Chips, electronic devices, and computer devices for processing carbon and water flux data

Abstract

The present invention relates to a chip, an electronic device, and a computer device for processing carbon-water flux data. The chip includes a processor, a memory, and a computer program stored in the memory and executable by the processor. The processor includes multiple cores. When the computer program is executed by the processor, the following steps are implemented: obtaining high-frequency carbon flux data and meteorological data within a first time period; extracting meteorological data and high-frequency carbon flux data of any minute within the first time period, and obtaining a calculated water vapor density value based on the meteorological data of the minute, and obtaining multiple water vapor density measurement values ​​based on the high-frequency carbon flux data of the minute; obtaining a water vapor density correction value based on the calculated water vapor density value and the multiple water vapor density measurement values; and performing mixing ratio conversion and water vapor density (WPL) correction based on the water vapor density correction value and the high-frequency carbon flux data within the first time period to obtain the high-frequency carbon flux data within the first time period after the WPL correction.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a chip, electronic equipment, and computer device for processing carbon-water flux data. Background Art

[0002] Accurate water vapor density measurements are crucial when performing carbon flux WPL corrections. Currently, the transport of heat or water vapor during carbon flux WPL corrections can cause changes in the density of trace gases, but this change does not necessarily indicate an actual increase or decrease in mass. Density changes are typically caused by heat-induced expansion or contraction of gases, resulting in a change in the number of gas molecules within a given volume. This does not necessarily mean that new material has been introduced or existing material has been reduced, thus rendering the measured water vapor density inaccurate. When the measured water vapor density is inaccurate, using it for WPL corrections introduces new uncertainties. Summary of the Invention

[0003] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a chip, electronic device, and computer device for processing carbon and water flux data, which solves the technical problems of inaccurate measured water vapor density in WPL correction in the prior art and the introduction of new uncertainties when using inaccurate water vapor density for WPL correction.

[0004] In order to achieve the above objectives, the main technical solutions adopted by the present invention include:

[0005] In a first aspect, an embodiment of the present invention provides a chip for processing carbon and water flux data, the chip comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, the processor comprising multiple cores, wherein when the computer program is executed by the processor, the following steps are implemented:

[0006] S1. Obtain high-frequency carbon flux data and meteorological data within a first time period;

[0007] The meteorological data include temperature, air pressure and relative humidity;

[0008] The high-frequency carbon flux data includes water vapor density measurement values ​​and carbon flux values;

[0009] S2. Extracting meteorological data and high-frequency carbon flux data for any minute within the first time period, and obtaining a calculated water vapor density value corresponding to the meteorological data for the minute based on the meteorological data for the minute, and obtaining a plurality of measured water vapor density values ​​in the high-frequency carbon flux data for the minute based on the high-frequency carbon flux data for the minute;

[0010] S3. Obtaining a corrected water vapor density value based on the calculated water vapor density value and a plurality of water vapor density measurements in the high-frequency carbon flux data within the minute;

[0011] S4. Based on the water vapor density correction value and the high-frequency carbon flux data in the first time period, the mixing ratio is converted and the WPL correction is performed to obtain the high-frequency carbon flux data in the first time period after the WPL correction.

[0012] Preferably, the step S2 of obtaining the calculated value of water vapor density corresponding to the minute's meteorological data according to the minute's meteorological data specifically includes:

[0013] According to the meteorological data of the minute, use formula (1) to obtain the calculated value of water vapor density corresponding to the meteorological data of the minute;

[0014] The formula (1) is:

[0015]

[0016] rho_c is the calculated value of water vapor density;

[0017] T is the temperature value in the meteorological data of that minute;

[0018] R v is the water vapor gas constant;

[0019]

[0020] RH is the relative humidity corresponding to the meteorological data of that minute;

[0021]

[0022] P is the air pressure value in the meteorological data of that minute;

[0023]

[0024] Preferably, step S3 specifically includes:

[0025] S31, combining a plurality of water vapor density measurement values ​​in the high-frequency carbon flux data within the minute into a first data set;

[0026] S32. Based on the first data set, obtain the number, average value, and standard deviation of water vapor density measurement values ​​in the first data set;

[0027] S33. Determine whether the number of water vapor density measurement values ​​in the first data set is greater than 360, and obtain a first determination result. If the first determination result is that the number of water vapor density measurement values ​​in the first data set is less than or equal to 360, use the calculated water vapor density value corresponding to the minute-long meteorological data as the water vapor density correction value.

