scholarly journals A Significant Population Signal in Iranian Temperature Records

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Shouraseni Sen Roy ◽  
Mohammad Sadegh Keikhosravi Kiany ◽  
Robert C. Balling
Keyword(s):  
Population Growth ◽  
Minimum Temperature ◽  
Winter Season ◽  
Population Data ◽  
Daily Maximum ◽  
Temperature Trends ◽  
The World ◽  
Temperature Signal ◽  
Temperature Records ◽  
Maximum Temperatures

We assembled daily maximum and minimum temperature records for 31 stations throughout Iran over the period 1961–2010. As with many other areas of the world, we found that both the maximum and minimum temperatures were increasing overall with the minimum temperatures increasing twice as fast as the maximum temperatures. We gathered population data for the stations near the beginning and end of the temperature records and found in all seasons and for both the maximum and minimum temperatures the magnitude of population growth positively influenced the temperature trends. However, unlike so many other studies, we found the strongest population growth signal in the winter for the maximum temperatures. We found evidence that this winter-season population-temperature signal is related snow cover. Our results illustrate that any number of processes are involved in explaining trends in historical maximum and minimum temperature records.

scholarly journals Methodology and Results of Calculating Central California Surface Temperature Trends: Evidence of Human-Induced Climate Change?

2006 ◽  
Vol 19 (4) ◽  
pp. 548-563 ◽  
Author(s):  
John R. Christy ◽  
William B. Norris ◽  
Kelly Redmond ◽  
Kevin P. Gallo
Keyword(s):  
Time Series ◽  
Sierra Nevada ◽  
Statistical Tests ◽  
Irrigated Agriculture ◽  
Daily Maximum ◽  
Central California ◽  
Temperature Trends ◽  
Significant Rate ◽  
Altered Surface ◽  
Temperature Records

Abstract A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this “homogeneous segments” of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910–2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25°C decade−1). The Valley trend of annual mean temperatures is +0.07° ± 0.07°C decade−1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable −0.02° ± 0.10°C decade−1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4°C decade−1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain.

Extreme temperatures analysis: A study for Campinas, Brazil

2021 ◽  
Author(s):  
Guilherme Correia ◽  
Ana Maria Ávila
Keyword(s):  
Minimum Temperature ◽  
Temperature Increase ◽  
Heat Waves ◽  
Vulnerable Groups ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
P Value ◽  
Significance Level ◽  
Historical Series ◽  
Maximum Temperatures

<p>Extreme events such as heat waves have adverse effects on human health, especially on vulnerable groups, which can lead to deaths, thus they must be faced as a huge threat. Many studies show general mean temperature increase, notably, minimum temperatures. The scope of this work was to assess daily data of a historical series (1890-2018) available on the Instituto Agronômico de Campinas (IAC), in Campinas, using a suite of indices derived from daily temperature and formulated by the Expert Team on Climate Change Detection and Indices (ETCCDI) and evaluate trends. To compute the extreme indices RClimDex 1.1 was used. The significance test is based on a t  test, with a significance level of 95% (p-value<0,05). Temperature increase is undoubtedly through many indices, especially from 1980, as there is a continuous rise of the temperature. Annual mean maximum temperature rose from 26°C to 29°C, whereas many years consistently have more than 50 days with maximum temperatures as high as 31°C and more than 20% of the days within a year are beyond the 90th percentile of the daily maximum temperatures. Annual mean minimum temperature rose from 14°C to 18°C, whereas many years consistently have more than 150 days with minimum temperatures as high as 18°C and more than 30% of the days within a year are beyond the 90th percentile of the daily minimum temperatures. Therefore, results indicate the increase of minimum temperature is greater than the increase of maximum temperatures.</p>

scholarly journals Spatiotemporal Lake Skin Summer Temperature Trends in the Northeast United States

2016 ◽  
Vol 20 (25) ◽  
pp. 1-21 ◽  
Author(s):  
Nathan Torbick ◽  
Beth Ziniti ◽  
Shuang Wu ◽  
Ernst Linder
Keyword(s):  
New England ◽  
Skin Temperature ◽  
Geographic Region ◽  
Daily Maximum ◽  
Large Area ◽  
Spatiotemporal Trends ◽  
Temperature Trends ◽  
Lake Temperature ◽  
Temperature Records ◽  
Minimum Daily Temperature

Abstract Lakes have been suggested as an indicator of climate change; however, long-term, systematic records of lake temperature are limited. Satellite remote sensing is capable of supporting lake temperature mapping with the advantage of large-area and systematic observations. The goal of this research application was to assess spatiotemporal trends in lake skin temperature for all lakes over 8 ha across northern New England for the past three decades. Nearly 10 000 Landsat scenes for July, August, and September from 1984 to 2014 were processed using MODTRAN and MERRA parameterizations to generate atmospherically corrected lake skin temperature records. Results show, on average, lakes warmed at a rate of 0.8°C decade−1, with smaller lakes warming at a faster rate. Complementing regression and space–time analyses showed similar results (R2 = 0.63) for lake temperature trends and found lakes, on average, are warming faster than daily maximum or minimum air temperature. No major hot spots were found as lake temperature changes were heterogeneous on a local scale and evenly distributed across the region. Maximum and minimum daily temperature, lake size, and elevation were found as significant drivers of lake temperature. This effort provides the first regionally focused and comprehensive spatiotemporal assessment of thousands (n = 3955) of lakes concentrated in one geographic region. The approach is scalable and adaptable to any region for assessing lake temperature trends and potential drivers.

