CN112345151B - Sensitivity test method of MWTS-II to sea surface air pressure based on natural atmosphere - Google Patents
Sensitivity test method of MWTS-II to sea surface air pressure based on natural atmosphere Download PDFInfo
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Abstract
A sensitivity test method of MWTS-II to sea surface air pressure based on natural atmosphere belongs to the technical field of microwave remote sensing. Establishing a matched data set of MWTS-II observation bright temperature and natural atmosphere data sets, and establishing a clear air matched data set; calculating an MWTS-II channel weight function based on a clear sky matching data set, and respectively establishing a clear sky adjusting data set for each channel of the MWTS-II according to the distribution rule of atmosphere layers where the peak value of each MWTS-II channel weight function is located; respectively establishing a test data set for testing sea surface air pressure sensitivity for each channel of the MWTS-II based on a clear sky adjustment data set according to an atmosphere layer where a peak value of a weight function of each channel of the MWTS-II is located; and aiming at each channel of the MWTS-II, establishing the change relation of the observed brightness temperature of each channel of the MWTS-II along with the sea surface air pressure respectively, and completing the sensitivity test of the MWTS-II on the sea surface air pressure. The method can reflect the change relation of the observed brightness temperature of each MWTS-II channel along with the sea surface air pressure more truly, can test the sensitivity of the sea surface air pressure more accurately, and is simple and easy to operate.
Description
Technical Field
The invention relates to the technical field of microwave remote sensing, in particular to a sensitivity test method of MWTS-II to sea surface air pressure based on natural atmosphere.
Background
Sea surface air pressure plays an important role in applications such as numerical weather forecasting, current weather analysis, climate change research and the like. The acquisition of high-precision sea surface air pressure value is one of the research hotspots in the field of earth science. The satellite-borne microwave radiometer is an important detecting instrument for carrying out global dense detection on sea surface air pressure, and can detect the sea surface air pressure by measuring the total absorption of a vertical column of oxygen. In the microwave band, the oxygen absorption spectral line forms a resonance absorption band with 60GHz as the center, and the microwave radiometer arranged in the 60GHz frequency band can measure the total absorption of the vertical column of oxygen, so that the sea surface air pressure can be detected.
Based on the brightness and temperature observed by the satellite-borne microwave radiometer, sea surface air pressure data can be obtained through inversion calculation. However, the sensitivity of the microwave radiometer channel to the sea surface barometric pressure is a prerequisite for the success of the inversion calculation. Therefore, sensitivity testing of the microwave radiometer channel is particularly important. At present, the sensitivity test method of the microwave radiometer channel to the atmospheric parameters is to input the manually disturbed atmospheric data into the radiation transmission model, establish the corresponding relation between the simulated brightness temperature output by the radiation transmission model and the atmospheric parameters, and then complete the sensitivity test of the microwave radiometer channel to the atmospheric parameters. And (3) fixing other atmospheric parameters such as temperature, humidity and the like, randomly disturbing the sea surface air pressure, and then inputting the disturbed sea surface air pressure into a radiation transmission model to obtain the relation of the simulated brightness temperature of the microwave radiometer along with the change of the sea surface air pressure. However, the actual observed brightness temperature of the microwave radiometer is the result of the combined action of the atmospheric parameters such as temperature, humidity and sea surface air pressure, and the sensitivity test method for manually disturbing atmospheric data not only neglects the correlation among the temperature, the humidity and the air pressure, but also introduces the calculation error of the radiation transmission model, so that the sensitivity test result of the microwave radiometer channel to the sea surface air pressure is inaccurate and even inconsistent with the actual result.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for testing the sensitivity of MWTS-II to sea surface air pressure based on natural atmosphere, which can reflect the change relation of the observed brightness temperature of each channel of MWTS-II (microwave thermometer II type) along with the sea surface air pressure more truly, can test the sensitivity of the sea surface air pressure more accurately, and is simple and easy to operate.
