Near-surface air temperature estimation method and system, storage medium and equipment

Abstract

The invention belongs to the technical field of near-surface air temperature estimation, and discloses a near-surface air temperature estimation method and system, a storage medium and equipment, and the method comprises the steps of obtaining four necessary satellite data inversion parameters related to the near-surface air temperature and seven alternative parameters which can be obtained by a ground meteorological station, and carrying out the preprocessing of the data; using fast Fourier transform to carry out fast conversion on the time sequence information of various observation elements, and extracting a public period between meteorological elements related to the temperature of a meteorological station; constructing a long short-term memory (LSTM) neural network, and training the LSTM network by taking the obtained common period and the estimation time as a data group to obtain an estimation temperature; and determining an estimation model precision evaluation index, constructing an air temperature estimation model based on the FFT-LSTM neural network, estimating the near-surface air temperature, and performing precision evaluation on the model. According to the invention, the model has a good estimation effect and high precision, and the defect of uneven distribution of meteorological station areas is overcome.

Description

technical field [0001] The invention belongs to the technical field of near-surface air temperature estimation, and in particular relates to a near-surface air temperature estimation method, system, storage medium and equipment. Background technique [0002] Near-surface air temperature generally refers to the temperature about 2 meters above the surface, which is a very important parameter in climate change research [Sun, Y.J., Wang J.F., Zhang, R.H., Gillies, R.R., Xue Y. and BoY. C., Air temperature retrieval from remote sensing data based on thermodynamics. Theoretical and Applied Climatology, 2005, 80: 37-48.]. Near-surface air temperature (hereinafter referred to as air temperature) is an important climate parameter in the land surface energy balance and one of the important observation elements in meteorological observation. Global climate change has seriously damaged the natural ecological environment and has had a serious impact on human society. The study found t...

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Problems solved by technology

The third is that Mao Kebiao et al. used the surface temperature and emissivity of ASTER data as prior knowledge to invert the near-surface air temperature from ASTER data. However, the band resolution of ASTER data is relatively high, which is difficult to meet the current needs.

[0005] Through the above analysis, the problems and defects of the existing technology are: the traditional neural network method cannot clearly obtain the mathematical relationship between different parameters, and the original data will be split into various features during the calculation process. These features are related to judging a The characteristics used by the firm are completely different. When a result is finally obtained through the model, it is not known which aspects it uses to obtain this result

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