Harris-Priester

The Harris-Priester model is a simple, computationally efficient atmospheric density model for altitudes between 100 km and 1000 km. It models the diurnal density variation using a cosine power law and exponential interpolation between tabulated minimum and maximum density profiles.

This package provides two variants of the model: the classic Harris-Priester and a modified version published in:

Hatten, N., & Russell, R. P. (2017). A smooth and robust Harris-Priester atmospheric density model for low Earth orbit applications. Advances in Space Research, 59(2), 571-586.

The modified variant uses cubic polynomial fits on the 81-day centered F10.7 solar flux average to model density variations across solar activity levels, ensuring continuous first derivatives and eliminating singularities.

Harris-Priester (Classic)

In this package, we can evaluate the classic model using the following functions:

AtmosphericModels.harrispriester(instant::DateTime, ϕ_gd::Number, λ::Number, h::Number; kwargs...) -> Float64
AtmosphericModels.harrispriester(jd::Number, ϕ_gd::Number, λ::Number, h::Number; kwargs...) -> Float64

where:

• jd::Number: Julian day to compute the model.
• instant::DateTime: Instant to compute the model represent using DateTime.
• ϕ_gd::Number: Geodetic latitude [rad].
• λ::Number: Longitude [rad].
• h::Number: Altitude [m].

The following keywords are available:

• n::Int: Cosine exponent for the diurnal bulge (2 ≤ n ≤ 6). A value of 2 produces a smooth day-night transition; 6 produces a sharp transition. (Default = 4)
• alt_ρ::AbstractMatrix: Custom density profile table with columns [altitude [m], ρ_min [kg/m³], ρ_max [kg/m³]]. (Default = built-in table for mean solar activity)

These functions return the atmospheric density [kg/m³].

Examples

julia> AtmosphericModels.harrispriester(
           DateTime("2018-06-19T18:35:00"),
           deg2rad(-22),
           deg2rad(-45),
           700e3
       )1.522940818810959e-13

julia> AtmosphericModels.harrispriester(
           DateTime("2018-06-19T18:35:00"),
           deg2rad(-22),
           deg2rad(-45),
           700e3;
           n = 2
       )1.820416292170482e-13

Modified Harris-Priester

In this package, we can evaluate the modified model using the following functions:

AtmosphericModels.harrispriester_modified(instant::DateTime, ϕ_gd::Number, λ::Number, h::Number[, F10ₐ::Number]; n::Number = 4) -> Float64
AtmosphericModels.harrispriester_modified(jd::Number, ϕ_gd::Number, λ::Number, h::Number[, F10ₐ::Number]; n::Number = 4) -> Float64

where:

• jd::Number: Julian day to compute the model.
• instant::DateTime: Instant to compute the model represent using DateTime.
• ϕ_gd::Number: Geodetic latitude [rad].
• λ::Number: Longitude [rad].
• h::Number: Altitude [m].
• F10ₐ::Number: 81-day centered average of the F10.7 solar flux index [sfu].
• n::Number: Cosine exponent for the diurnal bulge. The original Fortran implementation computes this from orbital inclination as n = 2.001 + 4sin²(i), yielding n ≈ 2 for equatorial orbits and n ≈ 6 for polar orbits. (Default = 4)

If we omit all space indices, the system tries to obtain them automatically for the selected day jd or instant. However, the indices must be already initialized using the function SpaceIndices.init().

These functions return the atmospheric density [kg/m³].

Examples

julia> AtmosphericModels.harrispriester_modified(
           DateTime("2018-06-19T18:35:00"),
           deg2rad(-22),
           deg2rad(-45),
           700e3,
           79.0
       )1.0589938036259446e-14

julia> SpaceIndices.init()
julia> AtmosphericModels.harrispriester_modified(
           DateTime("2022-06-19T18:35:00"),
           deg2rad(-22),
           deg2rad(-45),
           700e3
       )4.763723690180901e-14

If we use the automatic space index fetching mechanism, it is possible to obtain the fetched values by turning on the debugging logs according to the Julia documentation:

julia> using Logging
julia> with_logger(ConsoleLogger(stderr, Logging.Debug)) do
           AtmosphericModels.harrispriester_modified(
               DateTime("2022-06-19T18:35:00"),
               deg2rad(-22),
               deg2rad(-45),
               700e3
           )
       end4.763723690180901e-14