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Es werden 5 Niederschlagsdatensätze bereitgestellt, die für die Validierung der stochastischen Niederschlagsmodelle genutzt wurden. Jeder Datensatz besteht aus Zeitreihen für 45 ausgewählte Messstellen in Deutschland. Die Lage der Messstellen ist in der Abbildung 5 der zugehörigen Publikation dargestellt. Die Messstellennummern und Koordinaten (UTM ETRS 89; EPSG: 25832) der Stationen können der beiliegenden Exceltabelle entnommen werden. Die Datensätze sind wie folgt kurz beschrieben: 1. "REF" -> Referenz: beobachteter langjähriger Niederschlag am Ort (Zeitreihenlänge: 20 a) 2. "WAWI" -> Synthetischer Niederschlag vom Modell der Leibniz Uni Hannover (Zeitreihenlänge: 300 a), 3. "LHG" -> Synthetischer Niederschlag vom Modell der Uni Stuttgart (Zeitreihenlänge: 300 a), 4. "MIXED" -> Synthetischer Niederschlag alternierend gemischt von beiden Modellen WAWI & LHG (Zeitreihenlänge: 300 a, 150 a Jahre von jedem Modell), 5. "PRA" -> Praxis: beobachteter Niederschlag von der nächstgelegenen Beobachtungsstation des DWD (Zeitreihenlänge: 10 bis 20 a). Die Daten sind in Unterordnern mit der Messstellennummer jahresweise im MD-Format abgespeichert. Eine Formatbeschreibung ist beigelegt. Five precipitation data sets are provided, which have been used for validation of the precipitation models. Each data set contains time series for 45 selected stations in Germany. The location of the stations is shown in Fig. 5 of the associated paper. Station id's and coordinates are listed in the associated Excel table. The data sets are briefly described as follows: 1. "REF" -> Reference: observed precipitation with long records (time series length 20yr), 2. "WAWI" -> synthetic rainfall from the precipitation model of the Leibniz University Hannover (time series length 300 yr), 3. "LHG" -> synthetic rainfall from the precipitation model of the University Stuttgart (time series length 300yr), 4. "MIXED" -> synthetic rainfall alternating mixed from both precipitation models WAWI & LHG (time series length 300yr, 150yr from each model), 5. "PRA" -> Practice: observed rainfall from the closest to the reference station located DWD station (time series length 10 to 20 yr). The data are stored in folders with station id's which contain for each year in one file in MD format. A format description is attached.
The DFG Priority Program 1803 "EarthShape - Earth Surface Shaping by Biota” (www.earthshape.net) installed three meteorological stations at an elevational gradient in the National Park La Campana, Chile, in the sector Ocoa, within one catchment, that is one of the four EarthShape core research sites. They are located at a valley position, at the slope and the crest of the catchment. For reference, the valley station is neighbouring a weather station (Campbell Scientific) that the EarthShape project has installed earlier, in 2016 (Übernickel et al., 2020). The other two weather stations are installed on higher elevations. The weather stations are intended to provide baseline meteorological data along the elevational gradient within the La Campana catchment. Each station is configured to include sensors that record air temperature, relative humidity, barometric pressure as well as total solar radiation at 2 m height; precipitation at 1 m height. The data recording started in March 2019. This publication provides raw data as downloaded from the three stations, appended to one single *.xlsx file per station. The data is measured in 30 minutes intervals. The full description of the data and methods is provided in the data description file.
The atmosphere model of the Geophysical Fluid Dynamics Laboratory (GFDL-AM2) is coupled to a slab ocean in order to analyse the monsoon's sensitivity to changes in various forcing parameters on a planet with idealized topography. This monsoon planet design of a water planet with a zonal circumglobal land stripe allows to extract the relevant monsoon behaviour and reduces the influence of topography. Besides the width and location of the land stripe, the atmospheric CO2 concentration, incoming solar radiation, sulfate aerosol concentration and surface albedo are variied. Horizontal grid resolution is 2° latitude x 2.5° longitude. For the vertical grid, a hybrid coordinate grid with 24 vertical levels is implemented. The lowest model level starts about 30 m above the surface and the top level is at about 3 hPa. The vertical resolution is decreasing towards higher altitudes. Advective and physics time steps are 10 minutes and 0.5 hours, for atmopsheric radiation 3 hours time steps are used. Instead of an ocean general circulation model, a mixed-layer slab ocean is used.
