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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

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.

Effekt des Klimawandels auf die Bodenatmung

Die Vorhersage der Kohlenstoff(C)bilanz von Wäldern bei geänderten Klimabedingungen ist eine komplexe Aufgabe. Es bedarf des Verständnisses des Abbaus der organischen Substanz (SOM) im Boden wie etwa der Temperatur- und Feuchtigkeitsempfindlichkeit und der Substratqualität für Bodenmikroorganismen. Für eine Abschätzung der künftigen C-Speicherung in Waldökosystemen ist die Kenntnis der langfristigen Entwicklung des organischen Boden-Kohlenstoffvorrats entscheidend. Erhöhte Bodentemperaturen ermöglichen den Bodenmikroorganismen die organische Substanz schneller abzubauen. Das führt zu einer erhöhten Freisetzung von Bodenkohlenstoff in Form von CO2 (Bodenatmung). Sobald der leicht abbaubare Bodenkohlenstoff verbraucht ist, kann sich der temperaturbedingte Anstieg der Bodenatmung längerfristig wieder abschwächen. Die Rolle der Bodenmikroorganismen in diesem Zusammenhang ist noch nicht geklärt. So würde eine Verschiebung von einer bakterien-dominierten Gemeinschaft zu einer pilz-dominierten Gemeinschaft den Umsatz schwer abbaubaren organischen Materials fördern und den Effekt einer Erwärmung auf die CO2-Emission verstärken. Andererseits kann die physiologische Anpassung von Mikroorganismen an geänderte Umweltbedingungen den Temperatureffekt abschwächen. Eine weitere Unsicherheit ist die mikrobielle Aktivität im Winter und die damit verbundene CO2-Ausgasung aus dem Boden. Gerade in wenig produktiven Bergwäldern stellt die winterliche CO2-Emission einen beträchtlichen Teil des C-Flusses des ganzen Jahres dar. Neben der Bodentemperatur wirken sich auch Veränderungen der Niederschlagsmenge bzw. der zeitlichen Verteilung des Niederschlags unmittelbar auf den Bodenkohlenstoff-Umsatz aus. Klimasimulationen sagen für das Untersuchungsgebiet trockenere Sommer, mehr Niederschlag im Winter und eine Verlängerung der Schneedeckendauer vorher. Diese Effekte könnten den stimulierenden Effekt des Temperaturanstieges auf die Bodenatmung abschwächen. In unserer Studie soll ein bereits bestehendes Bodenerwärmungsexperiment adaptiert werden um die CO2-Emissionen aus dem Boden unter verschiedenen Niederschlagsszenarien auf Kontrollflächen und Erwärmungsflächen zu messen. Während der Vegetationsperiode beträgt die Temperaturerhöhung auf den Erwärmungsflächen konstante 3 C. Mit einer Dachkonstruktion soll im Sommer temporär eine Dürreperiode erzeugt werden. Erhöhter Niederschlag im Spätwinter wird durch Schneezugabe auf die Versuchsflächen simuliert. Die bestehende Versuchsanordnung ermöglicht die Unterscheidung zwischen autotropher und heterotropher Bodenatmung. Die Organismen, die für die heterotrophe Atmung zuständig sind, werden mit molekularen Methoden der Mikrobiologie untersucht. Die Ergebnisse des Experiments werden zeigen, ob die Böden von Bergwäldern in einer wärmeren Umwelt eine potentielle Quelle oder doch eine Senke von C sind. usw.

Remote sensing event campaign with various optical and thermal sensors for soil moisture and evapotranspiration derivation in Central Germany investigating possible effects of different spatial scales

The heat waves and droughts of 2018 / 2019 and in 2020 have had a devastating impact on the functioning of ecosystems and have led to an increasing vulnerability beyond the duration of heat waves (e.g. degradation and increased erosion, reduced carbon uptake by vegetation, modulated energy balance). Such impacts also include loss of agricultural production. A better understanding of the progression and the consequences of heatwaves and droughts is essential for the development and improvement of adaptation and protection measures. The airborne remote sensing event campaign performed in the agricultural area of the 'Magdeburger Boerde' in Central Germany aimed at providing remote sensing data sets from different platforms to derive high quality data for improving the understanding of influences and lag effects on hydrologic, biological/biogeochemical and atmospheric processes induced by the summer drought 2020. Multiple recurrences of drought periods in previous years may have led to irreversible changes in structure, composition and functioning of terrestrial ecosystems reducing ecosystem services and resilience. A second goal of the campaign with different available sensors in terms of an inter-calibration is to provide comprehensive and reliable data to ensure future campaign inter-comparability. The acquired data set includes airborne remote sensing data covering variable land cover types obtained by optical, thermal and multispectral sensors (see supplementary material: Schulz et al. (2020), Milewski et al. (2021) ). Furthermore, extensive data from various ground-truthing activities are available such as field spectrometer measurements, soil temperature mapping and soil moisture mapping via Cosmic Ray rovering and TDR-measurements. To complete the data set, micrometeorological time series, soil samples and vegetation characteristics were also taken.

Spatial distribution of aerosol and meteorological parameters measured during flight SourceFFR_ALADINA_20241018_25 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.

Air- and soil temperature data from PhytOakmeter plot DPFL_14 (Pfeiffhausen, Germany) from 2022

Soil temperature at 15cm depth and air temperature at 60cm height were collected using HOBO Pro V2 loggers, model U23-004. Two loggers were used. After data visualization, unrealistic values were removed manually for each logger, and mean temperature values were calculated at 30-minute intervals.

Air- and soil temperature data from PhytOakmeter plot DPFL_14 (Pfeiffhausen, Germany) from 2020

Soil temperature at 15cm depth and air temperature at 60cm height were collected using HOBO Pro V2 loggers, model U23-004. Two loggers were used. After data visualization, unrealistic values were removed manually for each logger, and mean temperature values were calculated at 30-minute intervals.

Air- and soil temperature data from PhytOakmeter plot DPFL_14 (Pfeiffhausen, Germany) from 2021

Soil temperature at 15cm depth and air temperature at 60cm height were collected using HOBO Pro V2 loggers, model U23-004. Two loggers were used. After data visualization, unrealistic values were removed manually for each logger, and mean temperature values were calculated at 30-minute intervals.

Air- and soil temperature data from PhytOakmeter plot DPFL_14 (Pfeiffhausen, Germany) from 2019

Soil temperature at 15cm depth and air temperature at 60cm height were collected using HOBO Pro V2 loggers, model U23-004. Two loggers were used. After data visualization, unrealistic values were removed manually for each logger, and mean temperature values were calculated at 30-minute intervals.

Soil- moisture and temperature from the plot DPFL_14 (Pfeiffhausen, 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.

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