Work Description

Title: Impacts of Lower Thermospheric Atomic Oxygen and Dynamics on Thermospheric Semiannual Oscillation using GITM and WACCM-X Open Access Deposited

h
Attribute Value
Methodology
  • These are full year simulations of GITM for 2010. The data here is diurnal and zonal average of winds, densities, and temperature for each of the simulations.

  • WACCM-X 2.0 densities, winds and temperature on pressure grid are interpolated to altitude grid and used in Global Ionosphere Thermosphere Model (GITM). WACCM-X is then used as the lower boundary in GITM and compared with GITM driven with MSIS-00 and HWM14 as the lower boundary. Other simulations are GITM with no SAO at the lower boundary, GITM with Nudged Dynamics till 140 km, GITM with time varying eddy diffusion coefficient, GITM with WACCM-X 2.1 as the lower boundary, and pure MSIS empirical model.
Description
  • This research aims to understand the influence of lower thermospheric atomic oxygen ([O]) and dynamics on the thermospheric Semi Annual Oscillation (SAO). [O] number densities between 95-100 km from WACCM-X are much closer to the observations from SABER instrument on TIMED satellite as compared to those from MSIS. We compare the phase and amplitude of SAO from different simulations with empirical models and observational datasets, and explore different mechanisms that can improve the SAO in IT models.
Creator
Depositor
  • garimam@umich.edu
Contact information
Discipline
Keyword
Citations to related material
  • Malhotra, G., Ridley, A., Jones, M., (2021) Impacts of Lower Thermospheric Atomic Oxygen and Dynamics on Thermospheric Semiannual Oscillation using GITM and WACCM-X, Journal of Geophysical Research: Space Physics
Resource type
Curation notes
  • To run read_pickle.py to check the files: Add these two lines at the end: ------------- print load_gitm_pickle('gitm_msis/') print load_waccmx_pickle('waccmx_cesm2.0/') ------------- Using Python 2.7: >>python2.7 read_pickle.py
Last modified
  • 11/23/2022
Published
  • 03/09/2021
Language
DOI
  • https://doi.org/10.7302/9gp8-kx76
License
To Cite this Work:
Malhotra, G., Ridley, A. (2021). Impacts of Lower Thermospheric Atomic Oxygen and Dynamics on Thermospheric Semiannual Oscillation using GITM and WACCM-X [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/9gp8-kx76

Relationships

This work is not a member of any user collections.

Files (Count: 10; Size: 1.13 GB)

Each of these directories contain pickled files for each model runs.
These are prepared using Python2.7 and can be read as shown in
read_pickle.py:

The runs in each directory are full year simulations of GITM
with different lower boundary (LB) conditions. For each run, diurnally
and zonally averaged parameters are provided in a dictionary data structure.
These can be read using the function load_gitm_pickle()

1. gitm_msis/ : G/MSIS simulation (NRLMSIS00 and HWM14)
2. gitm_noSAO/ : G/NOSAO simulation (AO, SAO Flags = 0)
3. gitm_waccm_lb_cesm2.0/ : G/WX (WACCM-X 2.0 as LB)
4. gitm_waccm_nudge/ : G/NUDGE (WACCMX 2.0 as LB with constrained dynamics)
5. gitm_waccm_eddy/ : G/EDDY (WACCM-X 2.0 as the LB with seasonally
varying Kzz)
6. gitm_waccm_lb_cesm2.1/ : G/WX 2.1 as the LB
7. pure_msis : MSIS empirical model output on the GITM grid

Point to note : These GITM simulations are 3D simulations with
lat x lon x alt as the coordinate system.

Each simulation/directory has quantities that are stored as pickled files
Some quantities are stored as dictionaries where the keys represent the
day of the year, 2010. And the values are daily and zonal averages with
shape, lats x alts. These quantities are as follows :

1. alti_daily.p : Altitude in m
2. N2_daily.p : Nitrogen number density(N2) in m-3
3. T_daily.p : Temperature(T) in K
4. O_daily.p : Atomic Oxygen number density(O) in m-3
5. rho_daily.p : Neutral Mass Density(rho) in kgm-3
6. U_daily.p : Zonal Wind Velocity(U) in m/s
7. V_daily.p : Meridional Wind Velocity(V) in m/s
8. W_daily.p : Total Vertical Wind Velocity(W) in m/s
9. W_O_daily.p : Total Vertical Wind Velocity(W) for O in m/s
10.W_O2_daily.p : Total Vertical Wind Velocity(W) for O2 in m/s
11.W_N2_daily.p : Total Vertical Wind Velocity(W) for N2 in m/s

The following quantities are stored as one-dimensional arrays :
12. lats : Latitude in radians
13. day_dtimes : Dates in datetime format

WACCM-X 2.0 daily and zonally averaged 2010 data is in the folder
waccmx_cesm2.0/ and can be read using the load_waccmx_pickle().
The output of the model is interpolated onto an altitude grid of GITM,
And the latitude grid can be defined as np.linspace(-90,90,96).

1. comb_waccmx_N2.p : Nitrogen number density(N2) in m-3
2. comb_waccmx_O.p : Atomic Oxygen number density(O) in m-3
3. comb_waccmx_O2.p : Molecular Oxygen number density(O) in m-3
4. comb_waccmx_U.p : Zonal Wind Velocity(U) in m/s
5. comb_waccmx_V.p : Meridional Wind Velocity(U) in m/s
6. comb_waccmx_W.p : Total Vertical Wind Velocity(U) in m/s
7. comb_waccmx_T.p : Temperature(T) in K

These quantities are used as the lower boundary conditions for different
GITM simulations.

Download All Files (To download individual files, select them in the “Files” panel above)

Total work file size of 1.13 GB may be too large to download directly. Consider using Globus (see below).



Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.