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1
Al-Jiboori, Monim, Mahmoud Jawad Abu Al-Shaeer, and Ahemd S. Hassan. "Statistical Forecast of Daily Maximum Air Temperature in Arid Areas at Summertime." Journal of Mathematical and Fundamental Sciences 52, no. 3 (2020): 353–65. http://dx.doi.org/10.5614/j.math.fund.sci.2020.52.3.8.
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Based on historical observations of summers for the period from 2004 to 2018 with a focus on daily maximum and minimum air temperatures and wind speed recorded at 0600 GMT, a non-linear regression hypothesis is developed for forecasting daily maximum air temperature (Tmax) in arid areas such as Baghdad International airport station, which has a hot climate with no cloud cover or rain. Observations with dust storm events were excluded, thus this hypothesis could be used to predict daily Tmax on any day during summers characterized by fair weather. Using mean annual daily temperature range, daily minimum temperature, and the trend of maximum temperature with wind speed, Tmax was forecasted and then compared to those recorded by meteorological instruments. To improve the accuracy of the hypothesis, daily forecast errors, bias, and mean absolute error were analyzed to detect their characteristics through calculating relative frequencies of occurrence. At the end of this analysis, a value of (-0.45ºC) was added to the hypothesis as a bias term.
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Sachindra, D. A., F. Huang, A. F. Barton, and B. J. C. Perera. "Statistical downscaling of general circulation model outputs to evaporation, minimum temperature and maximum temperature using a key-predictand and key-station approach." Journal of Water and Climate Change 6, no. 2 (2014): 241–62. http://dx.doi.org/10.2166/wcc.2014.145.
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A key-predictand and key-station approach was employed in downscaling general circulation model outputs to monthly evaporation, minimum temperature (Tmin) and maximum temperature (Tmax) at five observation stations concurrently. Tmax was highly correlated (magnitudes above 0.80 at p ≤ 0.05) with evaporation and Tmin at each individual station, hence Tmax was identified as the key predictand. One station was selected as the key station, as Tmax at that station showed high correlations with evaporation, Tmin and Tmax at all stations. Linear regression relationships were developed between the key predictand at the key station and evaporation, Tmin and Tmax at all stations using observations. A downscaling model was developed at the key station for Tmax. Then, outputs of this downscaling model at the key station were introduced to the linear regression relationships to produce projections of monthly evaporation, Tmin and Tmax at all stations. This key-predictand and key-station approach was proved to be effective as the statistics of the predictands simulated by this approach were in close agreement with those of observations. This simple multi-station multivariate downscaling approach enabled the preservation of the cross-correlation structures of each individual predictand among the stations and also the cross-correlation structures between different predictands at individual stations.
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Liu, Binhui, Ming Xu, Mark Henderson, Ye Qi, and Yiqing Li. "Taking China's Temperature: Daily Range, Warming Trends, and Regional Variations, 1955–2000." Journal of Climate 17, no. 22 (2004): 4453–62. http://dx.doi.org/10.1175/3230.1.
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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.
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Alfaro, Eric J., Alexander Gershunov, and Daniel Cayan. "Prediction of Summer Maximum and Minimum Temperature over the Central and Western United States: The Roles of Soil Moisture and Sea Surface Temperature." Journal of Climate 19, no. 8 (2006): 1407–21. http://dx.doi.org/10.1175/jcli3665.1.
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Abstract A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.
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Milošević, Dragan D., Stevan M. Savić, Uglješa Stankov, et al. "Maximum temperatures over Slovenia and their relationship with atmospheric circulation patterns." Geografie 122, no. 1 (2017): 1–20. http://dx.doi.org/10.37040/geografie2017122010001.
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This paper examines temporal and spatial patterns of annual and seasonal maximum temperatures (Tmax) in Slovenia and their relationship with atmospheric circulation patterns. A significant increase in maximum temperature (Tmax; from 0.3°C to 0.5°C·decade-1) was observed throughout the country at the annual scale in the period 1963–2014. Significant positive trends are observed on all stations in summer (from 0.4°C to 0.7°C·decade-1) and spring (from 0.4°C to 0.6°C·decade-1). The results indicate significant correlations between the mean annual maximum temperature (Tmax) and the East Atlantic Oscillation (EA) (from 0.5 to 0.7), the Arctic Oscillation (AO) (from 0.4 to 0.7) and the Scandinavian Oscillation (SCAND) (from −0.3 to −0.4) throughout the country. A significant EA influence is observed in all seasons, while the AO influence is noticed in winter and spring, SCAND in spring and summer, the North Atlantic Oscillation (NAO) and the Mediterranean Oscillation (MO) in winter, the East Atlantic/Western Russia Oscillation (EA/WR) in summer and the El Nino Southern Oscillation (ENSO) in autumn.
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Penalba, Olga Clorinda, María Laura Bettolli, and Pablo Andrés Krieger. "Surface Circulation Types and Daily Maximum and Minimum Temperatures in Southern La Plata Basin." Journal of Applied Meteorology and Climatology 52, no. 11 (2013): 2450–59. http://dx.doi.org/10.1175/jamc-d-13-039.1.
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AbstractLa Plata basin is one of the most important agricultural and hydropower-producing regions in the world. Extreme climate events such as cold and heat waves and frost events have a significant socioeconomic impact. This work analyzes the influence of the surface circulation in southern South America on daily maximum temperature TMAX and daily minimum temperature TMIN in southern La Plata basin. A Z test for the comparison of mean values and a Kolmogorov–Smirnov test for the comparison of distributions of TMAX and TMIN associated with each circulation pattern were performed. Specific daily surface circulation types are found to contribute to TMAX and TMIN anomalies and to have a predominant occurrence in the development of the extreme temperature events in the region. The TMAX spatial response to the regional low-level circulation is more homogenous and extended than is the response of TMIN.
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Muter, Sara A., Jasim H. Kadhum, and Ahmed S. Hassan. "Approaching of May maximum surface air temperature to characteristic summer season for Baghdad city." Scientific Review Engineering and Environmental Studies (SREES) 30, no. 3 (2021): 400–410. http://dx.doi.org/10.22630/pniks.2021.30.3.34.
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Seasonal variability is the complex non-linear response of the physical climate system. There are two types of natural variability: those external and internal to the climate system. In any given season, natural variability may cause the climate to be different than its long-term average. This study examines with the seasonal variation of the maximum temperatures during the summer season. In addition, the maximum temperatures in May become close to the characteristics of the summer season. The monthly data for maximum temperature of May, June and July were used from Iraqi Meteorological Organization and Seismology (IMOS) for 47 years from 1970 to 2017 for Baghdad city. This period was long enough to estimate the range of approaching maximum temperature (Tmax) May to summer. Results revealed a significant Tmax for Baghdad during the second period (1992–2017) and ?shown similar behavior of Tmax in May to June and July; on the contrary that first period (1970–1991). In second period, two phases have been found out, positive phase and negative phase. The positive phase were happened in 1995, 1999, and 2006, and the negative phase was four cases (1992, 2004, 2013, and 2016), while a few cases recorded in first period. The amplitudes of monthly variability had same distance of leaner correlation especially in 1999 and 2013 that represent coherent wave with summer seasons. The variance difference for Tmax between May and June approximately was 2°C for second study’s period, while exceed this range in first period. This variance change to 7.5°C when found difference between July and May.
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Yuan, Zhe, Jun Yin, Mengru Wei, and Yong Yuan. "Spatio-Temporal Variations in the Temperature and Precipitation Extremes in Yangtze River Basin, China during 1961–2020." Atmosphere 12, no. 11 (2021): 1423. http://dx.doi.org/10.3390/atmos12111423.
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Based on daily maximum temperature (Tmax), minimum temperature (Tmin), and precipitation of the Yangtze River Basin (YRB) from 1961 to 2020, we employed the trend analysis method and correlation analysis method to analyze spatiotemporal variations in 10 extreme indices and their associations with atmospheric and oceanic circulations. Results indicated that maximum Tmax (TXx), maximum Tmin (TNx), and minimum Tmin (TNn) all increased significantly, at rates of 0.19 °C, 0.19 °C, and 0.37 °C per decade, respectively, whereas minimum Tmax (TXn) did not show any significant trend. The diurnal temperature range (DTR) decreased by 0.09 °C per decade as minimum temperatures increased faster than maximum temperatures. TNx and TNn increased significantly in the majority of the YRB, but TXn showed no significant increases. TXn increased significantly in the upper reaches of the Yangtze River. The DTR increased significantly in the Jinsha River Basin and the lower reaches of the Yangtze River. Rx1day (maximum 1-day precipitation), SDII (Simple daily intensity index) and R99p (extremely wet-day precipitation) increased significantly, at rates of 1.12 mm, 0.09 mm, and 5.87 mm per decade, respectively, but the trends of Rx5day (maximum 5-day precipitation) and PRCPTOT (total wet-day precipitation) were not significant. However, the trends of precipitation extreme indices were not statistically significant in most of the YRB. In the future, maximum temperature and minimum temperature might increase while DTR might decrease. But, the trends of precipitation extremes in the future were ambiguous. Nearly all the extreme indices were related to the variability of Atlantic multidecadal oscillation (AMO) in the YRB. In addition, the correlations between extreme temperature indices and AMO are higher than that of extreme precipitation indices.
