Average temperature calculation for straight single-row-piped frozen soil wall

The average temperature of frozen soil wall is an essential parameter in the process of design, construction, and safety manage- ment of artificial ground freezing engineering. It is the basis of calculating frozen soil＇s mechanical parameters, fiarther prediction of bearing capacity and, ultimately, safety evaluation of the frozen soil wall. Regarding the average temperature of sin- gle-row-piped frozen soil wall, this paper summarizes several current calculation methods and their shortcomings. Furthermore, on the basis of Bakholdin＇s analytical solution for the temperature field under straight single-row-piped freezing, two new calcula- tion models, namely, the equivalent trapezoid model and the equivalent triangle model, are proposed. These two approaches are used to calculate the average temperature of a certain cross section which indicates the condition of the whole frozen soil wall. Considering the possible parameter range according to the freezing pipe layout that might be applied in actual construction, this paper compares the average temperatures of frozen soil walls obtained by the equivalent trapezoid method and the equivalent tri- angle method with that obtained by numerical integration of Bakholdin＇s analytical solution. The results show that the discrepancies are extremely small and these two new approaches are better than currently prevailing methods. However, the equivalent triangle method boasts higher accuracy and a simpler formula compared with the equivalent trapezoid method.

Study on Prediction Model for Spatial Distribution of the Average Temperature Based on GIS——Take Hainan Island as an Example

[ Objectivel The research aimed to study prediction model for spatial distribution of the average temperature based on GIS. [ Method l Average temperature over the years as research object, based on Ordinary Kriging （OK）, Inverse Distance Weight （ IDW）, SPLINE and Mixed In- terpolation （MLR）, monthly temperature data from 1979 to 2008 at 18 long-term meteorological observation stations in Hainan Island were conduc- ted spatial grid treatment. Via contrasts and analyses on different interpolation methods, the optimum interpolation method for average temperature over the years in Hainan Island was selected. [ Resuitl By error analyses of the four interpolation methods for average temperature in recent 30 years in Hainan Island, it was found that accuracy was MLR 〉 IDW 〉 OK 〉 SPLINE. Spatial interpolation effect of MLR was the best for average temperature in Hainan Island. Spatial distribution of the average temperature in Halnan Island had obvious south-high-north-low latitudinal zonality and vertical zonality of gradually declining as altitude rise. In addition, temperature along coast was slightly higher than that in inland. Lapse rate of the temperature in each month in Hainan Island was 0.38 -0.85℃/100 m, and lapse rate of the annual average temperature was about 0.74 ℃/ 100 m. In different areas, lapse rate of the temperature as altitude was different at different time. [ Condusion] The research provided basis for ob- taining continuous distribution situation of the agricultural meteorological factor and establishing accurate prediction model of the spatial distribution in Hainan Island.

Analysis on Change Characteristics of the Average Temperature in Sichuan in 50 Years

[Objective] The research aimed to analyze change characteristics of the average temperature in Sichuan in 50 years.[Method] By using average temperature data at 156 stations of Sichuan from 1961 to 2010,interannual and interdecadal evolution characteristics,regional and seasonal differences of the average temperature in Sichuan in 50 years were analyzed.[Result] Variations of the average temperatures in the whole province and each climatic region in 50 years all presented rise trends.Rise amplitude of the average temperature was obvious in the prior 10 years of the 21st century.Rise amplitude of the temperature was 0-0.5 ℃ in 48.7% of stations in the whole province,and was 0.5-1.0 ℃ in 32.3% of stations.Rise amplitude of the temperature was the maximum in winter.The second one was in spring,and the minimum was in autumn.The annual average temperature in the whole province in 50 years presented east-high-west-low spatial distribution.The regional difference was from-1.2 to 20.9 ℃,and temperature difference was 22.1 ℃.Interannual variation of the average temperature from 1961 to 1997 in the whole province was relatively stable.After that,it presented obvious fluctuation rise trend.Interdecadal variation of the average temperature from the 1960s to the 1990s was relatively stable,and average temperatures were from 8.56 to 8.86 ℃.The maximum interdecadal average temperatures in the whole province and each climatic region all emerged in the prior 10 years of the 21st century,while emergence decades of the minimums were different.[Conclusion] The research provided reference for analyzing climatic change characteristics in Sichuan.

