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- Author or Editor: Manola Brunet x
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Abstract
The aim of time series homogenization is to remove nonclimatic effects, such as changes in station location, instrumentation, observation practices, and so on, from observed data. Statistical homogenization usually reduces the nonclimatic effects but does not remove them completely. In the Spanish “MULTITEST” project, the efficiencies of automatic homogenization methods were tested on large benchmark datasets of a wide range of statistical properties. In this study, test results for nine versions, based on five homogenization methods—the adapted Caussinus-Mestre algorithm for the homogenization of networks of climatic time series (ACMANT), “Climatol,” multiple analysis of series for homogenization (MASH), the pairwise homogenization algorithm (PHA), and “RHtests”—are presented and evaluated. The tests were executed with 12 synthetic/surrogate monthly temperature test datasets containing 100–500 networks with 5–40 time series in each. Residual centered root-mean-square errors and residual trend biases were calculated both for individual station series and for network mean series. The results show that a larger fraction of the nonclimatic biases can be removed from station series than from network-mean series. The largest error reduction is found for the long-term linear trends of individual time series in datasets with a high signal-to-noise ratio (SNR), where the mean residual error is only 14%–36% of the raw data error. When the SNR is low, most of the results still indicate error reductions, although with smaller ratios than for large SNR. In general, ACMANT gave the most accurate homogenization results. In the accuracy of individual time series ACMANT is closely followed by Climatol, and for the accurate calculation of mean climatic trends over large geographical regions both PHA and ACMANT are recommended.
Abstract
The aim of time series homogenization is to remove nonclimatic effects, such as changes in station location, instrumentation, observation practices, and so on, from observed data. Statistical homogenization usually reduces the nonclimatic effects but does not remove them completely. In the Spanish “MULTITEST” project, the efficiencies of automatic homogenization methods were tested on large benchmark datasets of a wide range of statistical properties. In this study, test results for nine versions, based on five homogenization methods—the adapted Caussinus-Mestre algorithm for the homogenization of networks of climatic time series (ACMANT), “Climatol,” multiple analysis of series for homogenization (MASH), the pairwise homogenization algorithm (PHA), and “RHtests”—are presented and evaluated. The tests were executed with 12 synthetic/surrogate monthly temperature test datasets containing 100–500 networks with 5–40 time series in each. Residual centered root-mean-square errors and residual trend biases were calculated both for individual station series and for network mean series. The results show that a larger fraction of the nonclimatic biases can be removed from station series than from network-mean series. The largest error reduction is found for the long-term linear trends of individual time series in datasets with a high signal-to-noise ratio (SNR), where the mean residual error is only 14%–36% of the raw data error. When the SNR is low, most of the results still indicate error reductions, although with smaller ratios than for large SNR. In general, ACMANT gave the most accurate homogenization results. In the accuracy of individual time series ACMANT is closely followed by Climatol, and for the accurate calculation of mean climatic trends over large geographical regions both PHA and ACMANT are recommended.
Abstract
Instrumental meteorological measurements from periods prior to the start of national weather services are designated “early instrumental data.” They have played an important role in climate research as they allow daily to decadal variability and changes of temperature, pressure, and precipitation, including extremes, to be addressed. Early instrumental data can also help place twenty-first century climatic changes into a historical context such as defining preindustrial climate and its variability. Until recently, the focus was on long, high-quality series, while the large number of shorter series (which together also cover long periods) received little to no attention. The shift in climate and climate impact research from mean climate characteristics toward weather variability and extremes, as well as the success of historical reanalyses that make use of short series, generates a need for locating and exploring further early instrumental measurements. However, information on early instrumental series has never been electronically compiled on a global scale. Here we attempt a worldwide compilation of metadata on early instrumental meteorological records prior to 1850 (1890 for Africa and the Arctic). Our global inventory comprises information on several thousand records, about half of which have not yet been digitized (not even as monthly means), and only approximately 20% of which have made it to global repositories. The inventory will help to prioritize data rescue efforts and can be used to analyze the potential feasibility of historical weather data products. The inventory will be maintained as a living document and is a first, critical, step toward the systematic rescue and reevaluation of these highly valuable early records. Additions to the inventory are welcome.
