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2022 |
The latitudinal and temporal variation of atomic oxygen (O) is opposite between the empirical model, NRLMSISE-00 (MSIS) and the whole atmosphere model, whole atmosphere community climate model with thermosphere and ionosphere extension (WACCM-X) at 97–100 km. Atomic Oxygen from WACCM-X has maxima at solstices and summer mid-high latitudes, similar to [O] from Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). We use the densities and dynamics from WACCM-X to drive the Global Ionosphere Thermosphere Model (GITM) at its lower boundary and compare it with the MSIS driven GITM. We focus on the differences in the modeling of the thermospheric and ionospheric semiannual oscillation (T-I SAO). Our results reveal that driving GITM with WACCM-X causes the T-I SAO to maximize around solstices, opposite to when MSIS is used. This is because the global mixing in GITM during solstices is not strong enough to decrease the solstitial [O] densities below the equinoctial values between mesosphere and lower thermosphere (MLT) and upper thermosphere. Larger summer [O] in the MLT leads to the accumulation of [O] at lower latitudes in the thermosphere due to weaker meridional transport, which further increases the amplitude of the oppositely phased SAO. WACCM-X itself has the right phase of SAO in the upper thermosphere but wrong at lower altitudes. The exact mechanisms that can correct the phase of T-I SAO in GITM while using SABER-like [O] in the MLT are currently unknown and warrant further investigation. We suggest mechanisms that can reduce the solstitial maxima in the lower thermosphere, for example, stronger interhemispheric meridional winds, stronger residual circulation, seasonal variations in eddy diffusion, and momentum from breaking gravity waves. Malhotra, Garima; Ridley, Aaron; , Jones; Published by: Journal of Geophysical Research: Space Physics Published on: YEAR: 2022   DOI: 10.1029/2021JA029320 global ionosphere thermosphere modeling; semiannual oscillation; thermospheric and ionospheric SAO; thermospheric spoon mechanism; vertical coupling of thermosphere with lower atmosphere; whole atmosphere community climate model with thermosphere and ionosphere extension (WACCM-X) |
2021 |
The Earth’s Ionosphere and Thermosphere (IT) is a highly dynamic system persistently driven by variable forcings both from above (Solar EUV and the magnetosphere) and the lower atmosphere. The forcing from below accounts for the majority of the variability at low- and mid-latitude IT region during geomagnetic quiet times. The IT region is particularly sensitive to the composition, winds, and temperature of the Mesosphere and Lower Thermosphere (MLT) state. The goal of this dissertation is to help understand how the MLT region controls the upper atmosphere. This is achieved by using the IT model, Global Ionosphere Thermosphere Model (GITM) and altering its lower boundary (which is in the MLT) to allow a more accurate representation of the lower atmospheric physics within the model. At the beginning of this thesis, it is identified that recent solstitial observations of MLT atomic oxygen (O) from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument show larger densities in the summer hemisphere than in the winter hemisphere. This is opposite to what has been previously known and specified in the IT models, and its cause is still under investigation. The first study focuses on understanding the influence of this latitudinal distribution by using a more realistic specification of MLT [O] from the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X), in GITM. This study shows that despite being a minor species throughout the lower thermosphere, reversing the [O] distribution affects the pressure gradients, winds, temperature, and N2 in the lower thermosphere. These changes then map to higher altitudes through diffusive equilibrium, improving the agreement between GITM O/N2 and Global Ultraviolet Imager (GUVI) measurements. Secondly, the importance of MLT variations on the thermospheric and ionospheric semiannual variation (T-I SAO) is investigated. This is done by analyzing the sensitivity of T-I SAO in GITM to different lower boundary assumptions. This study reveals that the primary driver of T-I SAO is the thermospheric spoon mechanism, as a significant T-I SAO is reproduced in GITM without an SAO variation in the MLT. However, using a more realistic MLT [O] from WACCM-X produces an oppositely-phased T-I SAO, maximizing at solstices, disagreeing with the observations. Since the MLT [O] distribution is correct in WACCM-X, the results hint at incomplete specification/physics for lower thermospheric dynamics in GITM that can drive the transition of the SAO to its correct phase. These mechanisms warrant further investigation and may include stronger winter-to-summer winds, and lower thermospheric residual circulation. The goal of the last study is to examine the effects of spatially non-uniform turbulent mixing in the MLT on the IT system. This is achieved by introducing latitudinal variation in the eddy diffusion parameter (Kzz) in GITM. The results reveal larger spatial variability in O/N2 and TEC. However, the net effect is small (within 2-4\%) on the globally averaged quantities and depends on the area of the turbulent patch. The results also show a different response between the summer and the winter IT region, with winter exhibiting larger changes. Overall, this thesis has highlighted some of the outstanding questions in the domain of lower atmosphere-IT coupling and have answered them through exhaustive comparisons of GITM simulations with different satellite observations, and extensive term analyses of the GITM equations, while laying out a framework for coupling of GITM with WACCM-X. Published by: Published on: YEAR: 2021   DOI: 10.7302/2811 |
2020 |
Malhotra, Garima; Ridley, Aaron; Marsh, Daniel; Wu, Chen; Paxton, Larry; Mlynczak, Martin; Published by: Journal of Geophysical Research: Space Physics Published on: |
2019 |
The datasets that are used in these study for comparisons are GPS, GUVI, COSMIC and GRACE observations. Malhotra, Garima; Ridley, Aaron; Marsh, Daniel; Wu, Chen; Paxton, Larry; Published by: Published on: |
2018 |
Malhotra, Garima; Ridley, Aaron; Marsh, Daniel; Wu, Chen; Paxton, Larry; Published by: Published on: |
2017 |
Malhotra, Garima; Ridley, Aaron; Marsh, Daniel; Wu, Chen; Paxton, Larry; Published by: Published on: |
2002 |
Malhotra, Garima; Ridley, Aaron; Marsh, Daniel; Wu, Chen; Paxton, Larry; Published by: Published on: |
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