A four-parameter model for estimating typhoon motion states based on time difference of PWV arrival

doi:10.11947/j.AGCS.2024.20230473

Abstract

Abstract:

Typhoon is a kind of disastrous weather which seriously affects human production and activities. The effective monitoring of typhoon status is of great significance to avoid and reduce the loss of people's life and property. Water vapor is the main driving force of typhoon development. In this paper, a four-parameter model (TDOPA-4) for estimating typhoon's movement based on the time difference of precipitable water vapor (PWV) arrival (TDOPA) was proposed, which requires PWV time series of several stations near the typhoon's path as inputs. The initial linear velocity, initial direction angle, linear acceleration and angular velocity of the typhoon were estimated, and then the velocity and direction angle of the typhoon at any moment can be further calculated. The typhoon Lekima and Bailu in China in 2019 were selected as cases study for verifying the model. First, the accuracy of ERA5 datasets derived PWV (ERA5-PWV) was tested by using the ground-based global navigations satellite systems derived PWV in China, which was used to estimate the typhoon's movement based on the TDOPA-4 model. Then, the spatial distribution and temporal characteristics of PWV during typhoon's period were analyzed, and the moving trend and relationship between typhoon and water vapor were studied. Finally, the typhoon products provided by the China Meteorological Administration (CMA) and People's Government of Zhejiang Province (PGZP) were as reference, and the velocity and directional angle of Lekima and Bailu estimated from the TDOPA-4 model were evaluated. The results showed that the mean Bias, RMSE and STD were 0.25, 6.39, 6.38 km/h and 4.68°, 21.59° and 20.83° compared to the results from the CMA, respectively. Compared with the results of the PGZP, the mean Bias, RMSE and STD are 2.23, 5.41 and 4.27 km/h, respectively. The above results show that the TDOPA-4 can reflect the water vapor transport of typhoons, and provide a supplementary method for monitoring typhoon activities.

Key words: typhoon monitoring, ERA5, time difference of PWV arrival, GNSS, radiosonde station

CLC Number:

P228

Qimin HE, Kefei ZHANG, Li LI, Dajun LIAN, Wei ZHAO, Guodong CHEN, Erjiang FU, Rui WANG. A four-parameter model for estimating typhoon motion states based on time difference of PWV arrival[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(11): 2125-2137.

Figures/Tables 11

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站点	经度	纬度	高程/m
BJFS	115.89°E	39.61°N	87.5
CHAN	125.44°E	43.79°N	273.2
CKSV	120.22°E	23.00°N	59.7
HKSL	113.93°E	22.37°N	95.3
HKWS	114.34°E	22.43°N	63.8
JFNG	114.49°E	30.52°N	71.3
KMNM	118.39°E	24.46°N	49.1
LHAZ	91.10°E	29.66°N	3 624.6
NCKU	120.22°E	23.00°N	98.3
SHAO	121.20°E	31.10°N	22.0
TWTF	121.16°E	24.95°N	201.5
URUM	87.60°E	43.81°N	858.9
WUH2	114.36°E	30.53°N	28.2
TCMS	120.99°E	24.80°N	77.2

站点	Bias/mm	RMSE/mm	STD/mm	皮尔逊相关系数
BJFS	0.42	2.71	2.68	0.98
CHAN	-0.60	2.50	2.42	0.98
CKSV	0.09	2.92	2.92	0.97
HKSL	0.97	2.53	2.34	0.98
HKWS	0.86	2.45	2.29	0.98
JFNG	1.08	2.96	2.76	0.98
KMNM	0.53	2.77	2.72	0.98
LHAZ	2.24	3.11	2.15	0.96
NCKU	-0.29	2.84	2.83	0.98
SHAO	-0.66	2.44	2.35	0.94
TWTF	1.36	3.07	2.75	0.98
URUM	1.17	2.51	2.23	0.95
WUH2	0.68	3.01	2.93	0.98
TCMS	0.93	3.20	3.06	0.97
平均	0.63	2.79	2.60	0.97

台风	模型	CMA线速度/（km/h）			CMA方向角/（°）			PGZP线速度/（km/h）
台风	模型	Bias	RMSE	STD	Bias	RMSE	STD	Bias	RMSE	STD
利奇马	TDOPA-4	0.43	4.97	4.95	8.78	25.82	24.28	-0.60	3.99	3.95
利奇马	TDOPA	4.62	6.99	5.25	10.68	37.17	35.60	3.63	5.68	4.37
白鹿	TDOPA-4	0.08	7.81	7.81	0.58	17.37	17.38	5.06	6.84	4.60
白鹿	TDOPA	11.09	13.70	8.04	-2.88	32.84	32.97	14.37	15.09	4.62