1 Introduction
2 Data
3 Methodology
3.1 Calculation of Hazard Footprint
Class | 24-Hour rainfall | Wind | |||
---|---|---|---|---|---|
Grade | Range (mm) | Grade | Beaufort scale | Range (m s−1) | |
1 | Under moderate rain | 0–25.00 | Strong breeze | 6 | 10.80–13.90 |
2 | Big rain | 25.01–50.00 | High wind | 7 | 13.91–17.20 |
3 | Heavy rain | 50.01–100.00 | Gale | 8 | 17.21–20.80 |
4 | Very heavy rain | 100.01–250.00 | Strong gale | 9 | 20.81–24.50 |
5 | Extreme heavy rain | 250.01–1000 | Storm | 10 | 24.51–200 |
3.2 Loss Normalization
3.3 Trend Analysis
4 Results
4.1 Characteristics of Influential Tropical Cyclones During 1983–2015
No. | Typhoon ID | Year | Typhoon name | Landfall (yes/no) | Maximum wind speeda (m s−1) | Intensity class | Inflation-adjusted total losses (in 2015 bn CNY (USD)) |
---|---|---|---|---|---|---|---|
1 | 199608 | 1996 | Herb | Yes | 35 | TY | 93.42 (15.00) |
2 | 201323 | 2013 | Fitow | Yes | 42 | STY | 65.30 (10.48) |
3 | 199711 | 1997 | Winnie | Yes | 40 | TY | 60.75 (9.75) |
4 | 201209, 201210 | 2012 | Saola, Damrey | Yes | 25 | STS | 54.28 (8.71) |
5 | 200604 | 2006 | Bilis | Yes | 30 | STS | 45.50 (7.31) |
6 | 201409 | 2014 | Rammasun | Yes | 70 | SuperTY | 45.28 (7.27) |
7 | 201211 | 2012 | Haikui | Yes | 42 | STY | 39.89 (6.40) |
8 | 199406 | 1994 | Tim | Yes | 30 | STS | 37.68 (6.05) |
9 | 199417 | 1994 | Fred | Yes | 40 | TY | 32.41 (5.20) |
10 | 199615 | 1996 | Sally | Yes | 50 | STY | 31.29 (5.02) |
4.2 Provincial-Level Loss Normalization (PLN) Results
Province | Original losses (in bn CNY) | Inflation-adjusted losses (in 2015 bn CNY) | Normalized losses (in 2015 bn CNY) | Frequency of influential TCs |
---|---|---|---|---|
Zhejiang | 221.5 (1) | 259.5 (1) | 504.6 (1) | 62 (1) |
Fujian | 98.9 (3) | 124.6 (3) | 372.2 (2) | 49 (2) |
Guangdong | 184.7 (2) | 209.1 (2) | 369.2 (3) | 45 (3) |
Guangxi | 61.4 (4) | 73.1 (4) | 210.2 (4) | 43 (4) |
Hainan | 52.5 (5) | 60.6 (5) | 129.9 (5) | 38 (5) |
Hunan | 28.8 (6) | 37.0 (6) | 117.0 (6) | 25 (6) |
Shandong | 23.6 (7) | 27.0 (7) | 54.3 (7) | 19 (7) |
Anhui | 18.0 (9) | 21.0 (9) | 43.9 (8) | 15 (8) |
Jiangsu | 15.0 (10) | 17.9 (10) | 41.0 (9) | 12 (9) |
Jiangxi | 13.7 (12) | 16.2 (11) | 35.9 (10) | 12 (10) |
Liaoning | 21.5 (8) | 23.0 (8) | 26.4 (11) | 11 (11) |
Hebei | 14.6 (11) | 15.5 (12) | 16.6 (12) | 8 (12) |
Hubei | 5.5 (13) | 6.2 (13) | 11.8 (13) | 8 (13) |
Yunnan | 5.4 (14) | 5.8 (14) | 9.2 (14) | 6 (14) |
Shanghai | 3.7 (15) | 4.5 (15) | 7.7 (15) | 4 (15) |
Henan | 1.3 (17) | 1.7 (17) | 4.5 (16) | 2 (16) |
Jilin | 1.9 (16) | 2.0 (16) | 3.3 (17) | 2 (17) |
Heilongjiang | 1.1 (18) | 1.2 (18) | 1.2 (18) | 2 (18) |
Tianjin | 0.2 (19) | 0.3 (19) | 0.9 (19) | 1 (19) |
Guizhou | 0.2 (20) | 0.2 (20) | 0.5 (20) | 1 (20) |
4.3 National-Level (Total) Loss Normalization (TLN) for Tropical Cyclones in 1983–2015
\( R\_Inf \)
|
\( R\_Wealth \)
|
\( R\_Pop \)
| |
---|---|---|---|
Min. | 1.0 | 1.0 | 1.0 |
Max. | 5.3 | 13.7 | 2.0 |
Mean | 1.9 | 3.8 | 1.2 |
SD | 1.1 | 2.8 | 0.2 |
No. | Year | Typhoon ID | Name | Original loss (in bn CNY) |
\( R\_Inf \)
|
\( R\_Wealth \)
|
\( R\_Pop \)
| Normalized loss (in 2015 bn CNY (USD)) |
---|---|---|---|---|---|---|---|---|
1 | 1996 | 199608 | Herb | 65.3 | 1.4 | 6.0 | 1.1 | 611.8 (98.23) |
2 | 1997 | 199711 | Winnie | 43.6 | 1.4 | 4.0 | 1.2 | 283.9 (45.58) |
3 | 1994 | 199406 | Tim | 20.8 | 1.8 | 5.8 | 1.2 | 254.8 (40.91) |
4 | 1994 | 199417 | Fred | 17.9 | 1.8 | 5.5 | 1.3 | 226.1 (36.30) |
5 | 1996 | 199615 | Sally | 21.9 | 1.4 | 4.2 | 1.3 | 172.3 (27.66) |
6 | 1992 | 199216 | Polly | 7.6 | 2.6 | 5.7 | 1.2 | 136.7 (21.95) |
7 | 1986 | 198607 | Peggy | 2.1 | 4.4 | 7.8 | 1.8 | 130.4 (20.94) |
8 | 2006 | 200604 | Bilis | 34.8 | 1.3 | 2.0 | 1.1 | 97.6 (15.67) |
9 | 1994 | 199405 | Nameless | 8.5 | 1.8 | 4.4 | 1.4 | 93.2 (14.96) |
10 | 1985 | 198506 | Jeff | 1.2 | 4.7 | 11.3 | 1.3 | 88.4 (14.19) |