A real-time calculation method of cloud top height based on satellite infrared detection meta-parameters

Abstract

The present invention discloses a real-time calculation method of cloud top height based on satellite infrared detection element parameters. First, cloud profile data set, satellite hyperspectral sensor parameters and clear sky atmospheric profile data set are collected. The above data sets are used for cloud-sky radiation transmission calculation and clear sky radiation transmission calculation to obtain the clear sky and cloud sky ambient brightness temperature difference value; the calculated clear sky and cloud sky ambient brightness temperature difference value is combined with the cloud profile data set to calculate the lookup table of sub-pixel cloud amount, cloud top height and brightness temperature difference; the cloud top height is checked layer by layer by comparing the lookup table to see if the condition is met; if it is met, the hyperspectral pixel cloud amount and cloud top height are obtained; if not, the above steps are continued. The data calculation of the present invention is reliable.

Description

Technical Field

[0001] The invention relates to the field of satellite detection technology, and in particular to a real-time calculation method for cloud top height based on satellite infrared detection element parameters. Background Art

[0002] The assimilation of hyperspectral infrared detector data has become one of the main focuses of current research. Due to the fact that infrared radiation cannot penetrate clouds, it is very important to detect clouds when assimilating satellite hyperspectral infrared atmospheric detection data to eliminate observations affected by clouds. For different hyperspectral infrared atmospheric detectors, many researchers have proposed a variety of cloud detection methods for hyperspectral infrared observation data through different methods. The clear sky field detection method based on Bayesian theory (English et al., 1999) can give the probability of cloud-free observation field and can be used on various satellite data, but this method is the most conservative and can only retain about 5% of the data (Pavelin et al., 2008). The carbon dioxide slicing method (Chahine, 1974; Menzel et al., 1983) inverts cloud top pressure and effective cloud amount based on the main component of radiation transfer, realizes three-dimensional cloud detection with the help of the window channel in the hyperspectral satellite, and can input three-dimensional cloud parameters into the fast radiation transfer model to simulate cloud area radiation. McNally and Watts cloud detection method (McNally and Watts, 2003) assumes that there is no deviation between background and observation information. Based on the relationship between background brightness temperature and actual observation brightness temperature under clear sky conditions, it detects whether the channel observation is affected by clouds. It is also a three-dimensional cloud detection method with higher computational efficiency than the carbon dioxide slicing method. Cloud removal method (Eyre and Watts, 1987; Li et al., 2005) assumes that only the cloud amount will change in the observation of adjacent fields of view. The equivalent clear sky radiation value of the target field of view is obtained by integrating the observations of multiple fields of view. However, this assumption is rarely established and is difficult to be applied in numerical forecasting. Cloud mask auxiliary method (Li et al., 2004) takes into account that high-resolution imager data can provide information such as cloud mask and cloud phase, which can bring more cloud parameters to hyperspectral infrared observation data to achieve cloud detection. However, based on the two-dimensional clear sky field detection, this method is prone to excessively exclude observations at high levels that are not affected by clouds. Experience shows that when some channels of the satellite infrared hyperspectral data have large noise or large deviations in pixel registration, making it difficult to deal with the observation deviation well, cloud pollution and hyperspectral detection data are difficult to distinguish from clear sky data, making it difficult to actually apply them in numerical forecasting. Summary of the invention

[0003] The object of the present invention is to provide a method for real-time calculation of cloud top height based on satellite infrared detection element parameters, and the present invention is achieved in the following way:

[0004] A real-time calculation method for cloud top height based on satellite infrared detection meta-parameters is specifically performed in the following steps:

[0005] S1: First, collect cloud profile data sets, satellite hyperspectral sensor parameters and clear sky atmospheric profile data sets, and use the above data sets to calculate cloud-sky radiation transfer and clear sky radiation transfer to obtain the difference in ambient brightness temperature between the clear sky and the cloud-sky;

[0006] S2: The calculated brightness temperature difference between clear sky and cloudy sky is combined with the cloud profile data set to obtain a lookup table of sub-pixel cloud amount, cloud top height and brightness temperature difference;

[0007] S3: Check the cloud top height against the lookup table layer by layer to see if it meets the conditions;

[0008] S4: If satisfied, the cloud amount and cloud top height of the hyperspectral pixel are obtained;

[0009] S5: If not satisfied, continue to execute step S3.

[0010] In step S3, it also includes infrared imager cloud detection and parameter fusion data based on pixel area.

