A method for correcting ion production rate based on vertical sounding data

Abstract

The present invention discloses a method for correcting ion production rate based on vertical sounding data, comprising the following steps: Step 1, debugging the ionospheric physical model; Step 2, downloading ionospheric vertical sounding parameters; Step 3, calculating the corresponding time and location of the observation data source by the physical model; Step 4, obtaining the correction coefficient at this observation station; Step 5, correcting the physical model by using the correction coefficient obtained in Step 4; Step 6, cross-checking the accuracy of the corrected model. The method for correcting ion production rate based on vertical sounding data disclosed by the present invention can make the output result closer to the actual situation and significantly improve the model calculation accuracy through the correction of the key chemical parameters of the ionospheric physical model.

Description

Technical Field

[0001] The present invention belongs to the field of ionospheric environment prediction, and particularly relates to a method for correcting ion production rate based on vertical sounding data in this field. Background Art

[0002] The ionosphere is a very important region in space environment exploration and research, and has always received special attention in space engineering, space applications, and the utilization and development of space environment. There is enough ionized gas component in the ionosphere due to solar radiation, so that it can affect the propagation characteristics of radio waves in most bands, and is an important link affecting the smoothness of space information links. Therefore, accurate nowcasting and forecasting of the ionospheric state are of great significance.

[0003] Based on numerical methods and computing technologies, considering a large number of physical and chemical processes, through the continuity equation, momentum equation, and energy equation, the physical model can simulate complex physical and chemical processes and obtain the spatio-temporal distributions of ionospheric state parameters such as density, velocity, and temperature. Compared with empirical models, the physical model does not rely on observational data and can theoretically insight into what factors affect the changes in the ionosphere. However, at present, the driving factors such as wind field, electric field, and neutral component density of the physical model are obtained empirically. In addition, the physical model cannot comprehensively and accurately consider the physical and chemical processes and perturbation conditions in the ionosphere. For example, the key coefficients such as reaction rate and collision frequency in the chemical process are not accurate. Coupled with the uncertainty of boundary conditions and initial conditions, and the errors brought by numerical methods, the physical model can only describe the "climatology" behavior of the ionosphere and cannot accurately describe the ionospheric changes. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for correcting ion production rate based on vertical sounding data for the problem that the simulation accuracy of the ionospheric physical model is not high due to inaccurate description of chemical processes.

[0005] The present invention adopts the following technical solutions:

[0006] A method for correcting ion production rate based on vertical sounding data, the improvement lies in that it includes the following steps:

[0007] Step 1, debug the ionospheric physical model, input parameters: solar activity index F107, geomagnetic activity index AP, time, longitude and latitude;

[0008] Step 2, download the ionospheric vertical sounding parameter foF2 ionosonde , physical model input parameters: solar activity index F107 and geomagnetic activity index AP;

[0009] Step 3, the physical model calculates foF2 at the corresponding time and location of the observation data sourcemodel ;

[0010] Step 4. Use a linear regression model to represent the relationship between the physical model calculation results and the observed data at the observation station:

[0011] foF2 ionosonde = a0 + a1×foF2 model

[0012] where a0 and a1 are regression coefficients, and foF2 ionosonde and foF2 model are the observed value and the model calculation value respectively. The regression coefficient a1 obtained after fitting is the correction coefficient of this physical model at this observation station;

[0013] Step 5. Correct the physical model using the correction coefficient a1 obtained in Step 4. The method is as follows:

[0014] q = a1×q0

[0015] In the above formula, q0 and q are the ion production rates of the physical model before and after correction respectively;

[0016] Step 6. Cross-check the accuracy of the corrected model, that is, use the corrected physical model to calculate the ionospheric foF2, and then compare and verify it with the actual observed value.

