Over the last three decades, the Tibetan Plateau has exhibited a significant increase in air temperature and a significant decrease in wind speed. How the surface heat source has changed is an important issue in monso...Over the last three decades, the Tibetan Plateau has exhibited a significant increase in air temperature and a significant decrease in wind speed. How the surface heat source has changed is an important issue in monsoon research. Based on routine meteorological data, this study investigates the differences between methods for estimating trends in surface sensible heat flux on the Tibetan Plateau for the period 1984-2006. One is a physical method based on micro-meteorological theory and experi- ments, and takes into account both atmospheric stability and thermal roughness length. The other approach includes conven- tional empirical methods that assume the heat transfer coefficient is a constant value or a simple function of wind speed. The latter method is used widely in climatologic studies. Results from the physical method show that annual mean sensible heat flux has weakened by 2% per decade, and flux seasonal mean has weakened by -2%--4% except in winter. The two commonly used empirical methods showed high uncertainties in heat flux trend estimates, although they produced similar climatologies. Annual mean heat flux has weakened by 7% per decade when a fixed transfer coefficient is used, whereas the trend is negligible when the transfer coefficient is assumed a function of wind speed. Conventional empirical methods may therefore misrepresent the trend in sensible heat flux.展开更多
Here we use a Discriminant Genetic Algorithm Extended (DGAE) model to diagnose and predict seasonal sand and dust storm (SDS) activities occurring in Northeast Asia. The study employed the regular meteorological data,...Here we use a Discriminant Genetic Algorithm Extended (DGAE) model to diagnose and predict seasonal sand and dust storm (SDS) activities occurring in Northeast Asia. The study employed the regular meteorological data, including surface data, upper air data, and NCEP reanalysis data, collected from 1980–2006. The regional, seasonal, and annual differences of 3-D atmospheric circulation structures and SDS activities in the context of spatial and temporal distributions were given. Genetic algorithms were introduced with the further extension of promoting SDS seasonal predication from multi-level resolution. Genetic probability was used as a substitute for posterior probability of multi-level discriminants, to show the dual characteristics of crossover inheritance and mutation and to build a non-linear adaptability function in line with extended genetic algorithms. This has unveiled the spatial distribution of the maximum adaptability, allowing the forecast field to be defined by the population with the largest probability, and made discriminant genetic extension possible. In addition, the effort has led to the establishment of a regional model for predicting seasonal SDS activities in East Asia. The model was tested to predict the spring SDS activities occurring in North China from 2007 to 2009. The experimental forecast resulted in highly discriminant intensity ratings and regional distributions of SDS activities, which are a meaningful reference for seasonal SDS predictions in the future.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos. 40875009, 40810059006)Key Innovation Project of Chinese Academy of Sciences (Grant No. KZCX2-YW-Q11-01),"100-Talent" Program of Chinese Academy of Sciences
文摘Over the last three decades, the Tibetan Plateau has exhibited a significant increase in air temperature and a significant decrease in wind speed. How the surface heat source has changed is an important issue in monsoon research. Based on routine meteorological data, this study investigates the differences between methods for estimating trends in surface sensible heat flux on the Tibetan Plateau for the period 1984-2006. One is a physical method based on micro-meteorological theory and experi- ments, and takes into account both atmospheric stability and thermal roughness length. The other approach includes conven- tional empirical methods that assume the heat transfer coefficient is a constant value or a simple function of wind speed. The latter method is used widely in climatologic studies. Results from the physical method show that annual mean sensible heat flux has weakened by 2% per decade, and flux seasonal mean has weakened by -2%--4% except in winter. The two commonly used empirical methods showed high uncertainties in heat flux trend estimates, although they produced similar climatologies. Annual mean heat flux has weakened by 7% per decade when a fixed transfer coefficient is used, whereas the trend is negligible when the transfer coefficient is assumed a function of wind speed. Conventional empirical methods may therefore misrepresent the trend in sensible heat flux.
基金supported by National S & T Support Program (Grant No. 2008BAC40B02)National Basic Research Program of China (Grant Nos. 2006CB403703 and 2006CB403701)Basic Research Fund under Chinese Academy of Meteorological Sciences (Grant Nos. 2009Y002, 2009Y001)
文摘Here we use a Discriminant Genetic Algorithm Extended (DGAE) model to diagnose and predict seasonal sand and dust storm (SDS) activities occurring in Northeast Asia. The study employed the regular meteorological data, including surface data, upper air data, and NCEP reanalysis data, collected from 1980–2006. The regional, seasonal, and annual differences of 3-D atmospheric circulation structures and SDS activities in the context of spatial and temporal distributions were given. Genetic algorithms were introduced with the further extension of promoting SDS seasonal predication from multi-level resolution. Genetic probability was used as a substitute for posterior probability of multi-level discriminants, to show the dual characteristics of crossover inheritance and mutation and to build a non-linear adaptability function in line with extended genetic algorithms. This has unveiled the spatial distribution of the maximum adaptability, allowing the forecast field to be defined by the population with the largest probability, and made discriminant genetic extension possible. In addition, the effort has led to the establishment of a regional model for predicting seasonal SDS activities in East Asia. The model was tested to predict the spring SDS activities occurring in North China from 2007 to 2009. The experimental forecast resulted in highly discriminant intensity ratings and regional distributions of SDS activities, which are a meaningful reference for seasonal SDS predictions in the future.