[0028] S34. If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is greater than 360, obtaining a first value based on the number, average, and standard deviation of the water vapor density measurement values ​​in the first data set and the calculated water vapor density value corresponding to the minute-long meteorological data;

[0029] S35. Determine whether the absolute value of the first value is greater than a first set value to obtain a second determination result. If the second determination result is that the absolute value of the first value is greater than the first set value, delete the water vapor density measurement values ​​that meet the first condition in the first data set to obtain a new first data set.

[0030] S36. Repeat steps S31-S35 until the second judgment result is that the absolute value of the first value is less than the first set value, and then use the average value of the water vapor density measurement values ​​in the current new first data set as the water vapor density correction value.

[0031] Preferably, S34 specifically includes:

[0032] If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is greater than 360, then based on the number, average value, standard deviation of the water vapor density measurement values ​​in the first data set and the calculated water vapor density value corresponding to the minute meteorological data, formula (2) is used to calculate a first value t;

[0033] The formula (2) is:

[0034]

[0035] t is the first value;

[0036] n is the number of water vapor density measurements in the first data set;

[0037] μ is the average value of the water vapor density measurements in the first data set;

[0038] s is the standard deviation of the water vapor density measurements in the first data set.

[0039] Preferably,

[0040] The first set value is 2.586.

[0041] Preferably,

[0042] The water vapor density measurement value that meets the first condition is a water vapor density measurement value that is greater than the first threshold or less than the second threshold.

[0043] Preferably,

[0044] The first threshold is μ+3s;

[0045] The second threshold is μ-3s.

[0046] Preferably,

[0047] The first time period is 30 minutes;

[0048] The water vapor gas constant R v is 4.6148×10 -4 .

[0049] On the other hand, this embodiment further provides an electronic device, which includes a power supply and the chip for processing carbon and water flux data as described above, wherein the power supply is electrically connected to the chip.

[0050] On the other hand, this embodiment further provides a computer device, which includes the chip for processing carbon and water flux data as described above.

[0051] The present invention has the beneficial effect of: a processor in a chip for processing carbon-water flux data of the present invention can utilize meteorological data and high-frequency carbon flux data for any minute within a first time period, and obtain, based on the meteorological data for that minute, a calculated water vapor density value corresponding to the meteorological data for that minute, and obtain, based on the high-frequency carbon flux data for that minute, multiple water vapor density measurements within the high-frequency carbon flux data for that minute. Then, a water vapor density correction value is obtained based on the calculated water vapor density value and the multiple water vapor density measurements within the high-frequency carbon flux data for that minute. Finally, mixing ratio conversion and WPL correction are performed based on the water vapor density correction value and the high-frequency carbon flux data for the first time period, thereby obtaining WPL-corrected high-frequency carbon flux data for the first time period. Compared to the prior art, the carbon-water flux data processing method of the present invention obtains a water vapor density correction value using measured water vapor density measurements and calculated water vapor density values, thereby improving the accuracy of the obtained water vapor density. Furthermore, WPL correction is performed using the water vapor density correction value, thereby ensuring the accuracy of the WPL correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a schematic structural diagram of a chip for processing carbon-water flux data according to the present invention;

[0053] Figure 2 This is a schematic diagram of the process that can be implemented by the chip for processing carbon and water flux data of the present invention;

[0054] Figure 3 This is a schematic diagram of the process that can be implemented by the chip for processing carbon and water flux data in the second embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation methods in conjunction with the accompanying drawings.

[0056] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. Instead, these embodiments are provided to enable a clearer and more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0057] Example 1

[0058] See also Figure 1 This embodiment provides a chip for processing carbon and water flux data, characterized in that the chip includes a processor, a memory, and a computer program stored in the memory and executable by the processor, the processor includes multiple cores, and when the computer program is executed by the processor, see Figure 2 , implement the following steps:

[0059] S1. Acquire high-frequency carbon flux data and meteorological data within a first time period.

[0060] The meteorological data includes air temperature, air pressure and relative humidity; the high-frequency carbon flux data includes water vapor density measurement value and carbon flux value; the first time period is 30 minutes.

[0061] S2. Extract meteorological data and high-frequency carbon flux data for any minute in the first time period, and obtain a calculated water vapor density value corresponding to the meteorological data for the minute based on the meteorological data for the minute, and obtain multiple water vapor density measurement values ​​in the high-frequency carbon flux data within the minute based on the high-frequency carbon flux data for the minute.

