Novel Analytical Model of Mean Temperature and Experimental Research on the Rail Universal Rolling

For building the analytical model of mean temperature in rail universal rolling, the cross-section of workpieces and the profile of horizontal roll and vertical roll are simplified rationally. The mean temperature of the web of rail, the top of rail and the base of rail are considered individually. The temperature rises for plastic deformation and friction incorresponding deformation zone, the temperature drop for contact is calculated on the base of variation principle and energy conservation law. Then the mean temperature is obtained. For verifying the theoretical model, the 18 kg/m light rail universal rolling experiments are accomplished in Yanshan University Rolling Laboratory, China and the surface temperature is measured. The surface temperature is not exact enough to express the true temperature and the mean temperature can show the status of the true temperature basically. So the mean temperature can be used to express the true temperature and this theoretical model and its results can be applied as an important reference to control the temperature of rail universal rolling and the heat treatment of the rolled rail.

Empirical model for mean temperature and assessment of precipitable water vapor derived from GPS

The estimation of Precipitable Water Vapor （PWV） derived from Global Positioning System （GPS） data at the IGS site WUHN is assessed by comparing with PWV obtained from radiosonde data （No.57494） in Wuhan. The applicability of Saastamoinen （SAAS）, Hopfield and Black models used for estimating Zenith Hydrostatic Delay （ZHD） and Zenith Wet Delay （ZWD） and different models is verified in the estimation of GPS-derived PWV for the applied area. The experimental results demonstrated that ： 1 ） the precision of PWV estimated from Black model used for calculating ZHD （ ZHDs ） is lower than that of SAAS （ ZHDsAAs ） model and Hopfield model （ZHDn） with the RMS of 4. 16 ram; 2） the RMS of PWV estimated from SAAS model used for calculating ZWD （SAAS） is 3.78 ram; 3 ） the well-known Bevis model gives similar accuracy compared with the site-specific models for Tm in terms of surface temperature （ Ts ） and surface pressure （Ps）, which can reach the accuracy inside 1 mm in the GPS-derived PWV estimates.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Record-breaking High-temperature Outlook for 2023: An Assessment Based on the China Global Merged Temperature(CMST) Dataset

According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.

Meridional Distributions of Historical Zonal Averages and Their Use to Quantify the Global and Spheroidal Mean Near-Surface Temperature of the Terrestrial Atmosphere

The zonal averages of temperature (the so-called normal temperatures) for numerous parallels of latitude published between 1852 and 1913 by Dove, Forbes, Ferrel, Spitaler, Batchelder, Arrhenius, von Bezold, Hopfner, von Hann, and Börnstein were used to quantify the global (spherical) and spheroidal mean near-surface temperature of the terrestrial atmosphere. Only the datasets of Dove and Forbes published in the 1850s provided global averages below 〈T〉=14°C, mainly due to the poor coverage of the Southern Hemisphere by observations during that time. The global averages derived from the distributions of normal temperatures published between 1877 and 1913 ranged from 〈T〉=14.0°C (Batchelder) to 〈T〉=15.1°C (Ferrel). The differences between the global and the spheroidal mean near-surface air temperature are marginal. To examine the uncertainty due to interannual variability and different years considered in the historic zonal mean temperature distributions, the historical normal temperatures were perturbed within ±2σ to obtain ensembles of 50 realizations for each dataset. Numerical integrations of the perturbed distributions indicate uncertainties in the global averages in the range of ±0.3°C to ±0.6°C and depended on the number of available normal temperatures. Compared to our results, the global mean temperature of 〈T〉=15.0°C published by von Hann in 1897 and von Bezold in 1901 and 1906 is notably too high, while 〈T〉=14.4°C published by von Hann in 1908 seems to be more adequate within the range of uncertainty. The HadCRUT4 record provided 〈T〉≌?13.7°C for 1851-1880 and 〈T〉=13.6°C for 1881-1910. The Berkeley record provided 〈T〉=13.6°C and 〈T〉≌?13.5°C for these periods, respectively. The NASA GISS record yielded 〈T〉=13.6°C for 1881-1910 as well. These results are notably lower than those based on the historic zonal means. For 1991-2018, the HadCRUT4, Berkeley, and NASA GISS records provided 〈T〉=14.4°C, 〈T〉=14.5°C, and 〈T〉=14.5°C, respectively. The comparison of the 1991-2018 globally averaged near-surface temperature with those derived from distributions of zonal temperature averages for numerous parallels of latitude suggests no change for the past 100 years.

