Clear-air channel detection quality control method suitable for assimilation of geostationary satellite data

Abstract

The invention discloses a clear-air channel detection quality control method suitable for assimilation of geostationary satellite data, and the method comprises the following steps of (1) pre-processing the observed radiant brightness temperature and simulated brightness temperature of the geostationary satellite AHI imager data; (2) establishing a minimum residual algorithm to estimate cloud toppressure and cloud proportion of AHI observation pixels; (3) establishing a cloud criterion algorithm to identify cloud types and evaluate cloud pixels; and (4) forming a coupling scheme by the minimum residual algorithm in the step (2) and the cloud criterion algorithm in the step (3), and establishing a dual cloud detection scheme. The method of the invention improves the data quality control level of the infrared channel of the stationary satellite imager, and improves the numerical model prediction level by improving the satellite data assimilation analysis.

Description

technical field [0001] The invention relates to the field of atmospheric science research, in particular to a clear-air channel quality control method suitable for data assimilation of a new generation of static meteorological satellite infrared imager. Background technique [0002] With the continuous development of meteorological geostationary satellite observation technology, the assimilation of satellite infrared radiation data is more and more widely used in numerical weather prediction models. The infrared radiation of the earth-atmosphere system received by satellites can reflect the vertical structure characteristics of atmospheric temperature and humidity, and can provide important observation information for typhoon, rainstorm and convection and other disastrous weather forecasts. Therefore, geostationary satellite data assimilation is of great value in improving the initial field of numerical models and improving the level of numerical weather prediction. [0003...

AI Technical Summary

Problems solved by technology

Taking the Japanese Sunflower 8 satellite as an example, the 10 infrared channels of its Advanced Himawari Imager (AHI) imager include the water vapor sensitive channels of the upper, middle and upper layers, and the middle layer. If the currently commonly used clear-sky pixel detection scheme is used, it will cause Observation channels that are not affected by clouds are incorrectly excluded

[0007] In general, the existing infrared cloud detection of stationary satellites adopts the detection scheme of clear sky pixels, which can only determine whether there are clouds in the observation pixels of the satellite, but cannot determine whether the observation channels of satellite instruments that are sensitive to different altitude layers of the atmosphere are affected by clouds

The quality control method based on the detection of clear-sky pixels will lead to the false removal of high-level clear-sky channels in the case of low clouds, which reduces the utilization efficiency of satellite data

In addition, considering that when the clear sky channel detection scheme is applied to geostationary satellite instruments, there are two defects due to factors such as the small number of channels: (1) pixels with thin optical thickness clouds and cloud edges may be underreported; (2) Cloud height estimates for high-altitude cirrus and overlapping clouds are biased

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