Quantum Atmospheric Biophysics: A Comparison of Four Weather Stations in India on Average Monthly Temperatures Since 1892 and Forecasts to 2150

The identification method revealed asymmetric wavelets of dynamics, as fractal quanta of the behavior of the surface air layer at a height of 2 m, according to the average monthly temperature at four weather stations in India (Srinagar, Jolhpur, New Delhi and Guvahati). For Srinagar station, the maximum for all years is observed in July, for Jolhpur and New Delhi stations it shifts to June, and for Guvahati it shifts to August. With a high correlation coefficient of 0.9659, 0.8640 and 0.8687, a three-factor model of the form was obtained. The altitude, longitude and latitude of the station are given sequentially. The hottest month for Srinagar over a period of 130 years is in July. At the same time, the temperature increased from 23.4 °C to 24.2 °C (by 3.31%). A noticeable decrease in the intensity of heat flows in June occurred at Jolhpur (over 125 years, a decrease from 36.2 °C to 33.3 °C, or by 8.71%) and New Delhi (over 90 years, a decrease from 35.1 °C to 32.4 °C, or by 7.69%). For almost 120 years, Guvahati has experienced complex climate changes: In 1902, the hottest month was July, but in 2021 it has shifted to August. The increase in temperature at various stations is considered. At Srinagar station in 2021, compared to 1892, temperatures increased in June, September and October. Guvahati has a 120-year increase in December, January, March and April. Temperatures have risen in February, March and April at Jolhpur in 125 years, but have risen in February and March at New Delhi Station in 90 years. Despite the presence of tropical evergreen forests, the area around Guvahati Station is expected to experience strong warming.

Extraction of the key infrared radiation temperature features concerning stress and crack evolution of loaded rocks

The infrared radiation temperature(IRT)variation concerning stress and crack evolution of rocks is a critical focus in rock mechanics domain and engineering disaster warning.In this paper,a methodology to extract the key IRT features related to stress and crack evolution of loaded rocks is proposed.Specifically,the wavelet denoising and reconstruction in thermal image sequence(WDRTIS)method is employed to eliminate temporal noise in thermal image sequences.Subsequently,the adaptive partition temperature drift correction(APTDC)method is introduced to alleviate temperature drift.On this basis,the spatial noise correction method based on threshold segmentation and adaptive median filtering(OTSU-AMF)is proposed to extract the key IRT features associated with microcracks of loaded rocks.Following temperature drift correction,IRT provides an estimation of the thermoelastic factor in rocks,typically around 5.29×10^(-5) MPa^(-1) for sandstones.Results reveal that the high-temperature concentrated region in cumulative thermal images of crack evolution(TICE)can elucidate the spatiotemporal evolution of localized damage.Additionally,heat dissipation of crack evolution(HDCE)acquired from TICE quantifies the progressive failure process of rocks.The proposed methodology enhances the reliability of IRT monitoring results and provides an innovative approach for conducting research in rock mechanics and monitoring engineering disasters.

Average Annual Temperature Changes in the Holocene in China

Abstract: In 1876 Blytt proposed a post-glacial climatic classification, maintaining that the then temperature fluctuated 1–2°C higher or lower than that today. Lamb (1969) held that in Europe “the axis of the subtropical high pressure belt was generally displaced north by about 10° latitudes” during the Hypsithermal and that the temperature was three to six times higher than that in the postglacial period.

Quantum Biophysics of the Atmosphere:Asymmetric Wavelets of the Average Annual Air Temperature of Irkutsk for 1820-2019

