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Stündliche Stationsmessungen der Lufttemperatur und Luftfeuchte für Deutschland

Diese Daten stammen von den Stationen des DWD und rechtlich sowie qualitativ gleichgestellten Partnernetzen. Umfangreiche Stationsmetadaten (Stationsverlegungen, Instrumentenwechsel, Wechsel der Bezugszeit, Änderungen in den Algorithmen) werden beim Download mitgeliefert. Der Datensatz ist aufgeteilt in einen versionierten Teil mit abgeschlossener Qualitätsprüfung, im Verzeichnis ./historical/. Und einen sich kontinuierlich aktualisierenden Teil, für den die Qualitätsprüfung noch nicht abgeschlossen ist, im Verzeichnis ./recent/. In dem Ordner ./timeseries_overview/ stehen Angaben zu langen Zeitreihen zur Verfügung.

High-resolution measurements of essential climate variables in the North Sea from the autonomous surface vehicle HALOBATES during RV Heincke cruise HE614

The autonomous surface vehicle HALOBATES measured Essential Climate Variables (ECV), such as sea surface temperature (SST) and salinity (SSS), during the RV Heincke cruise HE614 in the German Bight. HALOBATES captured the SST and SSS at seven depths with a high vertical resolution of about 10 cm, from the near-surface layer (NSL) (between 30 and 100 cm) and the sea surface microlayer (SML) (upper millimeter). Conductivity, temperature, and depth (CTD) sensors measured temperature and conductivity (for salinity calculation) via a flow-through system on HALOBATES. Additional temperature sensors were mounted underneath the catamaran to measure in-situ temperature in situ at six depths in the NSL. Salinity was corrected with discrete water samples to remove biases between the sensors. Two data loggers with several meteorological stations on the catamaran captured important weather variables during operation time. The surfactant concentration was measured from discrete samples of SML and 100 cm depth. HALOBATES was operated between 01 March 2023 and 22 March 2023.

Butterflies observation data from restored grasslands and reference sites in Germany

This dataset provides detailed information on butterfly species richness and abundance as part of the Grassworks project, which investigates the grasslands restoration in Germany. Grasslands are globally threatened ecosystems, and the project aims to identify factors that contribute to successful restoration, focusing on ecological, economical and socio-ecological drivers. Data was collected from 187 grassland sites across three regions in North, Central, and South Germany, each with distinct socio-economic and ecological characteristics. Sampling occurred between 2022 and 2023 and included 40–41 restored grassland sites and 20–25 reference sites (10–12 positive, 10–13 negative) per region. Butterfly abundance and species richness were among the ecological metrics recorded.

High-resolution measurements of essential climate variables in the North Sea from the autonomous surface vehicle HALOBATES during RV Heincke cruise HE626

The autonomous surface vehicle HALOBATES collected key climate variables, including sea surface temperature (SST) and salinity (SSS), during the RV Heincke cruise HE626 in the German Bight. HALOBATES recorded SST and SSS at seven different depths with a high vertical resolution of approximately 10 cm, ranging from the near-surface layer (NSL) (between 30 and 100 cm) to the sea-surface microlayer (SML) (uppermost millimeter). Temperature and conductivity (used for salinity calculation) were measured using conductivity, temperature, and depth (CTD) sensors connected to a flow-through system on HALOBATES. Additional temperature sensors were placed beneath the catamaran to capture in-situ temperature at six depths within the NSL. Salinity measurements were adjusted using discrete water samples to correct for any sensor biases. During the operation, two data loggers equipped with meteorological stations on the catamaran monitored essential weather conditions. HALOBATES was in operation from July 21, 2023, to August 8, 2023.

Temperature measurements from SIMBA-type sea ice mass balance buoy 2018T51

Temperature and heating-induced temperature difference profiles were measured through the atmosphere, sea ice, and ocean using a SIMBA-type sea ice mass balance buoy equipped with a several meter long thermistor chain. The present dataset was recorded by SIMBA 2018T51 (original name Awi_33r) installed on drifting sea ice in the Arctic Ocean during the expedition Oden AO18 in 2018. Data is available between 2018-08-23 15:50:00 and 2019-03-30 13:31:00. The thermistor chain was Variable 5 m long and included 240 sensors with a regular spacing of 2 cm. The resulting time series includes the evolution of temperature and temperature differences at 30 s and 120 s during a heating cycle of 120 s as a function of location, depth and time. The sampling intervals were usually between hourly and daily, but were most frequently configured to 6 hours for temperature, and 24 hours for temperature differences. In addition to temperatures and geographic location, barometric pressure, ~1 m air temperature, instrument tilt, and compass heading were measured. The present dataset was processed as follows: obvious inconsistencies (missing values) and unrealistic values of GPS position have been removed. This instrument was deployed as part of the project Sea Ice Physics @ AWI (AWI_SeaIce).