A Method to Estimate Missing Daily Maximum and Minimum Temperature Observations

1995 ◽  
Vol 34 (2) ◽  
pp. 371-380 ◽  
Author(s):  
Arthur T. DeGaetano ◽  
Keith L. Eggleston ◽  
Warren W. Knapp
Keyword(s):  
United States ◽  
Minimum Temperature ◽  
Geographic Location ◽  
Observation Time ◽  
Daily Temperature ◽  
Daily Maximum ◽  
Northeastern United States ◽  
Maximum Temperatures ◽  
Observation Times ◽  
Station Density

Abstract A method to estimate missing daily maximum and minimum temperatures is presented. Temperature estimates are based on departures from daily temperature normals at the three closest stations with similar observation times. Although applied to Cooperative Observer Network stations in the northeastern United States, the approach can be used with any network of stations possessing an adequate station density and period of record. Generally, 75% of the estimates for both daily maximum and minimum temperature are within 1.7°C of the observed value. Median absolute differences between estimated and observed minimum temperatures, however, tend to be greater than those associated with maximum temperatures. For minimum temperatures, median absolute differences are approximately 1.0°C, whereas for maximum temperatures these differences are near 0.5°C. The accuracy of the estimates is independent of observation time, geographic location, and observed temperature but is influenced somewhat by station density.

Daily maximum and minimum temperature trends in a climate model

2002 ◽  
Vol 29 (9) ◽  
pp. 70-1-70-4 ◽  
Author(s):  
Dáithí A. Stone ◽  
Andrew J. Weaver
Keyword(s):  
Minimum Temperature ◽  
Climate Model ◽  
Daily Maximum ◽  
Temperature Trends

Population Growth: Evidence and Interpretation

1961 ◽  
Vol 7 ◽  
pp. 44-56
Author(s):  
John S. Aird
Keyword(s):  
Population Growth ◽  
Chinese Population ◽  
Population Data ◽  
Human Race ◽  
Technical Aspects ◽  
Rate Of Growth ◽  
The World ◽  
Differences Of Opinion ◽  
Communist China

A quarterof the human race resides hi Communist China, the largest population under a single authority in the world, and it has been growing. No one is likely to quarrel with that statement. But there are differences of opinion over just how large the population of China is and how rapid its rate of growth. This article will not attempt to review the technical aspects of these differences or to set one view against another, but will try to indicate what the range of opinion is, how the differences arise, why they cannot presently be resolved, and what they mean for those who wish to use Chinese population data.

Taking China's Temperature: Daily Range, Warming Trends, and Regional Variations, 1955–2000

2004 ◽  
Vol 17 (22) ◽  
pp. 4453-4462 ◽  
Author(s):  
Binhui Liu ◽  
Ming Xu ◽  
Mark Henderson ◽  
Ye Qi ◽  
Yiqing Li
Keyword(s):  
Atmospheric Aerosols ◽  
Solar Irradiance ◽  
Cloud Cover ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
Climate Data ◽  
Temperature Range ◽  
Temperature Trends ◽  
Air Temperatures ◽  
Maximum Temperatures

Abstract In analyzing daily climate data from 305 weather stations in China for the period from 1955 to 2000, the authors found that surface air temperatures are increasing with an accelerating trend after 1990. They also found that the daily maximum (Tmax) and minimum (Tmin) air temperature increased at a rate of 1.27° and 3.23°C (100 yr)−1 between 1955 and 2000. Both temperature trends were faster than those reported for the Northern Hemisphere, where Tmax and Tmin increased by 0.87° and 1.84°C (100 yr)−1 between 1950 and 1993. The daily temperature range (DTR) decreased rapidly by −2.5°C (100 yr)−1 from 1960 to 1990; during that time, minimum temperature increased while maximum temperature decreased slightly. Since 1990, the decline in DTR has halted because Tmax and Tmin increased at a similar pace during the 1990s. Increased minimum and maximum temperatures were most pronounced in northeast China and were lowest in the southwest. Cloud cover and precipitation correlated poorly with the decreasing temperature range. It is argued that a decline in solar irradiance better explains the decreasing range of daily temperatures through its influence on maximum temperature. With declining solar irradiance even on clear days, and with decreases in cloud cover, it is posited that atmospheric aerosols may be contributing to the changing solar irradiance and trends of daily temperatures observed in China.

scholarly journals Temperature Significantly Change COVID-19 Transmission in 429 cities

2020 ◽  
Author(s):  
Mao Wang ◽  
Aili Jiang ◽  
Lijuan Gong ◽  
Lina Lu ◽  
Wenbin Guo ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
Factor Model ◽  
Control Measures ◽  
Maximum Temperature ◽  
Cumulative Number ◽  
The World ◽  
Temperature Group ◽  
Linear Mixture Model ◽  
Maximum Temperatures ◽  
Lower Temperature

