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 ch...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, <span style="white-space:nowrap;">Δ</span>TPW, drive changes in water vapor heating, thus, the average global temperature, <span style="white-space:nowrap;">Δ</span>T<sub>Avg</sub>, in accordance with this principle, <span style="white-space:normal;"><span style="white-space:nowrap;">Δ</span>T</span><span style="white-space:normal;"><sub>Avg</sub>=0.4<span style="white-space:normal;"><span style="white-space:nowrap;">Δ</span>TPW </span></span>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 CO<sub>2</sub>;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.展开更多
<p> A. <span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Changes </span></span></span><...<p> A. <span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Changes </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">in</span></span></span><span><span><span style="font-family:" color:black;"=""><span style="font-family:Verdana;"> average global temperature are not driven by changes in the concentration of carbon dioxide;</span></span></span></span> </p> <p> <span style="font-family:Verdana;">B. </span><span style="font-family:Verdana;">Instead, autonomous changes in the concentration of water vapor, </span><span style="font-family:Verdana;">Δ</span><span style="font-family:Verdana;">TPW, </span><span color:black;"=""><span style="font-family:Verdana;">drive changes in water vapor heating, thus, </span><span style="background:#C00000;font-family:Verdana;">changes in</span><span style="font-family:Verdana;"> the average global temperature, </span></span><span style="font-family:Verdana;">Δ</span><span style="font-family:Verdana;"><i>T</i></span><span style="font-family:Verdana;"><sub>Avg</sub></span><span color:black;"=""><span style="font-family:Verdana;">, </span><span style="background:#C00000;font-family:Verdana;">in deg. Celsius are calculated</span><span style="font-family:Verdana;"> in accordance with this principle,</span></span> </p> <p style="text-align:center;margin-left:10pt;"> <span><span><span style="font-family:" color:black;"=""><span style="font-family:Verdana;"></span><img src="Edit_6e770969-a7c9-4192-a6ad-03de906a4d65.bmp" alt="" /><br /> </span></span></span> </p> <p align="center" style="margin-left:10.0pt;text-align:center;"> <span><span><span style="font-family:;" "=""><span></span></span></span><span><span><span style="font-family:" color:black;"=""></span></span></span></span> </p> <p> <span><span><span style="font-family:" color:black;background:#c00000;"=""><span style="font-family:Verdana;">measured in kg<span style="color:#4F4F4F;font-family:-apple-system, " font-size:16px;white-space:normal;background-color:#f7f7f7;"=""><span style="color:#4F4F4F;font-family:-apple-system, " font-size:16px;white-space:normal;background-color:#f7f7f7;"="">·</span></span>m</span><sup><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:-apple-system, " font-size:16px;white-space:normal;background-color:#ffffff;"="">-</span>2</span></sup><span style="font-family:Verdana;">,</span></span></span></span><span><span><span style="font-family:" color:black;"=""> </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">the average accuracy of which is ±0.14%, when compared to the variable annual, 1880 </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">-</span></span></span><span><span><span style="font-family:" color:black;"=""><span style="font-family:Verdana;"> 2019, </span><span style="background:#C00000;font-family:Verdana;">average global </span><span style="font-family:Verdana;">temperature record;</span></span></span></span> </p>展开更多
The tidal current duration (TCD) and velocity (TCV) and suspended sediment concentration (SSC) were measured in the dry season in December, 2011 and in the flood season in June, 2012 at the upper part of the Nor...The tidal current duration (TCD) and velocity (TCV) and suspended sediment concentration (SSC) were measured in the dry season in December, 2011 and in the flood season in June, 2012 at the upper part of the North Channel of Changjiang Estuary. They were assimilated with the measured data in 2003, 2004, 2006 and 2007, using the tidal range's proportion conversion. Variations in TCD and TCV, preferential flow and SSC have been calculated. Influences of typical engineering projects such as Qingcaosha fresh water reservoir, Yangtze River Bridge, and land reclamation on the ebb and flood TCD, TCV and SSC in the North Channel for the last 10 years are discussed. The results show that: (1) currently, in the upper part of North Channel, the ebb tide dominates; after the construction of the typical projects, ebb TCD and TCV tends to be larger and the vertical average ebb and flood SSC decrease during the flood season while SSC increases during the dry season; (2) changes in the vertical average TCV are mainly contributed by seasonal runoff variation during the flood season, which is larger in the flood season than that in the dry season; the controlling parameters of increasing ebb TCD and TCV are those large-scale engineering projects in the North Channel; variation in SSC may result mainly from the reduction of basin annual sediment loads, large-scale nearshore projects and so on.展开更多