In order to realize the technical purpose, the adopted technical scheme is as follows: a sensitivity test method of MWTS-II based on natural atmosphere to sea surface air pressure comprises the following steps:
the method comprises the following steps: establishing a matching data set of an MWTS-II observation bright temperature and natural atmosphere data set, and establishing a clear air matching data set by using the matching data set;
step two: the method comprises the steps of utilizing a clear sky matching data set as input of a radiation transmission model RTTOV, utilizing a channel weight function as output of the radiation transmission model RTTOV, calculating an MWTS-II channel weight function, and respectively establishing a clear sky adjusting data set for each channel of the MWTS-II according to the distribution rule of atmosphere layering where the peak value of each MWTS-II channel weight function is located;
step three: performing data selection on the clear sky adjustment data sets of the channels of the MWTS-II, selecting data meeting selection standards, and respectively establishing test data sets for testing sea surface air pressure sensitivity for the channels of the MWTS-II;
step four: and aiming at the test data set of each channel of the MWTS-II, establishing the change relation of the observed brightness temperature in the test data set of each channel of the MWTS-II along with the sea surface air pressure respectively, and completing the sensitivity test of the MWTS-II to the sea surface air pressure.
The first step of the invention specifically comprises the following steps:
firstly, selecting data from a climatology data set according to a natural atmosphere data selection standard to form a natural atmosphere data set; then, carrying out time and space matching on the natural atmosphere data set and the MWTS-II observed bright temperature, and establishing a matched data set of the MWTS-II observed bright temperature and the natural atmosphere data set; and finally, selecting clear air data, wherein if the cloud amount profile and the cloud water profile in the matched data are both 0, the group of data is clear air matched data, and all clear air matched data are selected to establish a clear air matched data set.
The matching conditions of the natural atmosphere data set and the MWTS-II for observing the bright temperature in time and space are that the time error is less than 0.5 h, and the mean difference between the longitude error and the latitude error is less than 0.1 degrees.
The second step of the invention specifically comprises:
firstly, taking each group of natural atmosphere data in a clear air matching data set as the input of a radiation transmission model RTTOV, taking a channel weight function as the output of the radiation transmission model RTTOV, calculating the channel weight function of each channel of MWTS-II, and aiming at each channel of the MWTS-II, corresponding to one group of channel weight functions changing along with atmosphere layering; then, for each channel of the MWTS-II, respectively counting the pressure layers distributed by the peak values of the channel weight functions corresponding to the channel, and taking the pressure layer distributed most as the pressure layer where the peak value of the channel weight function of the channel is locatedP nWherein n =1,2,3 …,13, n denotes an MWTS-II channel number; finally, the peak values are abandoned in the clear sky matching data set and are not distributed inP nThe group of clear sky matching data corresponding to the channel weight function forms 13 corresponding clear sky adjustment data sets.
The data set comprises a temperature profile, a humidity profile, a cloud volume profile, a cloud water profile, a 2 m temperature, a 2 m humidity, a skin temperature, a 10 m u wind speed, a 10 m v wind speed and sea surface air pressure as a set of natural atmosphere data.
The third step of the invention specifically comprises:
firstly, respectively solving a group of average atmospheric data corresponding to each channel of the MWTS-II aiming at a clear air adjustment data set corresponding to each channel of the MWTS-II formed in the step two; and then, selecting data in the clear sky adjustment data set formed in the step two, wherein the data selection criteria are two: (1) each group of natural atmosphere data in the clear sky adjustment data set is different from the average atmosphere data, and meanwhile, the absolute value of each difference of the temperature profile is less than 1K, the absolute value of each difference of the humidity profile is less than 1000 ppmv, the absolute value of each difference of the 2 m temperature is less than 1K, the absolute value of each difference of the 2 m humidity is less than 1000 ppmv, the absolute value of each difference of the 10 m u wind speed is less than 1 m/s, and the absolute value of each difference of the 10 m v wind speed is less than 10 m/sLess than 1 m/s; (2) pressure stratification distributed by the peaks of the channel weight function determined in step twoP nThe absolute value of the difference in temperature is less than 0.3K; and finally, selecting data simultaneously meeting the two data selection standards, establishing a test data set for testing sea surface air pressure sensitivity, and obtaining a corresponding test data set for each channel of the MWTS-II.