Analysis of the Weighted Mean Temperature of China Based on Sounding and ECMWF Reanalysis Data

Weighted mean temperature （Tin） is one of the most important conversion parameters for calculating precipitable water vapor by the signal path wet delay in ground-based GPS meteorology. This paper first discusses the Tm regression models for Hong Kong （HK） and the associated error statistics relative to the true values of Tm from the numerical method. The results show that there is little difference in precision between annual and seasonal Tm regression models for HK. The Bevis Tm-Ts （surface temperature） regression model is more suitable for northeastern China and the Qinghai-Tibetan Plateau than the local models. For areas lack of historical sounding data, the Kriging interpolation method and the ECMWF reanalysis product ERA-interim were employed to set up local Tm-Ts models. The results indicate that the Tm derived by the ERA-interim data coincides well with that by the sounding data, and the Kriging interpolation method can successfully obtain the coefficients of local Tm-Ts models, suggesting that these two approaches may serve as effective ways in the acquisition and localization of Tin.

ESTIMATES OF CLIMATE NOISES OF ANNUAL MEAN TEMPERATURES OVER CHINA

In this paper,a design to estimate climate noise of annual mean temperature has been made by means of the mini- mum interannual variance and effectively independent observations in time series.By using it the climate noises of annu- al mean surface air temperatures have been estimated based on the data from 1960 to 1991 in this country.The low val- ues of climate noises of annual mean temperatures are found in the southeastern Tibet Plateau,Yunnan,the Sichuan Ba- sin and south of the middle and lower reaches of the Changjiang River Valley.The high values are seen in the northwestern and northeastern China and the rest of the Tibet Plateau.A relatively low value region is in the southern Xinjiang.

Monthly Mean Temperature Prediction Based on a Multi－level Mapping Model of Neural Network BP Type

In terms of 34-year monthly mean temperature series in 1946-1979,the multi-level maPPing model of neural netWork BP type was applied to calculate the system's fractual dimension Do=2'8,leading tO a three-level model of this type with ixj=3x2,k=l,and the 1980 monthly mean temperture predichon on a long-t6rm basis were prepared by steadily modifying the weighting coefficient,making for the correlation coefficient of 97% with the measurements.Furthermore,the weighhng parameter was modified for each month of 1980 by means of observations,therefore constrcuhng monthly mean temperature forecasts from January to December of the year,reaching the correlation of 99.9% with the measurements.Likewise,the resulting 1981 monthly predictions on a long-range basis with 1946-1980 corresponding records yielded the correlahon of 98% and the month-tO month forecasts of 99.4%.

Temporal and spatial variation of annual mean air temperature in arid and semiarid region in northwest China over a recent 46 year period

