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

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.

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Jeremy J. Hess ◽  
Sathish LM ◽  
Kim Knowlton ◽  
Shubhayu Saha ◽  
Priya Dutta ◽  
...  

Background. Ahmedabad implemented South Asia’s first heat action plan (HAP) after a 2010 heatwave. This study evaluates the HAP’s impact on all-cause mortality in 2014–2015 relative to a 2007–2010 baseline. Methods. We analyzed daily maximum temperature (Tmax)-mortality relationships before and after HAP. We estimated rate ratios (RRs) for daily mortality using distributed lag nonlinear models and mortality incidence rates (IRs) for HAP warning days, comparing pre- and post-HAP periods, and calculated incidence rate ratios (IRRs). We estimated the number of deaths avoided after HAP implementation using pre- and post-HAP IRs. Results. The maximum pre-HAP RR was 2.34 (95%CI 1.98–2.76) at 47°C (lag 0), and the maximum post-HAP RR was 1.25 (1.02–1.53) estimated at 47°C (lag 0). Post-to-pre-HAP nonlagged mortality IRR for Tmax over 40°C was 0.95 (0.73–1.22) and 0.73 (0.29–1.81) for Tmax over 45°C. An estimated 1,190 (95%CI 162–2,218) average annualized deaths were avoided in the post-HAP period. Conclusion. Extreme heat and HAP warnings after implementation were associated with decreased summertime all-cause mortality rates, with largest declines at highest temperatures. Ahmedabad’s plan can serve as a guide for other cities attempting to increase resilience to extreme heat.


Author(s):  
Y. S. Onifade ◽  
V. B. Olaseni

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.


2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers

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.


2005 ◽  
Vol 18 (23) ◽  
pp. 5011-5023 ◽  
Author(s):  
L. A. Vincent ◽  
T. C. Peterson ◽  
V. R. Barros ◽  
M. B. Marino ◽  
M. Rusticucci ◽  
...  

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.


2021 ◽  
Author(s):  
Mastawesha Misganaw Engdaw ◽  
Andrew Ballinger ◽  
Gabriele Hegerl ◽  
Andrea Steiner

&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;


2013 ◽  
Vol 52 (10) ◽  
pp. 2363-2372 ◽  
Author(s):  
John R. Christy

AbstractThe International Surface Temperature Initiative is a worldwide effort to locate weather observations, digitize them for public access, and attach provenance to them. As part of that effort, this study sought documents of temperature observations for the nation of Uganda. Although scattered reports were found for the 1890s, consistent record keeping appears to have begun in 1900. Data were keyed in from images of several types of old forms as well as accessed electronically from several sources to extend the time series of 32 stations with at least 4 yr of data back as far as data were available. Important gaps still remain; 1979–93 has virtually no observations from any station. Because many stations were represented by more than one data source, a scheme is described to extract the “best guess” values for each station of monthly averages of the daily maximum, minimum, and mean temperature. A preliminary examination of the national time series indicates that, since the early twentieth century, it appears that Uganda experienced essentially no change in monthly-average daily maximum temperature but did experience a considerable rise in monthly-average daily minimum temperature, concentrated in the last three decades. Because there are many gaps in the data, it is hoped that readers with information on extant data that were not discovered for this study will contact the author or the project so that the data may be archived.


2009 ◽  
Vol 6 (8) ◽  
pp. 1361-1370 ◽  
Author(s):  
J. Xia ◽  
Y. Han ◽  
Z. Zhang ◽  
Z. Zhang ◽  
S. Wan

Abstract. The magnitude of daily minimum temperature increase is greater than that of daily maximum temperature increase under climate warming. This study was conducted to examine whether changes in soil respiration under diurnal warming are equal to the summed changes under day and night warming in a temperate steppe in northern China. A full factorial design with day and night warming was used in this study, including control, day (06:00 a.m.–06:00 p.m., local time) warming, night (06:00 p.m.–06:00 a.m.) warming, and diurnal warming. Day warming showed no effect on soil respiration, whereas night warming significantly increased soil respiration by 7.1% over the 3 growing seasons in 2006–2008. The insignificant effect of day warming on soil respiration could be attributable to the offset of the direct positive effects of increased temperature by the indirect negative effects via aggravating water limitation and suppressing ecosystem C assimilation. The positive effects of night warming on soil respiration were largely due to the stimulation of ecosystem C uptake and substrate supply via overcompensation of plant photosynthesis. Changes in both soil respiration (+20.7 g C m−2 y−1) and GEP (−2.8 g C m−2 y−1) under diurnal warming are smaller than their summed changes (+40.0 and +24.6 g C m−2 y−1, respectively) under day and night warming. Our findings that the effects of diurnal warming on soil respiration and gross ecosystem productivity are not equal to the summed effects of day and night warming are critical for model simulation and projection of climate-carbon feedback.


