April-September minimum temperature reconstruction based on Sabina tibetica ring-width chronology in the central eastern Tibetan Plateau,China

Minimum temperatures have remarkable impacts on tree growth at high-elevation sites on the Tibetan Plateau,but the shortage of long-term and high-resolution paleoclimate records inhibits understanding of recent minimum temperature anomalies.In this study,a warm season(April–September)reconstruction is presented for the past 467 years(1550–2016)based on Sabina tibetica ring-width chronology on the Lianbaoyeze Mountain of the central eastern Tibetan Plateau.Eight warm periods and eight cold periods were identified.Long-term minimum temperature variations revealed a high degree of coherence with nearby reconstructions.Spatial correlations between our reconstruction and global sea surface temperatures suggest that warm season minimum temperature anomalies in the central eastern Tibetan Plateau were strongly influenced by large-scale ocean atmospheric circulations,such as the El Ni?o-Southern Oscillation and the Atlantic Multidecadal Oscillation.

Application of Machine-Learning-Based Objective Correction Method in the Intelligent Grid Maximum and Minimum Temperature Predictions

Post-processing correction is an effective way to improve the model forecasting result. Especially, the machine learning methods have played increasingly important roles in recent years. Taking the meteorological observational data in a period of two years as the reference, the maximum and minimum temperature predictions of Shenyang station from the European Center for Medium-Range Weather Forecasts (ECMWF) and national intelligent grid forecasts are objectively corrected by using wavelet analysis, sliding training and other technologies. The evaluation results show that the sliding training time window of the maximum temperature is smaller than that of the minimum temperature, and their difference is the largest in August, with a difference of 2.6 days. The objective correction product of maximum temperature shows a good performance in spring, while that of minimum temperature performs well throughout the whole year, with an accuracy improvement of 97% to 186%. The correction effect in the central plains is better than in the regions with complex terrain. As for the national intelligent grid forecasts, the objective correction products have shown positive skills in predicting the maximum temperatures in spring (the skill-score reaches 0.59) and in predicting the minimum temperature at most times of the year (the skill-score reaches 0.68).

Temporal and Spatial Variation and Distribution Characteristics of Maximum and Minimum Temperature from 1971 to 2008 in Tibet

Based on temperature data of meteorological stations from 1971 to 2008 in Tibet,the temporal and spatial variation of maximum andminimum temperature in Tibet was analyzed.The results showed that both maximum temperature andminimum temperature increased distinctly,the warming amplitude of winter was the highest among the four seasons,and next came spring.The increment ofminimum temperature was visibly over that of maximum temperature,particularlyminimum temperature in winter with significant increment.For spatial variation,maximum temperature in most stations increased except particular stations,while theminimum temperature in all stations rose.In addition,the space variation law ofminimum temperature,being more obvious thanminimum temperature,increased from southeast to northwest with different spatial changes in various seasons.From decadal variation,both maximum andminimum temperature appeared increase from 1970s to the first eight years in the 21st century,and the rise ofminimum temperature was significant greater than maximum temperature.The increase of maximum andminimum temperature was the highest from 2001 to 2008,whereas the lowest in 1970s.

Ratio of Gravitational Force to Electric Force from Empirical Equations in Terms of the Cosmic Microwave Background Temperature

Previously, we presented several empirical equations using the cosmic microwave background (CMB) temperature. Next, we propose an empirical equation for the fine-structure constant. Considering the compatibility among these empirical equations, the CMB temperature (Tc) and gravitational constant (G) were calculated to be 2.726312 K and 6.673778 × 10−11 m3∙kg−1∙s−2, respectively. Every equation could be explained in terms of the Compton length of an electron (λe), the Compton length of a proton (λp) and a. Furthermore, every equation could also be explained in terms of Avogadro’s number and the number of electrons in 1 C. However, the ratio of the gravitational force to the electric force cannot be uniquely determined when the unit of the Planck constant (Js) is changed. In this study, we showed that every equation can be described in terms of Planck constant. From the assumption of minimum mass, the ratio of gravitational force to electric force could be elucidated.