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CARVALHO, PATRÍCIA GONÇALVES BAPTISTA DE, FABIAN BORGHETTI, MARCOS SILVEIRA BUCKERIDGE, LAURO MORHY, and EDIVALDO XIMENES FERREIRA FILHO. "Temperature-dependent germination and endo-beta -mannanase activity in sesame seeds." Revista Brasileira de Fisiologia Vegetal 13, no. 2 (2001): 139–48. http://dx.doi.org/10.1590/s0103-31312001000200003.
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The effects of temperature on germination and endo-beta-mannanase activity in seeds of Sesamum indicum was investigated. The minimum germination temperature (Tmin) lies between 12.8°C and 13.2°C while the maximum temperature (Tmax) is located between 45.5°C and 46°C. Germinabilities are statistically not different from estimated viability (88%) between 18.8°C and 43.2°C. The Mann-Whitney test indicated the interval 31.9°C to 35.1°C as the optimum temperature (Topt) range for germination rate. When seeds incubated at temperatures at or below the Tmin and close to or above the Tmax were transferred to 30°C, those incubated at lower temperatures achieved high germinability. On the other hand, the higher the pre-incubation temperature above Tmax, the lower the germinability achieved near Topt. Seed endosperm cell wall was found to contain mannose as the main monosaccharide. An increase in endo-beta-mannanase activity in the micropylar endosperm prior to seed germination was observed only at supra-optimum temperature.
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Corobov, Roman, Scott Sheridan, Kristie Ebi, and Nicolae Opopol. "Warm Season Temperature-Mortality Relationships in Chisinau (Moldova)." International Journal of Atmospheric Sciences 2013 (February 19, 2013): 1–9. http://dx.doi.org/10.1155/2013/346024.
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Results of the epidemiological study of relationships between air temperature and daily mortality in Chisinau (Moldova) are presented. The research’s main task included description of mortality dependence on different temperature variables and identification of thermal optimum (minimal mortality temperature, MMT). Total daily deaths were used to characterize the mortality of urban and rural populations in April–September of 2000–2008, excluding the extremely warm season of 2007. The simple moving average procedure and 2nd-order polynomials were used for daily mean (Tmean), maximum (Tmax), and minimum (Tmin) temperatures and mortality approximation. Thermal optimum for mortality in Chisinau (15.2 deaths) was observed at Tmean, Tmax, and Tmin about 22°C, 27-28°C, and 17-18°C, respectively. Considering these values as certain cut-points, the correlations between temperature and mortality were estimated below and above MMTs. With air temperatures below its optimal value, each additional 1°C increase of Tmean (Tmax, Tmin) was accompanied by 1.40% (1.35%, 1.52%) decrease in daily mortality. The increase of Tmean and Tmax above optimal values was associated with ~2.8% and 3.5% increase of mortality; results for Tmin were not statistically significant. The dependency of mortality on apparent temperature was somewhat weaker below MMT; a significant relationship above MMT was not identified.
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ABDUS SATTAR, GULAB SINGH, SHRUTI V. SINGH, MAHESH KUMAR, P. VIJAYA KUMAR, and S.K. BAL. "Evaluating temperature thresholds and optimizing sowing dates of wheat in Bihar." Journal of Agrometeorology 22, no. 2 (2021): 158–64. http://dx.doi.org/10.54386/jam.v22i2.156.
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 Studies on wheat-weather relationship were carried out at Pusa (25.98 oN, 85.67 oE, 52 m), Bihar situated in middle Gangetic plains of India, with three popular wheat cultivars viz. RW 3711, HD 2824 and HD273, grown under five fixed dates of sowing viz. 15 November, 25 November, 5 December, 15 December and 25 December, for five consecutive rabi seasons from 2011-12 to 2015-16. Thresholds of maximum temperature (Tmax), minimum temperature (Tmin) and bright sunshine hours (BSH), associated with higher productivity, occurring at different phenophases, were determined. Results revealed that temperature played a crucial role in achieving higher grain yield of wheat. Both Tmax and Tmin during flowering to milking and flowering to maturity phases increased with delayed sowing dates beyond 25 November with consequent reductions in grain yield. During 50 % flowering to milk stage, Tmax and Tmin above 24.6 oC and 11.6 oC, respectively, reduced grain yield below 4000 kg ha-1; significant reduction in grain yield was also noted beyond maximum temperature of 26.9 oC. During flowering to milk and flowering to maturity phases, Tmax and Tmin exhibited highly significant negative correlation with grain yield, indicating higher temperatures causing lower grain yield. With delayed sowing, sensitive phases of the crop experienced higher air temperatures which led to reduction in grain yield. An increase of Tmax from 29.2 to 32.1 oC during flowering to maturity phases reduced the wheat productivity drastically in this region of Indo-Gangetic plains. Grain yield declined by 399 kg ha-1 per 1 oC rise in Tmax during 50 % flowering to maturity stage. Considering grain yield vis-à-vis temperature regimes during flowering to maturity stage, the most important recommendation for the farmers of the region would be to finish wheat sowing before 25 November in order to enable them to escape terminal heat stress in wheat and thereby realizing higher grain yield. The anthesis-time management by manipulating sowing dates could be a realistic adaptation strategy for attaining optimum grain yield under changing climate scenario.
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Jamir, Tongdimenba, Alka Gadgil, Uday De, and Gaddam Krishnakumar. "Temperature patterns over Northeast and West Coast Regions of India." Bulletin of Geography. Physical Geography Series 10, no. 1 (2016): 51–63. http://dx.doi.org/10.1515/bgeo-2016-0004.
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Abstract The study examines whether maximum/minimum temperature is responsible for a warming/cooling trend. In order to accomplish this, linear regression was used in temperature series such as mean (Tmean), maximum (Tmax), minimum (Tmin) and diurnal temperature range (DTR). A detailed analysis indicates that 11 out of 13 stations over the West Coast region (WCR) show a significant increase in annual Tmean as a result of an increase in annual Tmax. However, the Northeast region (NER) shows a mixed trend, with 6 stations displaying significant increases in annual Tmean and 2 showing significant decreases. Both these patterns can be ascribed to a decrease or increase either in Tmin or Tmax. In DTR, 85% of the stations over the WCR show a significant increasing trend, while 60% of stations in the NER display a significant decreasing trend. Analysis of meteorological parameters reveals that low/medium cloud, calm days, winds, forest cover and population growth influence Tmax/Tmin for the NER, whereas low cloud cover and wind direction have an influence over the WCR.
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Yilbas, B. S., and M. Kalyon. "Parametric variation of the maximum surface temperature during laser heating with convective boundary conditions." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 216, no. 6 (2002): 691–700. http://dx.doi.org/10.1243/095440602320192337.
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Modelling of laser pulse heating of metallic substrates reduces the experimental cost and optimizes the laser heating parameters. In the present study, exponentially time-varying laser pulse heating with convective boundary conditions at the surface is considered. The closed-form solution for temperature distribution at the surface is presented. The effects of the heat transfer coefficient ( h∗) and pulse parameter (β∗) on the time corresponding to the maximum surface temperature ( t∗Tmax is significant for h∗≥0.02. Moreover, reducing the pulse parameter lowers t∗Tmax.
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Sonali, P., and D. Nagesh Kumar. "Spatio-temporal variability of temperature and potential evapotranspiration over India." Journal of Water and Climate Change 7, no. 4 (2016): 810–22. http://dx.doi.org/10.2166/wcc.2016.230.
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Worldwide, major changes in the climate are expected due to global warming, which leads to temperature variations. To assess the climate change impact on the hydrological cycle, a spatio-temporal change detection study of potential evapotranspiration (PET) along with maximum and minimum temperatures (Tmax and Tmin) over India have been performed for the second half of the 20th century (1950–2005) both at monthly and seasonal scale. From the observed monthly climatology of PET over India, high values of PET are envisioned during the months of March, April, May and June. Temperature is one of the significant factors in explaining changes in PET. Hence seasonal correlations of PET with Tmax and Tmin were analyzed using Spearman rank correlation. Correlation of PET with Tmax was found to be higher compared to that with Tmin. Seasonal variability of trend at each grid point over India was studied for Tmax, Tmin and PET separately. Trend Free Pre-Whitening and Modified Mann Kendall approaches, which consider the effect of serial correlation, were employed for the trend detection analysis. A significant trend was observed in Tmin compared to Tmax and PET. Significant upward trends in Tmax, Tmin and PET were observed over most of the grid points in the interior peninsular region.
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Sajjad, Sajjad Hussain, Khuram Shahzad, Tasawar Iqbal, and Nasir Ashraf. "Impact of urban evolution on local temperature trends of Rawalpindi and Islamabad." European Journal of Climate Change 2, no. 2 (2020): 33–46. http://dx.doi.org/10.34154/2020-ejcc-0202-33-46/euraass.
