Based on daily data sets of 17 meteorological factors during the period of 1954-2005 for 60 gauge stations distributed over Gansu Province of China and the corresponding dust storm records, the dust storm probabilitie...Based on daily data sets of 17 meteorological factors during the period of 1954-2005 for 60 gauge stations distributed over Gansu Province of China and the corresponding dust storm records, the dust storm probabilities related to different classes of each factor have been calculated and analyzed. On the basis of statistical analysis, a meteorological descriptor quantifying the daily dust storm occurrence probability for each station, which is referred to as the Dust Storm Occurrence Probability Index （DSOPI）, has been effectively established. According to the statistical characteristics of DSOPI for each station, a feasible judging criterion for a dust storm event has been determined, which can greatly contribute to forecasting dust storms and completing the unavailable historic dust storm records. Meanwhile, the average daily dust storm probability related to each factor on the dust storm day for each station has been specially analyzed in detail, finally disclosing that, in general, the more signifi- cant one factor＇s influence on dust storms, the greater its contribution to them; and each factor＇s contribution clearly varies from place to place. Moreover, on average, maximum and mean wind speeds, maximum-speed wind direction, daily sunny hours, evaporation, mean and lowest relative humidity, lowest surface air pressure and vapor pressure contribute to dust storm events in Gansu Province most greatly in order among all the 17 involved factors.展开更多
The probability distribution of wave heights under the assumption of narrowband linear wave theory follows the Rayleigh distribution and the statistical relationships between some characteristic wave heights, derived ...The probability distribution of wave heights under the assumption of narrowband linear wave theory follows the Rayleigh distribution and the statistical relationships between some characteristic wave heights, derived from this distribution, are widely used for the treatment of realistic wind waves. However, the bandwidth of wave frequency influences the probability distribution of wave heights. In this paper, a wave-spectrum-width parameter B was introduced into the JONSWAP spectrum. This facilitated the construction of a wind-wave spectrum and the reconstruction of wind-wave time series for various growth stages, based on which the probability density distributions of the wind-wave heights were studied statistically. The distribution curves deviated slightly from the theoretical Rayleigh distribution with increasing B. The probability that a wave height exceeded a certain value was clearly smaller than the theoretical value for B≥0.3, and the difference between them increased with the threshold value. The relation between the Hs/σ ratio and B was investigated statistically, which revealed that the Hs/σ ratio deviated from 4.005 and declined with B. When B reached 0.698 1, the Hs/σ ratio was 3.825, which is about 95.5% of its original value. This indicates an overestimation in the a potential method for improving the accuracy of the Hs extremely large waves under severe sea states. prediction of Hs from Hs=4.005σ, and provides remote sensing retrieval algorithm, critical for展开更多
基金funded by National Program on Key Basic Research Project (973 Program, Grant No. 2009CB421402)the open foundation from Key Laboratory for Semi-Arid Climate Change of the Ministry of Education,Lanzhou University,and National Natural Science Foundation of China (Grant No. 40975007)
文摘Based on daily data sets of 17 meteorological factors during the period of 1954-2005 for 60 gauge stations distributed over Gansu Province of China and the corresponding dust storm records, the dust storm probabilities related to different classes of each factor have been calculated and analyzed. On the basis of statistical analysis, a meteorological descriptor quantifying the daily dust storm occurrence probability for each station, which is referred to as the Dust Storm Occurrence Probability Index （DSOPI）, has been effectively established. According to the statistical characteristics of DSOPI for each station, a feasible judging criterion for a dust storm event has been determined, which can greatly contribute to forecasting dust storms and completing the unavailable historic dust storm records. Meanwhile, the average daily dust storm probability related to each factor on the dust storm day for each station has been specially analyzed in detail, finally disclosing that, in general, the more signifi- cant one factor＇s influence on dust storms, the greater its contribution to them; and each factor＇s contribution clearly varies from place to place. Moreover, on average, maximum and mean wind speeds, maximum-speed wind direction, daily sunny hours, evaporation, mean and lowest relative humidity, lowest surface air pressure and vapor pressure contribute to dust storm events in Gansu Province most greatly in order among all the 17 involved factors.
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2013AA09A505)the National Natural Science Foundation of China(Nos.U1133001,41376027,41406017)the NSFC-Shandong Joint Fund for Marine Science Research Centers(No.U1406401)
文摘The probability distribution of wave heights under the assumption of narrowband linear wave theory follows the Rayleigh distribution and the statistical relationships between some characteristic wave heights, derived from this distribution, are widely used for the treatment of realistic wind waves. However, the bandwidth of wave frequency influences the probability distribution of wave heights. In this paper, a wave-spectrum-width parameter B was introduced into the JONSWAP spectrum. This facilitated the construction of a wind-wave spectrum and the reconstruction of wind-wave time series for various growth stages, based on which the probability density distributions of the wind-wave heights were studied statistically. The distribution curves deviated slightly from the theoretical Rayleigh distribution with increasing B. The probability that a wave height exceeded a certain value was clearly smaller than the theoretical value for B≥0.3, and the difference between them increased with the threshold value. The relation between the Hs/σ ratio and B was investigated statistically, which revealed that the Hs/σ ratio deviated from 4.005 and declined with B. When B reached 0.698 1, the Hs/σ ratio was 3.825, which is about 95.5% of its original value. This indicates an overestimation in the a potential method for improving the accuracy of the Hs extremely large waves under severe sea states. prediction of Hs from Hs=4.005σ, and provides remote sensing retrieval algorithm, critical for
