Table 2 Maximum daily precipitation at landfall (mm).
From: Increasing typhoon impact and economic losses due to anthropogenic warming in Southeast China
Typhoon (year) | Observed | Historical hindcasts (mean ± \(\sigma )\) | CMIP5 RCP4.5 minus Historical | CMIP5 RCP8.5 minus Historical | HiFLOR RCP4.5 minus Historical |
|---|---|---|---|---|---|
Usagi (2013) | 143.0 | 195.4 ± 22.9 | 60.6 (31%) | 32.1 (16%) | − 12.1(6%) |
Haiyan (2013) | 320.4 | 314.0 ± 82.3 | 169.3(54%) | 249.1 (79%) | 181.3 (58%) |
Rammasun (2014) | 186.3 | 303.7 ± 58.9 | 14.0 (5%) | 96.2 (32%) | 70.4 (23%) |
Chan-hom (2015) | 267.7 | 144.7 ± 49.4 | 1.2 (1%) | − 5.2 (4%) | 27.2 (19%) |
Soudelor (2015) | 244.4 | 500.1 ± 44.6 | 151.0 (30%) | 227.8 (46%) | 94.8 (19%) |
Mujigae (2015) | 219.0 | 305.8 ± 43.2 | 19.8(6%) | 69.8 (23%) | 16.2 (5%) |
Meranti (2016) | 172.7 | 395.6 ± 39.0 | 10.3 (3%) | 73.0(15%) | 36.5 (9%) |
Maria (2018) | 141.0 | 113.8 ± 21.8 | − 0.6(1%) | 16.5 (14%) | 18.4 (16%) |
Mangkut (2018) | 173.5 | 245.7 ± 30.0 | 13.9 (6%) | 46.3 (19%) | 31.7 (13%) |
Lekima (2019) | 291.0 | 325.5 ± 28.8 | 56.4 (17%) | 47.0 (14%) | 69.3 (21%) |