The average atmospheric data includes average temperature profile, average humidity profile, average 2 m temperature, average 2 m humidity, average skin temperature, average 10 m u wind speed, average 10 m v wind speed.
The fourth step of the invention specifically comprises:
and in the test data set corresponding to each channel of the MWTS-II established in the third step, performing unary linear regression analysis by taking the observed bright temperature in the test data set of each channel of the MWTS-II as a dependent variable and the corresponding sea surface pressure as an independent variable, and respectively establishing the change relation of the observed bright temperature in the test data set of each channel of the MWTS-II along with the sea surface air pressure aiming at each channel of the MWTS-II to complete the sensitivity test of the MWTS-II on the sea surface air pressure.
The invention has the beneficial effects that: the sensitivity of each channel of MWTS-II to sea surface air pressure is measured by observing the brightness temperature by using natural atmosphere and MWTS-II, and the change relation of the brightness temperature observed by the test data set of each channel of MWTS-II along with the sea surface air pressure can be directly reflected. The test result of the sensitivity of the MWTS-II to sea surface air pressure can better accord with the actual atmosphere scene by using natural atmosphere. Meanwhile, the method avoids adverse effects caused by calculation errors of the radiation transmission model. Therefore, the method can more truly reflect the change relation of the observed brightness temperature of each channel of the MWTS-II along with the sea surface air pressure, can more accurately test the sensitivity of the sea surface air pressure, and is simple and easy to operate.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a graph showing the relationship between the observed brightness temperature of the test data set of each MWTS-II channel and the sea surface pressure in example 1.
FIG. 3 is a graph comparing the results of the test in example 1 using natural atmosphere and using artificially perturbed atmosphere data to test the sensitivity of MWTS-II to sea surface air pressure.
Detailed Description
The present invention is further described with reference to the following examples and the accompanying drawings, which are not intended to limit the scope of the invention as claimed.
All 13 channels of the MWTS-II (microwave thermometer II type) carried on Fengyun three-number C star and D star are arranged in a 60GHz resonance absorption band, so that the accurate measurement of the total absorption of the oxygen vertical column can be realized, and the MWTS-II has great potential for inverting the sea surface air pressure. In order to avoid the defect that the traditional sensitivity test method for manually disturbing atmospheric data ignores the correlation among atmospheric parameters such as temperature, humidity and air pressure and avoid the adverse effect of the calculation error of a radiation transmission model on the sensitivity test of a microwave radiometer channel on sea surface air pressure, the sensitivity of the sea surface air pressure is tested by using natural atmosphere and MWTS-II to observe the brightness temperature.
A sensitivity test method of MWTS-II based on natural atmosphere to sea surface air pressure comprises the following steps:
the method comprises the following steps: establishing a matching data set of an MWTS-II observation bright temperature and natural atmosphere data set, and establishing a clear air matching data set by using the matching data set;
step two: the method comprises the steps of utilizing a clear sky matching data set as input of a radiation transmission model RTTOV, utilizing a channel weight function as output of the radiation transmission model RTTOV, calculating an MWTS-II channel weight function, and respectively establishing a clear sky adjusting data set for each channel of the MWTS-II according to the distribution rule of atmosphere layering where the peak value of each MWTS-II channel weight function is located;
step three: performing data selection on the clear sky adjustment data sets of the channels of the MWTS-II, selecting data meeting selection standards, and respectively establishing test data sets for testing sea surface air pressure sensitivity for the channels of the MWTS-II;
step four: and aiming at the test data set of each channel of the MWTS-II, establishing the change relation of the observed brightness temperature in the test data set of each channel of the MWTS-II along with the sea surface air pressure respectively, and completing the sensitivity test of the MWTS-II to the sea surface air pressure.
