Other language confidence: 0.8961684721127315
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.
Oligozäne und Miozäne Sedimentfolgen aus der Taatsiin Gol und Taatsiin Tsagaan Nuur Region in der Zentral-Mongolei sind von außergewöhnlicher Bedeutung: hier liegen Basalte in Sedimenten der Hsanda Gol- und Loh Formation eingebettet, und die höchsten Fossilkonzentrationen finden sich zusammen mit Caliche und Paläoböden. Im Rahmen von Vorläuferprojekten wurde ein Stratigraphie-Konzept erarbeitet, das auf der Evolution von Säugetieren und auf radiometrischen Basalt-Altern beruht. 40Ar / 39Ar-Datierungen ergaben drei Altersgruppen von Basalten, eine Basalt I-Gruppe aus dem Früh-Oligozän (vor etwa 31.5 Millionen Jahren), eine Basalt II-Gruppe aus dem Spät-Oligozän (vor etwa 28 Millionen Jahren) und eine Basalt III-Gruppe aus dem Mittel-Miozän (vor etwa 13 Millionen Jahren). Das Taatsiin Gol-und Taatsiin Tsagaan Nuur Gebiet ist heute Schlüsselregion für die Oligozän-Miozän Stratigraphie der Mongolei und ist Bezugspunkt für internationale Korrelationen. Im neuen Projekt werden Klimaveränderungen im Oligozän und Miozän der Mongolei und ihre Auswirkungen auf Säugetiergemeinschaften und Lebensräume untersucht. Um diese Ziele zu erreichen müssen zahlreiche stratifizierte Caliche Lagen und Paläoböden beprobt und analysiert werden. Wir erwarten uns von Bodenanalysen und von der Interpretation der Signaturen stabiler Isotopen (?18O, ?13C) Hinweise auf Veränderungen von Paläoklima und Lebensräumen im Untersuchungsgebiet. Die stratifizierten und datierten Säugetierfaunen bestehen aus Amphibien, Reptilien und Säugetieren, wobei Hasenartige, Insektenfresser, Nagetiere und Wiederkäuer vorherrschen. Dieser reiche Fossil-Fundus bietet die Möglichkeit zur Analyse von einstigen Wirbeltier-Gemeinschaften, zu entwicklungsgeschichtlichen Studien und palökologischen Interpretationen. Besonderes Interesse gilt der Entwicklung und Funktion von Gebissstrukturen bei kleinen und großen Pflanzen fressenden Säugetieren. Hier kommen Methoden zur Anwendung (Microwear- und Mesowear-Analysen, Zahnschmelzuntersuchungen, Mikro-CT und 3D-Modellierung), die Rückschlüsse auf das Nahrungsspektrum und auf markante Veränderungen von Lebensräumen in dem untersuchten Zeitabschnitt von mehr als 20 Millionen Jahren erlauben. Die Feldarbeit in der Mongolei und die anschließenden wissenschaftlichen Studien werden in nationaler und internationaler Zusammenarbeit durchgeführt. Von diesen Synergien werden die Mongolischen und Österreichischen Forschungseinrichtungen und alle mitwirkenden Personen stark profitieren.
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.
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.
| Organisation | Count |
|---|---|
| Bund | 13 |
| Europa | 186 |
| Wissenschaft | 223 |
| Type | Count |
|---|---|
| Daten und Messstellen | 207 |
| Förderprogramm | 12 |
| Repositorium | 1 |
| Taxon | 1 |
| Text | 1 |
| unbekannt | 10 |
| License | Count |
|---|---|
| Offen | 229 |
| Unbekannt | 2 |
| Language | Count |
|---|---|
| Deutsch | 8 |
| Englisch | 223 |
| Resource type | Count |
|---|---|
| Archiv | 10 |
| Datei | 196 |
| Dokument | 1 |
| Keine | 24 |
| Webseite | 1 |
| Topic | Count |
|---|---|
| Boden | 32 |
| Lebewesen und Lebensräume | 219 |
| Luft | 202 |
| Mensch und Umwelt | 224 |
| Wasser | 24 |
| Weitere | 231 |