{"title":"1961-2018年挪威月降水序列的均一化","authors":"Elinah Khasandi Kuya, H. M. Gjelten, O. E. Tveito","doi":"10.5194/asr-19-73-2022","DOIUrl":null,"url":null,"abstract":"Abstract. The primary goal of the analysis was to establish a high-quality precipitation reference dataset, which is both consistent and homogeneous,\nfor calculation of the new standard climate normals (1991–2020). Climatol\nhomogenization method was applied to detect inhomogeneities in 325 Norwegian precipitation series, during the period 1961–2018. Results from homogeneity testing found inhomogeneities in 29 % of the 325 series, however, only 25 % were classified as inhomogeneous after conferring with metadata and therefore adjusted. Relocation of the precipitation gauge and automation were the main causes of all the inhomogeneities in the Norwegian series, explaining 71 % and 12 % respectively of all detected breaks. Results further showed benefits of incorporating metadata to the automatically detected inhomogeneities. Linear trend analysis showed increasing trends in the period 1961–2018 except in autumn where a decreasing trend was observed. The homogeneity analysis produced a 58-year long homogenous dataset for 325 monthly precipitation sums with regional temporal variability and spatial coherence that is better than that of non-homogenized series. The dataset is more reliable in explaining the large-scale climate variations and was used to calculate the new climate normals in Norway.\n","PeriodicalId":30081,"journal":{"name":"Advances in Science and Research","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Homogenization of Norwegian monthly precipitation series for the period 1961–2018\",\"authors\":\"Elinah Khasandi Kuya, H. M. Gjelten, O. E. Tveito\",\"doi\":\"10.5194/asr-19-73-2022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. The primary goal of the analysis was to establish a high-quality precipitation reference dataset, which is both consistent and homogeneous,\\nfor calculation of the new standard climate normals (1991–2020). Climatol\\nhomogenization method was applied to detect inhomogeneities in 325 Norwegian precipitation series, during the period 1961–2018. Results from homogeneity testing found inhomogeneities in 29 % of the 325 series, however, only 25 % were classified as inhomogeneous after conferring with metadata and therefore adjusted. Relocation of the precipitation gauge and automation were the main causes of all the inhomogeneities in the Norwegian series, explaining 71 % and 12 % respectively of all detected breaks. Results further showed benefits of incorporating metadata to the automatically detected inhomogeneities. Linear trend analysis showed increasing trends in the period 1961–2018 except in autumn where a decreasing trend was observed. The homogeneity analysis produced a 58-year long homogenous dataset for 325 monthly precipitation sums with regional temporal variability and spatial coherence that is better than that of non-homogenized series. The dataset is more reliable in explaining the large-scale climate variations and was used to calculate the new climate normals in Norway.\\n\",\"PeriodicalId\":30081,\"journal\":{\"name\":\"Advances in Science and Research\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Science and Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5194/asr-19-73-2022\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Science and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/asr-19-73-2022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
Homogenization of Norwegian monthly precipitation series for the period 1961–2018
Abstract. The primary goal of the analysis was to establish a high-quality precipitation reference dataset, which is both consistent and homogeneous,
for calculation of the new standard climate normals (1991–2020). Climatol
homogenization method was applied to detect inhomogeneities in 325 Norwegian precipitation series, during the period 1961–2018. Results from homogeneity testing found inhomogeneities in 29 % of the 325 series, however, only 25 % were classified as inhomogeneous after conferring with metadata and therefore adjusted. Relocation of the precipitation gauge and automation were the main causes of all the inhomogeneities in the Norwegian series, explaining 71 % and 12 % respectively of all detected breaks. Results further showed benefits of incorporating metadata to the automatically detected inhomogeneities. Linear trend analysis showed increasing trends in the period 1961–2018 except in autumn where a decreasing trend was observed. The homogeneity analysis produced a 58-year long homogenous dataset for 325 monthly precipitation sums with regional temporal variability and spatial coherence that is better than that of non-homogenized series. The dataset is more reliable in explaining the large-scale climate variations and was used to calculate the new climate normals in Norway.