Ensemble homogenization of Slovenian monthly air temperature series

Vertacnik, G.; Dolinar, Mojca; Bertalanič, Renato; Klancar, M.; Dvoršek, Damjan; Nadbath, Mateja

doi:10.1002/joc.4265

Cited by 31 publications

(43 citation statements)

References 16 publications

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“…Station relocation was found to be a second cause in a number of BPs, responsible for 13% of the BPs. While relocation is usually the main cause for inhomogeneity (Begert et al ., ; Brunet et al ., ; Vertačnik et al ., ), in the current study it was found to be the second cause after instrumentational issues. This is very likely related to the fact that this study includes non‐blended time series, where most of the base stations were not displace and the known relocations where characterized by short displacements of a few tens of meters to a few hundred meters in most cases.…”

Section: Resultsmentioning

confidence: 99%

Detecting and adjusting artificial biases of long‐term temperature records in Israel

Yosef

Aguilar

Alpert

2018

Intl Journal of Climatology

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Climate trends analyses are studied through the analysis of long‐term records which usually are compromised by artificial non‐climatic factors (e.g., station relocation, instrumental replacements, etc). The impact of these factors on the analysis must be assessed and corrected in a procedure called “Homogenization,” before computing any trends. An unbiased analysis is essential for the East Mediterranean climate change, which suffers from scarcity of long and reliable datasets. Here, for the first time, we address these problems by jointly applying some of the state‐of‐the‐art homogenization methods, to long‐term Israeli temperature records (TX and TN) at five different meteorological stations throughout the period of 1950–2011. All of the studied time series were found to be inhomogeneous, where instrumentational issues were responsible for almost 50% of the breaks. The most frequent adjustments range between [−0.6, +0.6] oC while some larger adjustments do not fall within the range of the [−1, +1] °C interval. The adjustment of these breaks is crucial because they introduce large errors that may lead to wrong conclusions about the estimated trends. The difference in the seasonal and annual trends between raw and homogenized series was analysed applying the Mann–Kendall test. The general annual trend differences before and after homogenization, fell within the range of [−0.12, 0.16] oC/decade. Based on the homogenized dataset, a highly significant positive trend was found for the annual trueTN¯ with 0.15 °C/decade (p = .002) whereas the trueTX¯ trend was 0.10 °C/decade (p = .051). In general, the maximum temperature trends are lower and less statistically significant than those for minimum temperature. The most pronounced seasonal trends were recorded for the summer, which was characterized by significant positive trends for trueTX¯ (0.15 °C/decade) and trueTN¯ (0.23 °C/decade), while the winter had mainly no significant positive trends.

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Section: Resultsmentioning

confidence: 99%

Detecting and adjusting artificial biases of long‐term temperature records in Israel

Yosef

Aguilar

Alpert

2018

Intl Journal of Climatology

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“…Data from the 30-year period (1981–2010) were used for calculating temperature means, and the 51-year period (1961–2011) was used for calculating long-term trends. This non-standard 51-year time period was used since it was assigned in the project “Climate variability of Slovenia” (Vertačnik et al 2015). The 30-year (1981–2010) averages of TmeanJJA, TmaxJUL, and HD were considered as the final indices, whereas their trends trTmeanJJA, trTmaxJUL, and trHD were obtained from the 51-year period 1961–2011 using the Theil-Sen method (Theil 1950; Sen 1968).…”