The regularities of the dynamics of the average annual temperature of Irkutsk from 1820 to 2019 were revealed.It is proposed to use the sum of temperatures.However,this indicator requires the continuity of the dynamic series,so for Irkutsk the sum of temperatures could be accepted only from 1873.The first three terms of the general wavelet model gave a very high correlation coefficient of 0.9996.The second indicator is a moving average,calculated as the ratio of the sum of temperatures to the current time.Here the first three wavelets gave a correlation coefficient of 0.9962.In the dynamics of the average annual temperature from 1820 to 2019,86 wavelets were obtained,of which 47 affect the future.The temperature has a high quantum certainty,and the change in the average annual temperature of Irkutsk is obtained up to a measurement error of 0.05℃,and the identification process occurs as a full wavelet analysis.The basis of the forecast in 200 years makes it possible to replace the non-linear two-term trend with an oscillatory perturbation.With an increase in the number of terms in the model,the ordinate of the average annual temperature increases:for three terms,the temperature interval is from-2.95℃ to 2.61℃;for 12 members from -4.06℃ to 4.02°C;for the forecast for 47 members for 2020-2220,from -4.62℃ to 4.40°C.

Analysis of Temperature Variation in Zhangqiu City during the Past 30 Years

[Objective] This study aimed to analyze the characteristics of temperature variation in Zhangqiu City during the past 30 years. [Method] Variation characteristics of average annual maximum temperature, average annual temperature and average annual minimum temperature in Zhangqiu City during the past 30 years were analyzed by using related temperature data during 1981 -2010 collected from National Meteorological Observation Station in Zhangqiu. [Result] Average annual maximum temperature, average annual temperature and average annual minimum temperature in Zhangqiu City showed an upward trend; average annual minimum temperature showed the most significant increasing tendency, with a tendency rate of 1.347 ℃/10 a; followed by average annual temperature; average annual maximum temperature showed the slowest increasing tendency, with a tendency rate of 0.062 ℃/10 a, indicating that the increase of average annual temperature mainly depended on the contribution of average annual minimum temperature. [Conclusion] This study provides reference and scientific basis for climate change monitoring, diagnosis, assessment, forecast and decision-making in Zhangqiu City.

Wavelet Analysis of Average

The identification method in the CurveExpert-1.40 software environment revealed asymmetric wavelets of changes in the average monthly temperature of New Delhi from 1931 to 2021.The maximum increment for 80 years of the average monthly temperature of 5.1℃was in March 2010.An analysis of the wave patterns of the dynamics of the average monthly temperature up to 2110 was carried out.For forecasting,formulas were adopted containing four components,among which the second component is the critical heat wave of India.The first component is the Mandelbrot law(in physics).It shows the natural trend of decreasing temperature.The second component increases according to the critical law.The third component with a correlation coefficient of 0.9522 has an annual fluctuation cycle.The fourth component with a semi-annual cycle shows the influence of vegetation cover.The warming level of 2010 will repeat again in 2035-2040.From 2040 the temperature will rise steadily.June is the hottest month.At the same time,the maximum temperature of 35.1℃in 2010 in June will again reach by 2076.But according to the second component of the heat wave,the temperature will rise from 0.54℃to 16.29°C.The annual and semi-annual cycles had an insignificant effect on the June temperature dynamics.Thus,the identification method on the example of meteorological observations in New Delhi made it possible to obtain summary models containing a different number of components.The temperature at a height of 2 m is insufficient.On the surface,according to space measurements,the temperature reaches 55°C.As a result,in order to identify more accurate asymmetric wavelets for forecasting,the results of satellite measurements of the surface temperature of India at various geographical locations of meteorological stations are additionally required.

Study on the Characteristics of Changes in Air Temperature and Precipitation in Shenyang in Recent 50 Years

Based on the data of monthly average air temperature,extreme maximum,minimum air temperature and precipitation of Shenyang from 1960 to 2009,the climate changes and its characteristics in Shenyang in recent 50 years were comprehensively analyzed and studied.The results showed that the increasing trend of air temperature in recent 50 years was obvious.With the rising of the air temperature,the precipitation in Shenyang City showed a decreasing trend.

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.

