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Assessing the Impact of Ground‐Based Wind Measurements on Mesospheric and Lower Thermospheric Weather Through Assimilation in a Whole Atmosphere Model.

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Title: Assessing the Impact of Ground‐Based Wind Measurements on Mesospheric and Lower Thermospheric Weather Through Assimilation in a Whole Atmosphere Model.
Authors: Hsu, C.‐T.1 (AUTHOR) chihting@ucar.edu, Pedatella, N. M.1 (AUTHOR), Chartier, A. T.2 (AUTHOR), Sassi, F.3 (AUTHOR), Liu, G.3 (AUTHOR), Janches, D.4 (AUTHOR), Stober, G.5,6 (AUTHOR), Chau, J. L.7 (AUTHOR), Conte, J. F.7 (AUTHOR), Andrioli, V. F.8 (AUTHOR), Batista, P. P.8 (AUTHOR), Buriti, R.9 (AUTHOR), Gulbrandsen, N.10 (AUTHOR), Jacobi, C.11 (AUTHOR), Kero, J.12 (AUTHOR), Kozlovsky, A. E.13 (AUTHOR), Latteck, R.7 (AUTHOR), Lester, M.14 (AUTHOR), Moffat‐Griffin, T.15 (AUTHOR), Nozawa, S.16 (AUTHOR)
Source: Journal of Geophysical Research. Space Physics. May2026, Vol. 131 Issue 5, p1-20. 20p.
Subject Terms: *Weather forecasting, *Mesosphere, Wind measurement, Data assimilation, Thermosphere, Atmospheric models, Radar meteorology, Kalman filtering
Abstract: The mesosphere and lower thermosphere (MLT) dynamics play a crucial role in the vertical coupling of the whole atmosphere and are a key component of space weather processes. However, accurately representing the MLT in whole atmosphere models remains challenging due to sparse observational coverage and limited assimilation of high‐altitude wind data. In this study, we evaluate the feasibility and impact of assimilating MLT wind observations from a ground‐based meteor radar network into the Whole Atmosphere Community Climate Model (WACCM) using the Ensemble Adjustment Kalman Filter (EAKF) within the Data Assimilation Research Testbed (DART). Two Observing System Simulation Experiments (OSSEs) were conducted for the 2018/2019 Northern Hemisphere winter. In the first OSSE, synthetic observations of lower atmospheric state variables and SABER and MLS neutral temperatures are assimilated. In the second OSSE, additional synthetic ground‐based MLT wind measurements were assimilated to assess their added value. Results show that assimilating meteor radar winds leads to localized improvements in neutral wind fields near the observation sites. Notably, the assimilation of ground‐based MLT winds results in substantial and widespread reductions in neutral temperature error, highlighting strong wind–temperature correlations within the model ensemble. However, wind corrections remain largely confined in both space and time, emphasizing the need for adjustments to the data assimilation methodology to extend their impact. These findings demonstrate the potential of ground‐based MLT wind assimilation to enhance upper atmospheric state estimation and emphasize the importance of optimizing localization, inflation, and multivariate update strategies. Plain Language Summary: The upper atmosphere, especially the region between about 80 and 100 km above the ground, plays an important role in how energy and momentum are transported between Earth's lower and upper atmosphere. This region is known as the mesosphere and lower thermosphere (MLT). The MLT is difficult to observe because only a few specialized instruments can measure conditions at these heights. To better monitor and simulate this region, we tested whether adding wind measurements from meteor radars could improve wind and temperature estimates in a whole‐atmosphere model. We ran two Observing System Simulation Experiments (OSSEs), which use synthetic observations to update the model. When MLT wind measurements were included, we found they significantly improved temperature predictions across the globe. Improvements in wind predictions were mostly limited to areas near the ground‐based stations. This means that while the model can use wind data to improve related variables like temperature, it struggles to propagate wind improvements in space and time. Our results suggest that including MLT wind observations can help improve the MLT weather monitoring and forecasting. Future work should focus on improving how these data are used in the model so that corrections can propagate more effectively in space and time. Key Points: Synthetic MLT wind, as if measured by meteor radar, was assimilated into a whole atmospheric model, DART + WACCMThe adjustment of neutral wind in the WACCM ensemble is largely limited to the observation locationsAdjustments of neutral temperature in the WACCM ensemble extends the impact of MLT winds in space and time [ABSTRACT FROM AUTHOR]
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Abstract:The mesosphere and lower thermosphere (MLT) dynamics play a crucial role in the vertical coupling of the whole atmosphere and are a key component of space weather processes. However, accurately representing the MLT in whole atmosphere models remains challenging due to sparse observational coverage and limited assimilation of high‐altitude wind data. In this study, we evaluate the feasibility and impact of assimilating MLT wind observations from a ground‐based meteor radar network into the Whole Atmosphere Community Climate Model (WACCM) using the Ensemble Adjustment Kalman Filter (EAKF) within the Data Assimilation Research Testbed (DART). Two Observing System Simulation Experiments (OSSEs) were conducted for the 2018/2019 Northern Hemisphere winter. In the first OSSE, synthetic observations of lower atmospheric state variables and SABER and MLS neutral temperatures are assimilated. In the second OSSE, additional synthetic ground‐based MLT wind measurements were assimilated to assess their added value. Results show that assimilating meteor radar winds leads to localized improvements in neutral wind fields near the observation sites. Notably, the assimilation of ground‐based MLT winds results in substantial and widespread reductions in neutral temperature error, highlighting strong wind–temperature correlations within the model ensemble. However, wind corrections remain largely confined in both space and time, emphasizing the need for adjustments to the data assimilation methodology to extend their impact. These findings demonstrate the potential of ground‐based MLT wind assimilation to enhance upper atmospheric state estimation and emphasize the importance of optimizing localization, inflation, and multivariate update strategies. Plain Language Summary: The upper atmosphere, especially the region between about 80 and 100 km above the ground, plays an important role in how energy and momentum are transported between Earth's lower and upper atmosphere. This region is known as the mesosphere and lower thermosphere (MLT). The MLT is difficult to observe because only a few specialized instruments can measure conditions at these heights. To better monitor and simulate this region, we tested whether adding wind measurements from meteor radars could improve wind and temperature estimates in a whole‐atmosphere model. We ran two Observing System Simulation Experiments (OSSEs), which use synthetic observations to update the model. When MLT wind measurements were included, we found they significantly improved temperature predictions across the globe. Improvements in wind predictions were mostly limited to areas near the ground‐based stations. This means that while the model can use wind data to improve related variables like temperature, it struggles to propagate wind improvements in space and time. Our results suggest that including MLT wind observations can help improve the MLT weather monitoring and forecasting. Future work should focus on improving how these data are used in the model so that corrections can propagate more effectively in space and time. Key Points: Synthetic MLT wind, as if measured by meteor radar, was assimilated into a whole atmospheric model, DART + WACCMThe adjustment of neutral wind in the WACCM ensemble is largely limited to the observation locationsAdjustments of neutral temperature in the WACCM ensemble extends the impact of MLT winds in space and time [ABSTRACT FROM AUTHOR]
ISSN:21699380
DOI:10.1029/2026JA035049