Abstract
Instrumental meteorological measurements from periods prior to the start of national weather services are designated “early instrumental data.” They have played an important role in climate research as they allow daily to decadal variability and changes of temperature, pressure, and precipitation, including extremes, to be addressed. Early instrumental data can also help place twenty-first century climatic changes into a historical context such as defining preindustrial climate and its variability. Until recently, the focus was on long, high-quality series, while the large number of shorter series (which together also cover long periods) received little to no attention. The shift in climate and climate impact research from mean climate characteristics toward weather variability and extremes, as well as the success of historical reanalyses that make use of short series, generates a need for locating and exploring further early instrumental measurements. However, information on early instrumental series has never been electronically compiled on a global scale. Here we attempt a worldwide compilation of metadata on early instrumental meteorological records prior to 1850 (1890 for Africa and the Arctic). Our global inventory comprises information on several thousand records, about half of which have not yet been digitized (not even as monthly means), and only approximately 20% of which have made it to global repositories. The inventory will help to prioritize data rescue efforts and can be used to analyze the potential feasibility of historical weather data products. The inventory will be maintained as a living document and is a first, critical, step toward the systematic rescue and reevaluation of these highly valuable early records. Additions to the inventory are welcome.
ABSTRACT
Two reports of Antarctic region potential new record high temperature observations (18.3°C, 6 February 2020 at Esperanza station and 20.8°C, 9 February 2020 at a Brazilian automated permafrost monitoring station on Seymour Island) were evaluated by a World Meteorological Organization (WMO) panel of atmospheric scientists. The latter figure was reported as 20.75°C in the media. The panel considered the synoptic situation and instrumental setups. It determined that a large high pressure system over the area created föhn conditions and resulted in local warming for both situations. Examination of the data and metadata of the Esperanza station observation revealed no major concerns. However, analysis of data and metadata of the Seymour Island permafrost monitoring station indicated that an improvised radiation shield led to a demonstrable thermal bias error for the temperature sensor. Consequently, the WMO has accepted the 18.3°C value for 1200 LST 6 February 2020 (1500 UTC 6 February 2020) at the Argentine Esperanza station as the new “Antarctic region (continental, including mainland and surrounding islands) highest temperature recorded observation” but rejected the 20.8°C observation at the Brazilian automated Seymour Island permafrost monitoring station as biased. The committee strongly emphasizes the permafrost monitoring station was not badly designed for its purpose, but the project investigators were forced to improvise a nonoptimal radiation shield after losing the original covering. Second, with regard to media dissemination of this type of information, the committee urges increased caution in early announcements as many media outlets often tend to sensationalize and mischaracterize potential records.
ABSTRACT
Two reports of Antarctic region potential new record high temperature observations (18.3°C, 6 February 2020 at Esperanza station and 20.8°C, 9 February 2020 at a Brazilian automated permafrost monitoring station on Seymour Island) were evaluated by a World Meteorological Organization (WMO) panel of atmospheric scientists. The latter figure was reported as 20.75°C in the media. The panel considered the synoptic situation and instrumental setups. It determined that a large high pressure system over the area created föhn conditions and resulted in local warming for both situations. Examination of the data and metadata of the Esperanza station observation revealed no major concerns. However, analysis of data and metadata of the Seymour Island permafrost monitoring station indicated that an improvised radiation shield led to a demonstrable thermal bias error for the temperature sensor. Consequently, the WMO has accepted the 18.3°C value for 1200 LST 6 February 2020 (1500 UTC 6 February 2020) at the Argentine Esperanza station as the new “Antarctic region (continental, including mainland and surrounding islands) highest temperature recorded observation” but rejected the 20.8°C observation at the Brazilian automated Seymour Island permafrost monitoring station as biased. The committee strongly emphasizes the permafrost monitoring station was not badly designed for its purpose, but the project investigators were forced to improvise a nonoptimal radiation shield after losing the original covering. Second, with regard to media dissemination of this type of information, the committee urges increased caution in early announcements as many media outlets often tend to sensationalize and mischaracterize potential records.
