Evaluation of vegetation structure and distribution simulations in Earth system models(ESMs)is the basis for understanding historical reconstruction and future projection of changes in terrestrial ecosystems,carbon cy...Evaluation of vegetation structure and distribution simulations in Earth system models(ESMs)is the basis for understanding historical reconstruction and future projection of changes in terrestrial ecosystems,carbon cycle,and climate based on these ESMs.Such assessments can also provide important information of models'merits and shortcomings or systematic biases,and so clues for model development.Vegetation structure and distribution in ESMs are primarily characterized by three variables:leaf area index(LAI),tree height,and fractional coverage of plant functional type(PFT).However,for the ongoing Coupled Model Intercomparison Project Phase 6(CMIP6),only temporal variabilities of global-averaged LAI time series were evaluated,others remain largely uninvestigated.This study systematically investigates the spatial and/or temporal variability of the three critical variables from 27 ESMs in CMIP6 using satellite observations.Our results show that all models and the multi-model ensemble mean(MME)can generally reproduce the observed LAI spatial pattern but all of them overestimate the global mean LAI mainly due to overestimation of LAI in non-forested vegetated areas.Most CMIP6 models fail to capture the temporal variability in the annual LAI because of large biases in both the simulated trend magnitude and temporal pattern of interannual variability.The average LAI seasonal cycles in different latitude zones are roughly reproduced by the models,but 1-2 months delays in the LAI peak appear in the Arctic-boreal zone.Additionally,CMIP6 models overall overestimate tree height,and largely overestimate the global grass area but underestimate tree and shrub areas,especially in the middle and high latitudes.It should be kept in mind that such biases may have further impacts on the simulations of the related carbon and land-atmosphere interaction variables(e.g.,ecosystem production,carbon storage,transpiration,and temperature)for global change research.Hence,bias-correction should be made to improve reliability of vegetation str展开更多
Body Mass Index (BMI), defined as the ratio of individual mass (in kilograms) to the square of the associated height (in meters), is one of the most widely discussed and utilized risk factors in medicine and public he...Body Mass Index (BMI), defined as the ratio of individual mass (in kilograms) to the square of the associated height (in meters), is one of the most widely discussed and utilized risk factors in medicine and public health, given the increasing obesity worldwide and its relation to metabolic disease. Statistically, BMI is a composite random variable, since human weight (converted to mass) and height are themselves random variables. Much effort over the years has gone into attempts to model or approximate the BMI distribution function. This paper derives the mathematically exact BMI probability density function (PDF), as well as the exact bivariate PDF for human weight and height. Taken together, weight and height are shown to be correlated bivariate lognormal variables whose marginal distributions are each lognormal in form. The mean and variance of each marginal distribution, together with the linear correlation coefficient of the two distributions, provide 5 nonadjustable parameters for a given population that uniquely determine the corresponding BMI distribution, which is also shown to be lognormal in form. The theoretical analysis is tested experimentally by gender against a large anthropometric data base, and found to predict with near perfection the profile of the empirical BMI distribution and, to great accuracy, individual statistics including mean, variance, skewness, kurtosis, and correlation. Beyond solving a longstanding statistical problem, the significance of these findings is that, with knowledge of the exact BMI distribution functions for diverse populations, medical and public health professionals can then make better informed statistical inferences regarding BMI and public health policies to reduce obesity.展开更多
The test-QD in-situ annealing method could surmount the critical nucleation condition of InAs/GaAs single quantum dots（SQDs） to raise the growth repeatability.Here,through many growth tests on rotating substrates,we...The test-QD in-situ annealing method could surmount the critical nucleation condition of InAs/GaAs single quantum dots（SQDs） to raise the growth repeatability.Here,through many growth tests on rotating substrates,we develop a proper In deposition amount（θ） for SQD growth,according to the measured critical θ for test QD nucleation（θ;）.The proper ratio θ/θ;,with a large tolerance of the variation of the real substrate temperature(T;),is 0.964-0.971 at the edge and> 0.989 but < 0.996 in the center of a 1/4-piece semi-insulating wafer,and around 0.9709 but < 0.9714 in the center of a 1/4-piece N;wafer as shown in the evolution of QD size and density as θ/θ;varies.Bright SQDs with spectral lines at 905 nm-935 nm nucleate at the edge and correlate with individual 7 nm-8 nm-height QDs in atomic force microscopy,among dense 1 nm-5 nm-height small QDs with a strong spectral profile around 860 nm-880 nm.The higher T;in the center forms diluter,taller and uniform QDs,and very dilute SQDs for a proper θ/θ;:only one 7-nm-height SQD in25 μm;.On a 2-inch（1 inch = 2.54 cm） semi-insulating wafer,by using θ/θ;= 0.961,SQDs nucleate in a circle in 22%of the whole area.More SQDs will form in the broad high-T;region in the center by using a proper θ/θ;.展开更多
In this paper, wind velocities and directions （sea and land） are recorded in different days and times. The data collected were compared with the weather data from the Brunei Darussalam Meteorological Service （BDMS...In this paper, wind velocities and directions （sea and land） are recorded in different days and times. The data collected were compared with the weather data from the Brunei Darussalam Meteorological Service （BDMS） and the findings of other researchers and were found to be in good agreement. The potential of wind energy is predicted from the available data collected. The average generated power （forenoon and afternoon） is found to be 25 （mean） and 18W （median）, 101 （mean） and 73W （median）, 912 （mean） and 660 W （median）, 10137 （mean） and 7331 W （median） for a rotor with a diameter of 2.5, 5, 15 and 50 m, respectively. The power density Pd for wind farming is found to be 0.26 （mean） and 0.19 （median）, 0.31 （mean） and 0.22 （median） for the rotor whose diameter is 2.5 and 50 m, respectively, while the average Pd values are found to be 0.28 （mean） and 0.2 （median） for the rotor whose diameter is 5 and 15 m.展开更多
基金the National Key Research and Development Program of China(2017YFA0604804,2017YFA0604302)National Natural Science Foundation of China(41630530,41875137)the National Key Scientific and Technological Infrastructure project Earth System Science Numerical Simulator Facility(EarthLab).
