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Data · dataset · 2026

Evaluating nudging techniques in implementing the lower atmosphere variability induced by tides and gravity waves into the TIEGCM

Listed in National Center for Atmospheric Research

We implement a nudging module into the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) to identify effective techniques for incorporating global‐scale tides and medium‐scale gravity waves (GWs) that induce ionospheric variability.

Description

Nudging the full fields of basic state variables minimizes contamination from spectral aliasing and mode coupling, ensuring the most accurate reproduction of each tidal component.

In contrast, nudging solely diurnal tides has substantial spectral leakage into semidiurnal tides, leading to underestimations of their own amplitudes and day‐to‐day variabilities (DTDVs). Nudging both diurnal and semidiurnal tides mitigates such underestimations, establishing a minimal requirement for reproducing tidal dynamics and ionospheric DTDVs. Lower boundary forcing (LBF) causes significant deviations of tidal amplitudes and DTDVs near the boundary, but only a ∼10% underestimation above it.

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The DTDV of vertical ion drift gradually increases with more wave components incorporated and shows a ∼10% underestimation with LBF. Constraining geopotential height ( Z *) is critical in TIEGCM to properly add GWs at lower levels. Model runs with Z

  • constrained exhibit reduced sensitivity to nudging levels: one‐level nudging and LBF runs show 20%–30% underestimations of TID magnitudes compared to a four‐scale‐height nudging run. Conversely, when Z
  • is unavailable and only U , V , T are constrained, one‐level nudging and LBF lead to 80%–90% underestimations of TIDs, with LBF entirely missing wave features. Therefore, multi‐level nudging, especially with Z
  • unconstrained, is recommended to incorporate GWs. Overall, nudging provides a powerful tool to realistically incorporate observed or simulated waves across medium to global scales into ionosphere‐thermosphere models, offering a data‐driven perspective of variability for lower boundary conditions.

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National Center for Atmospheric Research288aea65-b3de-4795-8731-b296bd03e31d8 d agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0