Purpose: The aim of this paper is to discuss how the keyword concentration change ratio(KCCR) is used while identifying the stability-mutation feature of Web search keywords during information analyses and predictions...Purpose: The aim of this paper is to discuss how the keyword concentration change ratio(KCCR) is used while identifying the stability-mutation feature of Web search keywords during information analyses and predictions.Design/methodology/approach: By introducing the stability-mutation feature of keywords and its significance, the paper describes the function of the KCCR in identifying keyword stability-mutation features. By using Ginsberg's influenza keywords, the paper shows how the KCCR can be used to identify the keyword stability-mutation feature effectively.Findings: Keyword concentration ratio has close positive correlation with the change rate of research objects retrieved by users, so from the characteristic of the 'stability-mutation' of keywords, we can understand the relationship between these keywords and certain information. In general, keywords representing for mutation fit for the objects changing in short-term, while those representing for stability are suitable for long-term changing objects. Research limitations: It is difficult to acquire the frequency of keywords, so indexes or parameters which are closely related to the true search volume are chosen for this study.Practical implications: The stability-mutation feature identification of Web search keywords can be applied to predict and analyze the information of unknown public events through observing trends of keyword concentration ratio.Originality/value: The stability-mutation feature of Web search could be quantitatively described by the keyword concentration change ratio(KCCR). Through KCCR, the authors took advantage of Ginsberg's influenza epidemic data accordingly and demonstrated how accurate and effective the method proposed in this paper was while it was used in information analyses and predictions.展开更多
The controlled simulation experiments revealed that ozone concentration increases cause various degrees of injury to leaves of crop and vegetable.The injury to vegetables is greater than that to crops.Ozone can dramat...The controlled simulation experiments revealed that ozone concentration increases cause various degrees of injury to leaves of crop and vegetable.The injury to vegetables is greater than that to crops.Ozone can dramatically affect stomatal conductance,photosynthetic rate and transpiration rate,and consequently the yield of crops.No matter how long exposure time was, stomatal conductance increased and photosynthetic and transpiration rates decreased with increases in ozone concentration.When ozone concentration was 100 nmol/mol,yields of rice and winter wheat declined by 27.1% and 60.5% respectively.When up to 200 nmol/mol,there was a significant reduction of yields:a decline up to 33.7% for rice and 81.3% for winter wheat.On the other hand,ozone benefits the improvement of grain quality such as amino acid and protein.展开更多
Based on the property of entropy,a new index Q was defined to measure the temporal concentration property of summertime daily rainfall in China,based on daily precipitation data collected at 553 observation stations i...Based on the property of entropy,a new index Q was defined to measure the temporal concentration property of summertime daily rainfall in China,based on daily precipitation data collected at 553 observation stations in China during 1961–2010.Furthermore,changes in the temporal concentration property of summer precipitation in China were investigated.The results indicate that the regions with larger Q values were located in most parts of Northwest China and the north of the Yellow River,where daily precipitation tended to become temporally concentrated during the study period.On the contrary,smaller Q values were found in eastern Tibetan Plateau,southeastern Northwest China,and most parts of Southwest and South China.The most obvious increasing trend of Q index was found in South China and most parts of Southwest China,where precipitation showed a temporal concentration trend.However,a decreasing trend of Q index was found in Northwest China,the Tibetan Plateau,and the north of the Huaihe River.Variations of the Q index and the summer rainfall total during 1961–2010 in China both exhibited an increasing trend,implying larger temporal variability in rainfall attributes.It is illustrated that the summer precipitation in general became more temporally concentrated with more intense rainfall events and wetter days.展开更多
The aim of this experiment was to determine the impacts of climate change on soil profile concentrations and diffusion effluxes of methane in a rice-wheat annual rotation ecosystem in Southeastern China. We initiated ...The aim of this experiment was to determine the impacts of climate change on soil profile concentrations and diffusion effluxes of methane in a rice-wheat annual rotation ecosystem in Southeastern China. We initiated a field experiment with four treatments:ambient conditions(CKs), CO2 concentration elevated to - 500 μmol/mol(FACE),temperature elevated by ca. 2°C(T) and combined elevation of CO2 concentration and temperature(FACE + T). A multilevel sampling probe was designed to collect the soil gas at four different depths, namely, 7 cm, 15 cm, 30 cm and 50 cm. Methane concentrations were higher during the rice season and decreased with depth, while lower during the wheat season and increased with depth. Compared to CK, mean methane concentration was increased by 42%, 57% and 71% under the FACE, FACE + T and T treatments, respectively, at the 7 cm depth during the rice season(p 〈 0.05). Mean methane diffusion effluxes to the 7 cm depth were positive in the rice season and negative in the wheat season, resulting in the paddy field being a source and weak sink, respectively. Moreover, mean methane diffusion effluxes in the rice season were 0.94, 1.19 and 1.42 mg C/(m^2·hr) in the FACE,FACE + T and T treatments, respectively, being clearly higher than that in the CK. The results indicated that elevated atmospheric CO2 concentration and temperature could significantly increase soil profile methane concentrations and their effluxes from a rice-wheat field annual rotation ecosystem(p 〈 0.05).展开更多
文摘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, <span style="white-space:nowrap;">Δ</span>TPW, drive changes in water vapor heating, thus, the average global temperature, <span style="white-space:nowrap;">Δ</span>T<sub>Avg</sub>, in accordance with this principle, <span style="white-space:normal;"><span style="white-space:nowrap;">Δ</span>T</span><span style="white-space:normal;"><sub>Avg</sub>=0.4<span style="white-space:normal;"><span style="white-space:nowrap;">Δ</span>TPW </span></span>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 CO<sub>2</sub>;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.
