Sea surface temperature cooperative inversion method based on near-infrared high spectrum and thermal infrared single-channel image

Abstract

The invention discloses a sea surface temperature cooperative inversion method based on a near-infrared high spectrum and a thermal infrared single-channel image, which is characterized in that the sea surface temperature cooperative inversion method comprises the following steps: S1, performing cloud detection on thermal infrared data; S2, performing atmosphere steam content inversion on high-spectrum data; S3, calculating an atmosphere transmittance and an effective average temperature; and S4, calculating the sea surface temperature. The atmosphere steam content is a main factor which affects infrared seam temperature inversion precision. Currently, a method of utilizing thermal infrared split-window technology or introducing meteorological observation auxiliary data for correcting atmosphere steam effect is widely used. The invention provides a novel method of utilizing near-infrared steam absorption peak high-spectrum data for acquiring the atmosphere steam content, thereby performing thermal infrared image sea surface temperature inversion and correcting the atmosphere effect. The method can effectively settle a problem that synchronous atmosphere steam content data is in shortage in sea surface temperature inversion by a thermal infrared single-channel image.

Description

technical field [0001] The invention relates to the technical field of satellite remote sensing applications, in particular to a sea surface temperature retrieval method. Background technique [0002] Water vapor is the most important atmospheric absorption gas in the near-infrared to thermal infrared spectrum, and it is also the main source of sea surface temperature retrieval errors for single-channel thermal infrared remote sensing loads. The existing single-channel thermal infrared sea temperature retrieval uses observation data from ground meteorological stations or Atmospheric water vapor content information obtained by numerical weather prediction models, due to the scarcity of island-based meteorological stations in remote seas, the spatial resolution of water vapor products output by numerical models is far lower than that of new thermal infrared remote sensing loads, and the forecast frequency is difficult to match with satellite transit time. Therefore, the accura...

AI Technical Summary

Problems solved by technology

[0002] Water vapor is the most important atmospheric absorption gas in the near-infrared to thermal infrared spectrum, and it is also the main source of sea surface temperature retrieval errors for single-channel thermal infrared remote sensing loads. The existing single-channel thermal infrared sea temperature retrieval uses observation data from ground meteorological stations or Atmospheric water vapor content information obtained by numerical weather prediction models, due to the scarcity of island-based meteorological stations in remote seas, the spatial resolution of water vapor products output by numerical models is far lower than that of new thermal infrared remote sensing loads, and the forecast frequency is difficult to match with satellite transit time. As a result, the accuracy of sea surface temperature retrieval is reduced

Images