[0011] Further, in step S1, the clear sky brightness temperature of the infrared hyperspectral channel is calculated by formula (1):

[0012]

[0013] Among them, L clr (v) is the clear sky brightness temperature of the channel, τ s (v) is the transmittance from the surface to the top of the atmosphere, ε s (v) is the surface emissivity of the channel, B(v, T s ) is the equivalent blackbody brightness temperature of the channel on the surface, B(v, T) is the equivalent blackbody brightness temperature of the channel, and τ is the atmospheric tomography transmittance.

[0014] Furthermore, in step S1, the cloud environment brightness temperature of the infrared hyperspectral channel is calculated by formula (2):

[0015]

[0016] Among them, L cld (v) is the top-of-atmosphere brightness temperature of the channel in a cloudy environment, τ cld (v) is the channel transmittance from the cloud top to the top of the atmosphere, B(v, T cld ) is the equivalent blackbody brightness temperature of the cloud surface.

[0017] Further, in step S1, the brightness temperature difference between the clear sky and the cloudy sky environment is calculated by formula (3):

[0018] diff=L clr (v)-L(v)=N(L clr (v)-L cld (v) Formula (3)

[0019] Among them, diff is the brightness temperature difference between the channel in the clear sky environment and the cloudy sky environment, and N is the cloud cover;

[0020] The N in formula (3) is cycled from 0 to 1 with a step size of 0.1. Each time N is cycled, the cloud top height is cycled from 1000 hPa to 322 hPa, and the channel brightness temperature difference between the clear sky and the cloudy environment under different cloud top heights and cloud amounts is calculated.

[0021] Further, in step S2, formula (1) to formula (3) are looped to calculate a lookup table of the brightness temperature difference between the clear sky and the cloudy environment relative to the pixel cloud amount and cloud top height in each channel.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. This method develops algorithms based on complete physical quantitative analytical equations and does not rely on statistical sample distribution and representativeness.

[0024] 2. This method pre-establishes a sequence of temperature detection channels with a weight function that increases or decreases monotonically, which has nothing to do with the working state of the onboard infrared hyperspectral detector.

[0025] 3. This method uses the detection data of the satellite-borne infrared imager with 40 years of business experience and its inversion cloud parameter products. The data is mature and highly reliable.

[0026] 4. Compared with the traditional method of using a single satellite-borne atmospheric detector to detect clouds and determine cloud top height, this method uses satellite inversion products to assist in completing data quality control of high-value atmospheric detectors on the same satellite platform. The use of more satellite detection data improves the efficiency of satellite use.

[0027] 5. This method provides the sub-pixel cloud distribution of infrared hyperspectral detection pixels, laying a certain foundation for future applications such as high-resolution numerical weather forecast data assimilation analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 It is a method flow chart of a method for real-time calculation of cloud top height based on satellite infrared detection element parameters of the present invention;

[0030] Figure 2 is the weight function of the GIIRS channel;

[0031] Figure 3 It is the brightness temperature of channel 32 (upper left), channel 85 (upper right), and channel 245 (lower left) at different cloud amounts and cloud top heights;

[0032] Figure 4 It is the lookup table for channel 32 (top), channel 85 (bottom left), and channel 245 (bottom right);

[0033] Figure 5 Cloud height distribution in the AGRI field of view before fusion (a) and in the GIIRS field of view after fusion (b). DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] See also Figure 1-5 ,A real-time calculation method of cloud top height based on satellite infrared detection meta-parameters, taking the cloud top height calculation of the FY-4 satellite AGRI and GIIRS as an example, firstly collect the cloud profile dataset, the satellite hyperspectral sensor parameters and the clear sky atmospheric profile dataset, and the above datasets are used through the cloud-sky radiation transfer calculation and the clear-sky radiation transfer calculation to obtain the clear-sky and cloud-sky ambient brightness temperature difference; through equations (1)-(3);

[0036]

[0037]

[0038] diff=L clr (v)-L(v)=N(L clr (v)-L cld(v)) Formula (3)

[0039] The calculated brightness temperature difference between clear sky and cloudy sky is combined with the cloud profile data set to obtain a lookup table of sub-pixel cloud amount, cloud top height and brightness temperature difference;

[0040] Pixel area fusion is used to match AGRI's cloud detection and cloud top height inversion data to GIIRS pixels. The number of matched AGRI pixels with clouds is counted in GIIRS pixels. GIIRS cloud amount = number of AGRI pixels with clouds / total number of matched AGRI pixels. In GIIRS pixels, the number of pixels whose cloud top height of matched AGRI pixels is the same as the isobaric surface height is counted from 322 hPa to 1000 hPa on each isobaric surface. Once an AGRI pixel that meets the conditions is found, the layered cloud amount of the GIIRS pixel on the isobaric surface is increased by one, and the isobaric surfaces below this height will no longer count the AGRI pixel.