Algorithms for Empirical Equations in Terms of the Cosmic Microwave Background Temperature

Previously, we presented several empirical equations using the cosmic microwave background (CMB) temperature. Next, we propose an empirical equation for the fine-structure constant. Considering the compatibility among these empirical equations, the CMB temperature (Tc) and gravitational constant (G) were calculated to be 2.726312 K and 6.673778 × 10−11 m3∙kg−1∙s−2, respectively. Every equation can be explained numerically in terms of the Compton length of an electron (λe), the Compton length of a proton (λp) and α. Furthermore, every equation can also be explained in terms of the Avogadro number and the number of electrons at 1 C. We show that every equation can be described in terms of the Planck constant. Then, the ratio of the gravitational force to the electric force can be uniquely determined with the assumption of minimum mass. In this report, we describe the algorithms used to explain these equations in detail. Thus, there are no dimension mismatch problems.

Homogenized Daily Mean/Maximum/Minimum Temperature Series for China from 1960-2008

Inhomogeneities in the daily mean/maximum/ minimum temperature （Tm/Tmax/Tmin） series from 1960- 2008 at 549 National Standard Stations （NSSs） in China were analyzed by using the Multiple Analysis of Series for Homogenization （MASH） software package. Typical biases in the dataset were illustrated via the cases of Beijing （B J）, Wutaishan （WT）, Urumqi （UR） and Henan （HN） stations. The homogenized dataset shows a mean warming trend of 0.261/0.193/0.344℃/decade for the annual series of Tm/Tmax/Tmin, slightly smaller than that of the original dataset by 0.006/0.009/0.007℃/decade. However, considerable differences between the adjusted and original datasets were found at the local scale. The adjusted Tmin series shows a significant warming trend almost everywhere for all seasons, while there are a number of stations with an insignificant trend in the original dataset. The adjusted Tm data exhibit significant warming trends annually as well as for the autumn and winter seasons in northern China, and cooling trends only for the summer in the middle reaches of the Yangtze River and parts of central China and for the spring in southwestern China, while the original data show cooling trends at several stations for the annual and seasonal scales in the Qinghai, Shanxi, Hebei, and Xinjiang provinces. The adjusted Tmax data exhibit cooling trends for summers at a number of stations in the mid-lower reaches of the Yangtze and Yellow Rivers and for springs and winters at a few stations in southwestern China, while the original data show cooling trends at three/four stations for the annual/autumn periods in the Qinghai and Yunnan provinces. In general, the number of stations with a cooling trend was much smaller in the adjusted Tm and Tmax dataset than in the original dataset. The cooling trend for summers is mainly due to cooling in August. The results of homogenization using MASH appear to be robust; in particular, different groups of stations with consideration of elevation led to minor effects in the results.

Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China

In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures （Tmax and Tmin） carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ （10 yr）-1 ＋ 0.269℃ （10 yr）-1 and 0.578℃ （10 yr）-1 ＋ 0.211℃ （10 yr）-1 in February,and the least being 0.022℃ （10 yr）-1 ＋ 0.085℃ （10 yr）-1 and 0.104℃ （10 yr）-1 ＋0.070℃ （10 yr）-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.

Minimum and Maximum Temperature Trends in Congo-Brazzaville: 1932-2010

Maximum and minimum temperatures time series of Congo-Brazzaville are analyzed for trend and discontinuities over the period 1932 to 2010. Temperatures series show an irregular increase. A total of 8 synoptic stations show positive trends in their annual mean maximum temperature series, and 7 of them are significant, with higher trends for urban stations. Annual mean minimum temperature showed 6 stations having positive trends. This increase is in relation with observations at regional scale. However, the differences are observed between large towns (Brazzaville and Pointe-Noire), and small or rural towns (Dolisie, Sibiti, Impfondo, Djambala). Trends in diurnal temperature range (DTR) are large positive trends in maximum temperature that are mainly observed in cities. The curve of DTR shows a decreasing trend which indicates the increasing of minimum temperatures. The effects of urbanization on temperature trends are investigated. Most stations regarded as urban stations are still useful for trend analysis;being situated on the suburban of the studied cities, they are therefore, not substantially influenced by the urban heat island.