[0062] In a specific application of this embodiment, the step S2 of obtaining the calculated water vapor density corresponding to the meteorological data of the minute according to the meteorological data of the minute specifically includes:

[0063] According to the meteorological data of the minute, the water vapor density calculation value corresponding to the meteorological data of the minute is obtained using formula (1).

[0064] The formula (1) is:

[0065]

[0066] rho_c is the calculated value of water vapor density; T is the temperature value in the meteorological data of that minute; R v is the water vapor gas constant; specifically, the water vapor gas constant Rv is 4.6148×10 -4 .

[0067]

[0068] RH is the relative humidity corresponding to the meteorological data of that minute.

[0069]

[0070] P is the air pressure value in the meteorological data of that minute;

[0071]

[0072] S3. Obtain a water vapor density correction value based on the calculated water vapor density value and a plurality of water vapor density measurement values ​​in the high-frequency carbon flux data within the minute.

[0073] Specifically, the S3 specifically includes:

[0074] S31. Combining a plurality of water vapor density measurement values ​​in the high-frequency carbon flux data within the minute into a first data set.

[0075] S32. Based on the first data set, obtain the number, average value, and standard deviation of water vapor density measurement values ​​in the first data set.

[0076] S33. Determine whether the number of water vapor density measurement values ​​in the first data set is greater than 360, and obtain a first judgment result. If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is less than or equal to 360, then use the calculated water vapor density value corresponding to the minute meteorological data as the water vapor density correction value.

[0077] S34. If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is greater than 360, then a first value is obtained based on the number, average value, standard deviation of the water vapor density measurement values ​​in the first data set and the calculated water vapor density value corresponding to the minute meteorological data.

[0078] S34 specifically includes:

[0079] If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is greater than 360, then based on the number, average value, standard deviation of the water vapor density measurement values ​​in the first data set and the calculated water vapor density value corresponding to the minute meteorological data, the first value t is calculated using formula (2).

[0080] The formula (2) is:

[0081]

[0082] t is a first value; n is the number of water vapor density measurements in the first data set; μ is the average value of the water vapor density measurements in the first data set; and s is the standard deviation of the water vapor density measurements in the first data set.

[0083] S35. Determine whether the absolute value of the first value is greater than a first set value to obtain a second judgment result. If the second judgment result is that the absolute value of the first value is greater than the first set value, delete the water vapor density measurement values ​​that meet the first condition in the first data set to obtain a new first data set.

[0084] The water vapor density measurement value that meets the first condition is a water vapor density measurement value that is greater than a first threshold or less than a second threshold; the first threshold is μ+3s; and the second threshold is μ-3s.

[0085] S36. Repeat steps S31-S35 until the second determination result indicates that the absolute value of the first value is less than the first set value, and then use the average of the water vapor density measurements in the current new first data set as the water vapor density correction value. In the actual application of this embodiment, the first set value is 2.586.

[0086] S4. Based on the water vapor density correction value and the high-frequency carbon flux data in the first time period, the mixing ratio is converted and the WPL correction is performed to obtain the high-frequency carbon flux data in the first time period after the WPL correction.

[0087] On the other hand, this embodiment further provides an electronic device, which includes a power supply and the chip as described above, wherein the power supply is electrically connected to the chip.

[0088] In this embodiment, a processor in a chip for processing carbon-water flux data can utilize meteorological data and high-frequency carbon flux data from any minute within a first time period, and, based on the meteorological data for that minute, obtain a calculated water vapor density value corresponding to the meteorological data for that minute, and, based on the high-frequency carbon flux data for that minute, obtain multiple water vapor density measurements within the high-frequency carbon flux data for that minute. Then, a corrected water vapor density value is obtained based on the calculated water vapor density value and the multiple water vapor density measurements within the high-frequency carbon flux data for that minute. Finally, a mixing ratio conversion and WPL correction are performed based on the corrected water vapor density value and the high-frequency carbon flux data for the first time period, thereby obtaining WPL-corrected high-frequency carbon flux data for the first time period. Compared to the prior art, the carbon-water flux data processing method of the present invention obtains a corrected water vapor density value using measured water vapor density values ​​and calculated water vapor density values, thereby improving the accuracy of the obtained water vapor density. Furthermore, WPL correction is performed using the corrected water vapor density value, thereby ensuring the accuracy of the WPL correction.

[0089] Example 2

[0090] This embodiment provides a chip for processing carbon and water flux data, characterized in that the chip includes a processor, a memory, and a computer program stored in the memory and executable by the processor, the processor includes multiple cores, and when the computer program is executed by the processor, see Figure 3 , implement the following steps:

[0091] 101. Obtain high-frequency carbon flux data and meteorological data within a first time period.