The first step of the invention specifically comprises the following steps:
firstly, a set of natural atmosphere data is taken as a standard, wherein the standard comprises a temperature profile, a humidity profile, a cloud volume profile, a cloud water profile, a 2 m temperature, a 2 m humidity, a skin temperature, a 10 m u wind speed, a 10 m v wind speed and sea surface air pressure. Selecting data from the climatology data set according to a natural atmosphere data selection standard to form a natural atmosphere data set; and then, carrying out time and space matching on the natural atmosphere data set and the MWTS-II observed bright temperature, and establishing a matched data set of the MWTS-II observed bright temperature and the natural atmosphere data set, wherein the time and space matching conditions of the natural atmosphere data set and the MWTS-II observed bright temperature are that the time error is less than 0.5 h, and the mean difference between the longitude error and the latitude error is less than 0.1 degree. And finally, selecting clear air data in the matching data set by taking the cloud amount profile and the cloud water profile as the standard, if the cloud amount profile and the cloud water profile in the matching data are both 0, selecting all clear air matching data to establish a clear air matching data set, and establishing a clear air matching data set of the MWTS-II observation bright temperature and natural atmosphere data set.
The second step of the invention specifically comprises:
firstly, taking a temperature profile, a humidity profile, a 2 m temperature, a 2 m humidity, a skin temperature, a 10 m u wind speed, a 10 m v wind speed and sea surface air pressure in each group of natural atmosphere data in a clear and air matching data set as the input of a radiation transmission model RTTOV, taking a channel weight function as the output of the radiation transmission model RTTOV, calculating a channel weight function of each channel of MWTS-II, and aiming at each channel of MWTS-II, corresponding to a group of channel weight functions which change along with atmosphere layering; then, for each channel of the MWTS-II, respectively counting the pressure layers distributed by the peak values of the channel weight functions corresponding to the channel, and taking the pressure layer distributed most as the pressure layer where the peak value of the channel weight function of the channel is locatedP nWherein n =1,2,3 …,13, n denotes an MWTS-II channel number; finally, the peak values are abandoned in the clear sky matching data set and are not distributed inP nThe set of clear-sky matching data corresponding to the channel weight function ofAnd forming 13 corresponding clear sky adjustment data sets.
The third step of the invention specifically comprises:
firstly, aiming at the clear sky adjustment data set corresponding to each channel of the MWTS-II formed in the second step, respectively calculating a group of average atmospheric data corresponding to each channel of the MWTS-II, wherein the average atmospheric data comprises an average temperature profile, an average humidity profile, an average temperature of 2 m, an average humidity of 2 m, an average skin temperature, an average wind speed of 10 m u and an average wind speed of 10 m v. And then, selecting data in the clear sky adjustment data set formed in the step two, wherein the data selection criteria are two: (1) making difference between each group of natural atmosphere data in the clear air adjustment data set and average atmosphere data, and simultaneously meeting the requirements that the absolute value of each difference of a temperature profile is less than 1K, the absolute value of each difference of a humidity profile is less than 1000 ppmv, the absolute value of the difference of 2 m temperature is less than 1K, the absolute value of the difference of 2 m humidity is less than 1000 ppmv, the absolute value of the difference of 10 m u wind speed is less than 1 m/s, and the absolute value of the difference of 10 m v wind speed is less than 1 m/s; (2) pressure stratification distributed by the peaks of the channel weight function determined in step twoP nThe absolute value of the difference in temperature is less than 0.3K; and finally, selecting data simultaneously meeting the two data selection standards, establishing a test data set for testing sea surface air pressure sensitivity, and obtaining a corresponding test data set for each channel of the MWTS-II.
The fourth step of the invention specifically comprises:
and in the test data set corresponding to each channel of the MWTS-II established in the third step, performing unary linear regression analysis by taking the observed bright temperature in the test data set of each channel of the MWTS-II as a dependent variable and the corresponding sea surface pressure as an independent variable, and respectively establishing the change relation of the observed bright temperature in the test data set of each channel of the MWTS-II along with the sea surface air pressure aiming at each channel of the MWTS-II to complete the sensitivity test of the MWTS-II on the sea surface air pressure.
