Regular and irregular observational data are used to analyze and simulate a torrential rain over the south of China on 18 - 24 June 2005. Since the regular data cannot depict the rainfall system fully, GRAPES model is...Regular and irregular observational data are used to analyze and simulate a torrential rain over the south of China on 18 - 24 June 2005. Since the regular data cannot depict the rainfall system fully, GRAPES model is used to simulate this process. Different data are assimilated for 12 hours by its simulating system and different analysis data are obtained. In order to analyze how well the model forecast has been improved with the addition of assimilated aircraft data, these different analysis data are used as the first-guess data to conduct two control numerical simulation tests. From these tests, it is proved that be model that adds aircraft assimilation data can simulate the main region of precipitation, which is more consistent with the observed precipitation than the model that does not, and that the accuracy rate is also improved. These numerical simulation tests not only show that it is necessary and capable to improve the modeling of this torrential rain process by using aircraft data, but also lays the foundation for forecasting heavy rains in the south of China based on aircraft data.展开更多
To investigate the annual and interaunual variability of ocean surface wind over the South China Sea (SCS), the vector empirical orthogonal function (VEOF) method and the Hilbert-Huang transform (HHT) method wer...To investigate the annual and interaunual variability of ocean surface wind over the South China Sea (SCS), the vector empirical orthogonal function (VEOF) method and the Hilbert-Huang transform (HHT) method were employed to analyze a set of combined satellite scatterometer wind data during the period from December 1992 to October 2009. The merged wind data were generated from European Remote Sensing Satellite (ERS)-1/2 Scatterometer, NASA Scatterometer (NSCAT) and NASA's Quick Scatterometer (QuikSCAT) wind products. The first VEOF mode corresponds to a winter-summer mode which accounts for 87.3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscil- lation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals were calculated. The temporal mode of the ftrst intcrannual VEOF is correlated with the Southern Oscillation Index (SOI) with a four-month lag. The second temporal interannual VEOF mode is correlated with the SOI with no time lag. The time series of the two interannual VEOFs were decomposed using the HI-IT method and the results also show a correlation between the interannual variability and El Nino-Southern Oscillation (ENSO) events.展开更多
基金Techniques for Monitoring and Pre-warning Lightening for Pearl River Delta Cities, a socialwelfare project of the Ministry of Science and Technology (2005 DIB3J110)Mesoscale Observation,Experiments and Research on Heavy Rains in Southern China (2004CB418307)Research on the Techniques forTropical Assimilation Based on Modern Measurement Techniques
文摘Regular and irregular observational data are used to analyze and simulate a torrential rain over the south of China on 18 - 24 June 2005. Since the regular data cannot depict the rainfall system fully, GRAPES model is used to simulate this process. Different data are assimilated for 12 hours by its simulating system and different analysis data are obtained. In order to analyze how well the model forecast has been improved with the addition of assimilated aircraft data, these different analysis data are used as the first-guess data to conduct two control numerical simulation tests. From these tests, it is proved that be model that adds aircraft assimilation data can simulate the main region of precipitation, which is more consistent with the observed precipitation than the model that does not, and that the accuracy rate is also improved. These numerical simulation tests not only show that it is necessary and capable to improve the modeling of this torrential rain process by using aircraft data, but also lays the foundation for forecasting heavy rains in the south of China based on aircraft data.
基金supported by the National Natural Science Foundation of China through G41006108the Open Research Fund of the Shandong Provincial Key Laboratory of Marine Ecology and Environment & Disaster Prevention and Mitigation through G2011001+1 种基金the Laboratory of Data Analysis and Application, State Oceanic Administration through LDAA-2013-02the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering through G2009586812
文摘To investigate the annual and interaunual variability of ocean surface wind over the South China Sea (SCS), the vector empirical orthogonal function (VEOF) method and the Hilbert-Huang transform (HHT) method were employed to analyze a set of combined satellite scatterometer wind data during the period from December 1992 to October 2009. The merged wind data were generated from European Remote Sensing Satellite (ERS)-1/2 Scatterometer, NASA Scatterometer (NSCAT) and NASA's Quick Scatterometer (QuikSCAT) wind products. The first VEOF mode corresponds to a winter-summer mode which accounts for 87.3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscil- lation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals were calculated. The temporal mode of the ftrst intcrannual VEOF is correlated with the Southern Oscillation Index (SOI) with a four-month lag. The second temporal interannual VEOF mode is correlated with the SOI with no time lag. The time series of the two interannual VEOFs were decomposed using the HI-IT method and the results also show a correlation between the interannual variability and El Nino-Southern Oscillation (ENSO) events.