scholarly journals Trends in Winter Warm Spells in the Central England Temperature Record

2020 ◽  
Vol 59 (6) ◽  
pp. 1069-1076
Author(s):  
S. C. Chapman ◽  
E. J. Murphy ◽  
D. A. Stainforth ◽  
N. W. Watkins
Keyword(s):  
Environmental Variability ◽  
Daily Maximum ◽  
Temperature Record ◽  
Ecological Processes ◽  
Threefold Increase ◽  
Central England Temperature ◽  
Maximum Temperatures ◽  
Crossing Theory ◽  
Warm Spell ◽  
Temperature Time

AbstractAn important impact of climate change on agriculture and the sustainability of ecosystems is the increase of extended warm spells during winter. We apply crossing theory to the central England temperature time series of winter daily maximum temperatures to quantify how increased occurrence of higher temperatures translates into more frequent, longer-lasting, and more intense winter warm spells. We find since the late 1800s an overall two- to threefold increase in the frequency and duration of winter warm spells. A winter warm spell of 5 days in duration with daytime maxima above 13°C has a return period that was often over 5 years but now is consistently below 4 years. Weeklong warm intervals that return on average every 5 years now consistently exceed ~13°C. The observed changes in the temporal pattern of environmental variability will affect the phenology of ecological processes and the structure and functioning of ecosystems.

Oxford’s urban growth and its potential impact on the local climate

2019 ◽  
pp. 28-37
Author(s):  
Stephen Burt ◽  
Tim Burt
Keyword(s):  
Urban Heat Island ◽  
Urban Growth ◽  
Rural Site ◽  
Temperature Record ◽  
Heat Island ◽  
Local Climate ◽  
Island Effect ◽  
Central England Temperature ◽  
Urban Heat ◽  
Period Data

This chapter deals with the growth of Oxford since 1767 and assessment of the potential influence of the expanding urban area on the temperature record from the Radcliffe Observatory, using long-period data from a semi-rural site at Rothamsted (Hertfordshire) and a more recent 3-year comparison with records from nearby Wallingford to assess the extent of, and changes in, Oxford’s urban heat island. The urban heat island effect remains small but is shown to have increased in magnitude in recent decades, and is likely to affect the homogeneity of the Oxford temperature record. In addition, the chapter provides a comparison of the data from the Radcliffe Observatory with that from the Central England Temperature series.

scholarly journals Reply to “Comment on ‘The Impact of Recent Forcing and Ocean Heat Uptake Data on Estimates of Climate Sensitivity’”

2020 ◽  
Vol 33 (1) ◽  
pp. 397-404 ◽  
Author(s):  
Nicholas Lewis ◽  
Judith Curry
Keyword(s):  
Time Windows ◽  
Internal Variability ◽  
Historical Record ◽  
Cmip5 Models ◽  
Temperature Record ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Total Uncertainty ◽  
The Impact ◽  
The Relationship

AbstractCowtan and Jacobs assert that the method used by Lewis and Curry in 2018 (LC18) to estimate the climate system’s transient climate response (TCR) from changes between two time windows is less robust—in particular against sea surface temperature bias correction uncertainty—than a method that uses the entire historical record. We demonstrate that TCR estimated using all data from the temperature record is closely in line with that estimated using the LC18 windows, as is the median TCR estimate using all pairs of individual years. We also show that the median TCR estimate from all pairs of decade-plus-length windows is closely in line with that estimated using the LC18 windows and that incorporating window selection uncertainty would make little difference to total uncertainty in TCR estimation. We find that, when differences in the evolution of forcing are accounted for, the relationship over time between warming in CMIP5 models and observations is consistent with the relationship between CMIP5 TCR and LC18’s TCR estimate but fluctuates as a result of multidecadal internal variability and volcanism. We also show that various other matters raised by Cowtan and Jacobs have negligible implications for TCR estimation in LC18.

scholarly journals Thermolabile drug storage in an ambulatory setting

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fernando do Pazo-Oubiña ◽  
Bartomeu Alorda-Ladaria ◽  
Ana Gomez-Lobon ◽  
Bàrbara Boyeras-Vallespir ◽  
María Margalida Santandreu-Estelrich ◽  
...  
Keyword(s):  
Tertiary Care ◽  
Statistical Treatment ◽  
Storage Conditions ◽  
Ambulatory Setting ◽  
Temperature Record ◽  
Care Hospital ◽  
Data Logger ◽  
Data Loggers ◽  
Ambulatory Patients ◽  
Clinical Consequences

AbstractMore thermolabile drugs are becoming available, and in most cases, these medications are dispensed to ambulatory patients. However, there is no regulation once medications are dispensed to patients and little is known with regard to what happens during transport and home storage. Previous studies suggest that these drugs are improperly stored. The present study was designed to determine the storage conditions of thermolabile drugs once they are dispensed to the patient in the Hospital Pharmacy Department. This is a prospective observational study to assess the temperature profile of 7 thermolabile drugs once they are dispensed to ambulatory patients at a tertiary care hospital. A data logger was added to the medication packaging. Temperature was considered inappropriate if one of the following circumstances were met: any temperature record less than or equal to 0 °C or over 25 °C; temperatures between 0–2 or 8–25 °C for a continuous period over 30 min. The time series of temperature measurements obtained from each data logger were analyzed as statistically independent variables. The data shown did not undergo any statistical treatment and must be considered directly related to thermal measurements. One hundred and fourteen patients were included and 107 patients were available for the analysis. On the whole, a mean of 50.6 days (SD 18.3) were measured and the mean temperature was 6.88 °C (SD 2.93). Three data loggers (2.8%) maintained all the measurements between 2 and 8 °C with less than 3 continuous data (< 30 min) out of this range but no data over 25 °C or below or equal to 0 °C. 28 (26.2%) data loggers had at least one measurement below zero, 1 data logger had a measurement greater than 25 °C and 75 (70.1%) were between 0 and 2 °C and/or between 8 and 25 °C for more than 30 min. In conclusion, once dispensed to patients, most thermolabile drugs are improperly stored. Future studies should focus on clinical consequences and possible solutions.

scholarly journals How to correctly apply Gaussian statistics in a non-stationary climate?

2021 ◽  
Author(s):  
Reinhold Steinacker
Keyword(s):  
Time Series ◽  
Actual Data ◽  
Temperature Record ◽  
Positive Trend ◽  
Positive Temperature ◽  
Climatic Trend ◽  
Filter Methods ◽  
Periodic Time Series ◽  
Past Data

AbstractTime series with a significant trend, as is now being the case for the temperature in the course of climate change, need a careful approach for statistical evaluations. Climatological means and moments are usually taken from past data which means that the statistics does not fit to actual data anymore. Therefore, we need to determine the long-term trend before comparing actual data with the actual climate. This is not an easy task, because the determination of the signal—a climatic trend—is influenced by the random scatter of observed data. Different filter methods are tested upon their quality to obtain realistic smoothed trends of observed time series. A new method is proposed, which is based on a variational principle. It outperforms other conventional methods of smoothing, especially if periodic time series are processed. This new methodology is used to test, how extreme the temperature of 2018 in Vienna actually was. It is shown that the new annual temperature record of 2018 is not too extreme, if we consider the positive trend of the last decades. Also, the daily mean temperatures of 2018 are not found to be really extreme according to the present climate. The real extreme of the temperature record of Vienna—and many other places around the world—is the strongly increased positive temperature trend over the last years.

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