Bibliographic Details
| Title: |
Projected Changes in Extratropical Cyclone Activity Under Climate Change Scenario in East Asia. |
| Authors: |
Byun, Ui‐Yong1,2 (AUTHOR), Chang, Eun‐Chul1,2,3 (AUTHOR) echang@kongju.ac.kr, Lee, Jae‐Deok1,2 (AUTHOR), Kim, Joowan1,2,3 (AUTHOR), Ahn, Joong‐Bae4 (AUTHOR), Cha, Dong‐Hyun5 (AUTHOR), Min, Seung‐Ki6 (AUTHOR) |
| Source: |
Journal of Geophysical Research. Atmospheres. 6/28/2026, Vol. 131 Issue 12, p1-17. 17p. |
| Subject Terms: |
*Climate change models, *Cyclones, *Climate change, East Asians, Atmospheric models, Cyclone tracking |
| Geographic Terms: |
East Asia |
| Abstract: |
Understanding the projected changes in extratropical cyclone (ETC) activity under climate change scenarios is essential for anticipating regional climate impacts and developing effective adaptation strategies. This study investigated how the ETC activity over East Asia responds to future climate conditions by dynamically downscaling simulations from the UK Earth System Model (UKESM6), which is part of Coupled Model Intercomparison Project Phase 6 (CMIP6), using four regional climate models (RCMs): GRIMs, WRF, RegCM, and CCLM. To robustly assess the changes in ETC characteristics, both Eulerian bandpass filtering and Lagrangian cyclone tracking methods were employed under four Shared Socioeconomic Pathway scenarios: SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5. The results highlight the added value of RCMs in significantly reducing the biases present in UKESM6 over complex terrain, primarily owing to the improved representation of high‐resolution topography and the associated dynamical processes. Distinct trends emerged between the land and ocean regions: ETC activity over land showed limited changes regardless of the emission scenario intensity, whereas oceanic ETC activity significantly declined under intensified warming scenarios (SSP3‐7.0 and SSP5‐8.5). Disentangling ETC‐related intensity changes from cyclone passage frequency also revealed that similar bulk ETC changes can arise from different combinations of these contributions depending on the scenario, highlighting the scenario‐dependent responses of oceanic and inland ETC activity. Overall, the results indicate that future ETC changes over East Asia are strongly scenario dependent, with relatively weak inland changes but a more robust weakening over the marine storm‐track region under stronger warming. Plain Language Summary: This study investigated how future changes in extratropical cyclone (ETC) activity—large storm systems common in midlatitudes might affect East Asia under different climate change scenarios. Researchers have used global climate model simulations and applied regional climate models (RCMs) to improve projection details and accuracy. Combining the two analytical methods, this study examined cyclone numbers and strength over land and oceans. The results showed that regional models help reduce errors in global models, especially in inland areas with complex topography, such as mountains and plateaus. Overland, the ETC activity shows only slight changes in the future, regardless of the extent of warming. However, stronger global warming over the ocean has led to a significant weakening of ETC activity, likely due to changes in the heat transfer between the ocean and atmosphere. These findings show that future ETC changes over East Asia depend strongly on the warming scenario: changes over land remain relatively small, whereas ETC activity over the ocean weakens more clearly under stronger warming. This land–ocean contrast provides a clearer picture of how future storm activity may evolve across East Asia. Key Points: Regional climate models driven by UKESM6 effectively reduce global biases in simulating extratropical cyclone activity over East AsiaETC activity under SSP scenarios shows contrasting trends between land and ocean regions, reflecting warming intensity effectsStorm track analysis combining bandpass filtering and Lagrangian tracking enhances our understanding of future ETC dynamics under climate change [ABSTRACT FROM AUTHOR] |
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| Database: |
GreenFILE |