Abstract
A World Meteorological Organization weather and climate extremes committee has judged that the world’s longest reported distance for a single lightning flash occurred with a horizontal distance of 321 km (199.5 mi) over Oklahoma in 2007, while the world’s longest reported duration for a single lightning flash is an event that lasted continuously for 7.74 s over southern France in 2012. In addition, the committee has unanimously recommended amendment of the AMS Glossary of Meteorology definition of lightning discharge as a “series of electrical processes taking place within 1 s” by removing the phrase “within 1 s” and replacing it with “continuously.” Validation of these new world extremes 1) demonstrates the recent and ongoing dramatic augmentations and improvements to regional lightning detection and measurement networks, 2) provides reinforcement regarding the dangers of lightning, and 3) provides new information for lightning engineering concerns.
Abstract
A World Meteorological Organization weather and climate extremes committee has judged that the world’s longest reported distance for a single lightning flash occurred with a horizontal distance of 321 km (199.5 mi) over Oklahoma in 2007, while the world’s longest reported duration for a single lightning flash is an event that lasted continuously for 7.74 s over southern France in 2012. In addition, the committee has unanimously recommended amendment of the AMS Glossary of Meteorology definition of lightning discharge as a “series of electrical processes taking place within 1 s” by removing the phrase “within 1 s” and replacing it with “continuously.” Validation of these new world extremes 1) demonstrates the recent and ongoing dramatic augmentations and improvements to regional lightning detection and measurement networks, 2) provides reinforcement regarding the dangers of lightning, and 3) provides new information for lightning engineering concerns.
On 13 September 1922, a temperature of 58°C (136.4°F) was purportedly recorded at El Azizia (approximately 40 km south-southwest of Tripoli) in what is now modern-day Libya. That temperature record of 58°C has been cited by numerous world-record sources as the highest recorded temperature for the planet. During 2010–11, a World Meteorological Organization (WMO) Commission of Climatology (CCl) special international panel of meteorological experts conducted an in-depth investigation of this record temperature for the WMO World Archive of Weather and Climate Extremes (http://wmo.asu.edu/). This committee identified five major concerns with the 1922 El Azizia temperature extreme record, specifically 1) potentially problematical instrumentation, 2) a probable new and inexperienced observer at the time of observation, 3) unrepresentative microclimate of the observation site, 4) poor correspondence of the extreme to other locations, and 5) poor comparison to subsequent temperature values recorded at the site. Based on these concerns, the WMO World Archive of Weather and Climate Extremes rejected this temperature extreme of 58°C as the highest temperature officially recorded on the planet. The WMO assessment is that the highest recorded surface temperature of 56.7°C (134°F) was measured on 10 July 1913 at Greenland Ranch (Death Valley), California.
On 13 September 1922, a temperature of 58°C (136.4°F) was purportedly recorded at El Azizia (approximately 40 km south-southwest of Tripoli) in what is now modern-day Libya. That temperature record of 58°C has been cited by numerous world-record sources as the highest recorded temperature for the planet. During 2010–11, a World Meteorological Organization (WMO) Commission of Climatology (CCl) special international panel of meteorological experts conducted an in-depth investigation of this record temperature for the WMO World Archive of Weather and Climate Extremes (http://wmo.asu.edu/). This committee identified five major concerns with the 1922 El Azizia temperature extreme record, specifically 1) potentially problematical instrumentation, 2) a probable new and inexperienced observer at the time of observation, 3) unrepresentative microclimate of the observation site, 4) poor correspondence of the extreme to other locations, and 5) poor comparison to subsequent temperature values recorded at the site. Based on these concerns, the WMO World Archive of Weather and Climate Extremes rejected this temperature extreme of 58°C as the highest temperature officially recorded on the planet. The WMO assessment is that the highest recorded surface temperature of 56.7°C (134°F) was measured on 10 July 1913 at Greenland Ranch (Death Valley), California.