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Rawalpindi and Islamabad commonly known as twin cities of Pakistan have 3.2 million population. Twin cities have rapidly urbanized in the last three decades. The objective of the present study is to compute the urban growth and its effect on evolution of local temperature trends of twin cities. To compute the land-cover change such as built-up area, vegetation cover, water and barren land, Landsat images of 1980, 1992, 2000 and 2013 are classified by using the supervised image classification with maximum likelihood rule and probability surface method. To evaluate the change in temperature trends, homogenized time series data of daily averaged monthly minimum (Tmin) and maximum (Tmax) temperatures for the period of 1983 to 2013 is analyzed by using the linear regression. The results show that built-up area of twin cities increased from 66 km2 in 1983 to 148 km2 in 2013 with an increase of 120 per cent within 31 years. Due to resulted urbanization, Tmin and Tmax of twin cities have been increasing. Tmin is increased more in Rawalpindi than Islamabad and Tmax is increased more in Islamabad than Rawalpindi. The highest increase in Tmin and Tmax at both stations is observed during spring season.
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Song, Libing, and Jiming Jin. "Effects of Sunshine Hours and Daily Maximum Temperature Declines and Cultivar Replacements on Maize Growth and Yields." Agronomy 10, no. 12 (2020): 1862. http://dx.doi.org/10.3390/agronomy10121862.
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In this study, the crop environment resource synthesis maize (CERES-Maize) model was used to explore the effects of declining sunshine hours (SSH), decreasing daily maximum temperature (Tmax), and cultivar replacements on growth processes and yields of maize in Northern China, a principal region of maize production. SSH were found to decrease at 189 of 246 meteorological stations in the northern provinces of China over the period of 1994–2012, and a decrease in Tmax was also seen at many of these stations. The most significant decrease in these two climate variables occurred during June to September, a period for summer maize growth. For this study, seven crop field stations in the ShaanXi province, in the Guanzhong Plain, were selected, all of which showed a downward trend in SSH and Tmax over the period of 1994–2012. The CERES-Maize model was first calibrated and validated against yield observations for these stations over the same period, and the yield simulations matched very well with observations. The model was then driven by the detrended SSH and Tmax data, and the simulations were compared with those with a trend in these two input variables. The decline in SSH was found to reduce the maize yield by 8% on average over these stations due mostly to limited root growth, and the decline for shorter SSH reduced the yield more than that for longer SSH. Meanwhile, the decrease in higher Tmax increased the yield by extending the growth period, while the decrease in lower Tmax reduced the yield by lowering the thermal time. In addition, the observed yield showed a significant upward trend, and our modeling results indicate that this increase can be attributed mainly to the frequent cultivar replacements over our study period. The replaced cultivars usually had a longer growth period than the prior ones, which compensated for the yield loss due to fewer SSH. Net maize production decreased with the combined effects of the declines in SSH and Tmax on yields. This study quantifies the contribution of changes in climate and cultivars to maize growth processes and yields and provides strong insights into maize production under a complex dynamic climate system.
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Christy, John R., William B. Norris, and Richard T. McNider. "Surface Temperature Variations in East Africa and Possible Causes." Journal of Climate 22, no. 12 (2009): 3342–56. http://dx.doi.org/10.1175/2008jcli2726.1.
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Abstract Surface temperatures have been observed in East Africa for more than 100 yr, but heretofore have not been subject to a rigorous climate analysis. To pursue this goal monthly averages of maximum (TMax), minimum (TMin), and mean (TMean) temperatures were obtained for Kenya and Tanzania from several sources. After the data were organized into time series for specific sites (60 in Kenya and 58 in Tanzania), the series were adjusted for break points and merged into individual gridcell squares of 1.25°, 2.5°, and 5.0°. Results for the most data-rich 5° cell, which includes Nairobi, Mount Kilimanjaro, and Mount Kenya, indicate that since 1905, and even recently, the trend of TMax is not significantly different from zero. However, TMin results suggest an accelerating temperature rise. Uncertainty estimates indicate that the trend of the difference time series (TMax − TMin) is significantly less than zero for 1946–2004, the period with the highest density of observations. This trend difference continues in the most recent period (1979–2004), in contrast with findings in recent periods for global datasets, which generally have sparse coverage of East Africa. The differences between TMax and TMin trends, especially recently, may reflect a response to complex changes in the boundary layer dynamics; TMax represents the significantly greater daytime vertical connection to the deep atmosphere, whereas TMin often represents only a shallow layer whose temperature is more dependent on the turbulent state than on the temperature aloft. Because the turbulent state in the stable boundary layer is highly dependent on local land use and perhaps locally produced aerosols, the significant human development of the surface may be responsible for the rising TMin while having little impact on TMax in East Africa. This indicates that time series of TMax and TMin should become separate variables in the study of long-term changes.
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TOMAR, C. S., D. SAHA, S. DAS, SANJAY SHAW, SANJAY BIST, and M. K. GUPTA. "Analysis of temperature variability and trends over Tripura." MAUSAM 68, no. 1 (2021): 149–60. http://dx.doi.org/10.54302/mausam.v68i1.444.
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Attempts have been made to study the temporal variations and trends in monthly, seasonal and annual temperature over two stations - Agartala and Kailashahar in Tripura, India for the period 1969 to 2014. Analysis has been carried for four temperature indices, namely - minimum temperature (Tmin), maximum temperature (Tmax), mean temperature (Tmean) and diurnal temperature range (DTR). Non-parametric Mann-Kendall (MK) test was used to detect the trends and the magnitude of the trends were determined with Sen’s estimator of slope. The analysis of the temperature data revealed significant increasing trends in Tmin, Tmax and Tmean variables at both the stations on annual scale, while decreasing trend in DTR was significant over Agartala only. On the seasonal scale, the increasing (decreasing) trends were observed in Tmin, Tmax and Tmean (DTR) temperature indices in all the four seasons - winter, pre-monsoon, monsoon and post-monsoon except non-significant decreasing trend in Tmax in winter season over Agatala. On the monthly scale, significant rising trends in Tmin, Tmax and Tmean were observed in the most of the months and significant decreasing trend in DTR was found only in the months of January and December.
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SAIKAT, PRAMANIK, SIL SOURAV, and MANDAL SAMIRAN. "Time series analysis of observed maximum and minimum air temperature at four urban cities of India during 1951-2015." MAUSAM 71, no. 1 (2021): 57–68. http://dx.doi.org/10.54302/mausam.v71i1.6.
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A sixty - five year (1951-2015) long data for monthly minimum temperature (TMIN) and maximum temperature (TMAX), observed by the India Meteorological Department (IMD), is statistically analyzed at four urban stations namely Bhubaneswar, Delhi, Mumbai and Chennai of India. A bimodal nature in seasonality is noticed for TMAX and TMIN at all locations. Two peaks for TMAX and TMIN are observed in May and September. Exceptionally, Mumbai shows TMAX peaks during May and November and Delhi shows TMIN peaks during June and September. Higher standard deviations (SD) for TMAX is noted at Delhi with a maximum in March (1.78 °C), while for Chennai, the SD for TMIN is lesser compared to other cities. Two different periods 1951-1980 (P1, the first half of the study period) and 1981-2015 (P2, the second half of the study period) were identified from the time series of both TMAX and TMIN. A higher increasing trend is observed during P2 than P1 in all the cities except in TMIN at Mumbai. The highest increasing trend (0.040 °C/year) is observed for TMIN in Mumbai during P1 time, but the trend is almost constant (0.001 °C/year) during P2 time. The highest increasing trend for TMIN at Mumbai is mainly contributed by the increasing trend in post-monsoon and winter months in P1. Surprisingly, in both P1 and P2, the trends are less during monsoon months for all the cities. A consistent 5-year (3-year) band is observed throughout the wavelet power spectrum at the coastal cities Bhubaneswar, Mumbai (Chennai). However, the 5-year signal is not consistent at Delhi and it is observed only during the year 1975-1980. The global wavelet power spectrum showed that TMIN at Chennai has less power (0.6 °C2) corresponding to 3-year signal and Mumbai has highest power (12 °C2) corresponding to the 5-year signal in comparison to other cities.
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Park, Seung-Eek, and Kug Sun Hong. "Variations of Structure and Dielectric Properties on Substituting A-site Cations for Sr2+ in (Na1/2Bi1/2)TiO3." Journal of Materials Research 12, no. 8 (1997): 2152–57. http://dx.doi.org/10.1557/jmr.1997.0288.
