Satellite‐Derived Upper‐Level Vorticity as an Indicator of Short‐Term Typhoon Intensity Evolution
7 affiliations
- 1School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Sun Yat‐sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Zhuhai China
- 2School of Science University of New South Wales Canberra ACT Australia
- 3Guangdong Province Engineering Laboratory for Air Pollution Control South China Institute of Environmental Sciences The Ministry of Ecology and Environment of PRC Guangzhou China
- 4Centre for New Energy Transition Research Federation University Australia Mount Helen VIC Australia
- 5Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites (LRCVES/CMA) National Satellite Meteorological Center China Meteorological Administration (NSMC/CMA) Beijing China
- 6State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Nanjing China
- 7School of Atmospheric Sciences Nanjing University of Information Science and Technology Nanjing China
Abstract
Accurate short‐term tropical cyclone (TC) intensity forecasting remains challenging because rapidly evolving inner‐core structures are difficult to observe at sufficiently high temporal resolution. Here, we derive an area‐mean upper‐level vorticity indicator (VORm) from minute‐scale atmospheric motion vectors retrieved from the Fengyun‐4B Geostationary High‐speed Imager (FY‐4B/GHI) using the Single‐Plane Assumption–Fast Approximate Barnes Interpolation framework. Analysis of western North Pacific TCs shows that VORm closely follows the broad evolution of storm intensity while retaining substantial high‐frequency structural variability. VORm exhibits a strong contemporaneous association with TC intensity and retains information related to subsequent 6‐hr intensity change after accounting for the current intensity and preceding intensity tendency, indicating potential value for short‐term intensity prediction. Forecast experiments further demonstrate this predictive potential. In the linear framework, incorporating VORm reduced the pooled 6‐hr RMSE from 6.27 to 5.97 kt, indicating additional predictive information beyond conventional intensity and environmental predictors. In the nonlinear XGBoost framework, VORm further reduced the RMSE from 6.26 to 6.18 kt even when the preceding 6‐hr intensity tendency was explicitly included, indicating that VORm still provides additional predictive information beyond recent intensity evolution. Because FY‐4B/GHI winds and the derived vorticity can be obtained with very low latency, this approach offers a practical pathway for rapidly incorporating high‐frequency inner‐core structural information into short‐range TC intensity forecasting.
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BibTeX
@article{xia2026satellitederived,
title = {{Satellite‐Derived Upper‐Level Vorticity as an Indicator of Short‐Term Typhoon Intensity Evolution}},
author = {Pan Xia and Difei Deng and Xia Yang and Savin S. Chand and Min Min and Jun Li and Na Xu and Deming Meng and Qiang Yu and Rundong Zhou},
journal = {AGU Advances},
year = {2026},
month = oct,
doi = {10.1029/2026av002688},
url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2026AV002688},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Satellite‐Derived Upper‐Level Vorticity as an Indicator of Short‐Term Typhoon Intensity Evolution
AU - Pan Xia
AU - Difei Deng
AU - Xia Yang
AU - Savin S. Chand
AU - Min Min
AU - Jun Li
AU - Na Xu
AU - Deming Meng
AU - Qiang Yu
AU - Rundong Zhou
PY - 2026
DA - 2026/10/15
JO - AGU Advances
DO - 10.1029/2026av002688
UR - https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2026AV002688
AB - Accurate short‐term tropical cyclone (TC) intensity forecasting remains challenging because rapidly evolving inner‐core structures are difficult to observe at sufficiently high temporal resolution. Here, we derive an area‐mean upper‐level vorticity indicator (VORm) from minute‐scale atmospheric motion vectors retrieved from the Fengyun‐4B Geostationary High‐speed Imager (FY‐4B/GHI) using the Single‐Plane Assumption–Fast Approximate Barnes Interpolation framework. Analysis of western North Pacific TCs shows that VORm closely follows the broad evolution of storm intensity while retaining substantial high‐frequency structural variability. VORm exhibits a strong contemporaneous association with TC intensity and retains information related to subsequent 6‐hr intensity change after accounting for the current intensity and preceding intensity tendency, indicating potential value for short‐term intensity prediction. Forecast experiments further demonstrate this predictive potential. In the linear framework, incorporating VORm reduced the pooled 6‐hr RMSE from 6.27 to 5.97 kt, indicating additional predictive information beyond conventional intensity and environmental predictors. In the nonlinear XGBoost framework, VORm further reduced the RMSE from 6.26 to 6.18 kt even when the preceding 6‐hr intensity tendency was explicitly included, indicating that VORm still provides additional predictive information beyond recent intensity evolution. Because FY‐4B/GHI winds and the derived vorticity can be obtained with very low latency, this approach offers a practical pathway for rapidly incorporating high‐frequency inner‐core structural information into short‐range TC intensity forecasting.
SN - 2576-604X
SN - 2576-604X
ER -