Homogenized mean monthly temperature time series (HClim), station Hom_HCLIM_Gottingen, Germany

Instrumental meteorological observations are essential for analysing past climate and reconstructing climate variability. However, many of the long instrumental climate series, some extending back to 1658, have been affected by inhomogeneities (artificial shifts) caused by changes in measurement conditions such as station relocations, instrumentation changes, and environmental modifications. To address this problem, homogenization procedures have been developed to detect and adjust such inhomogeneities. In this work, the records undergo homogenization analysis, during which these inhomogeneities are identified and corrected. The Standard Normal Homogeneity Test (SNHT), developed by Hans Alexandersson, is applied as the statistical method, comparing candidate series with neighbouring reference stations to assess relative homogeneity. The article presents homogenization analyses using three different tools (CLIMATOL, BART, and PHA) applied to the published global multivariable monthly instrumental climate database HCLIM (doi:10.1594/PANGAEA.940724). The resulting database includes the best-performing homogenized series - those produced by BART - comprising 2,892 homogenized temperature time series covering the period 1757–2020.

Homogenized mean monthly temperature time series (HClim), station Hom_HCLIM_Kyritz, Germany

Instrumental meteorological observations are essential for analysing past climate and reconstructing climate variability. However, many of the long instrumental climate series, some extending back to 1658, have been affected by inhomogeneities (artificial shifts) caused by changes in measurement conditions such as station relocations, instrumentation changes, and environmental modifications. To address this problem, homogenization procedures have been developed to detect and adjust such inhomogeneities. In this work, the records undergo homogenization analysis, during which these inhomogeneities are identified and corrected. The Standard Normal Homogeneity Test (SNHT), developed by Hans Alexandersson, is applied as the statistical method, comparing candidate series with neighbouring reference stations to assess relative homogeneity. The article presents homogenization analyses using three different tools (CLIMATOL, BART, and PHA) applied to the published global multivariable monthly instrumental climate database HCLIM (doi:10.1594/PANGAEA.940724). The resulting database includes the best-performing homogenized series - those produced by BART - comprising 2,892 homogenized temperature time series covering the period 1757–2020.

Homogenized mean monthly temperature time series (HClim), station Hom_HCLIM_Brandenburg-Gorden, Germany

Instrumental meteorological observations are essential for analysing past climate and reconstructing climate variability. However, many of the long instrumental climate series, some extending back to 1658, have been affected by inhomogeneities (artificial shifts) caused by changes in measurement conditions such as station relocations, instrumentation changes, and environmental modifications. To address this problem, homogenization procedures have been developed to detect and adjust such inhomogeneities. In this work, the records undergo homogenization analysis, during which these inhomogeneities are identified and corrected. The Standard Normal Homogeneity Test (SNHT), developed by Hans Alexandersson, is applied as the statistical method, comparing candidate series with neighbouring reference stations to assess relative homogeneity. The article presents homogenization analyses using three different tools (CLIMATOL, BART, and PHA) applied to the published global multivariable monthly instrumental climate database HCLIM (doi:10.1594/PANGAEA.940724). The resulting database includes the best-performing homogenized series - those produced by BART - comprising 2,892 homogenized temperature time series covering the period 1757–2020.

Homogenized mean monthly temperature time series (HClim), station Hom_HCLIM_Elsfleth, Germany

Instrumental meteorological observations are essential for analysing past climate and reconstructing climate variability. However, many of the long instrumental climate series, some extending back to 1658, have been affected by inhomogeneities (artificial shifts) caused by changes in measurement conditions such as station relocations, instrumentation changes, and environmental modifications. To address this problem, homogenization procedures have been developed to detect and adjust such inhomogeneities. In this work, the records undergo homogenization analysis, during which these inhomogeneities are identified and corrected. The Standard Normal Homogeneity Test (SNHT), developed by Hans Alexandersson, is applied as the statistical method, comparing candidate series with neighbouring reference stations to assess relative homogeneity. The article presents homogenization analyses using three different tools (CLIMATOL, BART, and PHA) applied to the published global multivariable monthly instrumental climate database HCLIM (doi:10.1594/PANGAEA.940724). The resulting database includes the best-performing homogenized series - those produced by BART - comprising 2,892 homogenized temperature time series covering the period 1757–2020.

Heating induced temperature difference measurements from SIMBA-type sea ice mass balance buoy 2019T57: 30 s after the start of the heating cycle

Temperature and heating-induced temperature difference profiles were measured through the atmosphere, sea ice, and ocean using a SIMBA-type sea ice mass balance buoy equipped with a several meter long thermistor chain. The present dataset was recorded by SIMBA 2019T57 (original name FMI05-08) installed on drifting sea ice in the Arctic Ocean during the expedition Polarstern PS122 (MOSAiC) in 2019/20. Data is available between 2019-10-07 03:00:00 and 2020-01-18 02:00:00. The thermistor chain was Variable 5 m long and included 241 sensors with a regular spacing of 2 cm. The resulting time series includes the evolution of temperature and temperature differences at 30 s and 120 s during a heating cycle of 120 s as a function of location, depth and time. The sampling intervals were usually between hourly and daily, but were most frequently configured to 6 hours for temperature, and 24 hours for temperature differences. In addition to temperatures and geographic location, barometric pressure, ~1 m air temperature, instrument tilt, and compass heading were measured. The present dataset was processed as follows: obvious inconsistencies (missing values) and unrealistic values of GPS position have been removed. This instrument was deployed as part of the project FMI.

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