[Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with soundi...[Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with sounding data, the physical quantities and radar parameter of hail shooting and heavy convective rainfall weather are compared and analyzed. [Result] The smaller Sl is conducive to the generation of hail weather. When K〉 35 ~C, the probability for occurrence of heavy rainfall weather is significantly increased; when K〈20 ^（3, the probability for occurrence of heavy rainfall weather is significantly decreased. When CAPE value is greater than 1 500 J/KG, the probability for occurrence of hail weather is significantly decreased, while the probability for occurrence of heavy rainfall weather is significantly in- creased. The possibility for occurrence of hail monomer is small when the wind shear is less than 5 m/s; and it is large while wind shear is greater than 20 m/s. The radar forecasting indexes of hail monomer is as follows： VIL value reaches 35 kg/m2 （May）, 43 kg/m2 （June and July）, the monomer height is greater than 9 km, the maximum reflectivity factor is larger than 60 dBz, strong center height reaches 3.3 km （May）, 4.3 km （June） and 5.5 km （July）; VlL value of heavy rainfall monomer generally is below 25 kg/m2. [Conclusion] The paper provides basis form prediction of hail and heavy rainfall.展开更多
Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflect...Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters,comprising leaf area index (LAI;m-2 green leaf area m-2 soil) and green leaf chlorophyll density (GLCD;mg chlorophyll m 2 soil),using stepwise multiple regression (SMR) models and support vector machines (SVMs).Four transformations of the rice canopy data were made,comprising reflectances (R),first-order derivative reflectances (D1),second-order derivative reflectances (D2),and logarithm transformation of reflectances (LOG).The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI,with a root mean square error (RMSE) of 1.0496 LAI units.The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD,with an RMSE of 523.0741 mg m-2.The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters,but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.展开更多
基金Supported by Science and Technology Development Project of Shandong Science and Technology Hall(2010GSF10805)National Natural Science Foundation of China(41140036)~~
文摘[Objective] The paper is to analyze physical quantities and radar parameter of hail shooting and heavy convective rainfall weather. [Method] Using radar data of Jinan station during 2002 and 2008, combined with sounding data, the physical quantities and radar parameter of hail shooting and heavy convective rainfall weather are compared and analyzed. [Result] The smaller Sl is conducive to the generation of hail weather. When K〉 35 ~C, the probability for occurrence of heavy rainfall weather is significantly increased; when K〈20 ^（3, the probability for occurrence of heavy rainfall weather is significantly decreased. When CAPE value is greater than 1 500 J/KG, the probability for occurrence of hail weather is significantly decreased, while the probability for occurrence of heavy rainfall weather is significantly in- creased. The possibility for occurrence of hail monomer is small when the wind shear is less than 5 m/s; and it is large while wind shear is greater than 20 m/s. The radar forecasting indexes of hail monomer is as follows： VIL value reaches 35 kg/m2 （May）, 43 kg/m2 （June and July）, the monomer height is greater than 9 km, the maximum reflectivity factor is larger than 60 dBz, strong center height reaches 3.3 km （May）, 4.3 km （June） and 5.5 km （July）; VlL value of heavy rainfall monomer generally is below 25 kg/m2. [Conclusion] The paper provides basis form prediction of hail and heavy rainfall.
基金supported by the National Natural Science Foundation of China(Grant Nos. 40571115 and 40271078)the National Hi-Tech Research and Development Program of China(Grant No. 2006AA10Z203)
文摘Hyperspectral reflectance (350-2500 nm) measurements were made over two experimental rice fields containing two cultivars treated with three levels of nitrogen application.Four different transformations of the reflectance data were analyzed for their capability to predict rice biophysical parameters,comprising leaf area index (LAI;m-2 green leaf area m-2 soil) and green leaf chlorophyll density (GLCD;mg chlorophyll m 2 soil),using stepwise multiple regression (SMR) models and support vector machines (SVMs).Four transformations of the rice canopy data were made,comprising reflectances (R),first-order derivative reflectances (D1),second-order derivative reflectances (D2),and logarithm transformation of reflectances (LOG).The polynomial kernel (POLY) of the SVM using R was the best model to predict rice LAI,with a root mean square error (RMSE) of 1.0496 LAI units.The analysis of variance kernel of SVM using LOG was the best model to predict rice GLCD,with an RMSE of 523.0741 mg m-2.The SVM approach was not only superior to SMR models for predicting the rice biophysical parameters,but also provided a useful exploratory and predictive tool for analyzing different transformations of reflectance data.