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Changes in structure and phase transition behavior of (Na1/2Bi1/2)1−xSrxTiO3 were investigated using x-ray diffraction (XRD) analysis and dielectric measurements. A decrease in the degree of lattice distortion was observed when the structure was rhombohedral (x < 0.26). Further substitution of Sr2+ (x ≥ 0.26) caused (Na1/2Bi1/2)1−xSrxTiO3 to show no macroscopic lattice distortion. However, all investigated samples (0.1 ≤ x ≤ 0.5) were ferroelectric at room temperature regardless of the lack of lattice distortion found in XRD patterns. Further XRD investigations revealed that nonuniform strains caused by nonuniform polarized islands were responsible for this behavior. A-site cation substitution of Sr2+ also resulted in the decrease of Tmax (the temperature where dielectric constant is maximum). Typical relaxor ferroelectric phase transition behavior, associated with the shift of Tmax, with respect to the measuring frequencies, was found above x = 0.18. This could be also ascribed to the decrease of Tmax—this reveals the increase in the shift of Tmax with frequency, with associated decrease in ionic displacement and space charge contributions and associated increase in the relative contribution to the polarization by microdomains and domain walls at temperatures near Tmax.
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Guan, Huade, Xinping Zhang, Oleg Makhnin, and Zhian Sun. "Mapping Mean Monthly Temperatures over a Coastal Hilly Area Incorporating Terrain Aspect Effects." Journal of Hydrometeorology 14, no. 1 (2013): 233–50. http://dx.doi.org/10.1175/jhm-d-12-014.1.
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Abstract Efforts in the past two decades on air temperature mapping based on sparse monitoring networks reveal that algorithms based on multiple linear regressions with geographical and topographical parameters perform promisingly. In this study, a multiple-regression model, previously for precipitation characterization using autosearched orographic and atmospheric effects (PCASOA), is applied to analyze spatial distribution of mean monthly daily maximum and minimum temperatures (at 33 stations) in Adelaide and the Mount Lofty Ranges (9000 km2), a coastal hilly area in South Australia. Terrain aspect (or slope orientation) is transformed and explicitly incorporated in the model, together with some other topographic variables. Overall, PCASOA captures 91% and 70% observed spatial variability for mean monthly maximum (Tmax) and minimum (Tmin) temperature, respectively. The regression also infers some physical processes influencing the air temperature distribution. The results indicate horizontal gradients of Tmax in the east–west and north–south directions, which can be related to the effects of dominant wind directions in the study area. The effect of terrain ruggedness on Tmax is likely related to the blockage of sea breeze in the complex terrain. Cold air drainage potential only influences Tmin during winter months in the study area. Terrain slope and aspect significantly contribute to interpreting Tmin spatial distribution and can be related to their sheltering effect from the dominant cool inland winds. They also contribute to interpreting Tmax spatial distribution, while the physical mechanism is not clear.
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LALAROY, SUKUMAR, SANJIB BANDYOPADHYAY, and SWETA DAS. "Prediction of maximum or minimum air temperature in a coastal location in West Bengal." MAUSAM 64, no. 4 (2021): 671–80. http://dx.doi.org/10.54302/mausam.v64i4.750.
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bl 'kks/k i= dk mÌs'; Hkkjrh; rVh; LFkku vFkkZr~ if'peh caxky ds vyhiqj ¼dksydkrk½ esa izsf{kr HkweaMyh; lkSj fofdj.k dh enn ls gjxzhCl fofdj.k QkWewZyk ls rkjh[kokj la'kksf/kr KRS irk djuk gS ftlls fd vkxs ;fn U;wure rkieku ¼Tmin½ Kkr gks rks vf/kdre rkieku ¼Tmax½ dk iwokZuqeku nsus esa vFkok blds foijhr] mi;ksx fd;k tk ldsA HkweaMyh; lkSj fofdj.k ds chp lglaca/k dh x.kuk rkjh[kokj fd, x, /kwi ds ?kaVkokj vk¡dM+ksa ds vkSlr ds mi;ksx ftlesa vkaXLVªkse izsLdkWV QkewZyk ls izkIr fu;rkad as = 0-25 vkSj bs = 0-5 gS] ls dh xbZZ gSA blesa izsf{kr fd, x, HkweaMyh; lkSj fofdj.k vkadM+ksa dk v/;;u fd;k x;k gSA ;g fuf'pr :i ls dgk tkrk gS fd vkaxLVªkse izsldkWV QkewZyk HkweaMyh; lkSj fofdj.k dk lVhd vkdyu djrk gS vkSj ;g lgh ik;k tkrk gSA bl 'kks/k i= esa gjxzhCl fofdj.k QkewZyk ¼ftles KRS = 0-19 fy;k x;k gS½ ls rkjh[kokj izkIr fd, x, vf/kdre rkiekuksa rFkk U;wure rkiekuksa ds vkSlr ¼vkadM+s Hkkjr ekSle foKku foHkkx ds vyhiqj] dksydkrk ftyk & 24 ijxuk ds dk;kZy; ls izkIr½ dk mi;ksx djds HkweaMyh; lkSj fofdj.k ds chp lglaca/k dh x.kuk dh xbZ gS vkSj bldk v/;;u izsf{kr HkweaMyh; lkSj fofdj.k ds lkFk Hkh fd;k x;k gSA rkjh[kokj la'kksf/kr KRS dh x.kuk gjxzhCl fofdj.k QkewZyk ls dh xbZA blesa HkweaMyh; lkSj fofdj.k ds izsf{kr vkadM+ksa] rkjh[kokj vf/kdre rkiekuksa vkSj U;wure rkiekuksa ds vkSlr mi;ksx esa fy, x, gSaA bls fdlh LVs'ku ds vf/kdre rkiekuksa vkSj U;wure rkieku vkadMksa ds rkjh[kokj KRS ds mi;ksx ds }kjk vkl ikl ds {ks=ksa ds ok"iksRltZu ds fy, HkweaMyh; lkSj fofdj.k dk vkdyu djus ds fy, Hkh mi;ksx esa yk;k tk ldrk gSA
 The objective of this study is to find the date wise corrected KRS from the Hargreaves Radiation formula with the help of observed global solar radiation for the Indian coastal location namely Alipore (Kolkata) in West Bengal so that subsequently it can be used for predicting maximum temperature Tmax if minimum temperature Tmin is known or vice-versa. The correlation between the global solar radiation calculated by using date wise average sunshine hour data with constants as = 0.25 and bs = 0.5, from Angstrom Prescott formula with the observed global solar radiation data was studied. The assertion that the Angstrom Prescott formula gives nearly accurate estimation of global solar radiation has been found to be correct. Correlation between the global solar radiation calculated by using date wise average of Tmax and Tmin (sourced from IMD located at Alipore, Kolkata, District - South 24 parganas) from Hargreaves Radiation formula (taking KRS = 0.19 ) with the observed global solar radiation data was also studied. Date wise corrected KRS by Hargreaves Radiation formula was computed using the observed data of global solar radiation, date wise average of maximum temperature Tmax and minimum temperature Tmin. The date wise corrected KRS can be used for better prediction of Tmax and Tmin. Also it can be used for estimation of global solar radiation for reference evapo-transpiration of the neighbourhood areas by utilizing the date wise KRS with the Tmax and Tmin of the station.
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Wang, Yangguang, Guoqin Huang, Yanfang Su, Meiqin Zhang, Zhen Tong, and Changcai Cui. "Numerical Analysis of the Effects of Pulsed Laser Spot Heating Parameters on Brazing of Diamond Tools." Metals 9, no. 5 (2019): 612. http://dx.doi.org/10.3390/met9050612.
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A 3D finite element (FE) model is built to numerically analyze heating parameters on temperature during brazing diamond grains by the pulsed laser spot heating. A pulsed Nd:YAG laser is used for experimental validation. The results show that during laser heating, the temperature varies periodically because of the pulsed heat flux. Four key thermal indices, the maximum temperature Tmax, the minimum temperature Tmin, the average temperature Tav and the temperature fluctuation amplitude ΔT are addressed. The primary factor affecting Tmax, ΔT and Tav is the pulse power and on Tmin is the pulse frequency. The secondary effect factor on Tmax, Tav and ΔT is the pulse width and on Tmin is the pulse power. For engineering practice, the order of designing heating parameters is recommended as: pulse power, second frequency and last width.
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Arbab, A., and M. R. McNeill. "Can critical temperatures be related to insect order." New Zealand Plant Protection 62 (August 1, 2009): 399. http://dx.doi.org/10.30843/nzpp.2009.62.4838.
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Insect phenology models are widely used for decision support in pest management and more recently in risk assessments During the last two decades numerous linear and nonlinear models have been used to describe insect development rates and estimate various critical temperatures (CT) including optimal development temperature (Topt) maximum development temperature (Tmax) minimum development temperature (Tmin) and thermal constant (K) (eg day degree requirements to complete development) Using a database comprising more than 600 species from laboratory and field experiments the relationship between CT for the six main insect orders Coleoptera Diptera Hymenoptera Lepidoptera Homoptera and Hemiptera was compared There were no significant differences (P>005) between Topt and Tmax for all orders but Tmin and K showed significant (P
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Li, Zhang, Qi, Wang, Liu, and Ding. "No Significant Shift of Warming Trend over the Last Two Decades on the Mid-South of Tibetan Plateau." Atmosphere 10, no. 7 (2019): 416. http://dx.doi.org/10.3390/atmos10070416.
