Clouds are crucial regulators of both weather and climate. Properties such as the amount,type,height,distribution and movement of them have an impact on the earth's radiation budget and the hydrological cycle,thus...Clouds are crucial regulators of both weather and climate. Properties such as the amount,type,height,distribution and movement of them have an impact on the earth's radiation budget and the hydrological cycle,thus cloud observation is very important. The disadvantages of zenith pointing measuring instruments and whole sky visible imagers limit the application of them.A summary of the actuality and application of ground-based whole sky infrared cloud measuring instruments and analyses of the techniques of radiometric calibrations,removal of atmospheric emission and calculation of cloud cover,amount,type are conducted to promote the automatically observation of the whole sky. Fully considering whole sky infrared cloud sounding theories,techniques and applications,there are still a lot of studies on improving the properties of instruments,enhancing the techniques of cloud base height measurements and establishing instrumental cloud classification criterion before actual operations.展开更多
Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural networ...Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.展开更多
Sodium layers (75–105 km) were measured by Na lidar on three nights during March 1–3, 1996. The lidar data were used to calculate the relative atmospheric density perturbations and their spectra. The average r. m. s...Sodium layers (75–105 km) were measured by Na lidar on three nights during March 1–3, 1996. The lidar data were used to calculate the relative atmospheric density perturbations and their spectra. The average r. m. s. density perturbations for early March at Wuhan are 5 %. The vertical wave number spectra exhibit power-law shapes with an average slope of -2.23 in the upper mesosphere when the associated mean density quantity of the day was used.展开更多
基金supported by National Natural Science Foundation of China ( Grant No. 41575024 and Grant No. 41205125)
文摘Clouds are crucial regulators of both weather and climate. Properties such as the amount,type,height,distribution and movement of them have an impact on the earth's radiation budget and the hydrological cycle,thus cloud observation is very important. The disadvantages of zenith pointing measuring instruments and whole sky visible imagers limit the application of them.A summary of the actuality and application of ground-based whole sky infrared cloud measuring instruments and analyses of the techniques of radiometric calibrations,removal of atmospheric emission and calculation of cloud cover,amount,type are conducted to promote the automatically observation of the whole sky. Fully considering whole sky infrared cloud sounding theories,techniques and applications,there are still a lot of studies on improving the properties of instruments,enhancing the techniques of cloud base height measurements and establishing instrumental cloud classification criterion before actual operations.
基金National Key Research and Development Program of China(2017YFC1501704,2016YFA0600703)Projects of International Cooperation and Exchanges NSFC(NSFC-RCUK_STFC)(61661136005)+2 种基金Major State Basic Research Development Program of China(973 Program)(2013CB430101)Six Talent Peaks Project in Jiangsu Province(2015-JY-013)Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD),Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites,National Satellite Meteorological Center,China Meteorological Administration
文摘Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.
文摘Sodium layers (75–105 km) were measured by Na lidar on three nights during March 1–3, 1996. The lidar data were used to calculate the relative atmospheric density perturbations and their spectra. The average r. m. s. density perturbations for early March at Wuhan are 5 %. The vertical wave number spectra exhibit power-law shapes with an average slope of -2.23 in the upper mesosphere when the associated mean density quantity of the day was used.
