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Multibeam bathymetry processed data (EM 1002 echosounder entire dataset) of RV MARIA S. MERIAN during cruise MSM62/2

Swath sonar bathymetry data used for that dataset was recorded during RV MARIA S. MERIAN cruise MSM62/2 using Kongsberg EM1002 multibeam echosounder. The cruise took place between 23.03.2017 and 27.03.2017 in the Baltic Sea. The cruise aimed to investigate the impact of the Littorina transgression on the inflow of saline waters into the western Baltic and assessed the potential for future diminution of ventilation in the central and northern deeper basins due to isostatic uplift [CSR]. CI Citation: Paul Wintersteller (seafloor-imaging@marum.de) as responsible party for bathymetry raw data ingest and approval. During the MSM62/2 cruise, the moonpooled KONGSBERG EM1002 multibeam echosounder (MBES) was utilized to perform bathymetric mapping in shallow depths. The echosounder has a curved transducer in which 111 beams are formed for each ping while the seafloor is detected using amplitude and phase information for each beam sounding. For further information on the system, consult https://www.km.kongsberg.com/. Postprocessing and products were conducted by the Seafloor-Imaging & Mapping group of MARUM/FB5, responsible person Paul Wintersteller (seafloor-imaging@marum.de). The open source software MB-System (Caress, D. W., and D. N. Chayes, MB-System: Mapping the Seafloor, https://www.mbari.org/products/research-software/mb-system, 2017) was utilized for this purpose. A sound velocity correction profile was applied to the MSM62/2 data; there were no further corrections for roll, pitch and heave applied during postprocessing. A tide correction was applied, based on the Oregon State University (OSU) tidal prediction software (OTPS) that is retrievable through MB-System. CTD measurements during the cruise were sufficient to represent the changes in the sound velocity throughout the study area. Using Mbeditviz, artefacts were cleaned manually. NetCDF (GMT) grids of the edited data as well as statistics were created with mbgrid. The published bathymetric EM1002 grid of the cruise MSM62/2 has a resolution of 15 m. No total propagated uncertainty (TPU) has been calculated to gather vertical or horizontal accuracy. A higher resolution is, at least partly, achievable. The grid extended with _num represents a raster dataset with the statistical number of beams/depths taken into account to create the depth of the cell. The extended _sd -grid contains the standard deviation for each cell. The DTMs projections are given in Geographic coordinate system Lat/Lon; Geodetic Datum: WGS84.

Watershed Boundaries of Global Runoff Data Centre Stations

The Watershed Boundaries of all GRDC Stations are generated on the basis of HydroSHEDS (Lehner et al., 2008) and the Multi-Error-Removed Improved-Terrain (MERIT) Hydro dataset (Yamazaki et al., 2019). It is updated as soon as changes in the metadata occur or new stations have to be implemented. The dataset is licensed under CC-BY-4.0. Source: Lehner, B., Verdin, K., and Jarvis, A.: New Global Hydrography Derived From Spaceborne Elevation Data, EOS, 89, 93-94, https://doi.org/10.1029/2008EO100001, 2008. Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and Pavelsky, T. M.: MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset, Water Resources Research, 55, 5053-5073, https://doi.org/10.1029/2019WR024873, 2019. The Watershed Boundaries of all GRDC Stations are generated on the basis of HydroSHEDS (Lehner et al., 2008) and the Multi-Error-Removed Improved-Terrain (MERIT) Hydro dataset (Yamazaki et al., 2019). It is updated as soon as changes in the metadata occur or new stations have to be implemented. The dataset is licensed under CC-BY-4.0. Source: Lehner, B., Verdin, K., and Jarvis, A.: New Global Hydrography Derived From Spaceborne Elevation Data, EOS, 89, 93-94, https://doi.org/10.1029/2008EO100001, 2008. Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and Pavelsky, T. M.: MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset, Water Resources Research, 55, 5053-5073, https://doi.org/10.1029/2019WR024873, 2019.

Global SnowPack - MODIS - Daily

This product shows globally the daily snow cover extent (SCE). The snow cover extent is the result of the Global SnowPack processor's interpolation steps and all data gaps have been filled. Snow cover extent is updated daily and processed in near real time (3 days lag). In addition to the near real-time product (NRT_SCE), the entire annual data set is processed again after the end of a calendar year in order to close data gaps etc. and the result is made available as a quality-tested SCE product. There is also a quality layer for each day (SCE_Accuracy), which reflects the quality of the snow determination based on the time interval to the next "cloud-free" day, the time of year and the topographical/geographical location. The “Global SnowPack” is derived from daily, operational MODIS snow cover product for each day since February 2000. Data gaps due to polar night and cloud cover are filled in several processing steps, which provides a unique global data set characterized by its high accuracy, spatial resolution of 500 meters and continuous future expansion. It consists of the two main elements daily snow cover extent (SCE) and seasonal snow cover duration (SCD; full and for early and late season). Both parameters have been designated by the WMO as essential climate variables, the accurate determination of which is important in order to be able to record the effects of climate change. Changes in the largest part of the cryosphere in terms of area have drastic effects on people and the environment. For more information please also refer to: Dietz, A.J., Kuenzer, C., Conrad, C., 2013. Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products. International Journal of Remote Sensing 34, 3879–3902. https://doi.org/10.1080/01431161.2013.767480 Dietz, A.J., Kuenzer, C., Dech, S., 2015. Global SnowPack: a new set of snow cover parameters for studying status and dynamics of the planetary snow cover extent. Remote Sensing Letters 6, 844–853. https://doi.org/10.1080/2150704X.2015.1084551 Dietz, A.J., Wohner, C., Kuenzer, C., 2012. European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products. Remote Sensing 4. https://doi.org/10.3390/rs4082432 Dietz, J.A., Conrad, C., Kuenzer, C., Gesell, G., Dech, S., 2014. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data. Remote Sensing 6. https://doi.org/10.3390/rs61212752 Rößler, S., Witt, M.S., Ikonen, J., Brown, I.A., Dietz, A.J., 2021. Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers. Geosciences 11, 130. https://doi.org/10.3390/geosciences11030130

