Annual Review of In Situ Observations of Tropical Cyclone–Ocean Interaction in the Western North Pacific during 2023

He, Hailun; Tian, Ruizhen; Lyu, Xinyan; Ling, Zheng; Sun, Jia; Cao, Anzhou

doi:10.3390/rs16111990

Open AccessReview

Annual Review of In Situ Observations of Tropical Cyclone–Ocean Interaction in the Western North Pacific during 2023

by

Hailun He

^1,2,*

,

Ruizhen Tian

¹,

Xinyan Lyu

³,

Zheng Ling

⁴,

Jia Sun

⁵

and

Anzhou Cao

⁶

¹

State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China

²

Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China

³

National Meteorological Center, China Meteorological Administration, Beijing 100081, China

⁴

Key Laboratory of Climate, Resources and Environment in Continental Shelf Sea and Deep Sea of Department of Education of Guangdong Province, College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China

⁵

First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China

⁶

Ocean College, Zhejiang University, Zhoushan 316021, China

^*

Author to whom correspondence should be addressed.

Remote Sens. 2024, 16(11), 1990; https://doi.org/10.3390/rs16111990

Submission received: 30 April 2024 / Revised: 28 May 2024 / Accepted: 30 May 2024 / Published: 31 May 2024

(This article belongs to the Special Issue Advances in Oceanic Dynamics by SAR and Numeric Model in Tropical Cyclone)

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Abstract

:

We present a review of in situ observations regarding the interactions between tropical cyclones and the ocean in the western North Pacific for the year 2023. A total of at least 13 tropical cyclones occurred during this period. According to the Japan Meteorological Agency, Typhoon Mawar recorded the yearly minimum pressure at 900 hPar. On average, each tropical cyclone captured 7.4 surface drifters and 25.2 Argo floats when the search radius is 300 km. During Guchol, the maximum in situ Lagrangian current reached 1.23 m/s, with sustained wind speeds of the tropical cyclone up to 31.7 m/s and a relative position of 174 km. Additionally, several Argo floats were active during tropical cyclones, with maximum sea surface temperature cooling reaching 0.66 °C. This annual review provides a comprehensive summary of the current state of in situ observations regarding tropical cyclone–ocean interaction. These findings serve as valuable references for both scientific research and operational forecasting.

Keywords:

annual review; tropical cyclone–ocean interaction; western North Pacific; typhoon; sea surface temperature; Argo float

1. Introduction

Tropical cyclone (TC)–ocean interaction provides basic dynamics for extremely short-term variations in the coupled atmosphere–ocean system [1,2,3,4]. TC–ocean interaction underpins the theoretic and numerical frameworks of operational TC forecasting [5]. Therefore, the study of TC–ocean interaction holds significant scientific importance [6] and operational relevance [7].

TC–ocean interaction always emphasizes the positive and negative feedback of the ocean to the TC. Positive feedback occurs through the enhanced air–sea enthalpy flux resulting from stronger wind speeds [8,9], while negative feedback is generated by weaker enthalpy flux due to the reduction in the sea surface temperature (SST) [10,11]. Challenges exist in parameterizing enthalpy flux, both in field measurements [12,13,14] and in numerical models [15,16,17]. Furthermore, numerical ocean models may struggle to accurately capture sea surface changes [18,19].

In situ observations remain limited in severe field environments [20,21]. These observations provide valuable evidence of multiscale ocean dynamics [4,22,23], offer essential initial and boundary conditions for numerical models, and are crucial for research and forecasting of extreme events like TCs [24].

In the western North Pacific, surface drifters and Argo floats play important roles in TC–ocean interaction observation [20,21,25]. During the historically intense TC Haiyan in 2013, the ocean response was monitored through near-daily sampling using Argo floats [26,27]. In situ observations were used for mechanical analysis. The pattern of surface currents under the TC was demonstrated using surface drifters [28]. Surface drifters were also used to validate SST parameterization under TC condition [29]. The surface drifter data reveal the low-frequency trend of tropical cyclone intensity [30].

Actually, annual reviews of tropical cyclone activity in the western North Pacific are routinely conducted [31,32,33]. However, to the best of our knowledge, annual reviews of tropical cyclone–ocean interactions are seldom reported. Here, we present a first attempt at such a review. Our research primarily focuses on observational data. Specifically, in situ surface drifters and Argo floats are main platforms for TC–ocean interaction.