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Climate warming on the Tibetan Plateau has been regarded as an important driving force of regional environmental change. Although several studies have analyzed the shift of warming trends on this plateau within the context of a recent global warming “hiatus” since 1998, their disparate findings have hindered a comprehensive and regional understanding. Based on the daily mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) collected from meteorological stations on the period of 1961–2017, we re-examined the timing and magnitude of temperature phase change using piecewise linear regression on the mid-south of Tibetan Plateau. The results show that among the trends in regional annual Tmean, Tmax and Tmin, the statistically significant change-point was observed only in annual Tmax (p < 0.01). The warming trend of annual Tmax has accelerated significantly since 1992 and has exceeded that of annual Tmin after 2000, causing a remarkable reversal from decline to increase in diurnal temperature range (DTR) (p < 0.01). Spatially, the occurrence time of change-points in Tmean, Tmax, and Tmin varied among stations, but most of them occurred before the mid-1990s. Besides, the trend shifts in Tmax/DTR during the cold season played a primary role in the significant trend shifts in annual Tmax/DTR. This study underscores that there is no significant shift of warming trends over the last two decades on the mid-south of Tibetan Plateau.
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Tadić, Jovan, and Sébastien Biraud. "Effects of Climate Change on Precipitation and the Maximum Daily Temperature (Tmax) at Two US Military Bases with Different Present-Day Climates." Climate 8, no. 2 (2020): 18. http://dx.doi.org/10.3390/cli8020018.
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In this study, the effects of climate change on precipitation and the maximum daily temperature (Tmax) at two USA locations that have different climates—the Travis Airforce Base (AFB) in California [38.27° N, 121.93° W] and Fort Bragg (FBR) in North Carolina [35.14 N, 79.00 W]—are analyzed. The effects of climate change on central tendency, tail distributions, and both auto- and cross-covariance structures in precipitation and Tmax fields for three time periods in the 21st century centered on the years 2020, 2050, and 2100 were analyzed. It was found that, on average, Tmax under the Representative Concentration Pathway (RCP) 4.5 emission scenario is projected to increase for the years 2020, 2050, and 2100 by 1.1, 2.0, and 2.2 °C, respectively, for AFB, and 0.9, 1.2, and 1.6 °C, respectively, for FBR, while under the RCP8.5 emission scenario Tmax will increase by 1.1, 1.9, and 2.7 °C, respectively, for AFB, and 0.1, 1.5, and 2.2 °C, respectively, for FBR. The climate change signal in precipitation is weak. The results show that, under different emission scenarios, events considered to be within 1% of the most extreme events in the past will become ~13–30 times more frequent for Tmax, ~and 0.05–3 times more frequent for precipitation in both locations. Several analytical methods were deployed in a sequence, creating an easily scalable framework for similar analyses in the future.
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Lin, Shu Xia, Cheng Lin Zhang, Jun Gao, and Li Qun Ruan. "Influence of Drawing Temperature and Die Clearance on Wall Thickness of AZ31B Deep Drawn Part." Applied Mechanics and Materials 229-231 (November 2012): 2415–18. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.2415.
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In this paper, AZ31B drawing test was carried out under the mechanical press with crank-slide mechanism. The influence of drawing temperature and drawing clearance on the wall thickness of AZ31B drawn parts was studied through testing. Some conclusions were drawn, which are: with the increase of drawing temperature, minimum wall thickness ( Tmin ) and maximum wall thickness ( Tmax ) of AZ31B drawn parts substantially decreased; with the increase of drawing clearance, Tmin and Tmax of AZ31B drawn parts increased.
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Qona’ah, Niswatul, Sutikno, Kiki Ferawati, and Muhammad Bayu Nirwana. "Temperature Forecast Using Ridge Regression as Model Output Statistics." Proceeding International Conference on Science and Engineering 3 (April 30, 2020): 383–88. http://dx.doi.org/10.14421/icse.v3.533.
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Over the past few years, BMKG (Meteorological, Climatological and Geophysical Agency) in Indonesia has used numerical weather forecasting techniques, namely Numerical Weather Prediction (NWP). However, the NWP forecast still has a high bias because it is only measured on a global scale and unable to capture the dynamics of atmosphere (Wilks, 2007). Hence, this study implements Ridge Regression as Model Output Statistics (MOS) for temperature forecast. This study uses the maximum temperature (Tmax) and minimum temperature (Tmin) observation at 4 stations in Indonesia as the response variables and NWP as the predictor variable. The results show that the performance of the model based on Root Mean Square Error of Prediction (RMSEP) is considered to be good and intermediate. The RMSEP for Tmax in all stations is intermediate (0.9-1.2), Tmin in all stations is good (0.5-0.8). The prediction result from Ridge Regression is more accurate than the NWP model and able to correct up to 90.49% of the biased NWP for Tmax forecasting.
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Christy, John R., and Richard T. McNider. "Time Series Construction of Summer Surface Temperatures for Alabama, 1883–2014, and Comparisons with Tropospheric Temperature and Climate Model Simulations." Journal of Applied Meteorology and Climatology 55, no. 3 (2016): 811–26. http://dx.doi.org/10.1175/jamc-d-15-0287.1.
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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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Al Blooshi, Latifa Saeed, Sofyan Alyan, Ngaina Joshua Joshua, and Taoufik Saleh Ksiksi. "Modeling Current and Future Climate Change in the UAE using Various GCMs in MarksimGCMR." Open Atmospheric Science Journal 13, no. 1 (2019): 56–64. http://dx.doi.org/10.2174/1874282301913010056.
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Introduction: Changes in climate have impacts on natural and human systems on all continents and across the oceans. Most countries, including the UAE, are expected to experience a huge impact of climate change, due to the undergoing rapid growth and huge urban developments. Materials & Methods: Representative Concentration Pathways, or RCPs, represent the latest generation of scenarios that are used as potential inputs into climate models to show imposed greenhouse-gas concentration pathways during the 21st century. Four emission scenarios have been used for climate research; namely RCP 2.6, RCP 4.5 and RCP 6 and RCP 8.5. RCP 4.5 and RCP 8.5 are used. The aims of this study are to assess different RCPs and their appropriateness to predict temperatures and rainfall and to study the effect of climate change on three different cities in the UAE. Results & Conclusion: The results show a strong correlation between the present Tmax vs Tmax 2020, Tmax 2040, Tmax 2060, Tmax 2080 and Tmax 2095 for both RCP4.5 and RCP8.5. This means that maximum temperatures are going to increase in the coming years based on the predictions according to the different scenarios using MarksimGCMR. Precipitation projections shows greater variation than temperature. In this paper the amount of increase in temperatures and precipitation change is shown for the end of the current century.
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Villordon, Arthur, Christopher Clark, Don Ferrin, and Don LaBonte. "Using Growing Degree Days, Agrometeorological Variables, Linear Regression, and Data Mining Methods to Help Improve Prediction of Sweetpotato Harvest Date in Louisiana." HortTechnology 19, no. 1 (2009): 133–44. http://dx.doi.org/10.21273/hortsci.19.1.133.
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Predictive models of optimum sweetpotato (Ipomoea batatas) harvest in relation to growing degree days (GDD) will benefit producers and researchers by ensuring maximum yields and high quality. A GDD system has not been previously characterized for sweetpotato grown in Louisiana. We used a data set of 116 planting dates and used a combination of minimum cv, linear regression (LR), and several algorithms in a data mining (DM) mode to identify candidate methods of estimating relationships between GDD and harvest dates. These DM algorithms included neural networks, support vector machine, multivariate adaptive regression splines, regression trees, and generalized linear models. We then used candidate GDD methods along with agrometeorological variables to model US#1 yield using LR and DM methodology. A multivariable LR model with the best adjusted r2 was based on GDD calculated using this method: maximum daily temperature (Tmax) – base temperature (B), where if Tmax > ceiling temperature [C (90 °F)], then Tmax = C, and where GDD = 0 if minimum daily temperature <60 °F. The following climate-related variables contributed to the improvement of adjusted r2 of the LR model: mean relative humidity 20 days after transplanting (DAT), maximum air temperature 20 DAT, and maximum soil temperature 10 DAT (log 10 transformed). In the DM mode, this GDD method and the LR model also demonstrated high predictive accuracy as quantified using mean square error. Using this model, we propose to schedule test harvests at GDD = 2600. The harvest date can further be optimized by predicting US#1 yield using GDD in combination with climate-based predictor variables measured within 20 DAT.
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Ahmad, Jawairia Imtiaz, Sara Giorgi, Ljiljana Zlatanovic, Gang Liu, and Jan Peter van der Hoek. "Maximizing Thermal Energy Recovery from Drinking Water for Cooling Purpose." Energies 14, no. 9 (2021): 2413. http://dx.doi.org/10.3390/en14092413.
