In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sit...In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sites, including 260 belonging to the Crustal Movement Observation Network of China （CMONOC） and 692 belonging to the China Meteorological Administration GNSS network （CMAGN）. Additionally, GNSS observation collecting and data processing procedures are presented and PWV data quality control methods are investigated. PWV levels as determined by GNSS and radiosonde are compared. The results show that GNSS estimates are generally in good agreement with measurements of radio- sondes and water vapor radiometers （WVR）. The PWV retrieved by the national GNSS network is used in weather forecasting, assimilation of data into numerical weather prediction models, the validation of PWV estimates by radiosonde, and plum rain monitoring. The network is also used to monitor the total ionospheric electron content.展开更多
China is one of the countries in the world claiming the most occurrences of severe natural disasters. The natural disasters occurring in this country, diversify in type, wide in geographic distribution, high frequency...China is one of the countries in the world claiming the most occurrences of severe natural disasters. The natural disasters occurring in this country, diversify in type, wide in geographic distribution, high frequency of occurrence, and bring heavy losses in terms of people's lives and properties.展开更多
Projection Pursuit (PP) Principal Component Analysis (PCA) method is herein introduced and applied to the field of meteorology for the first time. Some problems relevant to meteorological application are dis- cussed i...Projection Pursuit (PP) Principal Component Analysis (PCA) method is herein introduced and applied to the field of meteorology for the first time. Some problems relevant to meteorological application are dis- cussed in detail and comparisons with EOF method are made with the emphasis on robustness.展开更多
基金financially supported by the Special Fund for Meteorological Scientific Research in the Public Interest(GYHY201406012)the National Natural Science Foundation of China(41275114)a construction fund for CMONOC
文摘In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sites, including 260 belonging to the Crustal Movement Observation Network of China （CMONOC） and 692 belonging to the China Meteorological Administration GNSS network （CMAGN）. Additionally, GNSS observation collecting and data processing procedures are presented and PWV data quality control methods are investigated. PWV levels as determined by GNSS and radiosonde are compared. The results show that GNSS estimates are generally in good agreement with measurements of radio- sondes and water vapor radiometers （WVR）. The PWV retrieved by the national GNSS network is used in weather forecasting, assimilation of data into numerical weather prediction models, the validation of PWV estimates by radiosonde, and plum rain monitoring. The network is also used to monitor the total ionospheric electron content.
文摘China is one of the countries in the world claiming the most occurrences of severe natural disasters. The natural disasters occurring in this country, diversify in type, wide in geographic distribution, high frequency of occurrence, and bring heavy losses in terms of people's lives and properties.
文摘Projection Pursuit (PP) Principal Component Analysis (PCA) method is herein introduced and applied to the field of meteorology for the first time. Some problems relevant to meteorological application are dis- cussed in detail and comparisons with EOF method are made with the emphasis on robustness.