The structure of the present paper is as follows. We introduce the data in Section 2. Section 3 provides a detailed description of the results of the current research, and finally, we present a summary in Section 4.

2. Materials and Method

2.1. Tracks of TCs

The research domain of the present study covers the region from [100°, 180°]E × [0°, 45°]N. The best track data were provided by three affiliations, including the Japan Meteorological Agency (JMA), the Joint Typhoon Warning Center (JTWC), and the China Meteorological Administration (CMA). The best track data are made through a comprehensive analysis based on a multi-platform reconnaissance network. The best track commonly includes the central position, maximum wind speed, minimum pressure, and category of the typhoon at a certain time. Additionally, the JTWC data also provide information on the radius of the maximum winds. The temporal resolutions of JMA and CMA data are usually 6 h. It is also noted that in some cases, JMA and CMA provided data every three hours. JTWC provided data with a higher temporal resolution of 3 h. The JMA dataset includes a total of 13 TCs occurring from April to September. The JTWC and CMA datasets indicate 15 TCs, although 2 of them were relatively weak.

2.2. Surface Drifter Data

Surface drifters are provided by the Global Drifter Program (GDP) at the Atlantic Oceanographic and Meteorological Laboratory. The surface drifter records the position and, therefore, the Lagrangian current. The measurement depth of surface currents is roughly 15 m below the sea surface [21]. The surface drifter also measures the SST. The temporal resolution is typically 6 h. The precision of the SST sensor is roughly ±0.05 °C, and the surface current precision is approximately ±0.01 m/s [28,34,35].

2.3. Argo Float Data

The Argo data were downloaded from the Global Data Assembly Centre (GDAC). The floats are equipped with CTD sensors, allowing for high-resolution measurements of water temperature and salinity within the depth range of 0 to 2000 dbar (roughly 2000 m) or deeper. The temperature is accurate to ±0.005 °C, pressure is accurate to ±2.5 dbar (roughly 2.5 m for depth), and salinity is accurate to nearly ±0.01 psu [36].

3. Results

3.1. Tracks of TCs

Figure 1 shows 13 TC tracks from April to September in the western North Pacific Ocean in 2023. Most TC geneses were located in the western North Pacific, except Dora. The TC geneses of Sanvu and Mawar occurred near the equator, at a latitude of approximately 5°N. The best track of Sanvu was confined to a small region, reflecting its short lifespan in this year. Mawar initially moved mainly northward then changed direction to the northwest and eventually veered northeastward, reaching 34°N. Guchol originated in the subtropical ocean near 13°N and moved slightly northwest before turning northeast. Talim was generated west of the Philippine Islands, then it moved northwestward and landed on mainland China. Doksuri formed in the subtropical ocean near (134°E, 13°N), passed through the Luzon Strait, then proceeded to the Taiwan Strait before finally making landfall on mainland China. Khanun’s genesis location was near (138°E, 11°N). It moved northwestward to the East China Sea then turned eastward towards 132° before heading northward towards the Korean Peninsula. Otherwise, the TC geneses of Lan and Yum-yemy were nearly 20°N. Lan moved mainly northwestward and later turned northeastward. Yum-yemy moved solely northeastward. Saola originated east of the Philippines Islands, crossed the Luzon Strait, and made landfall at a location similar to Talim. Damrey and Haikui both originated at a location close to 18°N. Damrey primarily moved northward, while Haikui moved predominantly westward. Kriogi was generated around (155°E, 10°N), and its track was mainly along a northwest direction.

Table 1 lists the basic information of the best tracks. Typhoon geneses dates are mainly concentrated in July and August. The JTWC, JMA, and CMA have differences in typhoon genesis times, life cycles, and minimum pressures, which may be related to the different reconnaissance systems. Among the 13 TCs in 2023, Mawar had the longest life cycle (14.75/14.25/14.75 days according to JMA/JTWC/CMA) and the lowest pressure (900/897/905 hPa according to JMA/JTWC/CMA). Sanuv had the shortest life cycle according to JMA/JTWC/CMA, about 3.25/2.75/3.50 days, and the second-highest pressure according to JMA (996 hPa) and first highest pressure according to JTWC (999 hPa) and CMA (995 hPa). It is worth noting that Mawar was the strongest TC of the year in the western North Pacific, while the weakest TC was likely Sanvu or Yum-yemy. It is also worth mentioning that JMA, JTWC, and CMA show different life cycles for Doksuri, where JMA and CMA data indicate that it was longer than 10.25 days, but JTWC exhibits 6.75 days. Similarly, a difference with respect to the life cycle was found for Dora. One reason for the differences in life cycles is due to different start and end dates. For instance, in Dora, the genesis date according to CMA was 11 days earlier than that according to JMA. The three affiliations show sharply different genesis dates; this is probably attributed to inconsistent definitions of TC formation.

