UNITOV P-DBM CME propagation model

The CME propagation is modeled by using probability distribution functions. This allows us to evaluate the ICME arrival times and velocities along with the uncertainties on the forecast.

References

https://doi.org/10.1051/swsc/2018003

Model summary

internal_name:

unitov_pdb_model

publisher:

University of Rome Tor Vergata

alph_code:

39A

id_tmp:

xx

identifier:

aspis:///unitov/pdb_model

type:

software

language:

Python 3.x

dependencies:

numpy, matplotlib, ephem, astroquery, datetime, sunpy

latest update:

2023-11-10 12:45:00

Parameters

name

scope

type

description

domain

default

V0

input

float

velocity at launch

0-10000

600

sigma_V0

input

float

error on velocity at launch

0-500

50

Time_UTC

input

datetime

t0, datetime of start date

sigma_t0

input

float

error on start date

0-10000

3000

Rs

input

float

distance from the Sun at t0 in R_sun

0-50

21.5

dRs

input

float

error on Rs

0-10

1

Target

configuration

str

Propagation Target

Earth

W

input

float

solar wind average velocity

420,600

420

sigma_W

input

float

solar wind velocity standard devistion

50,66

50

gammaPDF

configuration

str

Type of PDF for Gamma

NORMAL, LOGNORMAL, SWEPT

LOGNORMAL

Phi_CME

input

float

Central meridian distance in degrees

-90-90

Sigma_Phi_CME

input

float

Error on Phi

0-60

5

Omega

input

float

Half width of the ICME

10-180

60

Sigma_Omega

input

float

Error on the the Width of the ICME

0-60

5

CME

output

PNG image

Visualization of the ICME propagation

ICME velocity

output

PNG image

Visualization of the distribution of the velocity of the ICME at target

Travel time

output

PNG image

Visualization of the distribution of the travel time of the ICME at target