Linear Global Temperature Correlation to Carbon Dioxide Level, Sea Level, and Innovative Solutions to a Projected 6°C Warming by 2100

Too many climate committees, conferences, articles and publications continue to suggest a one and a half (1.5°C) to two degrees (2°C) Celsius as an achievable global limit to climate changes without establishment of any causal link to the proposed anti-warming mechanism. A comprehensive review has found instead that observationally informed projections of climate science underlying climate change offer a different outlook of five to six-degree (5°C - 6°C) increase as “most accurate” with regard to present trends, climate history and models, yielding the most likely outcome for 2100. The most causative triad for the present warming trend from 1950 to the present is identified in this paper: 1) the tripling (3×) of world population;2) the quadrupling (4×) of carbon emissions;and 3) the quintupling (5×) of the world energy consumption. This paper presents a quantitative, linear global temperature correlation to carbon dioxide levels that has great predictive value, a short temporal feedback loop, and the finding that it is also reversible. The Vostok ice core temperature and CO2 values for the past 400,000 years, with past sea level estimates have produced the sufficiently evidential “Hansen’s Graph”. Detailed analysis results in an equation for global average temperature change and an indebted, long-term sea level rise, from even a 20 ppm of CO2 change above 290 ppm, commonly taken as a baseline for levels before 1950. Comparison to the well-known 800,000 year old Dome C ice core is also performed. The best-performing climate change models and observational analysis are seen to project more warming than the average model often relied upon. World atmosphere, temperature, and sea level trends for 2100 and beyond are analyzed. A laboratory experiment proves the dramatic heat-entrapment capability of CO2 compared to pure air, which yields insights into the future global atmospheric system. Policy-relevant climate remediation, including gigaton carbon capture, zero and negative emissions and positive individual action, are reviewed and updated, with recommendations.

Observed and Future Changes in the Temperature of the State of Jalisco, México Using Climdex and PRECIS

In the present study we analyzed the average and extreme temperatures observed and simulated by regional models in the State of Jalisco, Mexico. Data of daily mean, minimum and maximum temperatures of 208 stations distributed all over the State during the period 1971-2000 have been used to study the observed changes in the values of average and extreme temperatures. In addition, an assessment of future scenarios for the average and extreme temperatures associated with the increase in the concentration of greenhouse gases (GHG) was performed using simulations of a PRECIS (Providing Regional Climate for Impact Studies) regional climate modeling to create the climate for present (1971-2000), and future projections for the years 2020, 2050 and 2080. Observational analysis of the 208 stations suggests warming through increased intensity and frequency of hot events, with a decrease in the frequency of cold events. More than 35% to 76% of the stations have a tendency to a decrease in the number of cold events and 39% to 64% of the stations show a growing trend in the hot events. The percentage of stations showing warming through the indices of intensity of the highest maximums, lowest minimum temperatures is 37% to 70% and 30% to 65% of the stations, respectively. Observational analysis for the State of Jalisco as a whole also shows similar results. Anomalies in the average and extreme temperatures per month during the data period show an increase (decrease) in the frequency of hot (cold) events for every month. In general, PRECIS simulations under both scenarios A1B and A2 indicate an increase in warm events and decrease of cold extreme events towards the end of the 21st century. Both show similar patterns, but the scenario A2 shows slightly lower magnitudes of projected changes. Temperatures are likely to increase all year, but it is expected that changes in summer will be more prominent.

Impacts of climate change on the yields of leguminous crops in the Guinea Savanna agroecological zone of Ghana

The impacts of climate change on crop yields are receiving renewed interest,with focus on cereals and staple crops at the regional and national scales.Yet,the impacts of climate change on the yields of leguminous crops in the local context has not been explored.Thus,an in-depth understanding of climate change in the local context may support the design of locally relevant adaptation responses to current and future climate risks.This study examined the impacts of climate variables(annual rainfall,annual average temperature,rainfall indices(rainfall onset,rainfall cessation,and the length of rainy days),and the number of dry days)on the yields of leguminous crops(groundnuts,cowpeas,and soybeans)in the Guinea Savanna agroecological zone of Ghana during the period of 1989-2020.The data were analysed using Mann-Kendall’s trend,Sen’s slope test,correlation analysis,and Multiple Regression Analysis(MRA).The findings revealed that annual rainfall,annual average temperature,rainfall onset,rainfall cessation,and the length of rainy days,and the number of dry days all showed varied impacts on the yields of groundnuts,cowpeas,and soybeans.The trend analysis detected a marginal decrease in the amount of rainfall,rainfall onset,and the number of dry days from 1989 to 2020(P>0.050).Annual average temperature and the length of rainy days substantially varied(P<0.050)from 1989 to 2020,showing an increasing trend.The findings also showed a marked upward trend for the yields of groundnuts,cowpeas,and soybeans during 2005-2020.The climate variables analysed above increased the yields of groundnuts,cowpeas,and soybeans by 49.0%,55.0%,and 69.0%,respectively.The yields of groundnuts,cowpeas,and soybeans fluctuated with the variability of 30.0%,28.0%,and 27.0%from 2005 to 2020,respectively.The three leguminous crops under study demonstrated unpredictable yields due to the variations of annual rainfall,annual average temperature,rainfall onset,rainfall cessation,the length of rainy days,and the number of dry days,which stressed the need for agricultural diversification,changing planting dates,using improved seed variety,and irrigation to respond to climate change.The results of this study implied that climate change considerably impacts crop production in the Guinea Savanna agroecological zone of Ghana,emphasizing the urgency of locally based and farmer-induced adaptation measures for food security and resilient agricultural systems.