AbstractBackgroundThere is no evidence supporting that temperature changes COVID-19 transmission.MethodsWe collected the cumulative number of confirmed cases of all cities and regions affected by COVID-19 in the world from January 20 to February 4, 2020, and calculated the daily means of the average, minimum and maximum temperatures in January. Then, restricted cubic spline function and generalized linear mixture model were used to analyze the relationships.ResultsThere were in total 24,139 confirmed cases in China and 26 overseas countries. In total, 16,480 cases (68.01%) were from Hubei Province. The lgN rose as the average temperature went up to a peak of 8.72°C and then slowly declined. The apexes of the minimum temperature and the maximum temperature were 6.70°C and 12.42°C respectively. The curves shared similar shapes. Under the circumstance of lower temperature, every 1°C increase in average, minimum and maximum temperatures led to an increase of the cumulative number of cases by 0.83, 0.82 and 0.83 respectively. In the single-factor model of the higher-temperature group, every 1°C increase in the minimum temperature led to a decrease of the cumulative number of cases by 0.86.ConclusionThe study found that, to certain extent, temperature could significant change COVID-19 transmission, and there might be a best temperature for the viral transmission, which may partly explain why it first broke out in Wuhan. It is suggested that countries and regions with a lower temperature in the world adopt the strictest control measures to prevent future reversal.

scholarly journals Impact of Aligning Climatological Day on Gridding Daily Maximum–Minimum Temperature and Precipitation over Canada

2011 ◽  
Vol 50 (8) ◽  
pp. 1654-1665 ◽  
Author(s):  
Ron F. Hopkinson ◽  
Daniel W. McKenney ◽  
Ewa J. Milewska ◽  
Michael F. Hutchinson ◽  
Pia Papadopol ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Minimum ◽  
Temperature And Precipitation ◽  
Daily Data ◽  
National University ◽  
Maximum Temperatures

AbstractOn 1 July 1961, the climatological day was redefined to end at 0600 UTC at all principal climate stations in Canada. Prior to that, the climatological day at principal stations ended at 1200 UTC for maximum temperature and precipitation and 0000 UTC for minimum temperature and was similar to the climatological day at ordinary stations. Hutchinson et al. reported occasional larger-than-expected residuals at 50 withheld stations when the Australian National University Spline (ANUSPLIN) interpolation scheme was applied to daily data for 1961–2003, and it was suggested that these larger residuals were in part due to the existence of different climatological days. In this study, daily minimum and maximum temperatures at principal stations were estimated using hourly temperatures for the same climatological day as local ordinary climate stations for the period 1953–2007. Daily precipitation was estimated at principal stations using synoptic precipitation data for the climatological day ending at 1200 UTC, which, for much of the country, was close to the time of the morning observation at ordinary climate stations. At withheld principal stations, the climatological-day adjustments led to the virtual elimination of large residuals in maximum and minimum temperature and a marked reduction in precipitation residuals. Across all 50 withheld stations the climatological day adjustments led to significant reductions, by around 12% for daily maximum temperature, 15% for daily minimum temperature, and 22% for precipitation, in the residuals reported by Hutchinson et al.

Characteristics of Temperature Depressions Associated with Snow Cover across the Northeast United States

1995 ◽  
Vol 34 (2) ◽  
pp. 381-390 ◽  
Author(s):  
Daniel J. Leathers ◽  
Andrew W. Ellis ◽  
David A. Robinson
Keyword(s):  
United States ◽  
Snow Cover ◽  
Minimum Temperature ◽  
Large Scale ◽  
Winter Season ◽  
Heat Fluxes ◽  
Lower Atmosphere ◽  
Maximum Temperature ◽  
Daily Maximum ◽  
Northeast United States

Abstract Daily snow cover and temperature data are collected for a network of 91 stations covering the northeast United States and the association between the two is explored. Observations are examined for the six-month winter season, November–April, for the period 1948/49–1987/88. Daily maximum and minimum temperatures are stratified by 15-day periods and further by the presence or absence of a snow cover. It is found that for snow covers of 2.5 cm or greater, depressions of daily maximum and minimum temperature average approximately 6° and 5°C, respectively. Relatively large variations in the temperature depressions are observed across space, whereas smaller variability is found across the snow cover season. Temporally, maximum temperature depressions are greater during the early and later portions of the snow cover season and somewhat smaller during the midwinter months. The magnitude of minimum temperature depressions are larger during the midwinter months but decrease in size early and especially late in the snow cover season. The presence of a snow cover decreases the daily temperature range in November, March, and April and has little effect during the intervening months. Spatially, the magnitude of both maximum and minimum temperature depressions increases away from coastal areas. In the case of maximum temperature depressions, there is also a consistent increase toward the southern portion of the region. For minimum temperature depressions, no large-scale geographic control, except for coastal proximity, dominates the spatial distribution of the depression magnitudes. Potential geographic “forcing” mechanisms are evaluated. The results indicate that large sensible and, in some cases, latent heat fluxes from the lower atmosphere to the snowpack account for much of the observed temperature depressions.

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