| Autor: |
Pedatella, N. M., Liu, H.‐L, Marsh, D. R., Raeder, K., Anderson, J. L. |
| Předmět: |
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| Zdroj: |
Space Weather: The International Journal of Research & Applications; Oct2019, Vol. 17 Issue 10, p1442-1460, 19p |
| Abstrakt: |
The capability to forecast conditions in the mesosphere and lower thermosphere is investigated based on 30‐day hindcast experiments that were initialized bimonthly during 2009 and 2010. The hindcasts were performed using the Whole Atmosphere Community Climate Model with thermosphere‐ionosphere eXtension (WACCMX) with data assimilation provided by the Data Assimilation Research Testbed (DART) ensemble Kalman filter. Analysis of the WACCMX+DART hindcasts reveals several important features that are relevant to forecasting the middle atmosphere. The results show a clear dependence on spatial scale, with the slowest error growth occurring in the zonal mean and the fastest error growth occurring for small‐scale waves. The error growth rate is also found to be significantly greater in the upper mesosphere and lower thermosphere compared to in the upper stratosphere to lower mesosphere, suggesting that the forecast skill decreases with increasing altitude. The results demonstrate that the errors in the lower thermosphere reach saturation, on average, in less than 5 days, at least with the current version of WACCMX+DART. A seasonal dependency to the error growth is found at high latitudes in the Northern and Southern Hemispheres but not in the tropics or global average. We additionally investigate the error growth rates for migrating and nonmigrating atmospheric tides and find that the errors saturate after ∼5 days for tides in the lower thermosphere. The results provide an initial assessment of the error growth rates in the mesosphere and lower thermosphere and are relevant for understanding how whole atmosphere models can potentially improve space weather forecasting. Plain Language Summary: The ionosphere and thermosphere are known to vary significantly from day to day, and this day‐to‐day weather is driven by processes originating in the lower atmosphere (below 50 km), especially during periods of quiet solar activity. Accurate forecasting of the ionosphere‐thermosphere variability thus partially depends on the ability to forecast the component that originates in the lower atmosphere. This study makes use of recent developments in whole atmosphere models to provide the first comprehensive investigation of current capabilities to forecast the lower atmospheric drivers of ionosphere‐thermosphere day‐to‐day variability. We evaluate the error growth of a whole atmosphere‐ionosphere model with data assimilation (WACCMX+DART) at altitudes (60–120 km) that are relevant for generating the day‐to‐day variability in the ionosphere and thermosphere. We demonstrate that the error growth rate is larger at higher altitudes, and for smaller spatial scales. Furthermore, it is found that, on average, the error growth in the primary drivers of spatial and temporal variability in the ionosphere saturates after approximately 5 days. The forecast skill of the ionosphere is typically thought to be less than 24 hr; however, the present study illustrates that the forecast skill of the ionosphere can potentially be increased by incorporating forecasts of the lower atmospheric drivers. Key Points: Mesosphere and lower thermosphere error growth rate increases with increasing altitudeErrors in zonal mean and large scale waves grow more slowly than errors in small‐scale wavesAt altitudes relevant for space weather forecasting, the error in atmospheric tides saturates after approximately 5 days [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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