Airborne dust is an important constituent in the Martian atmosphere because of its radiative interaction with the atmospheric circulation.Dust size is one crucial factor in determining this effect.In reality dust size...Airborne dust is an important constituent in the Martian atmosphere because of its radiative interaction with the atmospheric circulation.Dust size is one crucial factor in determining this effect.In reality dust sizes are varied;however,in numerical modeling of dust processes,dust size has usually been described by choice of a particular size distribution function,or by use of fixed values of effective radius(ER)and effective variance(EV).In this work,we present analytical expressions that have been derived to specify ER and EV for Nbin dust schemes,based on a model-calculated dust mixing ratio.Numerical simulations based on this approach thus would consider the effects of variable ER on the atmospheric radiation and their interaction.Results have revealed some interesting features of the dust distribution parameters,such as seasonal and spatial variation of ER and EV,which are generally consistent with some previous observational and modeling studies.Compared with the usual approach of using a fixed ER,simulation results from the present approach suggest that the variability of ER can have significant effects on the simulated thermal field of the Martian atmosphere.展开更多
Linear mixed model (LMM) approaches have been widely applied in many areas of research data analysis because they offer great flexibility for different data structures and linear model systems. In this study, emphasis...Linear mixed model (LMM) approaches have been widely applied in many areas of research data analysis because they offer great flexibility for different data structures and linear model systems. In this study, emphasis is placed on comparing the properties of two LMM approaches: restricted maximum likelihood (REML) and minimum norm quadratic unbiased estimation (MINQUE) with and without resampling techniques being included. Bias, testing power, Type I error, and computing time were compared between REML and MINQUE approaches with and without Jackknife technique based on 500 simulated data sets. Results showed that MINQUE and REML methods performed equally regarding bias, Type I error, and power. Jackknife-based MINQUE and REML greatly improved power compared to non-Jackknife based linear mixed model approaches. Results also showed that MINQUE is more time-saving compared to REML, especially with the use of resampling techniques and large data set analysis. Results from the actual cotton data analysis were in agreement with our simulated results. Therefore, Jackknife-based MINQUE approaches could be recommended to achieve desirable power with reduced time for a large data analysis and model simulations.展开更多
基金the FDCT of Macao(Grant nos.080/2015/A3 and 0088/2018/A3).
文摘Airborne dust is an important constituent in the Martian atmosphere because of its radiative interaction with the atmospheric circulation.Dust size is one crucial factor in determining this effect.In reality dust sizes are varied;however,in numerical modeling of dust processes,dust size has usually been described by choice of a particular size distribution function,or by use of fixed values of effective radius(ER)and effective variance(EV).In this work,we present analytical expressions that have been derived to specify ER and EV for Nbin dust schemes,based on a model-calculated dust mixing ratio.Numerical simulations based on this approach thus would consider the effects of variable ER on the atmospheric radiation and their interaction.Results have revealed some interesting features of the dust distribution parameters,such as seasonal and spatial variation of ER and EV,which are generally consistent with some previous observational and modeling studies.Compared with the usual approach of using a fixed ER,simulation results from the present approach suggest that the variability of ER can have significant effects on the simulated thermal field of the Martian atmosphere.
文摘Linear mixed model (LMM) approaches have been widely applied in many areas of research data analysis because they offer great flexibility for different data structures and linear model systems. In this study, emphasis is placed on comparing the properties of two LMM approaches: restricted maximum likelihood (REML) and minimum norm quadratic unbiased estimation (MINQUE) with and without resampling techniques being included. Bias, testing power, Type I error, and computing time were compared between REML and MINQUE approaches with and without Jackknife technique based on 500 simulated data sets. Results showed that MINQUE and REML methods performed equally regarding bias, Type I error, and power. Jackknife-based MINQUE and REML greatly improved power compared to non-Jackknife based linear mixed model approaches. Results also showed that MINQUE is more time-saving compared to REML, especially with the use of resampling techniques and large data set analysis. Results from the actual cotton data analysis were in agreement with our simulated results. Therefore, Jackknife-based MINQUE approaches could be recommended to achieve desirable power with reduced time for a large data analysis and model simulations.
