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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 dataset contains an urban weather record from the hydro-meteorological monitoring station of the Institute of Geographical Sciences at the Freie Universitaet Berlin (working group Applied Geography, Environmental Hydrology and Resource Management; Geo Campus Lankwitz, Malteserstraße 74-100, 12249 Berlin). The station is located at an elevation of 45 m a.s.l. and consists of a 7.5 x 7.5 m wide fenced measuring field covered by short grass which is cut in weekly intervals (spring to fall) to ensure reference evaporation conditions.The field is equipped with a range of redundant devices that record weather information. In this summary we focus on a description of the devices from which data were included in the published dataset. A actual list of all devices is available at the Website of the Hydrometeorological monitoring station "Berlin-Lankwitz, FU Geo Campus" (https://www.geo.fu-berlin.de/en/geog/fachrichtungen/angeog/Messfeld-auf-dem-Campus/index.html).The dataset contains rainfall, air temperature, humidity, dew point temperature, air pressure, solar radiation as well as wind speed and direction, each measured in intervals of 15 min. It starts in January 2017 and is updated annually. Rainfall is collected with a Davis VantagePro tipping bucket which is part of the ISS (Integrated Sensor Suite, DAV-6323EU, manufactured before 2007) and mounted 2 m above ground. The collector diameter is 16.3 cm resulting in a collecting area of 210 cm². The measuring resolution of the tipping bucket is 0.25 mm (0.01 inch). During winter the DAVIS rain gauge is heated using the DAV-7720EU heating system. The begin of the heating period in each year is determined by the air temperature and starts before the daily minimum drops below 0°C. In addition a stainless steel Hellmann gauge with standard diameter of 16 cm (area: 200 m²) is installed on the monitoring field 1 m above ground. Rain water is collected in a steel can, which is emptied manually every morning from Monday to Friday using a DIN58667 measuring glass. Between December and February accumulated snow and ice is thawed. Paired data from the Hellman and DAVIS collector to assess accuracy are published separately (Reinhardt-Imjela et al. 2018). Temperature (°C), humidity (%) and air pressure (hPa) are measured 2 m above ground with the DAVIS ISS and the dew point is generated automatically from the data. Temperature includes mean, minimum and maximum of each 15 minute interval. Wind speed and direction are recorded by a Vaisale Weather Transmitter WXT520 2 m above ground. For solar radiation (W/m²) a Kipp & Zonen CMP3 Pyranometer is mounted also 2 m above ground.The data are provided as a tab-separated ASCII file with column names in the first line. The first column contains the date and time (date format: DD/MM/YYYY hh:mm). In the following columns all measured parameters are listed (units are included in the column name). Measuring errors or missing values are marked with “N/A”. Empty fields for the wind direction indicate intervals without measurable wind speed.
The data set contains hydrological, meteorological and gravity time series collected at Argentine-German Geodetic Observatory (AGGO) in La Plata, Argentina. The hydrological series include soil moisture, temperature, electric conductivity, soil parameters, and groundwater variation. The meteorological time series comprise air temperature, humidity, pressure, wind speed, solar short- and long-waver radiation, and precipitation. The observed hydrometeorological parameters are extended by modelled value of evapotranspiration and water content variation in the zone between deepest soil moisture sensor and the groundwater level. Gravity products include large-scale hydrological, oceanic as well as atmospheric effects. These gravity effects are furthermore extended by local hydrological effects and gravity residuals suitable for comparison and evaluation of the model performance. Provided are directly observed values denoted as Level 1 product along with pre-processed series corrected for known issues (Level 2). Level 3 products are model outputs acquired using Level 2 data. The maximal temporal coverage of the data set ranges from May 2016 up to November 2018 with some exceptions for sensors and models set up in May 2017. The data set is organized in a database structure suitable for implementation in a relational database management system. All definitions and data tables are provided in separate text files allowing for traditional use without database installation.Software related to the data acquisition, processing, and modelling can be found in a separate publication describing scripts applied to the data set presented here. The software publication is available at https://doi.org/10.5880/GFZ.5.4.2018.002 (Mikolaj, 2018)
This software publication describes the data acquisition, processing and modelling of hydrological, meteorological and gravity time series prepared for the Argentine-German Geodetic Observatory (AGGO) in La Plata, Argentina. The corresponding output data set is available at http://doi.org/10.5880/GFZ.5.4.2018.001 (Mikolaj et al., 2018).Processed hydrological series include soil moisture, temperature, electric conductivity, and groundwater variation. The processed meteorological time series comprise air temperature, humidity, pressure, wind speed, solar short- and long-waver radiation, and precipitation. Modelling scripts include evapotranspiration, combined precipitation, and water content variation in the zone between deepest soil moisture sensor and groundwater. In addition, large-scale hydrological, oceanic as well as atmospheric effect are modelled along with the local hydrological effects. To allow for a comparison of the model outputs to observations, processing script of gravity residuals is provided as well.