Example 1
The selected climatological data set is an Interim reanalysis data set of a European middle-term weather forecast center (ECMWF), the time range is from 2018 to 2019 and 8 months, the geographic range is (25 degrees N-45 degrees N, 160 degrees E-220 degrees E), the data resolution is 0.5 degrees multiplied by 0.5 degrees, and the pressure layer corresponding to the profile data is a 37-layer grid layer from the ground (1000 hPa) to the high altitude (1 hPa): 1000 hPa, 975 hPa, 950 hPa, 925 hPa, 900 hPa, 875 hPa, 850 hPa, 825 hPa, 800 hPa, 775 hPa, 750 hPa, 700 hPa, 650 hPa, 600 hPa, 550 hPa, 500 hPa, 450 hPa, 400 hPa, 350 hPa, 300 hPa, 250 hPa, 225 hPa, 200 hPa, 175 hPa, 150 hPa, 125 hPa, 100 hPa, 70 hPa, 50 hPa, 30 hPa, 20 hPa, 10 hPa, 7 hPa, 5 hPa, 3 hPa, 2 hPa and 1 hPa. And selecting the temperature profile, the humidity profile, the cloud volume profile, the cloud water profile, the 2 m temperature, the 2 m humidity, the skin temperature, the 10 m u wind speed, the 10 m v wind speed and the sea surface air pressure in the ECMWF Interim reanalysis data set as a group of natural atmosphere data, and forming a natural atmosphere data set. Selecting MWTS-II carried on Fengyun three-number D star to observe brightness temperature, wherein the time range is from 2018 9 to 2019 8, the geographic range is (25-45-degree N, 160-degree E-220-degree E), carrying out time and space matching on the natural atmosphere data set and the MWTS-II observed brightness temperature, wherein the time error is less than 0.5 h, the mean difference between the longitude error and the latitude error is less than 0.1, establishing a matched data set of the MWTS-II observed brightness temperature and the natural atmosphere data set, and totaling 1210152 groups of data. And (3) selecting clear sky data in the matching data set by taking the cloud amount profile and the cloud water profile as the standard, namely if the cloud amount profile and the cloud water profile in the matching data are both 0, the group of data is clear sky matching data, and establishing a clear sky matching data set of the MWTS-II observation bright temperature and natural atmosphere data set, wherein 65016 groups of data are in total.
Taking the temperature profile, the humidity profile, the 2 m temperature, the 2 m humidity, the skin temperature, the 10 m u wind speed, the 10 m v wind speed and the sea surface air pressure in each group of natural atmospheric data in the clear and air matching data set as the input of a radiation transmission model RTTOV, taking a channel weight function as the output of the radiation transmission model RTTOV, and calculating the channel weight function of each channel of MWTS-II, so that for each channel of MWTS-II, one group of atmospheric data corresponds to one group of channel weight functions which change along with atmospheric layering, and each channel of MWTS-II can obtain 65016 channel weight functions; for MWTS-IIEach channel respectively counts the pressure layers distributed by the peak values of the channel weight functions corresponding to the channels, and the pressure layer distributed most is taken as the pressure layer where the peak value of the channel weight function of the channel is locatedP nWhere n =1,2,3 …,13 denotes an MWTS-II channel number. Pressure layer where peak value of channel weight function of each MWTS-II channel is locatedP nAs shown in table 1.
TABLE 1 Peak distribution of MWTS-II channel weight function
For each channel of MWTS-II, the peak for the channel weight function is not distributed atP nThe set of clear-sky matching data corresponding to the channel weight function is discarded from the clear-sky matching data set by the channel weight function, so that a clear-sky adjustment data set for each channel of the MWTS-II can be formed, and 13 channels of the MWTS-II are counted to form 13 corresponding clear-sky adjustment data sets. The data volume of the clear sky adjustment data set of each channel of MWTS-II is shown in table 2.
