition from manual to automatic instruments.

show abstract

Interactive open access to climate observations from Germany

Cited by 8 publications

References 6 publications

FAIR: a project to realize a user-friendly exchange of open weather data

FAIR: a project to realize a user-friendly exchange of open weather data

A paradigm shift towards decentralized cloud-integrated spatial data infrastructures: Lessons learned and solutions provided for public authorities

Comparison of manual and automatic daily sunshine duration measurements at German climate reference stations

Contact Info

Product

Resources

About