We analyzed the 1961-2006 mean surface air temperature data of 138 stations in China’s northwest arid and semi-arid areas(CNASA),to measure climate change in terms of annual mean air temperature changes.We used methods of linear regression analysis,multinomial fitting,Empirical Or-thogonal Function(EOF),Rotated Empirical Orthogonal Function(REOF),Mann-Kendall,Glide T-examination,wavelet analysis and power spectrum analysis.The results show that(1) the warming rate of the annual mean air temperature in CNASA was 0.35oC/10a during the 1961-2006 study period.Some places in the west part of Xinjiang and east part of the Qinghai plateau,which is impacted by the terrain of leeward slope,exhibit smaller increasing trends.However,the majority of region has shown distinct warming in line with general global warming;(2) The standard deviation of the annual mean temperature distribution is non-uniform.The south Xinjiang and east Qinghai-south Gansu areas show relatively small standard deviations,but the inter-annual variation in annual mean air temperature in the greater part of the region is high;(3) Inner Mongolia,Shaanxi,Gansu,Ningxia and Tarim Basin are the areas where the temperature changes are most sensitive to the environment.The degree of uniformity in annual mean air temperature increase is higher in the arid and semi-arid area.From the early 1970s,the trend in tempera-ture changed from a decrease to an increase,and there was a marked increase in mean temperature in 1986.After that mean temperature went through a period of rapid increase.The entire area’s 10 hottest years all occurred in or since the 1990s,and 90% of various sub-districts’ hottest years also occurred after 1990.The process of temperature change appears to have a roughly 5-year and a 10-year cycle;(4) An-nual mean air temperature variation has regional differences.In Inner Mongolia-Xinjiang and Shaanxi-Gansu-Ningxia-Qinghai areas,the temperature variation in their northern areas was very different from that in their southern areas;(5) Using the REOF method we divided the region into 4 sub-regions:the Northern region,the Plateau region,the Southern Xinjiang region and the Eastern region.The region’s annual mean air temperature transition has regional differences.The Plateau and Southern Xinjiang re-gions got warmer steadily without any obvious acceleration in the rate of warming.The Northern region’s warming started about 5-years earlier than that of the low latitude Eastern region.The ’Startup region’ of the Qinghai-Tibet Plateau,appears to undergo temperature changes 3 to 10 years earlier than the other regions,and exhibits inter-decadal variations 1 to 2 years ahead of the other regions.

Study on the Influence of Piloti on Mean Radiant Temperature in Residential Blocks by 3-D Unsteady State Heat Balance Radiation Calculation

Piloti is commonly used in tropical and subtropical climate zones to get high wind velocity and create shadowed areas in order to optimize the living environment of residential blocks,but there are few studies to reveal the influence of piloti on the radiant environment of residential blocks systematically. Taking the city of Guangzhou as an example,using 3-D Unsteady State Heat Balance Radiation Calculation Method,this paper shows that the mean radiant temperature( MRT) under piloti area increases with the increase of piloti ratio,and especially when piloti ratio is equal to 100%,the MRT increase trend becomes sharp. The MRT of exposed area decreases with the increase of piloti ratio,especially when piloti ratio reaches 100%,the decrease trend of MRT becomes sharp,which offers the reference for the study on piloti design in subtropical climate zones and further research on living environment by CFD simulation in residential blocks.

Global Annual Mean Surface Air Temperature Anomalies and Their Link with Indian Summer Monsoon Failures

Analysis of the global mean annual temperature anomalies based on land and marine data for the last 88 years (1901-1988) of this century has been carried out with a view to find any relationship with failures in Indian summer monsoon rainfall. On the climatological scale (i.e. 30 years) it has been noticed that there is an abnormal increase in the frequency of drought years during epochs of global warming and cooling, while it is considerably less when global temperatures are near normal. Results are unchanged even when the data are filtered out for ENSO (El-Nino Southern Oscillation) effect.It has also been noticed that during warm and cold epochs in global temperatures the amount of summer monsoon rainfall decreases as compared to the rainfall during a normal temperature epoch.

Asymmetric Mean Annual Temperature Wavelets Surface Air Layer of Berlin for 1701-2021

The regularities of the dynamics of the average annual temperature of Ber­lin from 1701 to 2021 are revealed.A total of 65 wavelets were received.The temperature has a high quantum certainty,and the change in the aver­age annual temperature of Berlin was identified by a model that contains only two components for prediction.The basis of the forecast at 320 years makes it possible to look into the future until the year 2340.The forecast confirms the conclusions made in the CMIP5 report on global warming.With an increase in the number of components in the model up to five,the forecast is possible only until 2060.Therefore,the model with only two components is workable.The trend is characterized by a modified Man­delbrot equation showing exponential growth with a high growth rate of 1.47421.The wave equation also has an amplitude in the form of the Man­delbrot law(in mathematics,the Laplace law,in biology,the Zipf-Pearl law,in econometrics,the Pareto law),when the exponential growth activity is equal to 1.For 1701,the period of oscillation was 2×60.33333≈120.7 years.By 2021,the period decreased and became equal to 87.6 years.The trend is such that by 2340 the period of oscillation will decrease to 30.2 years.Such an increase in fluctuations indicates an imbalance in climate disturbances in temperature in Berlin.For Berlin,the last three years are characterized by sharp decreases in the average annual temperature from 11.8℃ to 10.5℃,i.e.by 12.4% in 2021.Therefore,the forecast is still unstable,as a further decrease in the average annual temperature of Berlin in the near future may change the picture of the forecast.

