The sounding data of meteorological satellites provide not only the real time weather information about the distribution of both cloud and rainfall,but also some others about the movement and state of atmosphere.They ...The sounding data of meteorological satellites provide not only the real time weather information about the distribution of both cloud and rainfall,but also some others about the movement and state of atmosphere.They are important variables and parameters for NWP model used to simulate and predict atmospheric state.In order to introduce remote sensing information from satellites into NWP model,there is an efficient way of establishing an RT model by use of the atmosphere radiation sounding data of meteorological satellites to get the variables and parameters valuable to NWP model.In this paper,we set up profiles of air temperature and water vapor from the surface to upper (0.1 hPa) using the radiosounding data and the surface data from May to August 1998 atmosphere East Asia.A TOVS RT model (RTTOV5) is provided to compute the value of radiation value of HIRS channels in NOAA14.Then the radiation values of 19 HIRS channels are gotten.After matching these data computed by the RT model and the corresponding values coming from satellite sounding in time,the statistic distribution of bias between tile model output and the satellite sounding at each sounding channel can be gotten.At the same time.the distribution of RMS to every TOVS HIRS channel,the standard biases to different scanning angle to each channel are also obtained.展开更多
Two simulations of five years (2003-2007) were conducted with the Regional Climate models RegCM4, one coupled with Land surface models BATS and the other with CLM4.5 over West Africa, where simulated air temperature a...Two simulations of five years (2003-2007) were conducted with the Regional Climate models RegCM4, one coupled with Land surface models BATS and the other with CLM4.5 over West Africa, where simulated air temperature and precipitation were analyzed. The purpose of this study is to assess the performance of RegCM4 coupled with the new CLM4.5 Land</span><span style="font-family:""> </span><span style="font-family:Verdana;">surface scheme and the standard one named BATS in order to find the best configuration of RegCM4 over West African. This study could improve our understanding of the sensitivity of land surface model in West Africa climate simulation, and provide relevant information to RegCM4 users. The results show fairly realistic restitution of West Africa’s climatology and indicate correlations of 0.60 to 0.82 between the simulated fields (BATS and CLM4.5) for precipitation. The substitution of BATS surface scheme by CLM4.5 in the model configuration, leads mainly to an improvement of precipitation over the Atlantic Ocean, however, the impact is not sufficiently noticeable over the continent. While the CLM4.5 experiment restores the seasonal cycles and spatial distribution, the biases increase for precipitation and temperature. Positive biases already existing with BATS are amplified over some sub-regions. This study concludes that temporal localization (seasonal effect), spatial distribution (grid points) and magnitude of precipitation and temperature (bias) are not simultaneously improved by CLM4.5. The introduction of the new land surface scheme CLM4.5, therefore, leads to a performance of the same order as that of BATS, albeit with a more detailed formulation.展开更多
Literature review indicates that sample size, attribute variance and within-sample choice distribution of alternatives are important considerations in the estimation of multinomial logit （MNL） models, but their impa...Literature review indicates that sample size, attribute variance and within-sample choice distribution of alternatives are important considerations in the estimation of multinomial logit （MNL） models, but their impacts on the estimation accuracy have not been systematically studied. Therefore, the objective of this paper is to provide an empirical examination to the above issues through a set of simulated discrete choice preference and rank ordered preference datasets. In this paper, the utility coefficients, alternative specific constants （ASCs）, and the mean and standard deviation of the four attributes for a set of seven hypothetical alternatives are specified as a priori. Then, synthetic datasets, with varying sample size, attribute variance and within-sample choice distribution are simulated. Based on these datasets, the utility coefficients and ASCs of the specified MNLs are re-estimated and compared with the original values specified as the priori. It is found that （1） the estimation accuracy of utility parameters increases as the sample size increases; （2） the utility coefficients can be re-estimated with reasonable accuracy, but the estimates of the ASCs are confronted with much larger errors; （3） as the variances of the alternative attributes increase, the estimation accuracy improves significantly; and （4） as the distribution of chosen choices becomes more balanced across alternatives within sample datasets, the hit-ratio decreases. The results indicate that （a） under a similar setting presented in this paper, a large sample consisting of a few thousand observations （3000 - 4000） may be needed in order to provide reasonable estimates for utility coefficients, particularly for ASCs; （b） a larger, but realistic attribute space is preferred in the stated preference survey design; and （c） choice datasets with unbalanced ＂chosen＂ choice frequency distribution is preferred, in order to better capture the elasticity between the ＂perceived utility＂ associated wit展开更多
基金This paper is supported by the National Key Project of Basic Theory Research"the Formation Mechanism and Prediction Theory of Severe Climatic and Synoptic Disasters in China" under Grant 199804096.