This data publication contains airborne wind and eddy covariance data files, that were recorded with the ASK-16, a motorized glider owned by the FU Berlin, Germany. These data files include a large range of meteorological variables (wind speed, direction, temperature, humidity, etc.), positioning information, but also information on atmospheric chemistry (mainly methane concentration, carbon dioxide concentration, water vapor concentration) and turbulent matter (CH4 and CO2) and energy fluxes (latent heat flux) is available. Measurements were recorded between 2017 and 2022 to: (1) obtain three-dimensional wind vectors in within the atmospheric boundary layer (2) calibrate of wind measurements (3) record turbulent energy and matter fluxes A lot of these data files have been used in the publication “The ASK-16 Motorized Glider: An Airborne Eddy Covariance Platform to measure Turbulence, Energy and Matter Fluxes (to be published in atmospheric measurement techniques)” by Wiekenkamp et al., 2024a. This publication also provides a lot of additional details on the measurement system, the data handling and processing.
The Regional Research Network „Water in Central Asia“ (CAWa) funded by the German Federal Foreign Office consists of 19 remotely operated multi-parameter stations (ROMPS) in Central Asia. These stations were installed by the German Research Centre for Geosciences (GFZ) in Potsdam, Germany in close cooperation with the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan, the national hydrometeorological services in Uzbekistan and Tajikistan, the Ulugh Beg Astronomical Institute in Tashkent, Uzbekistan, and the Kabul Polytechnic University, Afghanistan. The primary objective of these stations is to support the establishment of a reliable data basis of meteorological and hydrological data especially in remote areas with extreme climate conditions in Central Asia for applications in climate and water monitoring. Up to now, ten years of data are provided for an area of scarce station distribution and with limited open access data which can be used for a wide range of scientific or engineering applications. This dataset provides different types of raw hydrometeorological data such as air temperature, relative humidity, air pressure, wind speed and direction, precipitation, solar radiation, soil moisture and soil temperature as well as snow parameters and river discharge information for selected sites. The data has not undergone any quality control mechanism and should, therefore, be seen as raw data. A visual inspection of the data set has been made and some errors and quality degradation are listed in Zech et al. (2020) but does not claim to be complete. A quality control is strongly recommended by the authors before using the data. Each station data has its own storage directory at the data dissemination server named with the abbreviation (4-letter code) of the station. The data is sampled with a 5-minute interval and stored in hourly files separated by the type of data. These files are then archived as monthly files named with the station abbreviation, type of data, year and month. After one year, these monthly files are further archived to a yearly file. A detailed description for the stations is provided by the Station Exposure Descriptions. Further information about the dataset can be found in Zech et al. (2020). All data is compiled as ASCII data in two different formats which are explained in the documents GITW-SSP-FMT-GFZ-003.pdf (for the stations ALAI, ALA6, and SARY) and CAWA-SSP-FMT-GFZ-006.pdf (for all other stations). Monthly, the data will be dynamically extended as long as data can be acquired from the stations. Additionally, the near real-time data can be displayed and downloaded without any registration from the Sensor Data Storage System (SDSS) hosted at the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan.
In the last years, a whole series of codes has been developed to process airborne wind data. Initially, the PyWingpod package was mainly build to handle data from the Wingpod of the ASK-16 motorized glider of the FU Berlin. However, due to the modular buildup of the package, functions within the different libraries can also be used to process data from other airborne platforms. Functions and scripts within PyWingpod have been developed to: a. load and process airborne five hole probe and meteo data, this includes (1) 5 hole probe pressure sensor data (static pressure, dynamic pressure and the differential alpha and beta pressure), (2) INS-GNSS data, (3) Temperature and humidity data and (4) any auxillary data that you want to add to the time series/ data frame. b. calibrate pressure sensor data from the five hole probe (mainly to correct for any effect of aircraft movement) c. calculate a reliable wind vector based on the available data that are specified in a. and the calibration parameters, which are obtained in step b.
The described dataset resulted from a joint multidisciplinary measurement campaign in an agroforestry system in the Western Cape region in South Africa. Five participating institutions measured a range of environmental variables to characterise the influence of windbreak trees onto water fluxes, nutrient distribution and microclimate in the adjacent blackberry field. The dataset contains spatially collected soil characteristics, a soil profile description, time series of meteorological measurements as well as soil moisture and matric potential, information on soil hydraulic properties of the soil determined in the laboratory and windbreak characteristics and shape from a point cloud derived from terrestrial LiDAR scanning.
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