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Drinking water distribution networks (DWDNs) have a huge potential for cold thermal energy recovery (TED). TED can provide cooling for buildings and spaces with high cooling requirements as an alternative for traditional cooling, reduce usage of electricity or fossil fuel, and thus TED helps reduce greenhouse gas (GHG) emissions. There is no research on the environmental assessment of TED systems, and no standards are available for the maximum temperature limit (Tmax) after recovery of cold. During cold recovery, the water temperature increases, and water at the customer’s tap may be warmer as a result. Previous research showed that increasing Tmax up to 30 °C is safe in terms of microbiological risks. The present research was carried out to determine what raising Tmax would entail in terms of energy savings, GHG emission reduction and water temperature dynamics during transport. For this purpose, a full-scale TED system in Amsterdam was used as a benchmark, where Tmax is currently set at 15 °C. Tmax was theoretically set at 20, 25 and 30 °C to calculate energy savings and CO2 emission reduction and for water temperature modeling during transport after cold recovery. Results showed that by raising Tmax from the current 15 °C to 20, 25 and 30 °C, the retrievable cooling energy and GHG emission reduction could be increased by 250, 425 and 600%, respectively. The drinking water temperature model predicted that within a distance of 4 km after TED, water temperature resembles that of the surrounding subsurface soil. Hence, a higher Tmax will substantially increase the TED potential of DWDN while keeping the same comfort level at the customer’s tap.
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Firanj Sremac, Ana, Branislava Lalic, Joan Cuxart, and Milena Marcic. "Maximum, Minimum, and Daily Air Temperature Range in Orchards: What Do Observations Reveal?" Atmosphere 12, no. 10 (2021): 1279. http://dx.doi.org/10.3390/atmos12101279.
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This study was designed to better understand vegetation’s impact on air maximum (Tmax), minimum (Tmin), and daily temperature range (DTR), as well as seasonality and variability. We selected a flat, under synoptic-scale, northern Serbian region with an operational network of automated weather stations (AWS) for the study. Data were collected directly from the eighteen AWSs placed in the orchard canopy during 2013–2018. Meteorological data, plant phenological data in the form of the BBCH scale, and orchards’ soil characteristics data were collected. Environmental factors influencing the temperature were classified as static (slow or unchangeable) and dynamic (fast-changing). The impact of both factors on maximum, minimum, and daily temperature range and its variability were analyzed. Results show that static factors (like soil texture) affect the annual variation of Tmax, Tmin, and DTR rather than its variability over the season. The dynamic factors, mainly coming from the plant’s phenology, substantially affected the seasonal variability of these variables. Studies like this suffer from missing data and sparse spatial coverage by the AWS network. Therefore, the alternatives of orchard micrometeorological data, nearest climatological station, and ERA5-Land reanalysis data are tested. Both data sets showcased limitations in their applicability, while reanalysis data deviated more from the in-situ measurements, both seasonally and regionally.
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Su, Minshu, Xiao Huang, Zhen Xu, Weihong Zhu, and Zhehao Lin. "A Decrease in the Daily Maximum Temperature during Global Warming Hiatus Causes a Delay in Spring Phenology in the China–DPRK–Russia Cross-Border Area." Remote Sensing 14, no. 6 (2022): 1462. http://dx.doi.org/10.3390/rs14061462.
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Spring phenology is the most sensitive indicator of climate change and exploring its response to climate change has important implications for ecosystem processes in the study area. The temperature changes before and after the global warming hiatus may affect the spatiotemporal pattern of land surface phenology. In this paper, taking the China–DPRK (Democratic People’s Republic of Korea)–Russia cross-border region as an example, based on GIMMS NDVI data, the Polyfit-Maximum method was used to extract the start date of the vegetation growing season (SOS). The variation trend of SOS and its response to climate change were analyzed in the early (1982–1998) and late (1998–2015) periods of the warming hiatus. At the regional scale, the spatial distribution of the SOS in the China–DPRK–Russia (CDR) cross-border area presents an elevation gradient, which is earlier in high-elevation areas and later in low-elevation areas. The temporal and spatial trend of SOS is mainly correlated by daytime maximum temperature (Tmax). The significant increase in Tmax in the early period promoted the advance of SOS (0.47 days/year), and the decrease in Tmax in the later period caused the delay of SOS (0.51 days/year). While the main influencing factor of the SOS changes in the region in the early and late periods was Tmax, the response of the SOS changes in China, DPRK and Russia to climate change also changed with the dramatic temperature changes during the warming hiatus. The Chinese side is increasingly responding to Tmax, while the North Korean side is becoming less responsive to climatic factors, and precipitation and radiation on the Russian side are driving the advance of the SOS.
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Deng, Guorong, Hongyan Zhang, Xiaoyi Guo, et al. "Asymmetric Effects of Daytime and Nighttime Warming on Boreal Forest Spring Phenology." Remote Sensing 11, no. 14 (2019): 1651. http://dx.doi.org/10.3390/rs11141651.
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Vegetation phenology is the most intuitive and sensitive biological indicator of environmental conditions, and the start of the season (SOS) can reflect the rapid response of terrestrial ecosystems to climate change. At present, the model based on mean temperature neglects the role of the daytime maximum temperature (TMAX) and the nighttime minimum temperature (TMIN) in providing temperature accumulation and cold conditions at leaf onset. This study analyzed the spatiotemporal variations of spring phenology for the boreal forest from 2001 to 2017 based on the moderate-resolution imaging spectro-radiometer (MODIS) enhanced vegetation index (EVI) data (MOD13A2) and investigated the asymmetric effects of daytime and nighttime warming on the boreal forest spring phenology during TMAX and TMIN preseason by partial correlation analysis. The results showed that the spring phenology was delayed with increasing latitude of the boreal forest. Approximately 91.37% of the region showed an advancing trend during the study period, with an average advancement rate of 3.38 ± 0.08 days/decade, and the change rates of different land cover types differed, especially in open shrubland. The length of the TMIN preseason was longer than that of the TMAX preseason and diurnal temperatures showed an asymmetrical increase during different preseasons. The daytime and nighttime warming effects on the boreal forest are asymmetrical. The TMAX has a greater impact on the vegetation spring phenology than TMIN as a whole and the effect also has seasonal differences; the TMAX mainly affects the SOS in spring, while TMIN has a greater impact in winter. The asymmetric effects of daytime and nighttime warming on the SOS in the boreal forest were highlighted in this study, and the results suggest that diurnal temperatures should be added to the forest terrestrial ecosystem model.
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Lobell, David B., and Céline Bonfils. "The Effect of Irrigation on Regional Temperatures: A Spatial and Temporal Analysis of Trends in California, 1934–2002." Journal of Climate 21, no. 10 (2008): 2063–71. http://dx.doi.org/10.1175/2007jcli1755.1.
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Abstract The response of air temperatures to widespread irrigation may represent an important component of past and/or future regional climate changes. The quantitative impact of irrigation on daily minimum and maximum temperatures (Tmin and Tmax) in California was estimated using historical time series of county irrigated areas from agricultural censuses and daily climate observations from the U.S. Historical Climatology Network. Regression analysis of temperature and irrigation changes for stations within irrigated areas revealed a highly significant (p &lt; 0.01) effect of irrigation on June–August average Tmax, with no significant effects on Tmin (p &gt; 0.3). The mean estimate for Tmax was a substantial 5.0°C cooling for 100% irrigation cover, with a 95% confidence interval of 2.0°–7.9°C. As a result of small changes in Tmin compared to Tmax, the diurnal temperature range (DTR) decreased significantly in both spring and summer months. Effects on percentiles of Tmax within summer months were not statistically distinguishable, suggesting that irrigation’s impact is similar on warm and cool days in California. Finally, average trends for stations within irrigated areas were compared to those from nonirrigated stations to evaluate the robustness of conclusions from previous studies based on pairwise comparisons of irrigated and nonirrigated sites. Stronger negative Tmax trends in irrigated sites were consistent with the inferred effects of irrigation on Tmax. However, Tmin trends were significantly more positive for nonirrigated sites despite the apparent lack of effects of irrigation on Tmin from the analysis within irrigated sites. Together with evidence of increases in urban areas near nonirrigated sites, this finding indicates an important effect of urbanization on Tmin in California that had previously been attributed to irrigation. The results therefore demonstrate that simple pairwise comparisons between stations in a complex region such as California can lead to misinterpretation of historical climate trends and the effects of land use changes.
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Tomczyk, Arkadiusz M., Ewa Bednorz, and Katarzyna Szyga-Pluta. "Changes in Air Temperature and Snow Cover in Winter in Poland." Atmosphere 12, no. 1 (2021): 68. http://dx.doi.org/10.3390/atmos12010068.
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The primary objective of the paper was to characterize the climatic conditions in the winter season in Poland in the years 1966/67–2019/20. The study was based on daily values of minimum (Tmin) and maximum air temperature (Tmax), and daily values of snow cover depth. The study showed an increase in both Tmin and Tmax in winter. The most intensive changes were recorded in north-eastern and northern regions. The coldest winters were recorded in the first half of the analyzed multiannual period, exceptionally cold being winters 1969/70 and 1984/85. The warmest winters occurred in the second half of the analyzed period and among seasons with the highest mean Tmax, particularly winters 2019/20 and 1989/90 stood out. In the study period, a decrease in snow cover depth statistically significant in the majority of stations in Poland was determined, as well as its variability both within the winter season and multiannual.