1989 ◽  
Vol 37 (3) ◽  
pp. 239 ◽  
Author(s):  
BA Myers ◽  
WC Morgan

The responses -of germination of the salt-tolerant grass Diplachne fusca (L.) Beauv. to salinity and various temperature regimes are described. At temperatures of 30/20°C (12 h light and dark periods), final germination was 70% in distilled water, decreased to 50% in 175 mol m-3 NaCl (π = - 0.8 MPa) and 7% in 380 mol m-3 NaCl (π = -1.8 MPa). Increasing salinity from 0-130mol m-3 NaCl decreased the final germination percentage, but did not modify the threshold temperatures (day or night temperature > 27°C) at which germination occurred. Presoaking in distilled water or 1% CaCl2· 2H20 solution did not significantly affect the final germination percentage of seeds which were subsequently placed in solutions with a range of salinities from 0-210 mol m-3 NaCl (*#960 = 0 to - 1.0 MPa). How- ever, addition of CaCl2 to NaCl solution increased the final germination percentage compared with that in pure NaCl solution. Presoaking in concentrated (400 mol m-3) NaCl solution caused a decrease in subsequent germinability of 20 or 40% in 0 and 40 mol m-3 NaCl, respectively. Under field conditions (in soil with mean daily maximum temperature of 33°C and mean daily minimum temperature of 15°C), rates of seedling establishment were similar (16% of seed sown) in soils irrigated with 0 or 50 mol m-3 NaCl, and were 1% in those irrigated with 100 mol m-3 NaCl. The inhibition of germination in NaCl solution was largely an osmotic effect since there was a similar reduction in the final germination percentage in iso-osmotic solutions of NaCl and mannitol. However, the proportion of seeds germinating in NaCl solution was enhanced by adding calcium. The inhibition of germination was greater in sulfate solutions compared with that in chloride solutions and, to a lesser degree, in potassium compared with sodium solutions. The practical implications of our results are discussed. The incorporation of gypsum into the soil and measures to leach salts from the topsoil are recommended before D. fusca is sown on saline land.


2016 ◽  
Vol 55 (3) ◽  
pp. 811-826 ◽  
Author(s):  
John R. Christy ◽  
Richard T. McNider

AbstractThree time series of average summer [June–August (JJA)] daily maximum temperature (TMax) are developed for three interior regions of Alabama from stations with varying periods of record and unknown inhomogeneities. The time frame is 1883–2014. Inhomogeneities for each station’s time series are determined from pairwise comparisons with no use of station metadata other than location. The time series for the three adjoining regions are constructed separately and are then combined as a whole assuming trends over 132 yr will have little spatial variation either intraregionally or interregionally for these spatial scales. Varying the parameters of the construction methodology creates 333 time series with a central trend value based on the largest group of stations of −0.07°C decade−1 with a best-guess estimate of measurement uncertainty from −0.12° to −0.02°C decade−1. This best-guess result is insignificantly different (0.01°C decade−1) from a similar regional calculation using NOAA’s divisional dataset based on daily data from the Global Historical Climatology Network (nClimDiv) beginning in 1895. Summer TMax is a better proxy, when compared with daily minimum temperature and thus daily average temperature, for the deeper tropospheric temperature (where the enhanced greenhouse signal is maximized) as a result of afternoon convective mixing. Thus, TMax more closely represents a critical climate parameter: atmospheric heat content. Comparison between JJA TMax and deep tropospheric temperature anomalies indicates modest agreement (r2 = 0.51) for interior Alabama while agreement for the conterminous United States as given by TMax from the nClimDiv dataset is much better (r2 = 0.86). Seventy-seven CMIP5 climate model runs are examined for Alabama and indicate no skill at replicating long-term temperature and precipitation changes since 1895.


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