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Homogenized mean monthly temperature time series (HClim), station Hom_HCLIM_Meersburg, 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.

GDGT concentrations in ELSA stack samples of the Eifel volcanic field, Germany

Isoprenoid and branched GDGTs were measured in soils and lake sediment samples from the Eifel Volcanic field. The modern samples were used to understand sources of GDGTs in sediments, while sediment core samples from Schalkenmehrener Maar, Holzmaar, and Auel Maar were used to reconstruct temperatures during the past 60,000 years. Age model information and additional proxy data from the ELSA-20 stack are found in Sirocko et al., 2021 and Sirocko et al., 2022

GDGT concentrations in ELSA stack samples of the Eifel volcanic field, Germany

Isoprenoid and branched GDGTs were measured in soils and lake sediment samples from the Eifel Volcanic field. The modern samples were used to understand sources of GDGTs in sediments, while sediment core samples from Schalkenmehrener Maar, Holzmaar, and Auel Maar were used to reconstruct temperatures during the past 60,000 years. Age model information and additional proxy data from the ELSA-20 stack are found in Sirocko et al., 2021 and Sirocko et al., 2022

Homogenized mean monthly temperature time series (HClim), station Hom_HCLIM_Amberg-Unterammersricht, 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_Munster, 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_Heidelberg, 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_ALKASTENBERG, 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_Kleve, 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.

Homogenization of the Global early mean monthly temperature time series (HClim)

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.

Deuteriumexzess von polarem Schnee und Niederschlagsursprung

Interdisziplinäre Bewertung unterschiedlicher waldbaulicher Eingriffe in Eichenbeständen, daraus Ableitung von Handlungsempfehlungen. 'Um mögliche gegenwärtige oder zukünftige Klimaänderungen beurteilen zu können, ist es unerlässlich, das Klima der Vergangenheit genau zu kennen und zu verstehen. Wertvolle Informationen über das vergangene Klima sind in Eiskernen von den beiden großen Eisschilden Grönlands und der Antarktis gespeichert. Insbesondere sind die Verhältnisse der stabilen Isotope des Schnees, 18-O und Deuterium, mit der Lufttemperatur korreliert und werden daher für die klimatische Interpretation von Eiskernen verwendet. Aber der Isotopengehalt hängt nicht nur von der Temperatur, sondern auch von anderen Faktoren ab, wie z.B. Saisonalität und Ursprungsgebiet des Niederschlags. Daher wird der Deuteriumexzess, eine Größe, die die Information von 18-O und Deuterium kombiniert, verwendet, um die Ursprungsgebiete des Niederschlags zu untersuchen. d hängt hauptsächlich von der Meeresoberflächentemperatur, der relativen Feuchte und der Windgeschwindigkeit im Ursprungs-gebiet ab. Indem man tested, unter welchen Annahmen für die im Ursprungsgebiet vorherrschenden Bedingungen die im Schnee gemessenen d-Werte mit Hilfe eines einfachen Isotopenmodells reproduziert werden können, erhält man Informationen über das Ursprungsgebiet. Der Spielraum für die möglichen Annahmen ist überraschend klein. Die meisten Deuteriumexzessuntersuchungen wurden für große Zeitmaßstäbe durchgeführt (Wechsel von Glazial zu Interglazial). In dieser Untersuchung werden Daten von der deutschen Antarktis-Überwinterungsstation ''Neumayer'' für eine Untersuchung in einem kleinen Zeitscale verwendet. Dort werden seit 20 Jahren Neuschneeproben unmittelbar nach dem Schneefall genommen. Durch die vorherrschenden hohen Windgeschwindigkeit wird der Schnee in einem gewissen Ausmaß verfrachtet, was zu Fehlern führen kann. Daher werden zunächst mit Hilfe eines Trajektorienmodells die Transportwege der Luftmassen, die Niederschlag nach Neumayer bringen, berechnet. Verschiedene Trajektorienklassen werden definiert, für die der mittlere Deuteriumexzess der Schneeproben bestimmt wird. Dann wird ein Isotopenmodell verwendet, um den beobachteten Deuteriumexzess zu modellieren. Da dieser stark von der relativen Luftfeuchte im Ursprungsgebiet des Niederschlags, die meist nicht bekannt ist, abhängt, soll ferner die Phasendifferenz zwischen Deuterium und Deuteriumexzess untersucht werden. Dazu werden Daten von einem Firnkern verwendet, der den Zeitraum von 1892-1981 abdeckt. Diese Phasendifferenz ist weniger stark von den Sättigungsbedingungen im Ursprungsgebiet abhängig und ist daher eine unabhängigere Bedingung, um Information über die Wasserdampfquelle abzuleiten. usw.

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