Formulation and fitting techniques for whole-atmosphere empirical models

• US 10,641,925 B2
• Filed: 06/13/2019
• Issued: 05/05/2020
• Est. Priority Date: 06/13/2018
• Status: Active Grant

• Current Assignee: The Government Of The United States Of America, As Represented By The Secretary Of The Navy
• Original Assignee: The Government Of The United States Of America, As Represented By The Secretary Of The Navy
• Inventors: Emmert, John T., Drob, Douglas P., Picone, Julian Michael
• Primary Examiner(s): Odom, Curtis B
• Application Number:
  US16/440,092
• Publication Number:
  US 20190383968A1
• Time in Patent Office: 327 Days
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09
• CPC Class Codes: G01W 1/16 Measuring atmospheric potential differences, e.g. due to electrical charges in clouds measuring potentiels in general G01R
• CPC Class Codes: G06F 17/11 for solving equations , e.g. nonlinear equations, general mathematical optimization problems optimization specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 2111/10 Numerical modelling

Abstract

Systems and methods are provided for obtaining an empirical model of a planetary atmosphere as a function of the independent variables in a parametric formulation. Embodiments of the present disclosure can represent the temperature and individual species densities of the planetary atmosphere in the formulation, can robustly and efficiently carry out the computations needed to evaluate this formulation and to estimate the formulation'"'"'s parameters, and can thereby obtain the empirical model of the planetary atmosphere.

Claims

1. An atmospheric modeling device, comprising:

a data collator configured to;

receive atmospheric data from a plurality of sources, and

collate and weight the data; and

a parameter estimator configured to;

estimate a plurality of parameters, wherein the plurality of parameters includes parameters for an effective mass profile, and

tune the parameters to the data, thereby generating a plurality of coefficients.

2. The atmospheric modeling device of claim 1, wherein the data collator is configured to weight the data based on statistical significance of data from each source in the plurality of sources.

3. The atmospheric modeling device of claim 1, further comprising:

a client, wherein the client is configured to;

receive an input from a user, and

generate, based on the input and the plurality of coefficients, an output comprising an exosphere temperature, a plurality of temperatures at a plurality of altitudes, a plurality of major species in the air, and a total mass density of the major species.

4. The atmospheric modeling device of claim 3, wherein the input comprises a latitude, a longitude, a day of the year, a solar flux, and information regarding geomagnetic activity.

5. The atmospheric modeling device of claim 1, wherein the parameter estimator is further configured to:

determine an empirical formulation for representing the data, wherein the empirical formulation includes an effective mass profile formulation for the effective mass profile; and

estimate the plurality of parameters based on the empirical formulation.

6. The atmospheric modeling device of claim 1, wherein the effective mass profile identifies a transition from a first point in an altitude where major species in the air are mixed to a second point in the altitude where the major species are diffusive.

7. The atmospheric modeling device of claim 1, wherein the parameter estimator is configured to generate an effective mass profile based on parameters for the effective mass profile, and wherein the mass profile is C2 continuous.

8. A method, comprising:

receiving, using an atmospheric modeling device, atmospheric data from a plurality of sources, and

collating, using the atmospheric modeling device, the data;

weighting, using the atmospheric modeling device, the data;

estimating, using the atmospheric modeling device, a plurality of parameters, wherein the plurality of parameters includes parameters for an effective mass profile; and

tuning the parameters to the data, thereby generating a plurality of coefficients.

9. The method of claim 8, wherein weighting the data further comprises weighting the data based on statistical significance of data from each source in the plurality of sources.

10. The method of claim 8, further comprising:

receiving an input from a user; and

generating, based on the input and the plurality of coefficients, an output comprising an exosphere temperature, a plurality of temperatures at a plurality of altitudes, a plurality of major species in the air, and a total mass density of the major species.

11. The method of claim 10, wherein the input comprises a latitude, a longitude, a day of the year, a solar flux, and information regarding geomagnetic activity.

12. The method of claim 8, further comprising:

determining an empirical formulation for representing the data, wherein the empirical formulation includes an effective mass profile formulation for the effective mass profile; and

estimating the plurality of parameters based on the empirical formulation.

13. The method of claim 8, wherein the effective mass profile identifies a transition from a first point in an altitude where major species in the air are mixed to a second point in the altitude where the major species are diffusive.

14. The method of claim 8, further comprising generating an effective mass profile based on parameters for the effective mass profile, wherein the mass profile is C2 continuous.

15. An atmospheric modeling device, comprising:

a data collator configured to;

receive atmospheric data from a plurality of sources,

collate the data, and

weight the data based on statistical significance of data from each source in the plurality of sources;

a parameter estimator configured to;

determine an empirical formulation for representing the data, wherein the empirical formulation includes an effective mass profile formulation for the effective mass profile, and wherein the effective mass profile identifies a transition from a first point in an altitude where major species in the air are mixed to a second point in the altitude where the major species are diffusive,

estimate, based on the empirical formulation, a plurality of parameters, wherein the plurality of parameters includes parameters for an effective mass profile, and

tune the parameters to the data, thereby generating a plurality of coefficients; and

a client, wherein the client is configured to;

receive an input from a user, and

generate, based on the input and the plurality of coefficients, an output comprising an exosphere temperature, a plurality of temperatures at a plurality of altitudes, a plurality of major species in the air, and a total mass density of the major species.

16. The atmospheric modeling device of claim 15, wherein the parameter estimator is configured to generate an effective mass profile based on parameters for the effective mass profile, and wherein the mass profile is C2 continuous.

17. The atmospheric modeling device of claim 16, wherein the effective mass profile is configured to provide a seamless representation of densities of the major species.

18. The atmospheric modeling device of claim 16, wherein the effective mass profile approximates a logistic function.

19. The atmospheric modeling device of claim 15, wherein the parameter estimator is further configured to generate a density profile and a temperature profile.

20. The atmospheric modeling device of claim 19, wherein the density profile is decoupled from the temperature profile.