[0092] The meteorological data includes temperature, air pressure and relative humidity; the first time period is 30 minutes.

[0093] The high-frequency carbon flux data in this embodiment specifically includes three-dimensional wind speed data, high-frequency ultrasonic temperature data, carbon dioxide density data, and water vapor density data.

[0094] The high-frequency carbon flux data in this embodiment is measured by a closed-circuit eddy covariance system, which includes an infrared CO2 / H2O analyzer, a three-dimensional ultrasonic wind sensor, an air pressure sensor, an air temperature and humidity sensor, a data collector, and peripheral equipment (such as equipment support rods, observation towers, observation brackets, and lightning rods, which do not affect the measurement). The signals of the closed-circuit eddy covariance system are collected at a frequency of 10 Hz and stored in a chip. The chip calculates the carbon dioxide flux (Fc), latent heat flux (LE), and sensible heat flux (H) every 30 minutes.

[0095] 102. Extract meteorological data and high-frequency carbon flux data for any minute within the first time period, and obtain a calculated water vapor density value corresponding to the meteorological data for the minute based on the meteorological data for the minute, and obtain multiple water vapor density measurement values ​​in the high-frequency carbon flux data within the minute based on the high-frequency carbon flux data for the minute.

[0096] In a specific application of this embodiment, the step 102 of obtaining the calculated water vapor density corresponding to the meteorological data of the minute according to the meteorological data of the minute specifically includes:

[0097] According to the meteorological data of the minute, use formula (1) to obtain the calculated value of water vapor density corresponding to the meteorological data of the minute;

[0098] The formula (1) is:

[0099]

[0100] rho_c is the calculated value of water vapor density; T is the temperature value in the meteorological data of that minute; R v is the water vapor gas constant; specifically, the water vapor gas constant Rv is 4.6148×10 -4 .

[0101] RH is the relative humidity corresponding to the meteorological data of that minute.

[0102]

[0103] P is the air pressure value in the meteorological data of that minute.

[0104]

[0105] 103. Group a plurality of water vapor density measurement values ​​in the high-frequency carbon flux data within the minute into a first data set.

[0106] 104. Based on the first data set, obtain the number, average value, and standard deviation of water vapor density measurement values ​​in the first data set.

[0107] 105. Determine whether the number of water vapor density measurement values ​​in the first data set is greater than 360, and obtain a first judgment result. If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is less than or equal to 360, then use the calculated water vapor density value corresponding to the minute meteorological data as the water vapor density correction value.

[0108] 106. If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is greater than 360, then based on the number, average value, standard deviation of the water vapor density measurement values ​​in the first data set and the calculated water vapor density value corresponding to the minute meteorological data, the first value t is calculated using formula (2).

[0109] The formula (2) is:

[0110]

[0111] t is a first value; n is the number of water vapor density measurements in the first data set; μ is the average value of the water vapor density measurements in the first data set; and s is the standard deviation of the water vapor density measurements in the first data set.

[0112] 107. Determine whether the absolute value of the first numerical value is greater than a first set value to obtain a second judgment result. If the second judgment result is that the absolute value of the first numerical value is greater than the first set value, delete the water vapor density measurement values ​​that meet the first condition in the first data set to obtain a new first data set; wherein, the water vapor density measurement values ​​that meet the first condition are water vapor density measurement values ​​that are greater than a first threshold or less than a second threshold; the first threshold is μ+3s; and the second threshold is μ-3s.

[0113] 108. Repeat steps 103-107 until the second determination result indicates that the absolute value of the first value is less than the first set value, and then use the average value of the water vapor density measurements in the current new first data set as the water vapor density correction value. In the actual application of this embodiment, the first set value is 2.586.

[0114] 109. Based on the water vapor density correction value and the high-frequency carbon flux data in the first time period, perform mixing ratio conversion and WPL correction to obtain the high-frequency carbon flux data in the first time period after WPL correction.

[0115] Specifically, step 109 includes:

[0116] 109-1. Perform a series of processing on the high-frequency carbon flux data in the first time period to obtain high-frequency carbon flux data after the series of processing.

[0117] In this embodiment, a series of processing is performed on the high-frequency carbon flux data in the first time period, specifically including: data quality inspection processing, outlier removal processing, time lag elimination processing, coordinate rotation processing, ultrasonic temperature correction processing, and frequency correction processing.