The DFG Priority Program 1803 "EarthShape - Earth Surface Shaping by Biota” (www.earthshape.net, short description of the project below) installed a meteorological station network consisting of four stations between ~26 °S to ~38 °S in the Coastal Cordillera of Chile, South America. The stations are intended to provide baseline meteorological data along the climate and ecological gradient investigated in the EarthShape program. The stations are located in the EarthShape study areas, encompassing desert, semi-desert, mediterranean, and temperate climate zones. Each station is configured to include sensors that record precipitation at ground level, radiation at 2.8 m height, wind at 3 m height, 25 cm depth soil temperature, soil water content and bulk electrical conductivity, 2 m air temperature and relative humidity, and barometric pressure at 30-minute intervals. The data recording started in March/April 2016. The EarthShape project runs until December 2021. Data collection will continue until that date, and potentially longer depending on available funds. This publication provides two sets of data: raw data and processed data. The raw data contains 2 file types per meteorological station: (1) all measured parameters of the whole dataset measured in 30 minutes intervals as downloaded from the station. Furthermore, we provide (2) one table per station of high-resolution precipitation events, measured in 5 min. intervals that were triggered during rain events at each station. The processed data consists of a continuous timeseries of observations since the activation of each station. The processing consists of the exclusion of erroneous data, caused by maintenance of the weather-stations and sporadic malfunction of sensors detected during data screening. The excluded data is communicated in a logfile (excel table), comments from data screening, solar eclipse and others are summarized in history files (ASCII ). the full description of the data and methods is provided in the data description file (Data description file). ----------------------- Version history: 16 January 2023 (Version 1.1): Alexander Beer included as additional author, addition of new data from 2020-04-14 bis 2022-10-10. All files of the first version are moved to the "previous-versions" folder. 09 October 2023 (Version 1.2): Addition of new time series data to 2023-07-31. Detailed changelog information can be found in the “History” files in the respective subfolders for each site.
The new climate dataset BASD-CMIP6-PE for Peru and Ecuador based on the bias-adjusted and statistically downscaled CMIP6 projections of 10 GCMs addresses the need for reliable high-resolution (1d, 10km) climate data covering Peru and Ecuador. This dataset includes both historical simulations (1850-2014) and future projections (2015-2100) for precipitation and minimum, mean, and maximum temperature under three Shared Socioeconomic Pathways (SSPs; SSP1-2.6, SSP3-7.0, and SSP5-8.5). The BASD-CMIP6-PE climate data were generated using the trend-preserving Bias Adjustment and Statistical Downscaling (BASD) method (Lange, 2019, 2021) and data from regional observational datasets such as RAIN4PE (Fernandez-Palomino et al., 2021a, b) for precipitation and PISCO-temperature (Huerta et al., 2018) for temperatures as reference data. The Reliability of the BASD-CMIP6-PE was evaluated through hydrological modeling across Peruvian and Ecuadorian river basins in the historical period. The evaluation showed that the BASD-CMIP6-PE is reliable for describing the spatial patterns of atmospheric variables and streamflow simulation, including low and high flows. This suggests the usefulness of the new dataset for climate change impact assessment studies in Peru and Ecuador. The BASD-CMIP6-PE data are available for the domain covering Peru and Ecuador, located between 19°S and 2°N and 82-67°W, at 0.1° spatial and daily temporal resolution. The precipitation unit is mm, and the temperature is in °C. The data are in the NetCDF format and arranged by model, model member, experiment, variable, temporal resolution, and subset period (e.g., canesm5_r1i1p1f1_ssp126_pr_daily_2015_2020.nc).
