scholarly journals Analysis of the Mean of Daily Maximum Temperature within the Romanian Plain (1961-2015)

2017 ◽  
Vol XVI (1) ◽  
pp. 37-48
Author(s):  
Alina Vlăduţ
Keyword(s):  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
The Mean

scholarly journals Monitoring observed changes in warm-days extremes over Turkey

2018 ◽  
Vol 1 (4) ◽  
Author(s):  
Mohsen Abbasnia 1 ◽  
Hüseyin Toros2
Keyword(s):  
High Elevation ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Annual Number ◽  
Daily Maximum ◽  
Atmospheric Humidity ◽  
Eastern Area ◽  
Increased Risk ◽  
The Mean ◽  
Temperature Time

This study aimed to analyze warm-days changes extracted from daily maximum temperature time-series of 71 stations in Turkey during 1961–2016. First, the trend analysis of warm-days events indicated that the annual count of warm-days occurrences has been significance rising by a rate of 1.4 days per decade over more than 90 percent of the studied stations. Thus, there are consistent patterns in daily warming throughout the study area. The spatial maps showed that the lowest frequency in the minimum annual number of warm-days occurred in western areas by a total number of 21 days and its highest occurred in the eastern area by a total number of 35 days. Moreover, the highest frequency in the mean and minimum annual count of warm-days observed in the northwestern lowlands and their frequency has decreased toward the eastern mountainous. Also, the highest range of differences between the annual count of maximum and minimum values has happened in the eastern regions which are characterized by high elevation and the lower existence of atmospheric humidity. Therefore, a higher moisture content of the atmosphere in lowland coastal stations favors severe warm-days and the increased risk of human health.

Summer Temperature and All-cause Mortality from 2006 to 2015 for Smart City Jaipur, India

2021 ◽  
pp. 097206342110116
Author(s):  
Suresh K. Rathi ◽  
P. R. Sodani ◽  
Suresh Joshi
Keyword(s):  
Relative Humidity ◽  
Urban Population ◽  
Extreme Heat ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Mean Temperature ◽  
All Cause Mortality ◽  
The Mean

A considerable association between temperature and all-cause mortality has been documented in various studies. Further insights can be obtained from studying the impact of temperature and heat index (HI) for Jaipur city’s all-cause mortality. The objective of this work was to assess the association between the extreme heat (daily maximum temperature, daily minimum temperature, daily mean temperature, relative humidity and HI) and all-cause mortality for summer months (March to June) from 2006 to 2015 for urban population of Jaipur. For summer months, we collected the data on various temperature and all-cause mortality parameters for at least 10 years. The student’s t-test and ANOVA were used to analyse variations in mean temperature, maximum temperature and HI. The Pearson correlation coefficient was used to study the relationship between ambient heat and lag time effect all-cause mortality. A total of 75,571 deaths (all-cause mortality) for 1,203 summer days (2006–2015) were analysed in relation to temperature and relative humidity. The mean daily all-cause mortality has been estimated at 62.8 ± 15.2 for the study period. There is a significant increase of 39% per day all-cause mortality at the maximum temperature of 45 °C and above. However only 10% rise per day all-cause mortality for extreme danger days (HI > 54 °C). The mean daily all-cause mortality shows a significant association with daily maximum temperature ( F = 34.6, P < .0001) and HI (discomfort index) from caution to extreme danger risk days ( F = 5.0, P < .0019). The lag effect of extreme heat on all-cause mortality for the study period (2006 to 2015) was at a peak period on the same day of the maximum temperature ( r = 0.245 at P < .01) but continues up to four days. The study concludes that the effect of ambient heat on all-cause mortality increase is clearly evident (rise of 39% deaths/day). Accordingly, focus should be put on developing adaptation measures against ambient heat. This analysis may satisfy policy makers’ needs. Extreme heat-related mortality needs further study to reduce adverse effects on health among Jaipur’s urban population.