3.2. Surface Drifters

Figure 2 depicts the trajectories of surface drifters captured by TCs. The number of surface drifters recorded during Sanvu, Talim, Doksuri, Saola, and Yum-yemg was limited, with fewer than 5 drifters. The number of surface drifters did still not sharply improve for Khanun and Haikui. In contrast, during Mawar, Guchol, Lan, and Dora, each TC captured approximately 10 drifters. The observations from these surface drifters are believed to be beneficial for understanding the spatial distribution of ocean parameters. For Damrey and Kriogi, around 17 surface drifters were utilized within a 300 km search radius. The drifters were observed on both the left and right sides of the TC tracks. This indicates that SST and surface current measurements were likely relatively well-described during Damrey and Kriogi. Overall, there were 7.4 surface drifters per TC, regardless of the TC’s intensity or lifetime.

Table 2 shows the drift data of drifters within 300 km of 13 typhoons in the western North Pacific Ocean in 2023 (see also Table A1). Following the formation of the typhoons, most drifters recorded a decrease in SST, with a cooling range of 0° to −1.70 °C. The highest temperature drop was −1.70 °C for drifter 60428510 (42 km to the right of TC Damrey). Some drifters, however, experienced an increase in SST, ranging from 0 ° to 0.67 °C. The highest temperature increase was found in drifter 61656610, which was −293 km away from Typhoon Damrey, and the SST increased by 0.67 °C. Additionally, the maximum wind speed was notably high when the SST experienced a significant decrease. For example, during Typhoon Mawar and in proximity to drifter 61399350, located −58 km from the typhoon center, the SST decreased by 0.60 °C, and the surface current was 0.88 m/s. Conversely, SST warming often coincided with weaker wind speeds. For instance, drifter 62363790 during Typhoon Mawar, positioned −259 km from the typhoon center, recorded an SST increase of 0.14 °C, with a corresponding maximum sustained wind speed of 11.6 m/s. The maximum current speed was 1.23 m/s. The relevant TC was Guchol, and the drifter was 66813190. The drifter was located 174 km to the right of the TC. Accordingly, the maximum sustained wind speed of the TC was 31.7 m/s.

3.3. Argo Profiling

Figure 3 shows the trajectories of Argo floats positioned near the best tracks of TCs. The number of captured Argo floats is not small. For Sanvu, although its influential domain was relatively small, there were nearly 10 Argo floats within a 300 km search radius. For Mawar, a significant number of Argo floats were detected within the 300 km range. Initially, there were nearly 10 Argo floats present, and as the TC moved towards approximately 30°N, the number of Argo floats increased. The number of Argo floats under Guchol reached 61. Most floats were distributed north of 20°N. There were minimal Argo floats associated with TC Talim (the number is 0). For Doksuri, its track was northwestward, and Argo floats are only located in the relatively low latitude band ([10°–20°]N). The number of Argo floats under Khanun was 28, as its track mainly remained in the ocean during its lifetime. For Lan, which followed a relatively high latitude path above 20°N, there were a considerable number of Argo floats present. For TCs located near the central Pacific, such as Dora and Kirogi, there were a substantial number of Argo floats. The number of Argo floats under Saola and Haikui was relatively insufficient (smaller than 9). A considerable number of Argo floats was captured by Damrey (the number is 44). Meanwhile, there were about 22 Argo floats available for Yum-yemg. On average, 25.2 Argo floats were captured per TC.

Table 3 presents Argo data for 13 TCs in the western North Pacific during 2023 (also refer to Table A2) with a search radius of 300 km. Upon the typhoon’s arrival, most Argo floats registered a decrease in SSTs ranging from −0.66° to 0 °C. Substantial cooling was recorded by float 5906387, positioned −58 km from Typhoon Mawar, with a temperature decrease of −0.66 °C. A few Argo floats exhibited an increase in SSTs within the range of 0° to 0.56 °C. The most significant temperature rise occurred in Typhoon Mawar (float 2903689), presenting a 0.56 °C increase. Additionally, the data indicate deepening of the mixed layer depth (MLD) (Table 3). The definition of MLD follows Oginni et al. [27].