Version history: This datased is an updated version of Francke et al. (2017; http://doi.org/10.5880/fidgeo.2017.003) for a revised version of this discussion paper. It contains further data collected, some of which also resulted in the revision of previous data (e.g. updated rating curves).A comprehensive hydro-sedimentological dataset for the Isábena catchment, NE Spain, for the period 2010-2018 is presented to analyse water and sediment fluxes in a Mediterranean meso-scale catchment. The dataset includes rainfall data from twelve rain gauges distributed within the study area complemented by meteorological data of twelve official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSC) at six gauging stations of the Isábena river and its sub-catchments. Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses.The Isábena catchment (445 km²) is located in the Southern Central Pyrenees ranging from 450 m to 2,720 m in elevation, together with a pronounced topography this leads to distinct temperature and precipitation gradients. The Isábena river shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona reservoir. Main sediment source are badland areas located on Eocene marls that are well connected to the river network. The dataset features a wide set of parameters in a high spatial and temporal resolution suitable for advanced process understanding of water and sediment fluxes, their origin and connectivity, sediment budgeting and for evaluating and further developing hydro-sedimentological models in Mediterranean meso-scale mountainous catchments.The data have been published with the CUAHSI Water Data Center and is structured according to its guidelines (.csv format). For more detailed information please read the user guide on cloud publications with the CUAHSI Water Dater Center or the ODM guide for uploading data using CUAHSI´s ODM uploader added to the folder CUAHSI_ODM-Guide.zip. The database can be found in the HISCENTRAL catalogue (http://hiscentral.cuahsi.org/pub_network.aspx?n=5622). It is directly accessible via the API (http://hydroportal.cuahsi.org/isabena/cuahsi_1_1.asmx?WSDL) or in zipped archives at this DOI Landing Page (http://doi.org/10.5880/fidgeo.2018.011). For more detailed information, please read the user guide on cloud publications with the CUAHSI Water Dater Center (UserGuide.pdf) or the ODM guide for uploading data using CUAHSI´s ODM uploader in the ODM_Guide.zip archive.The data are available in four thematic zip folders:(1) hydro (hydrological data): water stage (manual readings and automatically recorded), river discharge (meterings and converted from stage)(2) meta (metadata) with the description of the different datafiles relevant for this dataset according to the CUAHSI HIS Standards(3) meteo (meteorological data): rainfall, temperature, radiation, humidity(4) sediment (sedimentological data): turbidity, suspended sediment concentration (from samples and from turbidity), sediment and soil reflectance spectraand are complemented by:(5) CUAHSI_ODM-Guide: User Guide, CUAHSI´s ODM uploader in Excel (.xlsx) and Open Office (.ods) formats(6) scripts: auxiliary R-script templates for data access, data analysis and visualisation(7) supplementary materials: stage-discharge- and turbidimeter rating curves
RAIN4PE is a novel daily gridded precipitation dataset obtained by merging multi-source precipitation data (satellite-based Climate Hazards Group InfraRed Precipitation, CHIRP (Funk et al. 2015), reanalysis ERA5 (Hersbach et al. 2020), and ground-based precipitation) with terrain elevation using the random forest regression method. Furthermore, RAIN4PE is hydrologically corrected using streamflow data in catchments with precipitation underestimation through reverse hydrology. Hence, RAIN4PE is the only gridded precipitation product for Peru and Ecuador, which benefits from maximum available in-situ observations, multiple precipitation sources, elevation data, and is supplemented by streamflow data to correct the precipitation underestimation over páramos and montane catchments. The RAIN4PE data are available for the terrestrial land surface between 19°S-2°N and 82-67°W, at 0.1° spatial and daily temporal resolution from 1981 to 2015. The precipitation dataset is provided in netCDF format. For a detailed description of the RAIN4PE development and evaluation of RAIN4PE applicability for hydrological modeling of Peruvian and Ecuadorian watersheds, readers are advised to read Fernandez-Palomino et al. (2021).
Version history:We recommend to use the revised version of this data publication (http://doi.org/10.5880/fidgeo.2018.011) which contains further data collected (2010-2018), some of which also resulted in the revision of previous data (e.g. updated rating curves).A comprehensive hydro-sedimentological dataset for the Isábena catchment, NE Spain, for the period 2010-2016 is presented to analyse water and sediment fluxes in a Mediterranean meso-scale catchment. The dataset includes rainfall data from twelve rain gauges distributed within the study area complemented by meteorological data of twelve official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSC) at six gauging stations of the Isábena river and its sub-catchments.Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses. The Isábena catchment (445 km²) is located in the Southern Central Pyrenees ranging from 450 m to 2,720 m in elevation, together with a pronounced topography this leads to distinct temperature and precipitation gradients.The Isábena river shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona reservoir. Main sediment source are badland areas located on Eocene marls that are well connected to the river network. The dataset features a wide set of parameters in a high spatial and temporal resolution suitable for advanced process understanding of water and sediment fluxes, their origin and connectivity, sediment budgeting and for evaluating and further developing hydro-sedimentological models in Mediterranean meso-scale mountainous catchments.The data are available in .csv format folllowing the CUAHSI Community Observations Data Model (ODM) as .zip files via this DOI Landing Page and directly from the CUASI HIS Database via http://hydroportal.cuahsi.org/isabena/cuahsi_1_1.asmx?WSDL.The data are provided in four thematic zip folders:(1) hydro (hydrological data): water stage (manual readings and automatically recorded), river discharge (meterings and converted from stage)(2) meta (metadata) with the description of the different datafiles relevant for this dataset according to the CUAHSI HIS Standards(3) meteo (meteorological data): rainfall, temperature, radiation, humidity(4) sediment (sedimentological data): turbidity, suspended sediment concentration (from samples and from turbidity), sediment and soil reflectance spectraFor more detailed information, please read the user guide on cloud publications with the CUAHSI Water Dater Center (UserGuide.pdf) or the ODM guide for uploading data using CUAHSI´s ODM uploader (ODMGuide.xlsx in folder ODM_Guide_2017.zip).
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