Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone
Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone A case study of the Great Arctic Cyclone 2012 (AC12) is used to understand the role of initial condition errors and model physics errors in the 2-3-day range predictability of high-impact summer Arct...
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ftoklahomaunivs:oai:shareok.org:11244/336019 2023-05-15T14:51:13+02:00 Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone Chen, Zhihong Wang, Xuguang Johnson, Aaron Cavallo, Steven 2022-08-04 application/vnd.openxmlformats-officedocument.wordprocessingml.document application/pdf https://hdl.handle.net/11244/336019 en_US eng OU Thesis and Dissertation Collections https://hdl.handle.net/11244/336019 Arctic Cyclones Data Assimilation Physics Parameterization EnKF 2022 ftoklahomaunivs 2023-01-25T21:32:29Z Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone A case study of the Great Arctic Cyclone 2012 (AC12) is used to understand the role of initial condition errors and model physics errors in the 2-3-day range predictability of high-impact summer Arctic Cyclones (ACs). The control forecasts initialized with analyses assimilating conventional in-situ observation demonstrate improved skills in predicting the peak intensity with less than 3 hPa difference from the verifying reanalysis. However, the forecasted AC12 reaches its peak intensity 18 hours earlier than in the verifying reanalysis and the cyclone track is biased towards the southwest. Using ensemble sensitivity analysis (ESA), the upstream trough, downstream ridge, and the tropopause polar vortex (TPV) to the northeast (NE TPV) of the AC12 are identified to be correlated with the deepening trend and the cyclone track error, but they are not well observed by current in-situ observation networks. Pseudo-observations are constructed from reanalysis and are added to the three features separately to study the impact of the initial condition error in each feature on the predictability of AC12. The cyclone deepening trend error and track error are greatly reduced when the initial condition is better constrained in either the NE TPV or the jet stream wind along the trough and ridge, as the former leads to a southward expansion of the NE TPV and the latter leads to successfully capturing of a shortwave trough at the 2PVU surface above the AC12. Varying the choice of model physics parameterization schemes does not further improve the cyclone track prediction. The cyclone intensity prediction is sensitive to the choice of longwave radiation schemes and planetary boundary layer (PBL) schemes. Varying longwave radiation schemes creates a large ensemble spread (~5 hPa) in the cyclone intensity prediction as the longwave cooling gradient near the tropopause affects the strength of TPVs. The Yonsei University (YSU) PBL ... Other/Unknown Material Arctic University of Oklahoma/Oklahoma State University: SHAREOK Repository Arctic |
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Open Polar |
collection |
University of Oklahoma/Oklahoma State University: SHAREOK Repository |
op_collection_id |
ftoklahomaunivs |
language |
English |
topic |
Arctic Cyclones Data Assimilation Physics Parameterization EnKF |
spellingShingle |
Arctic Cyclones Data Assimilation Physics Parameterization EnKF Chen, Zhihong Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone |
topic_facet |
Arctic Cyclones Data Assimilation Physics Parameterization EnKF |
description |
Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone A case study of the Great Arctic Cyclone 2012 (AC12) is used to understand the role of initial condition errors and model physics errors in the 2-3-day range predictability of high-impact summer Arctic Cyclones (ACs). The control forecasts initialized with analyses assimilating conventional in-situ observation demonstrate improved skills in predicting the peak intensity with less than 3 hPa difference from the verifying reanalysis. However, the forecasted AC12 reaches its peak intensity 18 hours earlier than in the verifying reanalysis and the cyclone track is biased towards the southwest. Using ensemble sensitivity analysis (ESA), the upstream trough, downstream ridge, and the tropopause polar vortex (TPV) to the northeast (NE TPV) of the AC12 are identified to be correlated with the deepening trend and the cyclone track error, but they are not well observed by current in-situ observation networks. Pseudo-observations are constructed from reanalysis and are added to the three features separately to study the impact of the initial condition error in each feature on the predictability of AC12. The cyclone deepening trend error and track error are greatly reduced when the initial condition is better constrained in either the NE TPV or the jet stream wind along the trough and ridge, as the former leads to a southward expansion of the NE TPV and the latter leads to successfully capturing of a shortwave trough at the 2PVU surface above the AC12. Varying the choice of model physics parameterization schemes does not further improve the cyclone track prediction. The cyclone intensity prediction is sensitive to the choice of longwave radiation schemes and planetary boundary layer (PBL) schemes. Varying longwave radiation schemes creates a large ensemble spread (~5 hPa) in the cyclone intensity prediction as the longwave cooling gradient near the tropopause affects the strength of TPVs. The Yonsei University (YSU) PBL ... |
author2 |
Wang, Xuguang Johnson, Aaron Cavallo, Steven |
author |
Chen, Zhihong |
author_facet |
Chen, Zhihong |
author_sort |
Chen, Zhihong |
title |
Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone |
title_short |
Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone |
title_full |
Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone |
title_fullStr |
Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone |
title_full_unstemmed |
Impact of data assimilation and model physics on the predictability of the 2012 Great Arctic Cyclone |
title_sort |
impact of data assimilation and model physics on the predictability of the 2012 great arctic cyclone |
publishDate |
2022 |
url |
https://hdl.handle.net/11244/336019 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
OU Thesis and Dissertation Collections https://hdl.handle.net/11244/336019 |
_version_ |
1766322266686095360 |