Title :
A New Method to Retrieve Near-sea Surface Meteorological Parameters
Author :
Zhang, Biao ; He, Yijun
Author_Institution :
Grad. Sch., Chinese Acad. of Sci., Beijing
fDate :
July 31 2006-Aug. 4 2006
Abstract :
A new method is presented to retrieve near-sea surface instantaneous air temperature and dew point temperature. Satellite data include the air temperature and point temperature at 1000 mb are inversed by TOVS data. Sea surface temperature is derived from AVHRR data. Ship-measured data come from the observations of NEAR-GOOS (North-East Asia Regional- Global Ocean observing) experiment. Then two different artificial neural network models are developed to retrieve near- sea surface instantaneous air temperature and dew point temperature. For the single parameter neural network model (SANN) model, the root mean square (RMS) error of near-sea surface instantaneous air temperature and dew point temperature are 1.85degC and 2.59degC respectively, but those for multi-parameter neural network (MANN) model are 1.92degcand 2.67degC respectively. The results indicate that the retrieval accuracy of the SANN model is superior to that of the MANN model and prove that there is a close relationship between near- sea surface air temperature and dew point temperature.
Keywords :
atmospheric humidity; atmospheric temperature; geophysics computing; mean square error methods; neural nets; ocean temperature; oceanographic techniques; remote sensing; AVHRR data; Advanced Very High Resolution Radiometer; MANN model; NEAR-GOOS experiment; North-East Asia Regional- Global Ocean observing experiment; SANN model; TOVS data; air temperature; dew point temperature; meteorological parameters; multi-parameter neural network; near-sea surface temperature; root mean square error; satellite data; ship-measured data; single parameter neural network; Artificial neural networks; Information retrieval; Meteorology; Neural networks; Ocean temperature; Root mean square; Satellites; Sea surface; Temperature measurement; Temperature sensors;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on
Conference_Location :
Denver, CO
Print_ISBN :
0-7803-9510-7
DOI :
10.1109/IGARSS.2006.336