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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.
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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