The Effect of High Day and Low Night Temperature on Pollen Production, Pollen Germination and Postharvest Quality of Tomatoes

Temperature integration where high day temperatures are compensated by lower night temperatures is one strategy that can be used to reduce energy consumption in greenhouses. Crop tolerance to temperature variation is a prerequisite for using such a strategy. Greenhouse experiments were conducted on tomatoes cvs, Capricia, Mecano and Cederico in order to investigate the effect of different day/night temperature regimes (24/17, 27/14 and 30/11℃) where the same mean temperature was maintained for the production and germination of pollen. In addition, fruit quality as determined by fruit firmness, dry matter content, soluble solids, titratable acids, and pH was examined at harvest and after seven and 14 days of storage. The 30/11℃ treatment significantly increased pollen production and germination compared to the 24/17℃ treatment, while the 27/14℃ treatment was generally in between the other two treatments. Fruits grown at the 27/14℃ treatment were significantly firmer, while fruits grown at 24/17℃ had higher dry matter content, soluble solids, and titratable acids compared to the other treatments. There were significant differences between cultivars with respect to firmness, dry matter, titratable acidity, and pH. The quality of the fruits changed during storage, but the storability of the tomatoes was not affected by preharvest temperature treatments. The overall conclusion was that the 27/14℃ treatment was superior to the other two temperature treatments with respect to the studied parameters.

Study on Temperature Changes in Jinan in Recent 30 Years

[ Objective] The aim was to study temperature changes in Jinan in recent 30 years. [ Method] Using temperature from 1981 to 2010 in six national ground meteorological observation stations in Jinan, and based on linear evaluation method, temperature changes in Jinan in recent 30 years were discussed. [ Result] The mean annual temperature, mean annual highest temperature and mean annual lowest temperature were rising in recent 30 years. Mean annual lowest temperature was increasing and its tendency rate was 0.502 ℃/10 a, followed by mean annual temperature whose tendency rate was 0.288℃/10 a. Mean annual highest temperature increased most slowly and its tendency rate was 0.144 ℃/10 a. The mean annual lowest temperature rose most significantly in Zhangqiu and its tendency rate was 1. 347℃/10 a. This indicated that the rising mean annual temperature in Jinan was due to the mean annual lowest temperature. The contribution of Zhangqiu City to the temperature changes in the entire Jinan was the largest. For single station, mean annual temperature, mean annual highest temperature and mean annual lowest temperature, temperature rising tendency was small and its contribution was the smallest. [ Conclusion] The study provided theoretical basis for the observation, diagnosis, evaluation and decision-making of climate changes in Jinan.

Climatic characteristics of high temperature in East China during 1961-2005

Based on the daily maximum temperature data covering the period 1961-2005, temporal and spatial characteristics and their changing in mean annual and monthly high temperature days（HTDs）and the mean daily maximum temperature（MDMT）during annual and monthly HTDs in East China were studied.The results show that the mean annual HTDs were 15.1 and the MDMT during annual HTDs was 36.3℃in the past 45 years.Both the mean annual HTDs and the MDMT during annual HTDs were negative anomaly in the1980s and positive anomaly in the other periods of time,oscillating with a cycle of about 12-15 years.The mean annual HTDs were more in the southern part,but less in the northern part of East China.The MDMT during annual HTDs was higher in Zhejiang,Anhui and Jiangxi provinces in the central and western parts of East China.The high temperature process（HTP） was more in the southwestern part,but less in northeastern part of East China.Both the HTDs and the numbers of HTP were at most in July,and the MDMT during monthly HTDs was also the highest in July.In the first 5 years of the 21st century,the mean annual HTDs and the MDMT during annual HTDs increased at most of the stations,both the mean monthly HTDs and the MDMT during monthly HTDs were positive anomalies from April to October,the number of each type of HTP generally was at most and the MDMT in each type of HTP was also the highest.