Section: Methodsmentioning

confidence: 99%

The effect of hot days on occupational heat stress in the manufacturing industry: implications for workers’ well-being and productivity

et al. 2018

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Climate change is expected to exacerbate heat stress at the workplace in temperate regions, such as Slovenia. It is therefore of paramount importance to study present and future summer heat conditions and analyze the impact of heat on workers. A set of climate indices based on summer mean (Tmean) and maximum (Tmax) air temperatures, such as the number of hot days (HD: Tmax above 30 °C), and Wet Bulb Globe Temperature (WBGT) were used to account for heat conditions in Slovenia at six locations in the period 1981–2010. Observed trends (1961–2011) of Tmean and Tmax in July were positive, being larger in the eastern part of the country. Climate change projections showed an increase up to 4.5 °C for mean temperature and 35 days for HD by the end of the twenty-first century under the high emission scenario. The increase in WBGT was smaller, although sufficiently high to increase the frequency of days with a high risk of heat stress up to an average of a third of the summer days. A case study performed at a Slovenian automobile parts manufacturing plant revealed non-optimal working conditions during summer 2016 (WBGT mainly between 20 and 25 °C). A survey conducted on 400 workers revealed that 96% perceived the temperature conditions as unsuitable, and 56% experienced headaches and fatigue. Given these conditions and climate change projections, the escalating problem of heat is worrisome. The European Commission initiated a program of research within the Horizon 2020 program to develop a heat warning system for European workers and employers, which will incorporate case-specific solutions to mitigate heat stress.Electronic supplementary materialThe online version of this article (10.1007/s00484-018-1530-6) contains supplementary material, which is available to authorized users.

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“…Nevertheless, the approach is currently being implemented in several weather services [e.g. Météo‐France, the Norwegian Meteorological Institute, MeteoSwiss, the Irish Meteorological Service Met Éireann, and the Slovenian Environment Agency (Vertačnik et al ., )], and it is already applied in countries where station networks are sparse such as Bolivia (Vicente‐Serrano et al ., ; López‐Moreno et al ., ) or Tanzania (Luhunga et al ., ).…”

Section: Introductionmentioning

confidence: 99%

“…However, only one publication comparing the homogenization of a dense and a thinned network is known to the authors: Vertačnik et al . (). They found that a reduction of the Slovenian station network from 60 to 44 (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…To this end, the recently developed semi‐automatic homogenization procedure HOMER (Mestre et al ., ) was chosen since it is state‐of‐the‐art (developed after the COST Action on Homogenization), freely available, and runs on the open‐source software R (R Development Core Team, ). Until now, only a few studies exist that evaluate HOMER (Freitas et al ., ; Coll et al ., ; Vertačnik et al ., ; Noone et al ., ). Nevertheless, the approach is currently being implemented in several weather services [e.g.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The influence of station density on climate data homogenization

Gubler

Hunziker

Begert

et al. 2017

Intl Journal of Climatology

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ABSTRACT:Relative homogenization methods assume that measurements of nearby stations experience similar climate signals and rely therefore on dense station networks with high-temporal correlations. In developing countries such as Peru, however, networks often suffer from low-station density. The aim of this study is to quantify the influence of network density on homogenization. To this end, the homogenization method HOMER was applied to an artificially thinned Swiss network.Four homogenization experiments, reflecting different homogenization approaches, were examined. Such approaches include diverse levels of interaction of the homogenization operators with HOMER, and different application of metadata. To evaluate the performance of HOMER in the sparse networks, a reference series was built by applying HOMER under the best possible conditions. Applied in completely automatic mode, HOMER decreases the reliability of temperature records. Therefore, automatic use of HOMER is not recommended. If HOMER is applied in interactive mode, the reliability of temperature and precipitation data may be increased in sparse networks. However, breakpoints must be inserted conservatively. Information from metadata should be used only to determine the exact timing of statistically detected breaks. Insertion of additional breakpoints based solely on metadata may lead to harmful corrections due to the high noise in sparse networks.

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Ensemble homogenization of Slovenian monthly air temperature series

Cited by 31 publications

References 16 publications

Detecting and adjusting artificial biases of long‐term temperature records in Israel

Detecting and adjusting artificial biases of long‐term temperature records in Israel

The effect of hot days on occupational heat stress in the manufacturing industry: implications for workers’ well-being and productivity

The influence of station density on climate data homogenization

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