文摘<p> A. <span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">Changes </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">in</span></span></span><span><span><span style="font-family:" color:black;"=""><span style="font-family:Verdana;"> average global temperature are not driven by changes in the concentration of carbon dioxide;</span></span></span></span> </p> <p> <span style="font-family:Verdana;">B. </span><span style="font-family:Verdana;">Instead, autonomous changes in the concentration of water vapor, </span><span style="font-family:Verdana;">Δ</span><span style="font-family:Verdana;">TPW, </span><span color:black;"=""><span style="font-family:Verdana;">drive changes in water vapor heating, thus, </span><span style="background:#C00000;font-family:Verdana;">changes in</span><span style="font-family:Verdana;"> the average global temperature, </span></span><span style="font-family:Verdana;">Δ</span><span style="font-family:Verdana;"><i>T</i></span><span style="font-family:Verdana;"><sub>Avg</sub></span><span color:black;"=""><span style="font-family:Verdana;">, </span><span style="background:#C00000;font-family:Verdana;">in deg. Celsius are calculated</span><span style="font-family:Verdana;"> in accordance with this principle,</span></span> </p> <p style="text-align:center;margin-left:10pt;"> <span><span><span style="font-family:" color:black;"=""><span style="font-family:Verdana;"></span><img src="Edit_6e770969-a7c9-4192-a6ad-03de906a4d65.bmp" alt="" /><br /> </span></span></span> </p> <p align="center" style="margin-left:10.0pt;text-align:center;"> <span><span><span style="font-family:;" "=""><span></span></span></span><span><span><span style="font-family:" color:black;"=""></span></span></span></span> </p> <p> <span><span><span style="font-family:" color:black;background:#c00000;"=""><span style="font-family:Verdana;">measured in kg<span style="color:#4F4F4F;font-family:-apple-system, " font-size:16px;white-space:normal;background-color:#f7f7f7;"=""><span style="color:#4F4F4F;font-family:-apple-system, " font-size:16px;white-space:normal;background-color:#f7f7f7;"="">·</span></span>m</span><sup><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:-apple-system, " font-size:16px;white-space:normal;background-color:#ffffff;"="">-</span>2</span></sup><span style="font-family:Verdana;">,</span></span></span></span><span><span><span style="font-family:" color:black;"=""> </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">the average accuracy of which is ±0.14%, when compared to the variable annual, 1880 </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">-</span></span></span><span><span><span style="font-family:" color:black;"=""><span style="font-family:Verdana;"> 2019, </span><span style="background:#C00000;font-family:Verdana;">average global </span><span style="font-family:Verdana;">temperature record;</span></span></span></span> </p>
文摘The tidal current duration (TCD) and velocity (TCV) and suspended sediment concentration (SSC) were measured in the dry season in December, 2011 and in the flood season in June, 2012 at the upper part of the North Channel of Changjiang Estuary. They were assimilated with the measured data in 2003, 2004, 2006 and 2007, using the tidal range's proportion conversion. Variations in TCD and TCV, preferential flow and SSC have been calculated. Influences of typical engineering projects such as Qingcaosha fresh water reservoir, Yangtze River Bridge, and land reclamation on the ebb and flood TCD, TCV and SSC in the North Channel for the last 10 years are discussed. The results show that: (1) currently, in the upper part of North Channel, the ebb tide dominates; after the construction of the typical projects, ebb TCD and TCV tends to be larger and the vertical average ebb and flood SSC decrease during the flood season while SSC increases during the dry season; (2) changes in the vertical average TCV are mainly contributed by seasonal runoff variation during the flood season, which is larger in the flood season than that in the dry season; the controlling parameters of increasing ebb TCD and TCV are those large-scale engineering projects in the North Channel; variation in SSC may result mainly from the reduction of basin annual sediment loads, large-scale nearshore projects and so on.