文摘The sounding data of meteorological satellites provide not only the real time weather information about the distribution of both cloud and rainfall,but also some others about the movement and state of atmosphere.They are important variables and parameters for NWP model used to simulate and predict atmospheric state.In order to introduce remote sensing information from satellites into NWP model,there is an efficient way of establishing an RT model by use of the atmosphere radiation sounding data of meteorological satellites to get the variables and parameters valuable to NWP model.In this paper,we set up profiles of air temperature and water vapor from the surface to upper (0.1 hPa) using the radiosounding data and the surface data from May to August 1998 atmosphere East Asia.A TOVS RT model (RTTOV5) is provided to compute the value of radiation value of HIRS channels in NOAA14.Then the radiation values of 19 HIRS channels are gotten.After matching these data computed by the RT model and the corresponding values coming from satellite sounding in time,the statistic distribution of bias between tile model output and the satellite sounding at each sounding channel can be gotten.At the same time.the distribution of RMS to every TOVS HIRS channel,the standard biases to different scanning angle to each channel are also obtained.
文摘Two simulations of five years (2003-2007) were conducted with the Regional Climate models RegCM4, one coupled with Land surface models BATS and the other with CLM4.5 over West Africa, where simulated air temperature and precipitation were analyzed. The purpose of this study is to assess the performance of RegCM4 coupled with the new CLM4.5 Land</span><span style="font-family:""> </span><span style="font-family:Verdana;">surface scheme and the standard one named BATS in order to find the best configuration of RegCM4 over West African. This study could improve our understanding of the sensitivity of land surface model in West Africa climate simulation, and provide relevant information to RegCM4 users. The results show fairly realistic restitution of West Africa’s climatology and indicate correlations of 0.60 to 0.82 between the simulated fields (BATS and CLM4.5) for precipitation. The substitution of BATS surface scheme by CLM4.5 in the model configuration, leads mainly to an improvement of precipitation over the Atlantic Ocean, however, the impact is not sufficiently noticeable over the continent. While the CLM4.5 experiment restores the seasonal cycles and spatial distribution, the biases increase for precipitation and temperature. Positive biases already existing with BATS are amplified over some sub-regions. This study concludes that temporal localization (seasonal effect), spatial distribution (grid points) and magnitude of precipitation and temperature (bias) are not simultaneously improved by CLM4.5. The introduction of the new land surface scheme CLM4.5, therefore, leads to a performance of the same order as that of BATS, albeit with a more detailed formulation.
文摘Literature review indicates that sample size, attribute variance and within-sample choice distribution of alternatives are important considerations in the estimation of multinomial logit （MNL） models, but their impacts on the estimation accuracy have not been systematically studied. Therefore, the objective of this paper is to provide an empirical examination to the above issues through a set of simulated discrete choice preference and rank ordered preference datasets. In this paper, the utility coefficients, alternative specific constants （ASCs）, and the mean and standard deviation of the four attributes for a set of seven hypothetical alternatives are specified as a priori. Then, synthetic datasets, with varying sample size, attribute variance and within-sample choice distribution are simulated. Based on these datasets, the utility coefficients and ASCs of the specified MNLs are re-estimated and compared with the original values specified as the priori. It is found that （1） the estimation accuracy of utility parameters increases as the sample size increases; （2） the utility coefficients can be re-estimated with reasonable accuracy, but the estimates of the ASCs are confronted with much larger errors; （3） as the variances of the alternative attributes increase, the estimation accuracy improves significantly; and （4） as the distribution of chosen choices becomes more balanced across alternatives within sample datasets, the hit-ratio decreases. The results indicate that （a） under a similar setting presented in this paper, a large sample consisting of a few thousand observations （3000 - 4000） may be needed in order to provide reasonable estimates for utility coefficients, particularly for ASCs; （b） a larger, but realistic attribute space is preferred in the stated preference survey design; and （c） choice datasets with unbalanced ＂chosen＂ choice frequency distribution is preferred, in order to better capture the elasticity between the ＂perceived utility＂ associated wit
