scholarly journals Excess semiannual variation in historical temperature records

Author(s):  
Yunxiang Song ◽  
Kyle B. Lawlor ◽  
Thomas A. Witten
Author(s):  
Varvara Mironova ◽  
Natalia Shartova ◽  
Andrei Beljaev ◽  
Mikhail Varentsov ◽  
Mikhail Grishchenko

The article presents the results of a spatio-temporal analysis of the changes of the favorability of climatic conditions for the transmission of vivax malaria in the Moscow megacity and its surroundings during the period from 1977 to 2016. Using the historical temperature records at urban and rural weather stations, we calculated the key indicators of climate favorability for malaria transmission, viz. the sum of effective temperatures, the duration of the season of effective infectiveness, and a new integral index of climate favorability. We demonstrated a dramatic increase of all three indicators, which accelerated after 1984, and a high spatial heterogeneity among them. Due to the urban heat island effect, the degree of climatic favorability is especially high in the densely urbanized areas of Moscow megacity compared with the suburban and rural areas. Climatic conditions for vivax malaria in Moscow are better now than before. The season of effective infectiveness continues in the central part of the city for 25 days longer, and the integral index of climate favorability is 85% higher in comparison to mean values over the rural surroundings. The study contains an alert regarding the risk of malaria resurgence in the Moscow region in the case of the sufficient importation of cases from abroad.


eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Susan Duncan ◽  
Svante Holm ◽  
Julia Questa ◽  
Judith Irwin ◽  
Alastair Grant ◽  
...  

The requirement for vernalization, a need for prolonged cold to trigger flowering, aligns reproductive development with favorable spring conditions. In Arabidopsis thaliana vernalization depends on the cold-induced epigenetic silencing of the floral repressor locus FLC. Extensive natural variation in vernalization response is associated with A. thaliana accessions collected from different geographical regions. Here, we analyse natural variation for vernalization temperature requirement in accessions, including those from the northern limit of the A. thaliana range. Vernalization required temperatures above 0°C and was still relatively effective at 14°C in all the accessions. The different accessions had characteristic vernalization temperature profiles. One Northern Swedish accession showed maximum vernalization at 8°C, both at the level of flowering time and FLC chromatin silencing. Historical temperature records predicted all accessions would vernalize in autumn in N. Sweden, a prediction we validated in field transplantation experiments. The vernalization response of the different accessions was monitored over three intervals in the field and found to match that when the average field temperature was given as a constant condition. The vernalization temperature range of 0–14°C meant all accessions fully vernalized before snowfall in N. Sweden. These findings have important implications for understanding the molecular basis of adaptation and for predicting the consequences of climate change on flowering time.


Author(s):  
Patrick T. Brown

Global average surface air temperature can change when it is either ‘forced’ to change by factors such as increasing greenhouse gasses, or it can change on its own through ‘unforced’ natural cycles like El-Niño/La-Niña. In this paper we estimated the magnitude of unforced temperature variability using historical datasets rather than the more commonly used computer climate models. We used data recorded by thermometers back to the year 1880 as well as data from “nature’s thermometers” – things like tree rings, corals, and lake sediments – that give us clues of how temperature varied naturally from the year 1000 to 1850. We found that unforced natural temperature variability is large enough to have been responsible for the decade-to-decade changes in the rate of global warming seen over the 20th century. However, the total warming over the 20th century cannot be explained by unforced variability alone and it would not have been possible without the human-caused increase in greenhouse gasses. We also found that unforced temperature variability may be the driver behind the reduced rate of global warming experienced at the beginning of the 21st century.


2014 ◽  
Vol 27 (4) ◽  
pp. 1742-1750 ◽  
Author(s):  
Naiming Yuan ◽  
Zuntao Fu

Abstract Large-scale variability in long historical temperature records around the North Atlantic Ocean is analyzed by means of power spectral density (PSD) analysis and detrended fluctuation analysis (DFA). It is found that the intensity of large-scale variability is changeable with time, and long memory analysis can be used to detect this possible intensity variation quantitatively. By estimating long-term memory (LTM) in subrecords of different time intervals, a century-scale variation of LTM is revealed, which further indicates a century-scale intensity modulation of the large-scale temperature variability. At the beginning of the nineteenth and twentieth centuries, the large-scale variability is more apparent, whereas in the second half of the nineteenth and twentieth centuries the large-scale variability becomes less significant. Considering the importance of large-scale variability, the findings herein suggest a new perspective on the understanding of climatic change.


2021 ◽  
pp. 002029402110130
Author(s):  
Xian Wang ◽  
Qian-cheng Zhao ◽  
Xue-bing Yang ◽  
Bing Zeng

The historical temperature data logged in the supervisory control and data acquisition (SCADA) system contains a wealth of information that can assist with the performance optimization of wind turbines (WTs). However, mining and using these long-term data is difficult and time-consuming due to their complexity, volume, etc. In this study, we tracked and analyzed the 5-year trends of major SCADA temperature rise variables in relation to the active power of four WTs in a real wind farm. To uncover useful information, an extended version of the bins method, which calculates the standard deviation (SD) as well as the average, is proposed and adopted. The implications of the analysis for engineering practice are discussed from multiple perspectives. The research results demonstrate a change in the patterns of the main temperature rise variables in a real wind farm, completeness of the monitoring of the WT internal temperature state, influence of wind turbine aging on temperature signals, a correlation between different measurement points, and a correlation between signals from different years. The knowledge gained from this research provides a reference for the development of more practical and comprehensive condition monitoring systems and methods, as well as better operation maintenance strategies.


2012 ◽  
Vol 27 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Erin L. McClymont ◽  
Raja S. Ganeshram ◽  
Laetitia E. Pichevin ◽  
Helen M. Talbot ◽  
Bart E. van Dongen ◽  
...  

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