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Soil texture, soil physicochemical properties and climatic data from the PhytOakmeter plot DGRL_14 (Greifenhagen, Germany)

PhytOakmeter (www.phytoakmeter.de) is a field platform using the Quercus robur oak clone DF159 outplanted since 2010. This platform is used to monitor the impact of climate change and land use management on the "soil - plant - interactor" complex. Sites from PhytOakmeter are located either in forest or grassland habitats and represent a wide range of environmental contexts with specific stressors. All sites are equipped with loggers measuring air and soil temperature and soil humidity. Soil cores have been collected to analyze their chemical and physical characteristic. The DGRL plot in Greifenhagen (Germany) started in 2015 with 11 oak trees outplanted over a 50m x 10m grassland plot. Soil and air temperature were measured since 2018, soil moisture was measured since 2019, and soil chemistry was assessed in the root-affected zone of trees in 2016, 2020 and 2022. Soil porosity and texture were evaluated in 2020.

CDC (Climate Data Center)

Free access and download to of a growing selection of DWD’s climate data. Via CDC Search you will find data for direct download and interactive access to station data. The interactive mode gives graphical and tabular previews of the German station data. In addition, all data sets remain accessible from our ftp server for direct download

Spatial distribution of aerosol and meteorological parameters measured during flight SourceFFR_ALADINA_20241018_21 with the UAS ALADINA near Frankfurt airport in October 2024

Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.

Spatial distribution of aerosol and meteorological parameters measured during flight SourceFFR_ALADINA_20241018_20 with the UAS ALADINA near Frankfurt airport in October 2024

Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.

Stadtklimatologie

Im Rahmen des Projektes wird seit 1977 die Stadtklimastation Theresienstrasse betrieben, in der im 2-min-Zyklus die meteorologischen Elemente Temperatur, Feuchte, Wind, Windrichtung, Globalstrahlung, Sonnenscheindauer, Niederschlag und Luftdruck, in Dachniveau (27 m) und in 2 m Hoehe gemessen, registriert werden. Die Station wird derzeit um die Elemente Gegenstrahlung, Ausstrahlung des Bodens, Bodentemperatur, Lufttruebung (kontinuierlich) und Einstrahlung auf geneigte Flaechen ergaenzt. Die Messwerte werden geprueft und als Stundenmittelwerte archiviert. Neben einer routimemaessigen statistischen Bearbeitung des Materials wird insbesondere ein Stadt-Land-Vergleich mit den Messungen der Flugwetterwarte Riem des DWD und des Meteorologischen Observatoriums Garching des Meteorologischen Instituts durchgefuehrt.

Soil- moisture and temperature from the PhytOakmeter plot DGRL_14 (Greifenhagen, Germany) from 2022

As part of PhytOakmeter (www.phytoakmeter.de), time-domain transmission, soil moisture and -temperature sensors with custom-made logger systems were used to measure time series of soil state variables. The aim of these investigations was to provide data on environmental properties used in a cross-disciplinary approach.The measurement device consisted of two sensors at three different depths. The dataset contains the values of time (UTC), relative permittivity, soil moisture (in % vol) derived from permittivity and soil temperature (in °C). Determination of soil moisture was done using the formula of Topp et al. (1980). As sensors, the SMT100 soil moisture sensors with integrated temperature measurement were used. All sensors were installed within the upper 50cm below ground. The exact depths for each sensor are listed in the dataset and parameter comment.

Soil- moisture and temperature from the PhytOakmeter plot DGRL_14 (Greifenhagen, Germany) from 2023

As part of PhytOakmeter (www.phytoakmeter.de), time-domain transmission, soil moisture and -temperature sensors with custom-made logger systems were used to measure time series of soil state variables. The aim of these investigations was to provide data on environmental properties used in a cross-disciplinary approach.The measurement device consisted of two sensors at three different depths. The dataset contains the values of time (UTC), relative permittivity, soil moisture (in % vol) derived from permittivity and soil temperature (in °C). Determination of soil moisture was done using the formula of Topp et al. (1980). As sensors, the SMT100 soil moisture sensors with integrated temperature measurement were used. All sensors were installed within the upper 50cm below ground. The exact depths for each sensor are listed in the dataset and parameter comment.

Soil- moisture and temperature from the PhytOakmeter plot DGRL_14 (Greifenhagen, Germany) from 2019

As part of PhytOakmeter (www.phytoakmeter.de), time-domain transmission, soil moisture and -temperature sensors with custom-made logger systems were used to measure time series of soil state variables. The aim of these investigations was to provide data on environmental properties used in a cross-disciplinary approach.The measurement device consisted of two sensors at three different depths. The dataset contains the values of time (UTC), relative permittivity, soil moisture (in % vol) derived from permittivity and soil temperature (in °C). Determination of soil moisture was done using the formula of Topp et al. (1980). As sensors, the SMT100 soil moisture sensors with integrated temperature measurement were used. All sensors were installed within the upper 50cm below ground. The exact depths for each sensor are listed in the dataset and parameter comment.

Untersuchung der Mineralisation der organischen Substanz in Buntsandstein-, Muschelkalk- und Keuperboeden; Containerversuch im Freiland

1. Untersuchung des Einflusses des Ausgangsgesteins und der Bodenart, des Humusgehaltes, der Witterungsverhaeltnisse sowie der mineralischen N-Duengung auf die Mineralisation der organischen Substanz des Bodens. 2. Pruefung der Verlagerung und des Austrags von Nitrat-Stickstoff. 3. Untersuchung der Zusammenhaenge zwischen Stickstoffangebot im Boden und der N-Aufnahme durch die Rebe. - Die o.g. Zielsetzungen sollen in einem 3-faktoriellen Versuch mit folgenden Faktoren geprueft werden: Faktor A: Bodenausgangsgesteine: 1. Buntsandstein, 2. Muschelkalk, 3. Gipskeuper. Faktor B: 1. ca. 1 v.H. Humus, 2. ca. 2 v.H. Humus. Faktor C: 1. 0 kg N/ha, 2. 120 kg N/ha. - Die Versuchskombinationen werden in 6 Wiederholungen angelegt. Jeweils 3 WH werden bereits ab dem Anlagejahr mit jeweils einer Pfropfrebe bepflanzt. Die Bepflanzung der uebrigen 3 WH erfolgt nach 3-jaehriger Versuchszeit. Der Rauminhalt der Container betraegt 0,6 m3.

Spatial distribution of aerosol and meteorological parameters measured during flight SourceFFR_ALADINA_20241016_13 with the UAS ALADINA near Frankfurt airport in October 2024

Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.

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