Characteristics of extreme hourly precipitation induced by tropical cyclones in Zhejiang, China: A comparative analysis based on two different datasets

This study investigates the characteristics of tropical cyclones (TCs) that cause extreme hourly precipitation (EXHP) in Zhejiang, China, using datasets from 67 national stations (Con-ST) and 1551 surface stations (All-ST), spanning 1973–2020 and 2011–2020, respectively. Our analysis revealed notable variations in the EXHP caused by individual TCs. The top 10 % of TCs contributed 37.2–38 % of the total TC-induced EXHP amount, while the bottom 50 % only accounted for 5.8–22.7 %. Using sparse stations may overestimate the impact of TCs causing EXHP in the lower to middle rankings. Long-term trend analysis suggested a consistent increase in TC-induced EXHP despite a decreasing trend in the number of TCs affecting Zhejiang. High-value EXHP centers tended to be concentrated in mountainous areas within 0–50 km from the coastline, where Con-ST stations are sparse and can significantly underestimate EXHP. The maximum amount of EXHP per TC increased logarithmically with the number of observation stations. In Zhejiang, EXHP predominantly occurred northeast of the TC centers (50.4–61.7 %) and within 500 km from the TC center (69.5–81.5 %). High-frequency EXHP centers exhibited a clockwise rotation with increasing distance from the TC center–a pattern resembling a “spiral rainband.” A key area where most EXHP in Zhejiang occurred when TC centers remained within this area was identified. The TC intensity within the key area was a key factor influencing EXHP occurrence in Zhejiang, whereas the duration of TC center residence within the key area and the distance of its movement were crucial predictors of significant EXHP occurrence. The analysis of large-scale environmental fields revealed that high-EXHP TCs are characterized by strong upper-level divergence, intense upward motion, and an expanded subtropical high. The southeasterly steering airflow drives these TCs northwestward, prolonging their impact on Zhejiang and resulting in significant moisture accumulation and EXHP. • From 1973 to 2020, 134 out of 208 tropical cyclones (TCs) affecting Zhejiang caused extreme hourly precipitation (EXHP) • Sparse station data can overestimate the impact of lower to middle-ranking TCs on EXHP in Zhejiang • High-value EXHP centers near coastlines (0–50 km) in mountainous areas are underestimated by sparse national stations • The maximum accumulated EXHP from TCs increased logarithmically with the number of observation stations • TC intensity and duration were crucial predictors of EXHP occurrence and magnitude, respectively

Authors

Publication Details

Journal
Atmospheric Research
Published
2024-09-30
DOI
https://doi.org/10.1016/j.atmosres.2024.107712
Citations
3
Primary Topic
Tropical and Extratropical Cyclones Research
Type
article
Field-Weighted Citation Impact
1.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characteristics of extreme hourly precipitation induced by tropical cyclones in Zhejiang, China: A comparative analysis based on two different datasets

Yefeng Chen, Feng Chen, Wu Mengwen, Meiying Dong
3 citations
Atmospheric Research
Tropical and Extratropical Cyclones Research
1.13
article

Characteristics of extreme hourly precipitation induced by tropical cyclones in Zhejiang, China: A comparative analysis based on two different datasets

Yefeng Chen, Feng Chen, Wu Mengwen, Meiying Dong
article en
3 citations

Abstract

This study investigates the characteristics of tropical cyclones (TCs) that cause extreme hourly precipitation (EXHP) in Zhejiang, China, using datasets from 67 national stations (Con-ST) and 1551 surface stations (All-ST), spanning 1973–2020 and 2011–2020, respectively. Our analysis revealed notable variations in the EXHP caused by individual TCs. The top 10 % of TCs contributed 37.2–38 % of the total TC-induced EXHP amount, while the bottom 50 % only accounted for 5.8–22.7 %. Using sparse stations may overestimate the impact of TCs causing EXHP in the lower to middle rankings. Long-term trend analysis suggested a consistent increase in TC-induced EXHP despite a decreasing trend in the number of TCs affecting Zhejiang. High-value EXHP centers tended to be concentrated in mountainous areas within 0–50 km from the coastline, where Con-ST stations are sparse and can significantly underestimate EXHP. The maximum amount of EXHP per TC increased logarithmically with the number of observation stations. In Zhejiang, EXHP predominantly occurred northeast of the TC centers (50.4–61.7 %) and within 500 km from the TC center (69.5–81.5 %). High-frequency EXHP centers exhibited a clockwise rotation with increasing distance from the TC center–a pattern resembling a “spiral rainband.” A key area where most EXHP in Zhejiang occurred when TC centers remained within this area was identified. The TC intensity within the key area was a key factor influencing EXHP occurrence in Zhejiang, whereas the duration of TC center residence within the key area and the distance of its movement were crucial predictors of significant EXHP occurrence. The analysis of large-scale environmental fields revealed that high-EXHP TCs are characterized by strong upper-level divergence, intense upward motion, and an expanded subtropical high. The southeasterly steering airflow drives these TCs northwestward, prolonging their impact on Zhejiang and resulting in significant moisture accumulation and EXHP. • From 1973 to 2020, 134 out of 208 tropical cyclones (TCs) affecting Zhejiang caused extreme hourly precipitation (EXHP) • Sparse station data can overestimate the impact of lower to middle-ranking TCs on EXHP in Zhejiang • High-value EXHP centers near coastlines (0–50 km) in mountainous areas are underestimated by sparse national stations • The maximum accumulated EXHP from TCs increased logarithmically with the number of observation stations • TC intensity and duration were crucial predictors of EXHP occurrence and magnitude, respectively

Atmospheric ResearchVol. 311
Climate action
Openalex Percentile: Top 24%
Tropical and Extratropical Cyclones Research
1.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.