Other language confidence: 0.896168472112731
Die polaren Eiskappen bilden ein wertvolles Archiv, das atmosphärische und klimatische Vorgänge der Vergangenheit widerspiegelt. Die intensive Untersuchung von Eisbohrkernen erlaubt insbesondere das Paleo-Klima der Erde bis zu etwa 800,000 Jahre zurückzuverfolgen. Indirekte Datierungen von Eis in den Dry Valleys der Antarktis deuten darauf hin, dass Eis im Bereich von Millionen von Jahren existiert. Bisher war es aber nicht möglich dieses Eis direkt zu datieren. Das gegenwärtige Proposal schlägt die Verwendung von zwei kosmogenen Radioisotopen, 10Be (t1/2 = 1.386 Ma) und 26Al (t1/2 = 0.717 Ma) vor, deren Atom-Verhältnis, 26Al/10Be, als Chronometer für altes Eis verwendet werden kann. In einem geschlossenen System, wie es Eis sein könnte, nimmt das anfängliche 26Al/10Be Verhältnis mit zunehmendem Alter mit einer effektiven Halbwertszeit von 1.49 Ma ab. Das Verhältnis von zwei Radioisotopen mit ähnlichen Eigenschaften, sowohl die Produktion durch kosmische Strahlung als auch den atmosphärischen Transport betreffend, scheint besser geeignet für eine zuverlässige Datierung als ein einzelnes Radioisotope. Damit die Methode funktioniert, müssen folgende Voraussetzungen erfüllt sein: i) Das 26Al/10Be-Verhältnis im Niederschlag muss global sowohl örtlich als auch zeitlich konstant sein, ii) es darf außerdem nicht anfällig für Fraktionierung der beiden Radioisotope nach dem Einschluss ins Eis sein. Unser Ziel ist es, die Anwendbarkeit der Methode zur direkten Datierung von Eis im Bereich von 0.5 bis 5 Millionen Jahren experimentell zu beweisen. In einem vorhergegangenen FWF Projekt (P17442-N02, 'Das Studium von kosmogenem 26Al in Atmosphären- und Klimaforschung') wurden detaillierte Studien über das bis dahin nur schlecht bekannte meteorische 26Al und erste Messungen des 26Al/10Be Verhältnisses in der Atmosphäre und in tiefem Eis mit vielversprechendem Erfolg durchgeführt (Auer et al., Earth Planet. Sci, Lett., in press). Unser Vorschlag hier ist nun i) eine deutliche Verbesserung der analytischen Aspekte der Datierungsmethode gegenüber dem vorhergehenden Projekt, insbesondere eine wesentliche Verringerung der erforderlichen Eismenge und eine Ausweitung der Methode für Eis, das starke mineralische Verunreinigungen enthält, ii) eine Klärung der Ursachen für beobachtete Abweichungen (Fraktionierung) des 26Al/10Be Verhältnisses in tiefen Eisproben, und iii) eine Anwendung der geeignet verbesserten Methode zur Datierung von basalem Eis von Bohrkernen und von Millionen Jahre altem Eis von 'rock glaciers' in der Antarktis. Ein wichtiger Teil des Projekts ist die enge Zusammenarbeit mit der Eisgruppe des Instituts für Umweltphysik der Universität Heidelberg, welche uns in allen Aspekten die Eisproben betreffend zur Seite stehen wird. usw.
The continuous growth of atmospheric nitrous oxide (N2O) is of concern for its potential role in global warming and future stratospheric ozone destruction. Climate feedbacks that enhance N2O emissions in response to global warming are not well understood, and past records of N2O from ice cores are not sufficiently well resolved to examine the underlying climate-N2O feedbacks on societally relevant time scales. Here, we present a new high-resolution and high-precision N2O reconstruction obtained from the Greenland NEEM (North Greenland Eemian Ice Drilling) and the Antarctic Styx Glacier ice cores. Covering the N2O history of the past two millennia, our reconstruction shows a centennial-scale variability of ~10 ppb. A pronounced minimum at ~600 CE coincides with the reorganizations of tropical hydroclimate and ocean productivity changes. Comparisons with proxy records suggest association of centennial- to millennial-scale variations in N2O with changes in tropical and subtropical land hydrology and marine productivity.
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.
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.
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.
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.
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.
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.
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.
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