Effects of Weather Conditions in Summer on the Maintenance Behavior of Western Grey Kangaroos, Macropus-Fuliginosus

1988 ◽  
Vol 15 (2) ◽  
pp. 129 ◽  
Author(s):  
GW Arnold ◽  
E Lecrivain ◽  
KG Johnson ◽  
A Grassia
Keyword(s):  
Environmental Conditions ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Ambient Temperatures ◽  
Cyclic Patterns ◽  
The Mean ◽  
Maintenance Behavior ◽  
Radiant Temperature

The behaviour of seven western grey kangaroos was observed, in a 0.2 ha paddock of annual pasture over nine days on which the daily maximum temperature ranged from 22�C to 42�C. Grazing, standing and lying activities and use of shade were recorded. Regression and fourier analyses were used to relate behavioural measurements to environmental conditions. Cyclic patterns of grazing and lying closely followed those of ambient and radiant temperatures. When maximum radiant and ambient temperatures were higher, grazing began later in the evening and ceased earlier in the morning. Grazing time decreased as daytime radiation and relative humidity rose. With increasing heat load, animals lay down more during the day; the radiant temperature in the sun between 0600 and 0900 h determined when they first lay down while radiant temperature in the shade determined when animals moved to shade. Environmental conditions did not greatly influence the time spent standing, but animals stood for more of their resting time with increased daytime humidity. Individuals differed in the mean times spent on major activities, but not in the timing of these activities or the use of shade.

scholarly journals Determining Temperature Extreme in Warri City, Niger-Delta Region, Nigeria

2019 ◽  
pp. 160-166
Author(s):  
Y. S. Onifade ◽  
V. B. Olaseni
Keyword(s):  
Least Square ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extreme ◽  
Monthly Temperature ◽  
Niger Delta Region ◽  
The Hours ◽  
The Mean

Climate change and global warming which is also known as a change in Earth’s overall climate or rising temperature have taken centre stage in international concerns, several fora and treaties have been observed with a view of stemming trend, in rising temperatures. This study evaluated ten years of maximum and minimum annual temperature of Warri  in Nigeria between (2005 and 2015) to determine trends and identified extreme fluctuation in temperature. Data used for this study were sourced from the Nigerian Meteorological Agency’s Zonal Office, Warri. An objective method for determining temperature extreme has been used. Least square linear regression equation has been used to estimate temperature that would be equalled or surpassed 1%, 5% and 10% of the hours at any given location during the warmest and coldest months of the year. These equations are based on an index calculated from the three readily available parameters; the mean monthly temperature, the mean daily maximum temperature for the month and the mean daily minimum temperature for the month. The warmest month in Warri was March with a mean monthly temperature of 33.9 while the coldest month was July with mean monthly of 25.8.

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

scholarly journals Observed Trends in Indices of Daily Temperature Extremes in South America 1960–2000

2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Extremes ◽  
Daily Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Increasing Trends

Abstract A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America.

Assessing the contribution of multiple forcings to changes in temperature extremes 1981–2020 using CMIP6 climate models

2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Climate Models ◽  
Temporal Trends ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Cold Temperatures

&lt;p&gt;In this study, we aim at quantifying the contribution of different forcings to changes in temperature extremes over 1981&amp;#8211;2020 using CMIP6 climate model simulations. We first assess the changes in extreme hot and cold temperatures defined as days below 10% and above 90% of daily minimum temperature (TN10 and TN90) and daily maximum temperature (TX10 and TX90). We compute the change in percentage of extreme days per season for October-March (ONDJFM) and April-September (AMJJAS). Spatial and temporal trends are quantified using multi-model mean of all-forcings simulations. The same indices will be computed from aerosols-, greenhouse gases- and natural-only forcing simulations. The trends estimated from all-forcings simulations are then attributed to different forcings (aerosols-, greenhouse gases-, and natural-only) by considering uncertainties not only in amplitude but also in response patterns of climate models. The new statistical approach to climate change detection and attribution method by Ribes et al. (2017) is used to quantify the contribution of human-induced climate change. Preliminary results of the attribution analysis show that anthropogenic climate change has the largest contribution to the changes in temperature extremes in different regions of the world.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; climate change, temperature, extreme events, attribution, CMIP6&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Acknowledgement:&lt;/strong&gt; This work was funded by the Austrian Science Fund (FWF) under Research Grant W1256 (Doctoral Programme Climate Change: Uncertainties, Thresholds and Coping Strategies)&lt;/p&gt;

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