[0118] The data quality check process includes: checking the sensor abnormality flags of the three-dimensional ultrasonic wind sensor and the infrared CO2 / H2O analyzer, and marking and quality checking the high-frequency carbon flux data within the first time period.

[0119] The outlier removal process is to remove large instantaneous noises in the high-frequency carbon flux data within the first time period, that is, points that may have a significant impact on the variance and covariance values.

[0120] The time lag elimination process is to use the maximum covariance method to calculate and remove the time lag of the infrared CO2 / H2O analyzer signal relative to the three-dimensional ultrasonic wind sensor (vertical wind speed) in the high-frequency carbon flux data in the first time period.

[0121] Coordinate rotation transforms the wind vector from the 3D ultrasonic wind sensor coordinate system to the natural coordinate system. This transformed coordinate system incorporates multiple wind directions over a longer period, resulting in better statistical significance and reducing the potential for excessive rotation and information loss caused by successive rotations.

[0122] The ultrasonic temperature correction process is to correct the influence of air humidity on the ultrasonic virtual temperature Ts related to air humidity in the high-frequency carbon flux data in the first time period.

[0123] The frequency correction processing is to correct the frequency loss when the closed-circuit eddy covariance system observes the carbon dioxide and water vapor fluxes, including low-pass filtering correction for low-frequency loss (the contribution of larger eddies is insufficiently estimated, mainly caused by time period averaging, that is, the averaging time is not long enough and there is linear detrending in the processing) and high-pass filtering correction for high-frequency loss (the contribution of smaller eddies is insufficiently estimated, mainly caused by path averaging caused by the sound path or optical path of the sensors in the closed-circuit eddy covariance system and the large spacing between different sensors during installation).

[0124] It should be noted that the serial processing of the high-frequency carbon flux data in the first time period in this embodiment is a prior art and will not be described in detail in this second embodiment.

[0125] 109-2. Based on the water vapor density correction value and the high-frequency carbon flux data after a series of processing, the mixing ratio is converted and the WPL correction is performed to obtain the high-frequency carbon flux data in the first time period after the WPL correction.

[0126] The carbon-water flux data processing method in this embodiment further includes:

[0127] 110. Perform footprint estimation processing on the high-frequency carbon flux data in the first time period after WPL correction to obtain final high-frequency carbon flux data.

[0128] In this embodiment, when the underlying surface of the closed-circuit eddy covariance system is patchy with vegetation, footprint estimation is often required to understand the contribution of different locations of the underlying surface, especially the underlying surface or vegetation of interest, to the turbulent flux measured by the sensor, and then make a quality judgment on the observation data.

[0129] In this embodiment, a processor in a chip for processing carbon-water flux data can utilize meteorological data and high-frequency carbon flux data from any minute within a first time period, and, based on the meteorological data for that minute, obtain a calculated water vapor density value corresponding to the meteorological data for that minute, and, based on the high-frequency carbon flux data for that minute, obtain multiple water vapor density measurements within the high-frequency carbon flux data for that minute. Then, a corrected water vapor density value is obtained based on the calculated water vapor density value and the multiple water vapor density measurements within the high-frequency carbon flux data for that minute. Finally, a mixing ratio conversion and WPL correction are performed based on the corrected water vapor density value and the high-frequency carbon flux data for the first time period, thereby obtaining WPL-corrected high-frequency carbon flux data for the first time period. Compared to the prior art, the carbon-water flux data processing method of the present invention obtains a corrected water vapor density value using measured water vapor density values ​​and calculated water vapor density values, thereby improving the accuracy of the obtained water vapor density. Furthermore, WPL correction is performed using the corrected water vapor density value, thereby ensuring the accuracy of the WPL correction.

[0130] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0131] In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connect," "fixed," etc. should be understood broadly. For example, they may refer to fixed connection, detachable connection, or integration; mechanical connection or electrical connection; direct connection or indirect connection through an intermediate medium; and internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0132] In the present invention, unless otherwise expressly specified or limited, when a first feature is "above" or "below" a second feature, it may mean that the first and second features are in direct contact, or that the first and second features are in indirect contact through an intermediate medium. Furthermore, when a first feature is "above," "above," or "above" a second feature, it may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is at a higher level than the second feature. When a first feature is "below," "below," or "below" a second feature, it may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is at a lower level than the second feature.

[0133] In the description of this specification, the terms "one embodiment", "some embodiments", "embodiments", "examples", "specific examples" or "some examples" refer to the specific features, structures, materials or characteristics described in conjunction with the embodiment or example and included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and features of different embodiments or examples, unless they are mutually inconsistent.