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GOTO, TSUNEAKI, and TOSHIRO SAKAKIBARA. "METAMAGNETISM AND SPIN FLUCTUATIONS IN Co-BASED INTERMETALLIC COMPOUNDS." International Journal of Modern Physics B 07, no. 01n03 (1993): 788–93. http://dx.doi.org/10.1142/s0217979293001669.
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High field magnetization and susceptibility of Co-based compounds Y(Co1−xA1x)2 are investigated in the paramagnetic region 0≤x≤0.11. In all the region, a sharp metamagnetic transition is observed, while the susceptibility shows a maximum at finite temperature Tmax. The transition field Hc exhibits a positive shift proportional to T2 with temperature. The Hc in the ground state is found to be proportional to Tmax. The experimental results are discussed with a new theory for itinerant electron metamagnetism based on the spin fluctuation model.
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Watkinson, Emily Jane, Ramy Mesalam, Jean-François Vigier, et al. "Thermal Properties and Behaviour of Am-Bearing Fuel in European Space Radioisotope Power Systems." Thermo 1, no. 3 (2021): 297–331. http://dx.doi.org/10.3390/thermo1030020.
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The European Space Agency is funding the research and development of 241Am-bearing oxide-fuelled radioisotope power systems (RPSs) including radioisotope thermoelectric generators (RTGs) and European Large Heat Sources (ELHSs). The RPSs’ requirements include that the fuel’s maximum temperature, Tmax, must remain below its melting temperature. The current prospected fuel is (Am0.80U0.12Np0.06Pu0.02)O1.8. The fuel’s experimental heat capacity, Cp, is determined between 20 K and 1786 K based on direct low temperature heat capacity measurements and high temperature drop calorimetry measurements. The recommended high temperature equation is Cp(T/K) = 55.1189 + 3.46216 × 102 T − 4.58312 × 105 T−2 (valid up to 1786 K). The RTG/ELHS Tmax is estimated as a function of the fuel thermal conductivity, k, and the clad’s inner surface temperature, Ti cl, using a new analytical thermal model. Estimated bounds, based on conduction-only and radiation-only conditions between the fuel and clad, are established. Estimates for k (80–100% T.D.) are made using Cp, and estimates of thermal diffusivity and thermal expansion estimates of americium/uranium oxides. The lowest melting temperature of americium/uranium oxides is assumed. The lowest k estimates are assumed (80% T.D.). The highest estimated Tmax for a ‘standard operating’ RTG is 1120 K. A hypothetical scenario is investigated: an ELHS Ti cl = 1973K-the RPSs’ requirements’ maximum permitted temperature. Fuel melting will not occur.
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Zahid, Maida, Richard Blender, Valerio Lucarini, and Maria Caterina Bramati. "Return levels of temperature extremes in southern Pakistan." Earth System Dynamics 8, no. 4 (2017): 1263–78. http://dx.doi.org/10.5194/esd-8-1263-2017.
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Abstract. Southern Pakistan (Sindh) is one of the hottest regions in the world and is highly vulnerable to temperature extremes. In order to improve rural and urban planning, it is useful to gather information about the recurrence of temperature extremes. In this work, return levels of the daily maximum temperature Tmax are estimated, as well as the daily maximum wet-bulb temperature TWmax extremes. We adopt the peaks over threshold (POT) method, which has not yet been used for similar studies in this region. Two main datasets are analyzed: temperatures observed at nine meteorological stations in southern Pakistan from 1980 to 2013, and the ERA-Interim (ECMWF reanalysis) data for the nearest corresponding locations. The analysis provides the 2-, 5-, 10-, 25-, 50-, and 100-year return levels (RLs) of temperature extremes. The 90 % quantile is found to be a suitable threshold for all stations. We find that the RLs of the observed Tmax are above 50 °C at northern stations and above 45 °C at the southern stations. The RLs of the observed TWmax exceed 35 °C in the region, which is considered as a limit of survivability. The RLs estimated from the ERA-Interim data are lower by 3 to 5 °C than the RLs assessed for the nine meteorological stations. A simple bias correction applied to ERA-Interim data improves the RLs remarkably, yet discrepancies are still present. The results have potential implications for the risk assessment of extreme temperatures in Sindh.
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Zhang, Hongbo, Fan Zhang, Guoqing Zhang, Xiaobo He, and Lide Tian. "Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan Plateau." Atmospheric Chemistry and Physics 16, no. 21 (2016): 13681–96. http://dx.doi.org/10.5194/acp-16-13681-2016.
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Abstract. Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data are often used as proxies for estimating daily maximum (Tmax) and minimum (Tmin) air temperatures, especially for remote mountainous areas due to the sparseness of ground measurements. However, the Tibetan Plateau (TP) has a high daily cloud cover fraction (> 45 %), which may affect the air temperature (Tair) estimation accuracy. This study comprehensively analyzes the effects of clouds on Tair estimation based on MODIS LST using detailed half-hourly ground measurements and daily meteorological station observations collected from the TP. It is shown that erroneous rates of MODIS nighttime cloud detection are obviously higher than those achieved in daytime. Large errors in MODIS nighttime LST data were found to be introduced by undetected clouds and thus reduce the Tmin estimation accuracy. However, for Tmax estimation, clouds are mainly found to reduce the estimation accuracy by affecting the essential relationship between Tmax and daytime LST. The errors of Tmax estimation are obviously larger than those of Tmin and could be attributed to larger MODIS daytime LST errors that result from higher degrees of LST heterogeneity within MODIS pixel compared to those of nighttime LST. Constraining MODIS observations to non-cloudy observations can efficiently screen data samples for accurate Tmin estimation using MODIS nighttime LST. As a result, the present study reveals the effects of clouds on Tmax and Tmin estimation through MODIS daytime and nighttime LST, respectively, so as to help improve the Tair estimation accuracy and alleviate the severe air temperature data sparseness issues over the TP.
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Чжан, В. Б., И. С. Терёшина, А. А. Курганская, С. А. Лушников, В. Н. Вербецкий та Е. А. Терёшина-Хитрова. "Новые магнитные материалы на основе соединений RNi для криогенной техники". Письма в журнал технической физики 46, № 6 (2020): 51. http://dx.doi.org/10.21883/pjtf.2020.06.49167.18156.
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Magnetocaloric properties of compounds Gd(Ni0.98Si0.02), Dy(Ni0.95Si0.05) and their hydrides Gd(Ni0.98Si0.02)H3, Dy(Ni0.95Si0.05)H4 were investigated in the temperature range 2 – 100K. It was found that partial substitution of Ni atoms by Si atoms, as well as subsequent hydrogenation can lead to a significant change in the Curie temperature (TC), the magnetocaloric effect, and the temperature at which the maximum MCE (Tmax) is observed. It is shown that the TC and Tmax of the hydrides are shifted by several degrees to the low temperature region with increasing or maintaining the MCE, which can significantly expand the application of such materials in cryogenic engineering.
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Huang, Nan-nan, Hao Zheng, Bin Li, et al. "The Short-term Effects of Temperature on Infectious Diarrhea among Children under 5 Years Old in Jiangsu, China: A Time-series Study (2015–2019)." Current Medical Science 41, no. 2 (2021): 211–18. http://dx.doi.org/10.1007/s11596-021-2338-x.
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SummaryThe association between meteorological factors and infectious diarrhea has been widely studied in many countries. However, investigation among children under 5 years old in Jiangsu, China remains quite limited. Data including infectious diarrhea cases among children under five years old and daily meteorological indexes in Jiangsu, China from 2015 to 2019 were collected. The lag-effects up to 21 days of daily maximum temperature (Tmax) on infectious diarrhea were explored using a quasi-Poisson regression with a distributed lag non-linear model (DLNM) approach. The cases number of infectious diarrhea was significantly associated with seasonal variation of meteorological factors, and the burden of disease mainly occurred among children aged 0–2 years old. Moreover, when the reference value was set at 16.7°C, Tmax had a significant lag-effect on cases of infectious diarrhea among children under 5 years old in Jiangsu Province, which was increased remarkably in cold weather with the highest risk at 8°C. The results of DLNM analysis implicated that the lag-effect of Tmax varied among the 13 cities in Jiangsu and had significant differences in 8 cities. The highest risk of Tmax was presented at 5 lag days in Huaian with a maximum RR of 1.18 (95% CI: 1.09, 1.29). Suzhou which had the highest number of diarrhea cases (15830 cases), had a maximum RR of 1.04 (95% CI:1.03, 1.05) on lag 15 days. Tmax is a considerable indicator to predict the epidemic of infectious diarrhea among 13 cities in Jiangsu, which reminds us that in cold seasons, more preventive strategies and measures should be done to prevent infectious diarrhea.
