Reassessment of the homogenization of daily maximum temperatures in the Netherlands since 1901

Dijkstra, Frans; Vos, R. de; Ruis, Jan; Crok, Marcel

doi:10.1007/s00704-021-03887-4

Cited by 4 publications

(3 citation statements)

References 17 publications

(19 reference statements)

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“…The number of continuous years was longer than at least 5 years but less than the recommended 15 years (Wang et al, 2010) after dividing by the breakpoints in the candidate station. Similarly, a length of 14 years was suggested for the homogenization of daily maximum temperatures in the Netherlands for great stability in counting tropical days (Dijkstra et al, 2022). However, long-term continuous years might be not available to BO because it has frequent changes in locations and the local site environments induced by rapid urbanization.…”

Section: Discussionmentioning

confidence: 99%

A method for homogenization of complex daily mean temperature data: Application at Beijing Observatory (1915–2021) and trend analysis

Chen,

Hu,

Wang

et al. 2024

Intl Journal of Climatology

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A homogenized daily mean temperature series from 1915 to 2021 at Beijing Observatory (BO) has been developed. A thorough investigation of observation records and historical metadata was carried out to identify specific non‐climatic biases. The inhomogeneities were detected and adjusted with the optimally selected reference stations using a statistical reduction methodology. The results indicated three types of non‐climatic biases in temperature records: the first was the relocation of BO from suburban to urban, which caused positive shifts in temperature records, especially for wintertime; the second arose from different methods for calculating daily mean temperature, which caused different sign biases varying with months; and the last was caused by the transition from manual to automatic measurements with site‐specific biases. The corresponding adjustments due to three type biases ranged from −1.13 to 0.63, −0.29 to 0.23 and −0.13 to 0.00°C, respectively. The new homogenized annual mean temperature series showed a warming trend of 0.199°C/decade during 1915–2021. The trend was more pronounced in winter than in the other three seasons. The warming trend in the new series is greater than those in the previous homogenized series (0.136–0.177°C/decade), primarily due to the more effective adjustment associated with the site relocation, particularly for more urban locations.

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Section: Discussionmentioning

confidence: 99%

A method for homogenization of complex daily mean temperature data: Application at Beijing Observatory (1915–2021) and trend analysis

Chen,

Hu,

Wang

et al. 2024

Intl Journal of Climatology

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“…Therefore, if we are interested in using these records to study regional, hemispheric or global temperature trends, it is important to accurately account for these biases. Indeed, many of us are actively engaged in developing and/or improving the reliability of the available temperature records for Europe [18,19,35,[44][45][46]49,[56][57][58][59][69][70][71][75][76][77][78][79] and elsewhere [18,19,38,39] through various homogenization techniques and/or the collection of more data.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Homogenization Adjustments Applied to European Temperature Records in the Global Historical Climatology Network Dataset

O’Neill

Connolly²,

Connolly³

et al. 2022

Atmosphere

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The widely used Global Historical Climatology Network (GHCN) monthly temperature dataset is available in two formats—non-homogenized and homogenized. Since 2011, this homogenized dataset has been updated almost daily by applying the “Pairwise Homogenization Algorithm” (PHA) to the non-homogenized datasets. Previous studies found that the PHA can perform well at correcting synthetic time series when certain artificial biases are introduced. However, its performance with real world data has been less well studied. Therefore, the homogenized GHCN datasets (Version 3 and 4) were downloaded almost daily over a 10-year period (2011-2021) yielding 3689 different updates to the datasets. The different breakpoints identified were analyzed for a set of stations from 24 European countries for which station history metadata were available. A remarkable inconsistency in the identified breakpoints (and hence adjustments applied) was revealed. Of the adjustments applied for GHCN Version 4, 64% (61% for Version 3) were identified on less than 25% of runs, while only 16% of the adjustments (21% for Version 3) were identified consistently for more than 75% of the runs. The consistency of PHA adjustments improved when the breakpoints corresponded to documented station history metadata events. However, only 19% of the breakpoints (18% for Version 3) were associated with a documented event within 1 year, and 67% (69% for Version 3) were not associated with any documented event. Therefore, while the PHA remains a useful tool in the community’s homogenization toolbox, many of the PHA adjustments applied to the homogenized GHCN dataset may have been spurious. Using station metadata to assess the reliability of PHA adjustments might potentially help to identify some of these spurious adjustments.

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“…There are numerous papers where results of QC and homogenization procedures applied on the global, national, regional or local level to station time series of various climate variables with the monthly (e.g., Aruffo & Di Carlo, 2019; Coll et al, 2020; Kessabi et al, 2022; Kolendowicz et al, 2018; Laapas & Venäläinen, 2017; Li et al, 2012; Mamara et al, 2013; Mamara et al, 2014; Mamara et al, 2017; Menne et al, 2018; Prohom et al, 2015; Vertačnik et al, 2015), daily (e.g., Dijkstra et al, 2021; Fioravanti et al, 2019; Hewaarachchi et al, 2017; Kuglitsch et al, 2009; Mateus & Potito, 2021; Randriamarolaza et al, 2021; Spinoni et al, 2014; Squintu et al, 2018; Trewin, 2012; Xu et al, 2013; Yosef et al, 2018) and even hourly (Dumitrescu et al, 2020) time resolutions are presented. For modern climatological research, time series with daily time resolution are specially precious.…”

Section: Introductionmentioning

confidence: 99%

Data quality control and homogenization of daily precipitation and air temperature (mean, max and min) time series of Ukraine

Skrynyk

Sidenko

Aguilar

et al. 2023

Intl Journal of Climatology

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In this paper we present the results of quality control and homogenization procedures applied to long time series of daily atmospheric precipitation sums (Rr) and daily mean (Tm), maximum (Tx) and minimum (Tn) air temperature collected in Ukraine. The daily data from 178 meteorological stations covering the period of 1946–2020 were analysed. In order to perform a thorough quality assurance check, we used the R package INQC, while the Climatol homogenization software was used to detect and remove breaks from the time series. The INQC quality assurance tests revealed a relatively small number of erroneous records (around 0.01% for each variable) and suspicious values (up to 0.09%). The application of Climatol resulted in 195, 296, 355 and 359 break points, detected for Rr, Tm, Tx and Tn, respectively. These quantities coincide roughly with the results of the HOMER homogenization procedure applied to monthly time series for the same stations and almost the same period (performed in the previous works of the authors). To verify the homogenization results, statistical comparison of the raw and homogenized time series was performed. The verification demonstrated that the quality control and homogenization procedures detected and removed errors and breaks very well, and air temperature and precipitation fields after the homogenization are more self‐consistent compared to the original raw data.

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Reassessment of the homogenization of daily maximum temperatures in the Netherlands since 1901

Cited by 4 publications

References 17 publications

A method for homogenization of complex daily mean temperature data: Application at Beijing Observatory (1915–2021) and trend analysis

A method for homogenization of complex daily mean temperature data: Application at Beijing Observatory (1915–2021) and trend analysis

Evaluation of the Homogenization Adjustments Applied to European Temperature Records in the Global Historical Climatology Network Dataset

Data quality control and homogenization of daily precipitation and air temperature (mean, max and min) time series of Ukraine

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