TERENO: German network of terrestrial environmental observatories

Central elements of the TERENO network are “terrestrial observatories” at the catchment scale which were selected in climate sensitive regions of Germany for the regional analyses of climate change impacts. Within these observatories small scale research facilities and test areas are placed in order to accomplish energy, water, carbon and nutrient process studies across the different compartments of the terrestrial environment. Following a hierarchical scaling approach (point-plot-field) these detailed information and the gained knowledge will be transferred to the regional scale using integrated modelling approaches. Furthermore, existing research stations are enhanced and embedded within the observatories. In addition, mobile measurement platforms enable monitoring of dynamic processes at the local scale up to the determination of spatial pattern at the regional scale are applied within TERENO

Research data management in agricultural sciences in Germany: We are not yet where we want to be

To meet the future challenges and foster integrated and holistic research approaches in agricultural sciences, new and sustainable methods in research data management (RDM) are needed. The involvement of scientific users is a critical success factor for their development. We conducted an online survey in 2020 among different user groups in agricultural sciences about their RDM practices and needs. In total, the questionnaire contained 52 questions on information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in RDM in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. We received 196 (partially) completed questionnaires from data providers, data users, infrastructure and information service providers. In addition to the diversity in the research data landscape of agricultural sciences in Germany, the study reveals challenges, deficits and uncertainties in handling research data in agricultural sciences standing in the way of access and efficient reuse of valuable research data. However, the study also suggests and discusses potential solutions to enhance data publications, facilitate and secure data re-use, ensure data quality and develop services (i.e. training, support and bundling services). Therefore, our research article provides the basis for the development of common RDM, future infrastructures and services needed to foster the cultural change in handling research data across agricultural sciences in Germany and beyond

Integrating Data Science and Earth Science

This open access book presents the results of three years collaboration between earth scientists and data scientists, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows

Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach

Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and temporal resolutions of available forecast products have hindered their widespread use in such modelling applications, which usually require high-resolution input data. In this study, we applied sub-seasonal (up to 4 months) and seasonal (7 months) weather forecasts from the latest European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5) in a land surface modelling approach using the Community Land Model version 5.0 (CLM5). Simulations were conducted for 2017–2020 forced with sub-seasonal and seasonal weather forecasts over two different domains with contrasting climate and cropping conditions: the German state of North Rhine-Westphalia (DE-NRW) and the Australian state of Victoria (AUS-VIC). We found that, after pre-processing of the forecast products (i.e. temporal downscaling of precipitation and incoming short-wave radiation), the simulations forced with seasonal and sub-seasonal forecasts were able to provide a model output that was very close to the reference simulation results forced by reanalysis data (the mean annual crop yield showed maximum differences of 0.28 and 0.36 t ha−1 for AUS-VIC and DE-NRW respectively). Differences between seasonal and sub-seasonal experiments were insignificant. The forecast experiments were able to satisfactorily capture recorded inter-annual variations of crop yield. In addition, they also reproduced the generally higher inter-annual differences in crop yield across the AUS-VIC domain (approximately 50 % inter-annual differences in recorded yields and up to 17 % inter-annual differences in simulated yields) compared to the DE-NRW domain (approximately 15 % inter-annual differences in recorded yields and up to 5 % in simulated yields). The high- and low-yield seasons (2020 and 2018) among the 4 simulated years were clearly reproduced in the forecast simulation results. Furthermore, sub-seasonal and seasonal simulations reflected the early harvest in the drought year of 2018 in the DE-NRW domain. However, simulated inter-annual yield variability was lower in all simulations compared to the official statistics. While general soil moisture trends, such as the European drought in 2018, were captured by the seasonal experiments, we found systematic overestimations and underestimations in both the forecast and reference simulations compared to the Soil Moisture Active Passive Level-3 soil moisture product (SMAP L3) and the Soil Moisture Climate Change Initiative Combined dataset from the European Space Agency (ESA CCI). These observed biases of soil moisture and the low inter-annual differences in simulated crop yield indicate the need to improve the representation of these variables in CLM5 to increase the model sensitivity to drought stress and other crop stressors.</p

Integrating Data Science and Earth Science

This open access book presents the results of three years collaboration between earth scientists and data scientist, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows

Design and Implementation of a Research Data Management System: The CRC/TR32 Project Database (TR32DB)