TABLE 2 data volume of MWTS-II clear sky adjustment data set
Respectively calculating average atmospheric data of the clear sky adjustment data set corresponding to each channel of the MWTS-II, wherein the average atmospheric data comprises an average temperature profile, an average humidity profile, an average temperature of 2 m, an average humidity of 2 m, an average skin temperature, an average wind speed of 10 m u and an average wind speed of 10 m v, and each channel of the MWTS-II corresponds to a group of average atmospheric data; and selecting data in the clear sky adjustment data set, wherein for the clear sky adjustment data set corresponding to each channel of the MWTS-II, two data selection standards are adopted: (1) each group of natural atmosphere data in the clear air adjustment data set is different from the average atmosphere data, and the absolute value of each difference of the temperature profile is less than 1K, and the absolute value of the humidity profileThe absolute value of each difference is less than 1000 ppmv, the absolute value of the difference of 2 m temperature is less than 1K, the absolute value of the difference of 2 m humidity is less than 1000 ppmv, the absolute value of the difference of 10 m u wind speed is less than 1 m/s, and the absolute value of the difference of 10 m v wind speed is less than 1 m/s; (2) pressure stratification distributed according to the peak of the channel weight function in Table 1P nIn aP nThe absolute value of the difference in temperature is less than 0.3K; and finally, selecting data simultaneously meeting the two data selection standards, and establishing a test data set for testing sea surface air pressure sensitivity, so that each channel of the MWTS-II respectively obtains the corresponding test data set. The data volume of the test data set for each channel of MWTS-II is shown in Table 3.
TABLE 3 data volume of MWTS-II test data set
For each channel of the MWTS-II, in the corresponding test data set, the relationship between the observed brightness temperature of each channel and the sea surface air pressure is shown in FIG. 2. As can be seen from FIG. 2, the observed light temperature of each channel of MWTS-II shows a linear change with the change of the sea surface air pressure, i.e., each channel of MWTS-II has an obvious sensitivity to the sea surface air pressure. And (3) performing unary linear regression fitting by taking the observed brightness temperature in the test data set corresponding to each channel of the MWTS-II as a dependent variable and the corresponding sea surface pressure as an independent variable, and comparing the fitting result with the result of the sensitivity test method for manually disturbing the atmospheric data, as shown in FIG. 3. The sensitivity of MWTS-II to sea surface air pressure is tested by using a method of manually disturbing atmospheric data, and the method specifically comprises the following steps: inputting the average atmospheric data and sea surface air pressure data of the clear air adjustment data set corresponding to each channel of the MWTS-II formed in the third step into a radiation transmission model, setting an observation elevation angle to be 0, and manually disturbing the sea surface air pressure data, wherein the specific method comprises the following steps: the initial value of the sea surface pressure data is 1000 hPa, and the sea surface pressure data is increased by steps of 0.1 hPa to 1035 hPa, so as to obtain the simulated light temperature of each channel of MWTS-II. The simulation brightness temperature of each channel of MWTS-II changes along with the change of sea surface air pressure, namely, the result of sensitivity test by the method of manually disturbing atmospheric data. As can be seen from FIG. 3, the sensitivity test method for manually disturbing atmospheric data can only test the linear change relationship of the simulated brightness temperatures of the channels 1,2,3 and 4 of the MWTS-II along with the sea surface air pressure, i.e., the MWTS-II only has the sensitivity of the channels 1,2,3 and 4 to the sea surface air pressure, however, the test result of the sensitivity test method for the MWTS-II based on natural atmosphere to the sea surface air pressure shows that all the channels of the MWTS-II have the sensitivity to the sea surface air pressure. The method directly models the relationship between the actual observed bright temperature of each MWTS-II channel and the sea surface air pressure, more truly reflects the change relationship of the observed bright temperature of each MWTS-II channel along with the sea surface air pressure, more accurately tests the sensitivity of the sea surface air pressure, and is simple and easy to operate.