[0134] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may alter, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A chip for processing carbon-water flux data, characterized in that: The chip includes a processor, a memory, and a computer program stored in the memory and executable by the processor. The processor includes multiple cores. When the computer program is executed by the processor, the following steps are implemented: S1. Obtain high-frequency carbon flux data and meteorological data within a first time period; The meteorological data include temperature, air pressure and relative humidity; The high-frequency carbon flux data includes water vapor density measurement values ​​and carbon flux values; S2. Extracting meteorological data and high-frequency carbon flux data for any minute within the first time period, and obtaining a calculated water vapor density value corresponding to the meteorological data for the minute based on the meteorological data for the minute, and obtaining a plurality of measured water vapor density values ​​in the high-frequency carbon flux data for the minute based on the high-frequency carbon flux data for the minute; S3. Obtaining a corrected water vapor density value based on the calculated water vapor density value and a plurality of water vapor density measurements in the high-frequency carbon flux data within the minute; S4. Based on the water vapor density correction value and the high-frequency carbon flux data in the first time period, performing mixing ratio conversion and WPL correction, thereby obtaining the high-frequency carbon flux data in the first time period after WPL correction; Step S3 specifically includes: S31, combining a plurality of water vapor density measurement values ​​in the high-frequency carbon flux data within the minute into a first data set; S32. Based on the first data set, obtain the number, average value, and standard deviation of water vapor density measurement values ​​in the first data set; S33. Determine whether the number of water vapor density measurement values ​​in the first data set is greater than 360, and obtain a first determination result. If the first determination result is that the number of water vapor density measurement values ​​in the first data set is less than or equal to 360, use the calculated water vapor density value corresponding to the minute-long meteorological data as the water vapor density correction value. S34. If the first determination result is that the number of water vapor density measurement values ​​in the first data set is greater than 360, obtaining a first value based on the number, average, and standard deviation of the water vapor density measurement values ​​in the first data set for that minute, and the calculated water vapor density value corresponding to the meteorological data for that minute; S35. Determine whether the absolute value of the first value is greater than a first set value to obtain a second determination result. If the second determination result is that the absolute value of the first value is greater than the first set value, delete the water vapor density measurement values ​​that meet the first condition in the first data set to obtain a new first data set. S36, repeating steps S31-S35 until the second judgment result is that the absolute value of the first value is less than the first set value, and then using the average value of the water vapor density measurement values ​​in the current new first data set as the water vapor density correction value; S34 specifically includes: If the first judgment result is that the number of water vapor density measurement values ​​in the first data set is greater than 360, then based on the number, average value, standard deviation of the water vapor density measurement values ​​in the first data set and the calculated water vapor density value corresponding to the minute meteorological data, formula (2) is used to calculate a first value t; The formula (2) is: rho_c is the calculated value of water vapor density; t is the first value; n is the number of water vapor density measurements in the first data set; μ is the average value of the water vapor density measurements in the first data set; s is the standard deviation of the water vapor density measurements in the first data set; The water vapor density measurement value that meets the first condition is a water vapor density measurement value that is greater than the first threshold or less than the second threshold.

2. The chip for processing carbon-water flux data according to claim 1, characterized in that: The step S2 of obtaining the calculated water vapor density value corresponding to the meteorological data of the minute according to the meteorological data of the minute specifically includes: According to the meteorological data of the minute, use formula (1) to obtain the calculated value of water vapor density corresponding to the meteorological data of the minute; The formula (1) is: T is the temperature value in the meteorological data of that minute; R v is the water vapor gas constant; RH is the relative humidity corresponding to the meteorological data of that minute; P is the air pressure value in the meteorological data of that minute; 3. The chip for processing carbon-water flux data according to claim 2, characterized in that: The first set value is 2.

586.

4. The chip for processing carbon-water flux data according to claim 3, characterized in that: The first threshold is μ+3s; The second threshold is μ-3s.

5. The chip for processing carbon-water flux data according to claim 4, characterized in that: The first time period is 30 minutes; The water vapor gas constant R v is 4.6148×10 -4 .

6. An electronic device, characterized in that: The electronic device comprises a power supply and a chip for processing carbon and water flux data according to any one of claims 1 to 5, wherein the power supply is electrically connected to the chip.

7. A computer device, characterized in that: The computer device comprises the chip for processing carbon and water flux data according to any one of claims 1 to 5.

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