[0017] The beneficial effects of the present invention are:

[0018] There are many complex physical and chemical processes in the ionosphere, and it is difficult for physical models to comprehensively and accurately describe these processes, which is an important reason for inaccurate calculation results. The method for correcting the ion production rate based on vertical sounding data disclosed in the present invention can make the output result closer to the actual situation and significantly improve the model calculation accuracy through the correction of the key chemical parameters of the ionospheric physical model. As the core of ionospheric numerical prediction, the improvement of the simulation accuracy of the ionospheric physical model can provide technical support for the development of ionospheric numerical nowcasting and forecasting technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flowchart of the method of the present invention;

[0020] FIG. 2(a) is a comparison diagram of the simulation value and the observed value before correction using the method of the present invention;

[0021] FIG. 2(b) is a comparison diagram of the simulation value and the observed value after correction using the method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0022] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0023] Embodiment 1 discloses a method for correcting the ion production rate based on vertical sounding data. Based on the critical frequency foF2 of the F2 layer of the ionosphere obtained by vertical sounding, the key parameter of the physical model, the ion production rate, is corrected to improve the model simulation accuracy.

[0024] As Figure 1 shown, it includes the following steps:

[0025] Step 1: Debug the ionosphere physical model (height range: 90 - 550 km, time step: 6 minutes), and input parameters: solar activity index F107, geomagnetic activity index AP, time, longitude and latitude;

[0026] Step 2: Obtain original data:

[0027] Download the ionosphere vertical sounding parameter foF2 ionosonde , and download the input parameters required for the ionosphere physical model: solar activity index F107 and geomagnetic activity index AP; to ensure the improvement effect, the data should cover all seasons and solar activity levels.

[0028] Step 3: Use the ionosphere physical model to calculate the ionosphere foF2 at the corresponding time (time period) and location (station) of the observation data source model ;

[0029] Step 4: Solve the correction coefficient, perform linear regression on the observation data and the calculation result of the physical model, and obtain the correction coefficient of this physical model at this observation station:

[0030] Use the linear regression model to represent the relationship between the calculation result of the physical model and the observation data of the observation station:

[0031] foF2 ionosonde = a0 + a1 × foF2 model

[0032] where a0 and a1 are regression coefficients, foF2 ionosonde and foF2 model are the observed value and the model calculation value respectively, and the regression coefficient a1 obtained after fitting is the correction coefficient of this physical model at this observation station;

[0033] Step 5: Correct the ion production rate of the physical model:

[0034] Use the correction coefficient a1 obtained in step 4 to correct the key parameters of the ionospheric physical model: the ion production rate. The method is as follows:

[0035] q = a1 × q0

[0036] In the above formula, q0 and q are the ion production rates of the physical model before and after correction, respectively;

[0037] Step 6, cross-check the accuracy of the corrected model (the effectiveness of the correction coefficient), that is, use the corrected physical model to calculate the ionospheric foF2 and then compare it with the actual observed value for verification.

[0038] Figure 2(a) is a comparison chart of the calculation results and actual observed values before the method of the present invention is applied to the ionospheric physical model; Figure 2(b) is a comparison chart of the calculation results and actual observed values after the method of the present invention is applied to the ionospheric physical model.

[0039] In summary, the present invention discloses a method for correcting the ion production rate based on vertical sounding data. Based on the critical frequency foF2 of the F2 layer of ionospheric vertical sounding data, the ion production rate in the ionospheric physical model is corrected, so that the model calculation result is closer to the actual situation and the model accuracy is improved.

Claims

1. A method for correcting ion production rate based on vertical sounding data, characterized in that It includes the following steps: Step 1: Debug the ionospheric physical model, and input parameters: solar activity index F107, geomagnetic activity index AP, time, longitude and latitude; Step 2, download the ionospheric vertical sounding parameter foF2 ionosonde , input parameters of the physical model: solar activity index F107 and geomagnetic activity index AP; Step 3, calculate the corresponding time and location of the observed data source of the physical model for foF2 model ; Step 4: Use the linear regression model to represent the relationship between the calculation results of the physical model and the observation data of the observatory: foF2 ionosonde = a0 + a1 × foF2 model where a0 and a1 are regression coefficients, and foF2 ionosonde and foF2 model are the observed value and the model calculated value respectively. The regression coefficient a1 obtained after fitting is the correction coefficient of this physical model at this observation station; Step 5: Use the correction coefficient a1 obtained in Step 4 to correct the physical model, and the method is as follows: q = a1 × q0 In the above formula, q0 and q are the ion production rates of the physical model before and after correction, respectively; Step 6: Cross-check the accuracy of the corrected model, that is, use the corrected physical model to calculate the ionospheric foF2 and then compare it with the actual observed value for verification.

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