Research data management (RDM) includes all processes and measures which ensure that research data are well-organised, documented, preserved, stored, backed up, accessible, available, and re-usable. Corresponding RDM systems or repositories form the technical framework to support the collection, accurate documentation, storage, back-up, sharing, and provision of research data, which are created in a specific environment, like a research group or institution. The required measures for the implementation of a RDM system vary according to the discipline or purpose of data (re-)use. In the context of RDM, the documentation of research data is an essential duty. This has to be conducted by accurate, standardized, and interoperable metadata to ensure the interpretability, understandability, shareability, and long-lasting usability of the data. RDM is achieving an increasing importance, as digital information increases. New technologies enable to create more digital data, also automatically. Consequently, the volume of digital data, including big data and small data, will approximately double every two years in size. With regard to e-science, this increase of data was entitled and predicted as the data deluge. Furthermore, the paradigm change in science has led to data intensive science. Particularly scientific data that were financed by public funding are significantly demanded to be archived, documented, provided or even open accessible by different policy makers, funding agencies, journals and other institutions. RDM can prevent the loss of data, otherwise around 80-90 % of the generated research data disappear and are not available for re-use or further studies. This will lead to empty archives or RDM systems. The reasons for this course are well known and are of a technical, socio-cultural, and ethical nature, like missing user participation and data sharing knowledge, as well as lack of time or resources. In addition, the fear of exploitation and missing or limited reward for publishing and sharing data has an important role. This thesis presents an approach in handling research data of the collaborative, multidisciplinary, long-term DFG-funded research project Collaborative Research Centre/Transregio 32 (CRC/TR32) “Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation”. In this context, a RDM system, the so-called CRC/TR32 project database (TR32DB), was designed and implemented. The TR32DB considers the demands of the project participants (e.g. heterogeneous data from different disciplines with various file sizes) and the requirements of the DFG, as well as general challenges in RDM. For this purpose, a RDM system was established that comprises a well-described self-designed metadata schema, a file-based data storage, a well-elaborated database of metadata, and a corresponding user-friendly web interface. The whole system is developed in close cooperation with the local Regional Computing Centre of the University of Cologne (RRZK), where it is also hosted. The documentation of the research data with accurate metadata is of key importance. For this purpose, an own specific TR32DB Metadata Schema was designed, consisting of multi-level metadata properties. This is distinguished in general and data type specific (e.g. data, publication, report) properties and is developed according to the project background, demands of the various data types, as well as recent associated metadata standards and principles. Consequently, it is interoperable to recent metadata standards, such as the Dublin Core, the DataCite Metadata Schema, as well as core elements of the ISO19115:2003 Metadata Standard and INSPIRE Directive. Furthermore, the schema supports optional, mandatory, and automatically generated metadata properties, as well as it provides predefined, obligatory and self-established controlled vocabulary lists. The integrated mapping to the DataCite Metadata Schema facilitates the simple application of a Digital Object Identifier (DOI) for a dataset. The file-based data storage is organized in a folder system, corresponding to the structure of the CRC/TR32 and additionally distinguishes between several data types (e.g. data, publication, report). It is embedded in the Andrew File System hosted by the RRZK. The file system is capable to store and backup all data, is highly scalable, supports location independence, and enables easy administration by Access Control Lists. In addition, the relational database management system MySQL stores the metadata according to the previous mentioned TR32DB Metadata Schema as well as further necessary administrative data. A user-friendly web-based graphical user interface enables the access to the TR32DB system. The web-interface provides metadata input, search, and download of data, as well as the visualization of important geodata is handled by an internal WebGIS. This web-interface, as well as the entire RDM system, is self-developed and adjusted to the specific demands. Overall, the TR32DB system is developed according to the needs and requirements of the CRC/TR32 scientists, fits the demands of the DFG, and considers general problems and challenges of RDM as well. With regard to changing demands of the CRC/TR32 and technologic advances, the system is and will be consequently further developed. The established TR32DB approach was already successfully applied to another interdisciplinary research project. Thus, this approach is transferable and generally capable to archive all data, generated by the CRC/TR32, with accurately, interoperable metadata to ensure the re-use of the data, beyond the end of the project

Evaluating the value of a network of cosmic-ray probes for improving land surface modelling

Land surface models can model matter and energy fluxes between the land surface and atmosphere, and provide a lower boundary condition to atmospheric circulation models. For these applications, accurate soil moisture quantification is highly desirable but not always possible given limited observations and limited subsurface data accuracy. Cosmic-ray probes (CRPs) offer an interesting alternative to indirectly measure soil moisture and provide an observation that can be assimilated into land surface models for improved soil moisture prediction. Synthetic studies have shown the potential to estimate subsurface parameters of land surface models with the assimilation of CRP observations. In this study, the potential of a network of CRPs for estimating subsurface parameters and improved soil moisture states is tested in a real-world case scenario using the local ensemble transform Kalman filter with the Community Land Model. The potential of the CRP network was tested by assimilating CRP-data for the years 2011 and 2012 (with or without soil hydraulic parameter estimation), followed by the verification year 2013. This was done using (i) the regional soil map as input information for the simulations, and (ii) an erroneous, biased soil map. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the biased soil map, soil moisture characterization improved in both periods strongly from a ERMS of 0.11 cm3/cm3 to 0.03 cm3/cm3 (assimilation period) and from 0.12 cm3/cm3 to 0.05 cm3/cm3 (verification period) and the estimated soil hydraulic parameters were after assimilation closer to the ones of the regional soil map. Finally, the value of the CRP network was also evaluated with jackknifing data assimilation experiments. It was found that the CRP network is able to improve soil moisture estimates at locations between the assimilation sites from a ERMS of 0.12 cm3/cm3 to 0.06 cm3/cm3 (verification period), but again only if the initial soil map was biased

The WASCAL hydrometeorological observatory in the Sudan Savanna of Burkina Faso and Ghana

Watersheds with rich hydrometeorological equipment are still very limited in West Africa but are essential for an improved analysis of environmental changes and their impacts in this region. This study gives an overview of a novel hydrometeorological observatory that was established for two mesoscale watersheds in the Sudan Savanna of Southern Burkina Faso and Northern Ghana as part of the West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) program. The study area is characterized by severe land cover changes due to a strongly increasing demand of agricultural land. The observatory is designed for long-term measurements of >30 hydrometeorological variables in subhourly resolution and further variables such as CO2. This information is complemented by long-term daily measurements from national meteorological and hydrological networks, among several other datasets recently established for this region. A unique component of the observatory is a micrometeorological field experiment using eddy covariance stations implemented at three contrasting sites (near-natural, cropland, and degraded grassland) to assess the impact of land cover changes on water, energy, and CO2 fluxes. The datasets of the observatory are needed by many modeling and field studies conducted in this region and are made available via the WASCAL database. Moreover, the observatory forms an excellent platform for future investigations and can be used as observational foundation for environmental observatories for an improved assessment of environmental changes and their socioeconomic impacts for the savanna regions of West Africa