Effect of horizontal radiant temperature asymmetry on thermal comfort and environmental parameters in a warm sitting area

Taiwan is a hot and humid place;in addition,the sunlight is strong and sufficient,the naturally ventilated classrooms have large-area windows for better lighting and ventilation in Taiwan.However,subjects sitting close to the large-area windows will encounter the problem of radiant temperature asymmetry,which may cause local thermal discomfort during summer.Hence,this paper is to investigate the influence of horizontal radiant temperature asymmetry on the thermal sensation of subjects and the correlative variation of environmental parameters in a warm sitting area.The evaluation results show that the predicted mean vote(PMV)index can be used to predict the overall thermal sensation of a group of sedentary subjects in a warm environment with horizontal radiant temperature asymmetry;even subjects feel local discomfort on exposed parts of their body.The measured results of environmental parameters indicate that the averaged radiant temperature difference is about 4.6 ℃ from right shoulder to left shoulder;the temperature difference does not only cause correlative variations of other environmental parameters,but also result in thermal discomfort on the right cheeks and forearms of subjects in the warm sitting area.

Study on Ann-Based Multi-Step Prediction Model of Short-Term Climatic Variation

In the context of 1905–1995 series from Nanjing and Hangzhou, study is undertaken of estab-lishing a predictive model of annual mean temperature in 1996–2005 to come over the Changjiang (Yangtze River) delta region through mean generating function and artificial neural network in combination. Results show that the established model yields mean error of 0.45°C for their abso-lute values of annual mean temperature from 10 yearly independent samples (1986–1995) and the difference between the mean predictions and related measurements is 0.156°C. The developed model is found superior to a mean generating function regression model both in historical data fit-ting and independent sample prediction. Key words Climate trend prediction. Mean generating function (MGF) - Artificial neural network (ANN) - Annual mean temperature (AMT)

Empirical T_m modeling in the region of Guangxi

This paper presents three strategies for modeling the regional empirical Tm （the weighted mean tem- perature of the atmosphere） to obtain more accurate determinations in a regional empirical model that is better adapted to the geographical and climatic characteristics of the applied area. The proposed models utilize data from four radiosonde stations in Guangxi, at Nanning, Guilin, Wuzhou and Baise, over an 11 month period （from Jan. to Nov. of 2011 ）. The experimental results demonstrated the following： （1） there is no significant

Establishment and analysis of global gridded Tm-Ts relationship model

In ground-based GPS meteorology, Tm is a key parameter to calculate the conversion factor that can convert the zenith wet delay（ZWD） to precipitable water vapor（PWV）. It is generally acknowledged that Tm is in an approximate linear relationship with surface temperature Ts, and the relationship presents regional variation. This paper employed sliding average method to calculate correlation coefficients and linear regression coefficients between Tm and Ts at every 2°× 2.5° grid point using Ts data from European Centre for Medium-Range Weather Forecasts（ECMWF） and Tm data from ＂GGOS Atmosphere＂, yielding the grid and bilinear interpolation-based Tm Grid model. Tested by Tm and Ts grid data, Constellation Observation System of Meteorology, Ionosphere, and Climate（COSMIC） data and radiosonde data, the Tm Grid model shows a higher accuracy relative to the Bevis Tm-Ts relationship which is widely used nowadays. The Tm Grid model will be of certain practical value in high-precision PWV calculation.

Hall effects on hydromagnetic flow on an oscillating porous plate

In this paper, an analysis is made on the unsteady flow of an incompressible electrically conducting viscous fluid bounded by an infinite porous flat plate. The plate executes harmonic oscillations at a frequency n in its own plane. A uniform magnetic field Ho is imposed perpendicular to the direction of the flow. It is found that the solution also exists for blowing at the plate. The temperature distribution is also obtained by taking viscous and Joule dissipation into account. The mean wall temperature θo（O） decreases with the increase in the Hall parameter m. It is found that no temperature distribution exists for the blowing at the plate.