scholarly journals Diurnal temperature cycle deduced from extreme daily temperatures and impact over a surface reanalysis system

2015 ◽  
Vol 12 (1) ◽  
pp. 137-140 ◽  
Author(s):  
F. Besson ◽  
E. Bazile ◽  
C. Soci ◽  
J.-M. Soubeyroux ◽  
G. Ouzeau ◽  
...  
Keyword(s):  
Daily Temperature ◽  
Temperature Cycle ◽  
Extreme Temperatures ◽  
Temperature Analysis ◽  
Diurnal Temperature ◽  
Hourly Temperature ◽  
Observation Network ◽  
Temperature Observations ◽  
Analysis System ◽  
Extreme Daily Temperature

Abstract. Due to the evolution of the observation network, hourly 2 m temperature analysis performed by reanalysis systems shows temporal inhomogeneities. The observation network gap is less present for extreme daily temperature observations. In order to reduce inhomogeneities and enable a climatological use of temperature analysis, information from extreme temperatures could be useful. In this study, the diurnal temperature cycle has been reconstructed for stations which only record extreme temperatures. These new "pseudo" hourly temperature observations are then provided to the analysis system. Two methods have been used to deduce hourly temperatures from extremes and compared to real observations. The results have shown that using those new pseudo-observations as an input for two different reanalysis systems enables reducing the bias in temperature analysis.

scholarly journals What’s the temperature in tropical caves?

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0237051
Author(s):  
Luis Mejía-Ortíz ◽  
Mary C. Christman ◽  
Tanja Pipan ◽  
David C. Culver
Keyword(s):  
Rainy Season ◽  
Temporal Pattern ◽  
Temperature Variability ◽  
Daily Temperature ◽  
The Other ◽  
Quintana Roo ◽  
Temperature Cycle ◽  
Hourly Temperature ◽  
Surface Variation ◽  
One Year

Hourly temperature was measured for approximately one year at 17 stations in three caves in Quintana Roo, Mexico. Thirteen of these stations were in the extensive twilight zones of all three caves. All seventeen stations showed seasonality in temperature with a 3°C drop during the Nortes season. Two of the caves, Muévelo Sabrosito and Muévelo Rico, showed greater variability during the winter months while in Río Secreto (Tuch) variability was greatest during the rainy season. Río Secreto is less open to the surface than the other two. All sites also showed a daily temperature cycle, although it was very faint in some Río Secreto (Tuch) sites. While temperature variability is diminished relative to surface variation, its temporal pattern is worthy of further study.

scholarly journals What’s the Temperature in Tropical Caves?

2020 ◽  
Author(s):  
Luis Mejía-Ortíz ◽  
Mary C Christman ◽  
Tanja Pipan ◽  
David C Culver
Keyword(s):  
Rainy Season ◽  
Temporal Pattern ◽  
Temperature Variability ◽  
Daily Temperature ◽  
The Other ◽  
Quintana Roo ◽  
Temperature Cycle ◽  
Hourly Temperature ◽  
Surface Variation ◽  
One Year

AbstractHourly temperature was measured for approximately one year at 17 stations in three caves in Quintana Roo, Mexico. Thirteen of these stations were in the extensive twilight zones of all three caves. All seventeen stations showed seasonality in temperature with a 3 °C drop during the Nortes season. Two of the caves, Muévelo Sabrosito and Muévelo Rico, showed greater variability during the winter months while in Rio Secreto variability was greatest during the rainy season. Río Secreto is less open to the surface than the other two. All sites also showed a daily temperature cycle, although it was very faint in some Rio Secreto sites. While temperature variability is diminished relative to surface variation, its temporal pattern is worthy of further study.

scholarly journals Diurnal water temperature dynamics in lowland rivers: A case study from Central Poland

2018 ◽  
Vol 36 (1) ◽  
pp. 89-97 ◽  
Author(s):  
Maksym A. Łaszewski
Keyword(s):  
Water Temperature ◽  
Seasonal Pattern ◽  
Measurement Data ◽  
Daily Temperature ◽  
Extreme Temperatures ◽  
Lowland Rivers ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Temperature Dynamics ◽  
Maximum Water Temperature

AbstractThe paper examines spatial and seasonal variations in diurnal water temperature dynamics in lowland rivers. Temperature data was obtained from digital temperature loggers located in nine sites across the Mazovian Lowland during the hydrological year 2016. On the basis of measurement data, mean, maximum, and minimum daily ranges were calculated in the monthly timescale, as well as the timing of extreme temperatures during the day. The results indicate that water temperature dynamics of lowland rivers have a clear seasonal pattern, with the highest variations of temperature in May and June and the lowest in January. Statistically significant differences were found in the daily temperature range between groups of the investigated sites; a higher diurnal temperature range was observed in sites draining a smaller catchment area, while larger rivers were generally more thermally stable in the daily timescale. There was also found an effect of anthropopressure on diurnal temperature dynamics in urbanized catchments, mainly due to impoundments and sewage inflows. Maximum water temperature in the studied sites usually occurred in the morning, from 06:00 to 10:00 CEST, while minimum temperature occurred in the late afternoon, from 14:00 to 18:00 CEST. Spatially, the timing of the maximum and minimum water temperatures during the day was similar in all of the investigated sites, with no statistically significant differences. However, cluster analysis indicated that in the summer half of the year the timing of the extreme temperatures was more varied between investigated sites. The results provide new insight into short-term river thermal behaviour and they are valuable in the context of game fisheries due to the significance of daily temperature variations in fish activity and feeding.