Asymmetrical Change Characteristics of Maximum and Minimum Temperatures in Shangqiu in Recent 50 Years

[Objective] The research aimed to analyze temporal and spatial variation characteristics of temperature in Shangqiu City during 1961-2010.[Method] Based on temperature data in eight meteorological stations of Shangqiu during 1961-2010,by using trend analysis method,the temporal and spatial evolution characteristics of annual average temperature,annual average maximum and minimum temperatures,annual extreme maximum and minimum temperatures,daily range of annual average temperature in Shangqiu City were analyzed.M-K method was used to determine mutation year of temperature.[Result] The annual average temperature,annual average minimum temperature and annual extreme minimum temperature respectively rose at 0.122,0.255 and 0.488 ℃/10 a.The variation trend of annual average maximum temperature wasn’t obvious.The daily range of annual average temperature and annual extreme maximum temperature respectively declined at-0.217 and-0.292 ℃/10 a.Seen from spatial distribution,the increase amplitudes of annual average temperature,annual average minimum temperature and annual extreme minimum temperature were all large in the east and small in the west.The decrease amplitude of daily range of annual average temperature was large in the east and small in the west.The decrease amplitude of annual extreme maximum temperature was large in the west and small in the east.The annual average maximum temperature had trends of increase and decrease.The annual average temperature,annual average minimum temperature and daily range of annual average temperature all mutated in 1997.The annual average maximum temperature didn’t have obvious mutation point.The annual extreme maximum temperature mutated in 1973.The annual extreme minimum temperature respectively mutated in 1989 and 1999.[Conclusion] The research played important guidance significances in adjustment of agricultural production structure,regional climate planning,reasonably using climate resource and replying climate change in Shangqiu City.

Analysis on the Spatial and Temporal Distribution of Extremely Maximum Temperature in Liaoning Province Based on REOF

By selecting the daily maximum temperatures during 1961-2005 in 35 representative stations in Liaoning Province, the temporal and spatial distribution characteristics of extremely maximum temperature event were studied. By using REOF, the mean-square deviation and so on, the variation and distribution situation of extremely maximum temperature in the different regions of Liaoning were reflected. The results showed that the extremely maximum temperature in Liaoning Province could be divided into 3 regions where were respectively the northeast area, the west and the northwest area, the south and the southeast area. The distribution characteristic of extremely maximum temperature threshold value in Liaoning Province was basically consistent with the distribution characteristic of average temperature. The zone where the extremely maximum temperature threshold was relatively high was in the northwest area of Liaoning, and the low threshold zone was in the southeast area and most areas in the east. The variation of extremely maximum temperature in winter was the greatest and in summer was the smallest. The variation of extremely maximum temperature days was the greatest in summer and wasn’t great in spring, autumn, winter.

Effects of Body Weight and Water Temperature on Maximum Food Consumption of JuvenileSebastodes fuscescens (Houttuyn)

Maximum rate of food consumption (C max) was determined for juvenile Sebastodes fuscescens (Houttuyn) at water temperature of 10, 15, 20 and 25℃. The relationships of C max to the body weight (W) at each temperature were described by a power equation: lnC max = a + b lnW. Covariance analysis revealed significant interaction of the temperature and body weight. The relationship of adjusted C max to water temperature (T) was described by a quadratic equation: C max =-0.369 + 0.456T - 0.0117T 2. The optimal feeding temperature calculated from this equation was 19.5℃. The coefficients of the multiple regression estimation relating C max to body weight (W) and water temperature (T) were given in the Table 2.

Effect of elevated temperature and silica sand particle size on minimum fluidization velocity in an atmospheric bubbling fluidized bed

The impact of temperature and particle size on minimumfluidizing velocity was studied and analyzed in a small pilot scale of bubbling fluidized bed reactor.This study was devoted to providing some data about fluidization to the literature under high temperature conditions.The experiments were carried out to evaluate the minimum fluidizing velocity over a vast range of temperature levels from 20℃ to 850℃ using silica sand with a particle size of 300-425μm,425-500μm,500-600μm,and 600-710μm.Furthermore,the variation in the minimumfluidized voidage was determined experimentally at the same conditions.The experimental data revealed that the Umf directly varied with particle size and inversely with temperature,whileεmf increases slightly with temperature based on the measurements of height at incipient fluidization.However,for all particle sizes used in this test,temperatures above 700℃ has a marginal effect on Umf.The results were compared with many empirical equations,and it was found that the experimental result is still in an acceptable range of empirical equations used.In which,our findings are not well predicted by the widely accepted correlations reported in the literature.Therefore,a new predicted equation has been developed that also accounts for the affecting of mean particle size in addition to other parameters.A good mean relative deviation of 5.473% between the experimental data and the predicted values was estimated from the correlation of the effective dimensionless group.Furthermore,the experimental work revealed that the minimum fluidizing velocity was not affected by the height of the bed even at high temperature.

