The invention belongs to the technical field of atmospheric
microwave remote sensing and monitoring, and relates to a rapid temperature and
humidity profile inversion method for a multi-frequency atmospheric
microwave radiometer. Acquiring a
brightness temperature data set of the multi-frequency atmospheric
microwave radiometer, performing space-time matching on the
brightness temperature data set and corresponding ERA5 reanalysis or sounding
balloon temperature and
humidity profile data, constructing a matched
data set, and dividing the matched data set into a
test set, a
training set and a
verification set; establishing an
atmosphere temperature and
humidity profile inversion model based on a CNN-LSTM combined neural network; and training the model by using the
training set, guiding the model optimization process by using the
verification set, finally inputting multi-frequency
brightness temperature data measured by the multi-frequency
microwave radiometer into the trained model, and carrying out inversion to obtain an
atmosphere temperature and humidity profile. According to
observation data of the multi-frequency
atmosphere microwave radiometer, regional atmosphere temperature and humidity profile data are rapidly and accurately obtained, and efficient inversion of the temperature and humidity profile is achieved; the vertical detection
advantage of the multi-frequency
microwave radiometer is exerted, the inversion efficiency is improved, and the method has a wide application prospect.