Analysis of Spatial Distribution of Agricultural Meteorological Conditions in Sanjiang Plain during Nearly 50 Years

[ Objective] The study aimed to analyze the spatial distribution of agricultural meteorological conditions in Sanjiang Plain during nearly 50 years. [ Method] Accumulated temperature of Sanjiang Plain was computed based on meteorological observation data from different meteorological stations in Sanjiang Plain, including temperature, precipitation, sunshine time, etc. A spatial interpolation map involving varieties of meteorological elements in neady 50 years was generated based on the Kriging interpolation, and the spatial distribution characteristics of those meteorological ele- ments were analyzed. [ Result] Temperature of Sanjiang Plain decreased with the increase of latitude and altitude, and the annual average temper- atura varied from 2.5 to 4.5 ~（3 generally, showing a zonal distribution. Precipitation of Sanjiang Plain changed spatially and the annual average pre- cipitation varied from 500 to 600 mm symmetrically in northwest-southeast direction. Spatial distribution of the annual average wind speed in San- jiang Plain was identical with the spatial pattern of topography here, and the annual average wind speed changed from 3.0 to 3.6 rn/s in most re- gions. Relative air humidity of Sanjiang Plain in summer half year was relatively high and always above 65%. The maximum sunshine hours of San- jiang Plain in one year distributed similarly to the annual changing curve of solar declination, and both of them presented a normal distribution and changed with geographic latitude. The days from the beginning to the end of daily average temperature ~〉 10 ~C in Sanjiang Plain were 135 -146 d, and its distribution presented a latitudinal trend, with certain vertical zonality. [ Conclusion] The research could provide scientific references for the reasonable arrangement of agricultural production and effective prevention of meteorological disasters in Sanjiang Plain.

Climate Characters of Summer Drought in Mountain City and the Effect on Flowers and Trees

[Objective] The aim was to provide references for development of industries engaging in flowers and trees in Beipei area in Chongqing. [Method] The occurring trend, intensity trend of summer drought, relationship of intensity with rainfall and extremely highest temperature, occurring trend during initial period of summer drought and the effects in mountain cities were analyzed, based on information on lasting period, rainfall, average temperature, extremely highest temperature of sum- mer drought in Beipei area in mountain cities during 1981-2010 and, growth condi- tion and phenological phenomena of Michelia champaca during 2005-2007. [Result] The occurring probability of summer drought in mountain cities was 57% and the probabilities of light, moderate, heavy and extreme drought were 30%, 10%, 7% and 10%; intensity of summer drought was none of linear relation with rainfall and ex- tremely highest temperature. In summer drought, daily average rainfall was less than 0.9 ram; extremely highest temperature was 35.0-45.0 ℃ with probability at 30%; initial period of summer drought was from later June to middle August and of extreme drought was later June-later July; the ending period was early September. During drought, when the extremely highest temperature （〉35.0 ℃） occurred in three days within a Hou, flowers and trees were affected by the hot drought and when the extreme temperature （〉40.0 ℃） occurred in three days within a Hou, the plants were seriously affected. [Conclusion] Based on characters of summer drought, pre- cautions can be taken to reduce effects of summer drought on flowers and trees with the help of weather forecast.