Performance evaluation of minimum quantity lubrication by vege-table oil in terms of cutting force,cutting zone temperature,tool wear,job dimension and surface finish in turning AISI-1060 steel

In all machining processes, tool wear is a natural phenomenon and it leads to tool failure. The growing demands for high productivity of machining need use of high cutting velocity and feed rate. Such machining inherently produces high cutting temperature, which not only reduces tool life but also impairs the product quality. Metal cutting fluid changes the performance of machining operations because of their lubrication, cooling and chip flushing functions, but the use of cutting fluid has become more problematic in terms of both employee health and environmental pollution. The minimization of cutting fluid also leads to economical benefits by way of saving lubricant costs and workpiece/tool/machine cleaning cycle time. The concept of minimum quantity lubrication (MQL) has been suggested since a decade ago as a means of addressing the issues of environmental intru- siveness and occupational hazards associated with the airborne cutting fluid particles on factory shop floors. This paper deals with experimental investigation on the role of MQL by vegetable oil on cutting temperature, tool wear, surface roughness and dimen- sional deviation in turning AISI-1060 steel at industrial speed-feed combinations by uncoated carbide insert. The encouraging results include significant reduction in tool wear rate, dimensional inaccuracy and surface roughness by MQL mainly through reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interaction.

The deconvolution of lunar brightness temperature based on the maximum entropy method using Chang'e-2 microwave data

A passive and multi-channel microwave sounder onboard the Chang＇e-2 orbiter has successfully acquired microwave observations of the lunar surface and subsurface structure. Compared with the Chang＇e-1 orbiter, the Chang＇e-2 orbiter obtained more accurate and comprehensive microwave brightness temperature data, which are helpful for further research. Since there is a close relationship between mi- crowave brightness temperature data and some related properties of the lunar regolith, such as the thickness, temperature and dielectric constant, precise and high resolution brightness temperature data are necessary for such research. However, through the detection mechanism of the microwave sounder, the brightness temperature data ac- quired from the microwave sounder are weighted by the antenna radiation pattern, so the data are the convolution of the antenna radiation pattern with the lunar brightness temperature. In order to obtain the real lunar brightness temperature, a deconvolution method is needed. The aim of this paper is to solve the problem associated with per- forming deconvolution of the lunar brightness temperature. In this study, we introduce the maximum entropy method （MEM） to process the brightness temperature data and achieve excellent results. The paper mainly includes the following aspects： first, we introduce the principle of the MEM; second, through a series of simulations, the MEM has been verified as an efficient deconvolution method; and third, the MEM is used to process the Chang＇e-2 microwave data and the results are significant.

Effect of Temperature on Frost-Free Days and Length of Crop Growing Season across Southern Ontario

Climate change has an impact on various climatic variables. In this study our focus is mainly on temperature characteristics of climate parameter. In temperate and humid regions like southern Ontario, the effect of climate change on Frost-free days in winter is distinctive. The average annual temperature is going upward but the extreme increase is in the winter temperature. Winter average temperature is going up by about 2˚C. However, extreme daily minimum temperature is going up by more than 3˚C. This climate effect has a great impact on the nature of precipitation and length of frost-free days. The snowfall over winter months is decreasing and the rainfall is increasing. However, the number of frost-free days during late fall months, early winter months, late winter months and early spring months are increasing. This result reveals an increase in length of the growing season. This research focuses on the effect of change in climatic variables on Frost-free days in Southern Ontario. Therefore, special attention should be given to the effect of change in climate Frost-free conditions on length of crop growing in winter season for potential investigation.

Study on Refined Forecast Method of Daily Maximum Temperature in Wugang City from July to September

[Objective] The aim was to study the refined forecast method of daily highest temperature in Wugang City from July to September. IM[ethod] By dint of ECMWF mode product and T231 in 2009 and 2010 and daily maximum temperature in the station in corresponding period, multi-factors similar forecast method to select forecast sample, multivariate regression multi-mode integration MOS method, after dynamic corrected mode error and regression error, dynamic forecast equation was concluded to formulate the daily maximum temperature forecast in 24 -120 h in Wugang City from July to September. [ Result] Through selection, error correction, the daily maximum temperature equation in Wugang City from July to September was concluded. Through multiple random sampling, F test was made to pass test with significant test of 0.1. [ Conclusionl The method integrated domestic and foreign forecast mode, made full use of useful information of many modes, absorbed each others advantages, con- sidered local regional environment, lessen mode and regression error, and improved forecast accuracy.