[0041] In this embodiment, according to the matching total cloud amount of the GIIRS pixel and the layered cloud amount on each isobaric surface, on the basis of a given brightness temperature difference between the clear sky and the cloudy environment, the lookup table is searched from 322 hPa to 1000 hPa for each isobaric surface until the first channel that satisfies the correspondence between the total cloud amount and the layered cloud amount is found. The weight function height of the channel is the representative cloud top height of the GIIRS pixel.

[0042] In this embodiment, the calculation results are as follows: Figure 4 As shown in the figure, the brightness temperature difference between clear sky and cloud environment of representative high-level, middle-level and low-level temperature detection channels of GIIRS varies with the total cloud amount of pixels and the cloud top height of pixels. These brightness temperature differences and the corresponding total cloud amount of pixels and cloud top height of pixels constitute the cloud top height calculation lookup table of GIIRS pixels.

[0043] After completing the entire process, the representative cloud top height of the pixel can be obtained, such as Figure 5 As shown, this is the cloud top height of the AGRI pixel matched to the GIIRS and the representative cloud top height of the GIIRS pixel calculated using the cloud top height calculation lookup table of the GIIRS pixel.

[0044] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A real-time calculation method for cloud top height based on satellite infrared detection meta-parameters, characterized in that: Please follow the steps below: S1: First, collect cloud profile data sets, satellite hyperspectral sensor parameters and clear sky atmospheric profile data sets, and use the above data sets to calculate cloud-sky radiation transfer and clear sky radiation transfer to obtain the difference in ambient brightness temperature between clear sky and cloud-sky; S2: The calculated brightness temperature difference between clear sky and cloudy sky is combined with the cloud profile data set to obtain a lookup table of sub-pixel cloud amount, cloud top height and brightness temperature difference; S3: Check the cloud top height against the lookup table layer by layer to see if it meets the conditions; S4: If satisfied, the cloud amount and cloud top height of the hyperspectral pixel are obtained; S5: If not satisfied, continue to execute step S3; In step S1, the clear sky brightness temperature of the infrared hyperspectral channel is calculated by formula (1): Among them, L clr (v) is the clear sky brightness temperature of the channel, τ s (v) is the transmittance from the surface to the top of the atmosphere, ε s (v) is the surface emissivity of the channel, B(v, T s ) is the equivalent blackbody brightness temperature of the channel on the surface, B(v, T) is the equivalent blackbody brightness temperature of the channel, and τ is the atmospheric tomography transmittance; In step S1, the cloud environment brightness temperature of the infrared hyperspectral channel is calculated by formula (2): Among them, L cld (v) is the top-of-atmosphere brightness temperature of the channel in a cloudy environment, τ cld (v) is the channel transmittance from the cloud top to the top of the atmosphere, B(v, T cld ) is the equivalent blackbody brightness temperature of the cloud surface; In step S1, the brightness temperature difference between the clear sky and the cloudy sky is calculated by equation (3): diff = L clr (v) - L(v) = N(L clr (v) - L cld (v)) Equation (3) Among them, diff is the brightness temperature difference between the channel in the clear sky environment and the cloudy sky environment, and N is the cloud cover; The N in formula (3) is cycled from 0 to 1 with a step size of 0.

1. Each time N is cycled, the cloud top height is cycled from 1000 hPa to 322 hPa, and the channel brightness temperature difference between the clear sky and the cloudy environment under different cloud top heights and cloud amounts is calculated.

2. A cloud top height real-time calculation method based on satellite infrared detection meta-parameters according to claim 1, characterized in that: In step S3, it also includes infrared imager cloud detection and parameter fusion data based on pixel area.

3. The method for real-time calculation of cloud top height based on satellite infrared detection meta-parameters according to claim 1, characterized in that: In step S2, formula (1) to formula (3) are looped to calculate the lookup table of the brightness temperature difference between the clear sky and the cloudy environment relative to the pixel cloud amount and cloud top height in each channel.

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