Climatic Characteristics of Extreme Cold and Frost Disaster and the Effects on Flowers and Trees in Mountain City in 2010

[Objective] The aim was to explore climatic characteristics of cold and frost disaster and the effects on flowers and trees in mountain city in 2010. [Method] Extremism of cold and frost disaster in temperature and lasting period, and the effects on flowers and trees in 2010 were researched based on information of average ten-day temperatures and extreme lowest temperature in 1951-2010 and Michelia alba DC. growth in a Hou in 2008-2010, as per statistical analysis technique. [Result] Cold and frost disaster in winter of 2010 proved the longest in lasting period, lowest in average temperature, and most serious for flowers and trees, resulting in serious loss of flowers and trees in Beibei area. [Conclusion] Countermeasures in the research would reduce owners’ loss in flowers and trees.

Study on Cloud Change Trend in Southern China under the Influence of Climate Warming

[ Objective] The research aimed to study influences of the climate warming on cloudage and cloud-like structure in southern China. [ Method] Annual average temperature, total cloudage and low cloudage in Gan County, Nankang, Shangyou and Xinfeng of southern Jiangxi from 2004 to 2011 were selected. Influences of the annual average temperature change on annual average total cloudage, annual average low cloudage and cloud-like structure in southern Jiangxi were analyzed. [ Result] Climate warming was affecting cloudage and cloud-like structure in southern China. When annual average temperature rose, annual average total cloudage and low cloudage both presented decrease trends. When annual av- erage temperature declined, annual average total cloudage and low cloudage both presented rise trends. When annual average temperature was equal to that in prior year at low point, annual average total cloudage and low cloudage increased. Annual average low cloudage was different in mountain area and basin. Influences of the annual average temperature on annual average total cloudage and low cloudage in basin at the low alti- tude presented slow fluctuation form, and had severe influence on that in mountain area at the high altitude. Rise of the annual average temperature had larger influence on high cloudage, while decline of the annual average temperature had larger influence on annual average low cloudage. Under different weather situations, formation and disappearance change of the low cloud had different manifestation forms. [ Conclusion] The research provided scientific basis for studying changes of the cloudage and cloud-like structure in southern China as climate warming.

Autonomous Changes in the Concentration of Water Vapor Drive Climate Change

When compared to the average annual global temperature record from 1880, no published climate model posited on the assumption that the increasing concentration of atmospheric carbon dioxide is the driver of climate change can accurately replicate the significant variability in the annual temperature record. Therefore, new principles of atmospheric physics are developed for determining changes in the average annual global temperature based on changes in the average atmospheric concentration of water vapor. These new principles prove that: 1) Changes in average global temperature are not driven by changes in the concentration of carbon dioxide;2) Instead, autonomous changes in the concentration of water vapor, ΔTPW, drive changes in water vapor heating, thus, the average global temperature, ΔTAvg, in accordance with this principle, ΔTAvg=0.4ΔTPW the average accuracy of which is ±0.14%, when compared to the variable annual, 1880-2019, temperature record;3) Changes in the concentration of water vapor and changes in water vapor heating are not a feedback response to changes in the concentration of CO2;4) Rather, increases in water vapor heating and increases in the concentration of water vapor drive each other in an autonomous positive feedback loop;5) This feedback loop can be brought to a halt if the average global rate of precipitation can be brought into balance with the average global rate of evaporation and maintained there;and, 6) The recent increases in average global temperature can be reversed, if average global precipitation can be increased sufficiently to slightly exceed the average rate of evaporation.

Erratum to “Autonomous Changes in the Concentration of Water Vapor Drive Climate Change” [Atmospheric and Climate Sciences 10 (2020) 443-508]

A. Changes in average global temperature are not driven by changes in the concentration of carbon dioxide; B. Instead, autonomous changes in the concentration of water vapor, ΔTPW, drive changes in water vapor heating, thus, changes in the average global temperature, ΔTAvg, in deg. Celsius are calculated in accordance with this principle, measured in kg·m-2, the average accuracy of which is ±0.14%, when compared to the variable annual, 1880 - 2019, average global temperature record;