CropTypes - Crop Type Maps for Germany - Yearly, 10m

This raster dataset shows the main type of crop grown on each field in Germany each year. Crop types and crop rotation are of great economic importance and have a strong influence on the functions of arable land and ecology. Information on the crops grown is therefore important for many environmental and agricultural policy issues. With the help of satellite remote sensing, the crops grown can be recorded uniformly for whole Germany. Based on Sentinel-1 and Sentinel-2 time series as well as LPIS data from some Federal States of Germany, 18 different crops or crop groups were mapped per pixel with 10 m resolution for Germany on an annual basis since 2018. These data sets enable a comparison of arable land use between years and the derivation of crop rotations on individual fields. More details and the underlying (in the meantime slightly updated) methodology can be found in Asam et al. 2022.

API des Data Cubes des Umweltbundesamtes

Mit den Daten zur Umwelt stellt das UBA ein großes Angebot an aktuellen Daten zum Zustand der Umwelt bereit. Ein neues System – der UBA Data Cube – verbessert die Nutzbarkeit dieser Daten. Die Schnittstelle (API) dient zum programmatischen Abruf der Daten aus dem Data Cube des Umweltbundesamtes.

Data used for the paper "Implicit time discretisation as a potential avenue to achieve full coupling between shallow water flow and bedload transport" [Utz, 2025]

This dataset contains all data, which have been used to write the linked paper. In addition, it contains all Python scripts used for the evaluation of the data.

KRITIS Scalable Safe and Secure Modules

Under the IT Security Act 2.0, operators of critical infrastructures are obliged to operate their IT systems in accordance with the current state of the art. At the same time, the number of cyber attacks on communications equipment and operational facilities is growing, with the aim of causing damage and gaining control of critical systems. Without IT security measures, attacks can lead to the point of disruption of service. However, challenges arise when integrating established security functions from the enterprise environment into SCADA networks, which require innovative new approaches to improve resilience in the long term. In addition to the need for a system to effectively detect attacks, there is the problem of updating cryptographic techniques over the deployment period of the components to counteract the much shorter expected lifetime of the algorithms. The funding project therefore aims to protect all vertical and horizontal data communications from control centers to terminals by integrating security modules into the systems at various scaling levels. These modules are to implement state-of-the-art IT security functions over the entire service life of the CRITIS components, cryptographically securing communications and detecting attacks at an early stage. In the specific sub-project, OTH will focus on the scientific work objectives. It will be investigated how IT security functions can be integrated into the systems of the critical infrastructure with their requirements and limitations. Based on the security modules to be developed, innovative approaches to longevity will also be researched so that cryptographic functions achieve the required service life. Finally, it will be investigated how effective, decentralized attack detection can be implemented using the modules.

Modelling nutrient acquisition from the sub-soil for different crops with specific consideration of bio-pores (NutrAcMod)

The importance of nutrient supply from the sub-soil for crop growth is not well understood and may vary depending on bio-pores, nutrient turnover rates and the crop specific root systems. Simulation modelling provides a means to consider the complexity of the processes involved to describe the nutrient dynamics of the plant-soil system in an integrated way. However, approaches that describe the dynamics of phosphorus and potassium in combination with soil water, soil carbon and nitrogen and specifically consider the sub-soil and the bio-pores herein are scarce. Accordingly, the main objective of SP 10 is to develop a field-scale cropping system model which describes nutrient (emphasis in the 1st phase of the project is on phosphorus) mobilization and nutrient fluxes from the sub-soil to the crops considering soil nutrient pools, the bio-pore system and the crop nutrient demand. A two step approach is followed in which results from controlled experiments on soil cores will be used to develop detailed process models of root development and nutrient acquisition. These are the basis for deriving simplified algorithms to be used in a cropping system model for the field scale. The latter model will be applied to assess, after thorough validation with data from long-term experiments, the contribution of nutrients from the sub-soil and bio-pores to the growth of different crops. The sub-project combines modelling activities with experimental measurements and has a strong integrating role within the collaborative project.

Land rights, Social capital and investments in sustainable management practices and productivity enhancing inputs in Ghana

The proposed research project aims at analyzing the impacts of land tenure rights and social capital on farmers' investments in sustainable management practices and productivity-enhancing inputs. The theoretical emphasis on the benefits from more secure land rights is at variance with the empirical literature, particularly in Sub-Saharan Africa. Meanwhile a growing body of empirical evidence suggests that social capital and especially social networks may be equally important in promoting investments. Even some linkages between social capital and land tenure rights have been identified. However, very little empirical work is available on these linkages and how they both influence farmers' investment in sustainable management practices. The proposed research project intends to contribute to closing these gaps by specifying a comprehensive model of farmers' investment behavior that considers both the impacts of land tenure arrangements and social capital on investment and farm productivity. The empirical analysis will make use of data being collected in the Brong-Ahafo region of Ghana. Econometric models will analyze interdependencies and the influence of land tenure rights and social capital on investment and farm productivity. Qualitative analysis of perceived needs of the farmers will be undertaken to complement the econometric analysis.

GTS Bulletin: FTKN32 HKMO - Forecast (details are described in the abstract)

The FTKN32 TTAAii Data Designators decode as: T1 (F): Forecast T1T2 (FT): Aerodrome (VT >= 12 hours) A1A2 (KN): Kenya (Remarks from Volume-C: NilReason)

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