Last Glacial Maximum Sea Surface Temperatures: A Model-Data Comparison

In this study,the authors investigated changes in Last Glacial Maximum （LGM） sea surface temperature （SST） simulated by the Paleoclimate Modelling Intercomparison Project （PMIP） multimodels and reconstructed by the Multiproxy Approach for the Reconstruction of the Glacial Ocean Surface （MARGO） project,focusing on model-data comparison.The results showed that the PMIP models produced greater ocean cooling in the North Pacific and Tropical Ocean than the MARGO,particularly in the northwestem Pacific,where the modeldata mismatch was larger.All the models failed to capture the anomalous east-west SST gradient in the North Atlantic.In addition,large discrepancies among the models were observed in the mid-latitude ocean,particularly with models in the second phase of the PMIP.Although these models showed better agreement with the MARGO,the latest models in the third phase of the PMIP did not show substantial progresses in simulating LGM ocean surface conditions.That is,improvements in the modeling community are still needed to describe SST for a better understanding of climate during the LGM.

Prediction of Minimum Spouting Velocity at Elevated Pressures and Temperatures

Minimum spouting velocity （Ums） is one of the most important flow characteristics for proper design and operation of spouted bed reactors. Many correlations for Ums have been published since spouted bed technology was initiated in 1955. In this paper, a new correlation is developed for Ums based on 767 published experimental data covering both high pressure and high temperature conditions. The calculated and the measured results of Ums are in better agreement than other published correlations.

Short-time Forecast Method of Winter Minimum Temperature in the Northern Area of Fujian

[Objective] The research aimed to study the short-time forecast method of winterminimum temperature in the northern area of Fujian.[Method] By analyzing the variation trends and distribution characteristics of extremely and averageminimum temperatures in northern Fujian in winter during 1969-2008,the relative meteorological factors which affected the low temperature weather in winter were found.The influences of relative meteorological factors on winterminimum temperature and the forecast method were summarized by combining with the climate characteristics in northern Fujian.[Result] Winterminimum temperature in Guangze and Pucheng in the north of northern Fujian was the lowest.The second one was in Shaowu,Wuyishan,Jianyang,Songxi and Zhenghe.Theminimum temperature in Jian’ou and Shunchang was higher and was the highest in Yanping.Theminimum temperature mainly depended on the temperature reduction degree from the afternoon to the night.The temperature reduction degree varied with the sky condition and cold air intensity.The temperature reduction included the advection,radiation,advection-radiation and non-advection-radiation types.The temperature had the different reduction characteristics under the different sky conditions.The forecast ofminimum temperature should be carried out based on the weather typing.Meanwhile,the successful forecast key ofminimum temperature was grasping the shift pathway and speed of cold air.[Conclusion] The research provided the theory basis for improving the forecast accuracy of winterminimum temperature.

Quantification of relationship between annual daily maximum temperature and annual daily maximum rainfall in South Australia

The empirical relationship between annual daily maximum temperature(ADMT)and annual daily maximum rainfall(ADMR)was investigated.The data were collected from four weather stations located in Adelaide,South Australia,from 1988 to 2017.Due to the influence of sea surface temperature on rainfall and temperature,the distance from the weather station to the sea was considered in the selection of weather stations.Two weather stations near the sea and two inland weather stations were selected.Three non-parametric statistical tests(Kruskal–Wallis,Mann–Whitney,and correlation)were applied to perform statistical analysis on the ADMT and ADMR data.It was revealed that the temperature and rainfall in South Australia varies according to weather station location.The distance from the sea to the weather station was found to have limited influence on temperature and rainfall.Meanwhile,with the 0.05 level of significance,the association between ADMT and ADMR near sea stations is not as significant as the association between the two inland weather stations.It is relatively unrealistic to use ADMR to predict ADMT,or vice versa,since their correlation is not statistically significant(Spearman’s rank correlation coefficient:−0.106).