scholarly journals Estimation of seasonal boundaries using temperature data: a case of northwest part of Bangladesh

2020 ◽  
Vol 6 (1) ◽  
pp. 50-62
Author(s):  
Syed Mustafizur Rahman ◽  
Syed Mahbubur Rahman ◽  
Md. Shuzon Ali ◽  
Md. Abdullah Al Mamun ◽  
Md. Nezam Uddin
Keyword(s):  
Spectral Analysis ◽  
Crop Productivity ◽  
Temperature Data ◽  
Daily Temperature ◽  
Temperature Cycle ◽  
Local Climate ◽  
Higher Power ◽  
Cycle Plays ◽  
Maximum Temperatures ◽  
Harmonic Analyses

Abstract Seasons are the divisions of the year into months or days according to the changes in weather, ecology and the intensity of sunlight in a given region. The temperature cycle plays a major role in defining the meteorological seasons of the year. This study aims at investigating seasonal boundaries applying harmonic analysis in daily temperature for the duration of 30 years, recorded at six stations from 1988 to 2017, in northwest part of Bangladesh. Year by year harmonic analyses of daily temperature data in each station have been carried out to observe temporal and spatial variations in seasonal lengths. Periodic nature of daily temperature has been investigated employing spectral analysis, and it has been found that the estimated periodicities have higher power densities of the frequencies at 0.0027 and 0.0053 cycles/day. Some other minor periodic natures have also been observed in the analyses. Using the frequencies between 0.0027 to 0.0278 cycles/day, the observed periodicities in spectral analysis, harmonic analyses of minimum and maximum temperatures have found four seasonal boundaries every year in each of the stations. The estimated seasonal boundaries for the region fall between 19-25 February, 19-23 May, 18-20 August and 17-22 November. Since seasonal variability results in imbalance in water, moisture and heat, it has the potential to significantly affect agricultural production. Hence, the seasons and seasonal lengths presented in this research may help the concerned authorities take measures to reduce the risks for crop productivity to face the challenges arise from changing climate. Moreover, the results obtained are likely to contribute in introducing local climate calendar.

scholarly journals Body Temperatures in Some Australian Mammals II.Peramelidae

1962 ◽  
Vol 15 (2) ◽  
pp. 386 ◽  
Author(s):  
PR Morrison
Keyword(s):  
Body Temperature ◽  
Ambient Temperature ◽  
Active Phase ◽  
Temperature Measurements ◽  
Temperature Cycle ◽  
Body Temperatures ◽  
Ambient Temperatures ◽  
Diurnal Temperature

Body temperature measurements on the short-nosed bandicoot (Thylacis obeaulus) have shown a nocturnal cycle with a range of 1� 2�C and a short active phase at 2200-0400 hr. The bilby or rabbit bandicoot (Macrotis lagoti8) had a sharply defined temperature cycle, with a range of almost 3�C after several months of captivity, during which the day-time resting temperature was progressively lowered from 36� 4 to 34� 2�C. Forced activity raised the diurnal temperature substantially but not to the nocturnal level. Forced activity did not raise the nocturnal level which was similar in the two species (37' O�C). Both species could regulate effectively at an ambient temperature of 5�C, but only Thylaci8 showed regulation at ambient temperatures of between 30 and 40�C.

A Comparison of Daily Temperature-Averaging Methods: Spatial Variability and Recent Change for the CONUS

2018 ◽  
Vol 31 (3) ◽  
pp. 979-996 ◽  
Author(s):  
Jase Bernhardt ◽  
Andrew M. Carleton ◽  
Chris LaMagna
Keyword(s):  
Spatial Variability ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Underlying Assumption ◽  
First Order ◽  
Daily Average ◽  
Hourly Temperature ◽  
Significant Difference ◽  
Weather Stations

Abstract Traditionally, the daily average air temperature at a weather station is computed by taking the mean of two values, the maximum temperature (Tmax) and the minimum temperature (Tmin), over a 24-h period. These values form the basis for numerous studies of long-term climatologies (e.g., 30-yr normals) and recent temperature trends and changes. However, many first-order weather stations—such as those at airports—also record hourly temperature data. Using an average of the 24 hourly temperature readings to compute daily average temperature has been shown to provide a more precise and representative estimate of a given day’s temperature. This study assesses the spatial variability of the differences in these two methods of daily temperature averaging [i.e., (Tmax + Tmin)/2; average of 24 hourly temperature values] for 215 first-order weather stations across the conterminous United States (CONUS) over the 30-yr period 1981–2010. A statistically significant difference is shown between the two methods, as well as consistent overestimation of temperature by the traditional method [(Tmax + Tmin)/2], particularly in southern and coastal portions of the CONUS. The explanation for the long-term difference between the two methods is the underlying assumption for the twice-daily method that the diurnal curve of temperature is symmetrical. Moreover, this paper demonstrates a spatially coherent pattern in the difference compared to the most recent part of the temperature record (2001–15). The spatial and temporal differences shown have implications for assessments of the physical factors influencing the diurnal temperature curve, as well as the exact magnitude of contemporary climate change.

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