文摘Evaluation of vegetation structure and distribution simulations in Earth system models(ESMs)is the basis for understanding historical reconstruction and future projection of changes in terrestrial ecosystems,carbon cycle,and climate based on these ESMs.Such assessments can also provide important information of models'merits and shortcomings or systematic biases,and so clues for model development.Vegetation structure and distribution in ESMs are primarily characterized by three variables:leaf area index(LAI),tree height,and fractional coverage of plant functional type(PFT).However,for the ongoing Coupled Model Intercomparison Project Phase 6(CMIP6),only temporal variabilities of global-averaged LAI time series were evaluated,others remain largely uninvestigated.This study systematically investigates the spatial and/or temporal variability of the three critical variables from 27 ESMs in CMIP6 using satellite observations.Our results show that all models and the multi-model ensemble mean(MME)can generally reproduce the observed LAI spatial pattern but all of them overestimate the global mean LAI mainly due to overestimation of LAI in non-forested vegetated areas.Most CMIP6 models fail to capture the temporal variability in the annual LAI because of large biases in both the simulated trend magnitude and temporal pattern of interannual variability.The average LAI seasonal cycles in different latitude zones are roughly reproduced by the models,but 1-2 months delays in the LAI peak appear in the Arctic-boreal zone.Additionally,CMIP6 models overall overestimate tree height,and largely overestimate the global grass area but underestimate tree and shrub areas,especially in the middle and high latitudes.It should be kept in mind that such biases may have further impacts on the simulations of the related carbon and land-atmosphere interaction variables(e.g.,ecosystem production,carbon storage,transpiration,and temperature)for global change research.Hence,bias-correction should be made to improve reliability of vegetation str
文摘Body Mass Index (BMI), defined as the ratio of individual mass (in kilograms) to the square of the associated height (in meters), is one of the most widely discussed and utilized risk factors in medicine and public health, given the increasing obesity worldwide and its relation to metabolic disease. Statistically, BMI is a composite random variable, since human weight (converted to mass) and height are themselves random variables. Much effort over the years has gone into attempts to model or approximate the BMI distribution function. This paper derives the mathematically exact BMI probability density function (PDF), as well as the exact bivariate PDF for human weight and height. Taken together, weight and height are shown to be correlated bivariate lognormal variables whose marginal distributions are each lognormal in form. The mean and variance of each marginal distribution, together with the linear correlation coefficient of the two distributions, provide 5 nonadjustable parameters for a given population that uniquely determine the corresponding BMI distribution, which is also shown to be lognormal in form. The theoretical analysis is tested experimentally by gender against a large anthropometric data base, and found to predict with near perfection the profile of the empirical BMI distribution and, to great accuracy, individual statistics including mean, variance, skewness, kurtosis, and correlation. Beyond solving a longstanding statistical problem, the significance of these findings is that, with knowledge of the exact BMI distribution functions for diverse populations, medical and public health professionals can then make better informed statistical inferences regarding BMI and public health policies to reduce obesity.
基金supported by the National Key Basic Research Program of China(Grant No.2013CB933304)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB01010200)the National Natural Science Foundation of China(Grant No.65015196)
文摘The test-QD in-situ annealing method could surmount the critical nucleation condition of InAs/GaAs single quantum dots（SQDs） to raise the growth repeatability.Here,through many growth tests on rotating substrates,we develop a proper In deposition amount（θ） for SQD growth,according to the measured critical θ for test QD nucleation（θ;）.The proper ratio θ/θ;,with a large tolerance of the variation of the real substrate temperature(T;),is 0.964-0.971 at the edge and> 0.989 but < 0.996 in the center of a 1/4-piece semi-insulating wafer,and around 0.9709 but < 0.9714 in the center of a 1/4-piece N;wafer as shown in the evolution of QD size and density as θ/θ;varies.Bright SQDs with spectral lines at 905 nm-935 nm nucleate at the edge and correlate with individual 7 nm-8 nm-height QDs in atomic force microscopy,among dense 1 nm-5 nm-height small QDs with a strong spectral profile around 860 nm-880 nm.The higher T;in the center forms diluter,taller and uniform QDs,and very dilute SQDs for a proper θ/θ;:only one 7-nm-height SQD in25 μm;.On a 2-inch（1 inch = 2.54 cm） semi-insulating wafer,by using θ/θ;= 0.961,SQDs nucleate in a circle in 22%of the whole area.More SQDs will form in the broad high-T;region in the center by using a proper θ/θ;.
文摘In this paper, wind velocities and directions （sea and land） are recorded in different days and times. The data collected were compared with the weather data from the Brunei Darussalam Meteorological Service （BDMS） and the findings of other researchers and were found to be in good agreement. The potential of wind energy is predicted from the available data collected. The average generated power （forenoon and afternoon） is found to be 25 （mean） and 18W （median）, 101 （mean） and 73W （median）, 912 （mean） and 660 W （median）, 10137 （mean） and 7331 W （median） for a rotor with a diameter of 2.5, 5, 15 and 50 m, respectively. The power density Pd for wind farming is found to be 0.26 （mean） and 0.19 （median）, 0.31 （mean） and 0.22 （median） for the rotor whose diameter is 2.5 and 50 m, respectively, while the average Pd values are found to be 0.28 （mean） and 0.2 （median） for the rotor whose diameter is 5 and 15 m.