Claims (6)
1. A sensitivity test method of MWTS-II based on natural atmosphere to sea surface air pressure is characterized by comprising the following steps:
the method comprises the following steps: establishing a matching data set of an MWTS-II observation bright temperature and natural atmosphere data set, and establishing a clear air matching data set by using the matching data set;
step two: the method comprises the steps of utilizing a clear sky matching data set as input of a radiation transmission model RTTOV, utilizing a channel weight function as output of the radiation transmission model RTTOV, calculating an MWTS-II channel weight function, and respectively establishing a clear sky adjusting data set for each channel of the MWTS-II according to the distribution rule of atmosphere layering where the peak value of each MWTS-II channel weight function is located;
the specific implementation comprises the following steps: firstly, taking each group of natural atmosphere data in a clear air matching data set as the input of a radiation transmission model RTTOV, taking a channel weight function as the output of the radiation transmission model RTTOV, calculating the channel weight function of each channel of MWTS-II, and aiming at each channel of the MWTS-II, corresponding to one group of channel weight functions changing along with atmosphere layering; then, for each channel of MWTS-II, respectively counting the pressure layers distributed by the peak values of the channel weight functions corresponding to the channel, and taking the pressure layer with the most distribution as the pressure layer of the channelPressure layer where the peak of the channel weight function is located
Wherein, in the step (A),
，
representing the serial number of the MWTS-II channel; finally, the peak values are abandoned in the clear sky matching data set and are not distributed in
The set of clear-sky matching data corresponding to the channel weight function is formed
A respective clear sky adjustment dataset;
step three: performing data selection on the clear sky adjustment data sets of the channels of the MWTS-II, selecting data meeting selection standards, and respectively establishing test data sets for testing sea surface air pressure sensitivity for the channels of the MWTS-II;
the specific implementation comprises the following steps: firstly, respectively solving a group of average atmospheric data corresponding to each channel of the MWTS-II aiming at a clear air adjustment data set corresponding to each channel of the MWTS-II formed in the step two; and then, selecting data in the clear sky adjustment data set formed in the step two, wherein the data selection criteria are two: (1) making difference between each group of natural atmosphere data in the clear air adjustment data set and average atmosphere data, and simultaneously meeting the requirements that the absolute value of each difference of a temperature profile is less than 1K, the absolute value of each difference of a humidity profile is less than 1000 ppmv, the absolute value of the difference of 2 m temperature is less than 1K, the absolute value of the difference of 2 m humidity is less than 1000 ppmv, the absolute value of the difference of 10 m u wind speed is less than 1 m/s, and the absolute value of the difference of 10 m v wind speed is less than 1 m/s; (2) pressure stratification distributed by the peaks of the channel weight function determined in step two
The absolute value of the difference in temperature is less than 0.3K; finally, selecting data meeting the two data selection standards at the same time, establishing a test data set for testing sea surface air pressure sensitivity, and obtaining a corresponding test data set for each channel of the MWTS-II;
step four: and aiming at the test data set of each channel of the MWTS-II, establishing the change relation of the observed brightness temperature in the test data set of each channel of the MWTS-II along with the sea surface air pressure respectively, and completing the sensitivity test of the MWTS-II to the sea surface air pressure.
2. The method for testing the sensitivity of the MWTS-II based on the natural atmosphere to the sea surface air pressure according to the claim 1, wherein the first step specifically comprises the following steps:
firstly, selecting data from a climatology data set according to a natural atmosphere data selection standard to form a natural atmosphere data set; then, carrying out time and space matching on the natural atmosphere data set and the MWTS-II observed bright temperature, and establishing a matched data set of the MWTS-II observed bright temperature and the natural atmosphere data set; and finally, selecting clear air data, wherein if the cloud amount profile and the cloud water profile in the matched data are both 0, the group of data is clear air matched data, and all clear air matched data are selected to establish a clear air matched data set.
3. The method for testing the sensitivity of MWTS-II based on natural atmosphere to sea surface air pressure according to claim 1, wherein: the matching conditions of the natural atmosphere data set and the MWTS-II for observing the bright temperature in time and space are that the time error is less than 0.5 h, and the mean difference between the longitude error and the latitude error is less than 0.1 degrees.