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Du, Jizeng, Kaicun Wang, Jiankai Wang, Shaojing Jiang, and Chunlüe Zhou. "Diurnal Cycle of Surface Air Temperature within China in Current Reanalyses: Evaluation and Diagnostics." Journal of Climate 31, no. 11 (2018): 4585–603. http://dx.doi.org/10.1175/jcli-d-17-0773.1.
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Abstract Diurnal cycle of surface air temperature T is an important metric indicating the feedback of land–atmospheric interaction to global warming, whereas the ability of current reanalyses to reproduce its variation had not been assessed adequately. Here, we evaluate the daily maximum temperature Tmax, daily minimum temperature Tmin, and diurnal temperature range (DTR) in five reanalyses based on observations collected at 2253 weather stations over China. Our results show that the reanalyses reproduce Tmin very well; however, except for Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), they substantially underestimate Tmax and DTR by 1.21°–6.84°C over China during the period of 1980–2014. MERRA-2 overestimates Tmax and DTR by 0.35° and 0.81°C, which are closest with observation. The reanalyses are skillful in reproducing the interannual variability of Tmax and Tmin but relatively poor for DTR. All reanalyses underestimate the warming trend of Tmin by 0.13°–0.17°C (10 yr)−1 throughout China during 1980–2014, and underestimate the warming trend of Tmax by 0.24°–0.40°C (10 yr)−1 in northwestern China while overestimating this quantity by 0.18°–0.33°C (10 yr)−1 in southeastern China. These trend biases in Tmax and Tmin introduce a positive trend bias in DTR of 0.01°–0.26°C (10 yr)−1 within China, especially in the north China plain and southeastern China. In the five reanalyses, owing to the sensitivity discrepancies and trend biases, the surface solar radiation Rs and precipitation frequency (PF) are notable deviation sources of the diurnal cycle of air temperature, which explain 31.0%–38.7% (31.9%–37.8%) and 9.8%–22.2% (7.4%–15.3%) of the trend bias in Tmax (DTR) over China, respectively.
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Elias, Scott A. "Late Pleistocene Climates of Beringia, Based on Analysis of Fossil Beetles." Quaternary Research 53, no. 2 (2000): 229–35. http://dx.doi.org/10.1006/qres.1999.2093.
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AbstractThirty-one fossil beetle assemblages from central and eastern Beringia (Alaska, the Yukon Territory, and the now-submerged Bering Land Bridge) have yielded seasonal temperature estimates for the interval 43,550–9250 14C yr before present (yr B.P.). Estimates of the mean temperature of the warmest (TMAX) and coldest (TMIN) months were derived by the Mutual Climatic Range method. Assemblages from northern and western sites show a mid-Wisconsin interstadial TMAX warming from 35,000–30,000 yr B.P.; this warming is less pronounced in assemblages for interior regions. There is little or no beetle evidence for the spread of coniferous forest in eastern Beringia during this interstade, except for in parts of the Yukon Territory. During the last glacial maximum TMAX values were depressed by about 2°–2.5°C in Arctic regions of Beringia, and by about 4°C in the interior; TMIN values were about 8°C colder in both regions. TMAX and TMIN values rose rapidly at northern sites after 12,000 yr B.P. Seasonal temperatures peaked at 11,000 yr B.P., just as the Bering Land Bridge was inundated. This was followed by a sharp climatic cooling between 11,000 and 10,000 yr B.P., the equivalent of a Younger Dryas cooling in eastern Beringia.
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Hess, Jeremy J., Sathish LM, Kim Knowlton, et al. "Building Resilience to Climate Change: Pilot Evaluation of the Impact of India’s First Heat Action Plan on All-Cause Mortality." Journal of Environmental and Public Health 2018 (November 1, 2018): 1–8. http://dx.doi.org/10.1155/2018/7973519.
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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.
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WANG, DAN, YU HAO, and JIANPEI WANG. "IMPACT OF CLIMATE CHANGE ON CHINA’S RICE PRODUCTION — AN EMPIRICAL ESTIMATION BASED ON PANEL DATA (1979–2011) FROM CHINA’S MAIN RICE-PRODUCING AREAS." Singapore Economic Review 63, no. 03 (2018): 535–53. http://dx.doi.org/10.1142/s0217590817400240.
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Climate change is attracting increasing attention from the international community. To assess the impact of climate change on China’s rice production, this paper re-organizes the main rice-producing areas by adding up the annual production of the provincial level regions between 1979 and 2011, utilizes Cobb–Douglas function using daily weather data over the whole growing season. Our analysis of the panel data shows that minimum temperatures (Tmin), maximum temperatures (Tmax), temperature difference (TD) and precipitation (RP) are the four key climate determinants of rice production in China. Among these, temperature difference is surprisingly significant and all except maximum temperatures have positive effects. However, because the actual minimum temperatures and precipitation in China’s main rice-producing areas declined while the maximum temperatures and the temperature difference increased during our sample period, climate change has actually provided a negative contribution to the increase in China’s rice production.
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Cook, Nigel J., Brady Chabot, Tong Liu, Denise Froehlich, and Manuel Juàrez. "Radiated temperature of weaned piglets and the response to in-feed antibiotics with correction for ambient conditions." Canadian Journal of Animal Science 101, no. 2 (2021): 318–28. http://dx.doi.org/10.1139/cjas-2020-0010.
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Growth performance, health status, and the radiated thermal temperatures of groups of piglets consuming non-medicated feed and in-feed antibiotics (chlortetracycline hydrochloride and tiamulin) were monitored continuously for up to 35 d, from weaning at 28 d of age until moving to commercial pens at approximately 63 d of age. There was a trend (P = 0.1) for body weight at the time of moving to be higher for the medicated animals. The average daily gain was higher in medicated piglets (P = 0.03). Radiated temperature variables were the maximum (Tmax) and the average (Tmean) pig temperatures, and both were higher for the medicated piglets (P < 0.0001). A threshold temperature was derived to partition the image and derive the background radiated temperature that was used to obtain the expected radiated temperature of the pigs. Temperature data were adjusted for environmental effects by expressing the residual temperature. The residual for Tmax (TmaxRes) and for Tmean (TmeanRes) were higher in medicated piglets (P < 0.0001). In-feed antibiotics were associated with increased growth rates and with an increase in radiated temperature variables, particularly those corrected for environmental conditions, possibly mediated through increased metabolic activity related to growth.
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K.SHARMA, R. K. SHARMA, S. CHANDER, and V. JILU. "Effects of weather parameters on Guava fruit fly (Bactrocera zonata) population at IARI, New Delhi." Journal of Agrometeorology 17, no. 2 (2015): 227–29. http://dx.doi.org/10.54386/jam.v17i2.1012.
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Relationship of each of the weather parameters viz., maximum temperature (Tmax), minimum temperature (Tmin), rainfall (RF), morning relative humidity (RH), evening relative humidity (RH 2,) and bright sunshine hours (BSS) of six years (2007-2012) at IARI (New Delhi) was individually explored with peaks of guava fruit fly, Bactrocera zonata MAT (Male Annihilation Technique) trap catches. Peaks of fruit fly trap catches exhibited significant correlation with Tmax, RH1, RH2, RF and BSS of April 1st week and Tmin of March 3rd week. Weather-based prediction model for guava fruit fly was developed by regressing peaks of fruit fly trap catches on mean values of different weather parameters of aforesaid weeks (R2=0.80). Of the weather parameters, only Tmax, Tmin, RH2 and BSS were found to be relevant through stepwise regression.
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Shrestha, Dibas, Shankar Sharma, Sandeep Bhandari, and Rashila Deshar. "Statistical Downscaling and Projection of Future Temperature and Precipitation Change in Gandaki Basin." Journal of Institute of Science and Technology 26, no. 1 (2021): 16–27. http://dx.doi.org/10.3126/jist.v26i1.37810.
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Understanding the present and future spatial and temporal variations of precipitation and temperature is important for monitoring climate-induced disasters. Satellite and global reanalysis data can provide evenly distributed climate data; however, they are still too coarse to resolve fundamental processes over complex terrains. The study applies global climate model CGCM4/CANESM2, to project future maximum temperature, minimum temperature, and precipitation across the cross-section of the Gandaki River basin, Nepal. Large scale atmospheric variables of the National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis (NCEP/NCAR) datasets are downscaled using Statistical Downscaling Model (SDSM) under different emission scenarios. For the variability and changes in maximum temperature (Tmax), minimum temperature (Tmin), and precipitation for future periods (2020s, 2050s, and 2080s), three different scenarios RCP2.6, RC4.5, and RCP8.5 of CGCM4 model were performed. The study revealed that both the temperature and precipitation would increase for three RCPs (representative concentration pathways) in the future. The highest increase in precipitation was found in the arid region compared to humid and sub-humid regions by the end of 2100. Similarly, the increase in mean monthly Tmin and Tmax was more pronounced in Jomsom station than Baglung and Dumkauli stations. Overall, a decrease in summer temperature and increase in winter temperature was expected for future periods across all regions. Further, spatial consistency was observed for Tmax and Tmin, whereas spatial consistency was not found for precipitation.