基金supported by National Social Science Foundation of China(Grand No.13&ZD173)
文摘Purpose: The aim of this paper is to discuss how the keyword concentration change ratio(KCCR) is used while identifying the stability-mutation feature of Web search keywords during information analyses and predictions.Design/methodology/approach: By introducing the stability-mutation feature of keywords and its significance, the paper describes the function of the KCCR in identifying keyword stability-mutation features. By using Ginsberg's influenza keywords, the paper shows how the KCCR can be used to identify the keyword stability-mutation feature effectively.Findings: Keyword concentration ratio has close positive correlation with the change rate of research objects retrieved by users, so from the characteristic of the 'stability-mutation' of keywords, we can understand the relationship between these keywords and certain information. In general, keywords representing for mutation fit for the objects changing in short-term, while those representing for stability are suitable for long-term changing objects. Research limitations: It is difficult to acquire the frequency of keywords, so indexes or parameters which are closely related to the true search volume are chosen for this study.Practical implications: The stability-mutation feature identification of Web search keywords can be applied to predict and analyze the information of unknown public events through observing trends of keyword concentration ratio.Originality/value: The stability-mutation feature of Web search could be quantitatively described by the keyword concentration change ratio(KCCR). Through KCCR, the authors took advantage of Ginsberg's influenza epidemic data accordingly and demonstrated how accurate and effective the method proposed in this paper was while it was used in information analyses and predictions.
基金supported by the key project of the National Natural Science Foundation of China (49899270)
文摘The controlled simulation experiments revealed that ozone concentration increases cause various degrees of injury to leaves of crop and vegetable.The injury to vegetables is greater than that to crops.Ozone can dramatically affect stomatal conductance,photosynthetic rate and transpiration rate,and consequently the yield of crops.No matter how long exposure time was, stomatal conductance increased and photosynthetic and transpiration rates decreased with increases in ozone concentration.When ozone concentration was 100 nmol/mol,yields of rice and winter wheat declined by 27.1% and 60.5% respectively.When up to 200 nmol/mol,there was a significant reduction of yields:a decline up to 33.7% for rice and 81.3% for winter wheat.On the other hand,ozone benefits the improvement of grain quality such as amino acid and protein.
基金Supported by the National Natural Science Foundation of China(41575094 and 41275092)Project for Postgraduate Scientific Research and Innovation of Jiangsu Province(KYLX_0842 and CXZZ12-0485)Innovation Program of the State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences(2015LASW-A03)
文摘Based on the property of entropy,a new index Q was defined to measure the temporal concentration property of summertime daily rainfall in China,based on daily precipitation data collected at 553 observation stations in China during 1961–2010.Furthermore,changes in the temporal concentration property of summer precipitation in China were investigated.The results indicate that the regions with larger Q values were located in most parts of Northwest China and the north of the Yellow River,where daily precipitation tended to become temporally concentrated during the study period.On the contrary,smaller Q values were found in eastern Tibetan Plateau,southeastern Northwest China,and most parts of Southwest and South China.The most obvious increasing trend of Q index was found in South China and most parts of Southwest China,where precipitation showed a temporal concentration trend.However,a decreasing trend of Q index was found in Northwest China,the Tibetan Plateau,and the north of the Huaihe River.Variations of the Q index and the summer rainfall total during 1961–2010 in China both exhibited an increasing trend,implying larger temporal variability in rainfall attributes.It is illustrated that the summer precipitation in general became more temporally concentrated with more intense rainfall events and wetter days.
基金supported by and the Fundamental Research Funds for the National Science Foundation of China (No. 41171238)the Ministry of Science and Technology (No. 2013BAD11B01)+1 种基金the Central Universities (No. KYTZ201404)the Nonprofit Research Foundation for Agriculture (No. 200903003)
文摘The aim of this experiment was to determine the impacts of climate change on soil profile concentrations and diffusion effluxes of methane in a rice-wheat annual rotation ecosystem in Southeastern China. We initiated a field experiment with four treatments:ambient conditions(CKs), CO2 concentration elevated to - 500 μmol/mol(FACE),temperature elevated by ca. 2°C(T) and combined elevation of CO2 concentration and temperature(FACE + T). A multilevel sampling probe was designed to collect the soil gas at four different depths, namely, 7 cm, 15 cm, 30 cm and 50 cm. Methane concentrations were higher during the rice season and decreased with depth, while lower during the wheat season and increased with depth. Compared to CK, mean methane concentration was increased by 42%, 57% and 71% under the FACE, FACE + T and T treatments, respectively, at the 7 cm depth during the rice season(p 〈 0.05). Mean methane diffusion effluxes to the 7 cm depth were positive in the rice season and negative in the wheat season, resulting in the paddy field being a source and weak sink, respectively. Moreover, mean methane diffusion effluxes in the rice season were 0.94, 1.19 and 1.42 mg C/(m^2·hr) in the FACE,FACE + T and T treatments, respectively, being clearly higher than that in the CK. The results indicated that elevated atmospheric CO2 concentration and temperature could significantly increase soil profile methane concentrations and their effluxes from a rice-wheat field annual rotation ecosystem(p 〈 0.05).