4. The method for testing the sensitivity of MWTS-II based on natural atmosphere to sea surface air pressure according to claim 1 or 2, wherein: the data set comprises a temperature profile, a humidity profile, a cloud volume profile, a cloud water profile, a 2 m temperature, a 2 m humidity, a skin temperature, a 10 m u wind speed, a 10 m v wind speed and sea surface air pressure as a set of natural atmosphere data.
5. The method for testing the sensitivity of MWTS-II based on natural atmosphere to sea surface air pressure according to claim 1, wherein: the average atmospheric data includes average temperature profile, average humidity profile, average 2 m temperature, average 2 m humidity, average skin temperature, average 10 m u wind speed, average 10 m v wind speed.
6. The method for testing the sensitivity of the MWTS-II based on the natural atmosphere to the sea surface air pressure according to the claim 1, wherein the fourth step specifically comprises the following steps:
and in the test data set corresponding to each channel of the MWTS-II established in the third step, performing unary linear regression analysis by taking the observed bright temperature in the test data set of each channel of the MWTS-II as a dependent variable and the corresponding sea surface pressure as an independent variable, and respectively establishing the change relation of the observed bright temperature in the test data set of each channel of the MWTS-II along with the sea surface air pressure aiming at each channel of the MWTS-II to complete the sensitivity test of the MWTS-II on the sea surface air pressure.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2728502C1 (en) * | 2019-12-26 | 2020-07-29 | Публичное акционерное общество "Красногорский завод им. С.А. Зверева", ПАО КМЗ | Wind, pressure and temperature sensor |
| CN111737641A (en) * | 2020-06-15 | 2020-10-02 | 洛阳师范学院 | MWHTS channel weight function calculation method based on neural network |
| CN111737912A (en) * | 2020-06-15 | 2020-10-02 | 洛阳师范学院 | MWHTS simulated bright temperature calculation method based on deep neural network |
| CN111737913A (en) * | 2020-06-15 | 2020-10-02 | 洛阳师范学院 | MWHTS clear sky observation bright temperature selection method based on cloud water content inversion |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170031056A1 (en) * | 2014-04-10 | 2017-02-02 | Board Of Regents, The University Of Texas System | Solar Energy Forecasting |
| CN108827878B (en) * | 2018-04-08 | 2021-05-18 | 中国科学院国家空间科学中心 | Passive microwave remote sensing detection method for surface air pressure |
| CN110969609B (en) * | 2019-11-29 | 2022-04-29 | 华中科技大学 | Microwave remote sensing bright temperature image cloud detection method |
-
2020
- 2020-10-15 CN CN202011104185.2A patent/CN112345151B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2728502C1 (en) * | 2019-12-26 | 2020-07-29 | Публичное акционерное общество "Красногорский завод им. С.А. Зверева", ПАО КМЗ | Wind, pressure and temperature sensor |
| CN111737641A (en) * | 2020-06-15 | 2020-10-02 | 洛阳师范学院 | MWHTS channel weight function calculation method based on neural network |
| CN111737912A (en) * | 2020-06-15 | 2020-10-02 | 洛阳师范学院 | MWHTS simulated bright temperature calculation method based on deep neural network |
| CN111737913A (en) * | 2020-06-15 | 2020-10-02 | 洛阳师范学院 | MWHTS clear sky observation bright temperature selection method based on cloud water content inversion |
Non-Patent Citations (4)
| Title |
|---|
| FY-3C卫星微波温湿探测仪反演大气温湿廓线研究;贺秋瑞;《中国优秀博硕学位论文全文数据库（博士） 基础科学辑》;20170915(第09期);A009-15 * |
| Microwave hyperspectral measurements for temperature and humidity atmospheric profiling from satellite: The clear-sky case;Filipe Aires 等;《Journal of Geophysical Research: Atmospheres》;20151109;第11334-11351页 * |
| Statistical Temperature Profile Retrievals in Clear-Air Using Passive 118-GHz 02 Observations;A. J. Gasiewski 等;《IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》;19930131;第31卷(第1期);第106-115页 * |
| 应用AMSU-B 微波资料分析0509号Matsa 台风水汽场分布特征;王新 等;《气象》;20091231;第35卷(第12期);第30-36页 * |
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