In order to study the ocean stratification changes caused by TCs, we further analyzed the observation data of an Argo float (float 5906387) using Typhoon Guchol as an example. Float 5906387 was located 121 km to the right of the typhoon center (2023-06-06 21:00:00). Figure 4 shows the vertical distributions of temperature and salinity from 1 June to 16 June. The upper ocean temperature showed significant cooling during the passage of the typhoon, decreasing by 0.8 °C from 29.45 °C on 3 June (before the arrival of the typhoon) to 28.65 °C when the typhoon arrived on 7 June. Sea surface salinity (SSS) began to decrease during the passage of the typhoon: from 34.43 psu on June 4 (before the arrival of the typhoon) to 33.07 psu after the typhoon’s passage (10 June), decreasing by 1.36 psu.

4. Summary

We conducted an overview of TCs in the western North Pacific in 2023, focusing on two in situ oceanic measurement methods for studying TC–ocean interactions: surface drifters and Argo floats. The maximum SST cooling induced by a TC was −1.70 °C at the forcing stage. Accordingly, the maximum surface current was 1.23 m/s. The maximum number of Argo floats captured by a TC was 61. The TC was Typhoon Guchol. During Guchol, the SST dropped 0.66 °C as measured by the Argo floats in the typhoon forcing stage, corresponding to the MLD becoming deeper by 10.3 m.

The present findings illustrate the current state of in situ observations in TC–ocean interaction studies. Therefore, the observational information is far to satisfy TC studies as well as for operational forecasting. In comparison to previous studies, the observational capability has remained largely unchanged for at least a decade. Therefore, we urge increased observational efforts utilizing unmanned platforms.

The geographic distributions of surface drifters and Argo floats are uneven; this is partially attributed to flow-driven factors. South of Japan, for instance, the higher concentration of drifters and floats may be linked to the Kuroshio circulation. In the future, there is a pressing need to enhance observations in areas that are less conducive to circulation in order to ensure a more comprehensive understanding of TC–ocean interactions.

By combining surface drifters and Argo floats, we recommend focusing on studying TCs Guchol and Damrey, as these two cases have a considerable number of drifters and floats deployed. It is possible to obtain a suitable snapshot of the SST at a specific moment during these two cases. During TC conditions, microwave remote sensing of SSTs proves to be more effective than visible remote sensing. The microwave SST product could potentially provide valuable supplementary information on regional SSTs. Exploring the integration of in situ and microwave SST data for more reliable SST snapshots and tracking the evolution of SSTs is a promising area for future research.

Author Contributions

Conceptualization, H.H.; methodology, H.H.; software, H.H.; validation, H.H. and R.T.; formal analysis, H.H. and R.T.; investigation, H.H. and R.T.; resources, H.H.; data curation, H.H. and R.T.; writing—original draft preparation, H.H. and R.T.; writing—review and editing, H.H., R.T., X.L., Z.L., J.S. and A.C.; visualization, H.H. and R.T.; supervision, H.H.; project administration, H.H.; funding acquisition, H.H. and X.L.; All authors have read and agreed to the published version of the manuscript.

Funding

This study is supported by the National Natural Science Foundation of China (grant NOs. 42227901 and 42175016) and the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (grant No. SL2020MS030).

Data Availability Statement

JMA best track data were downloaded from https://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html (accessed on 16 May 2024). JTWC best track data were downloaded from the National Oceanic and Atmospheric Administration’s International Best Paths for Climate Management Archive (IBTrACS; https://www.ncei.noaa.gov/products/international-best-track-archive; accessed on 19 November 2023). CMA best track data were downloaded from https://tcdata.typhoon.org.cn/en/zjljsjj.html (accessed on 18 May 2024) Surface drifter data were downloaded from ftp.aoml.noaa.gov (accessed on 2 March 2024). Argo float data were downloaded from https://argo.ucsd.edu/ (accessed on 28 April 2024).

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Surface drifters captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinate, while

V_{m a x}

denotes the maximum sustained wind speed of the TC. ΔSST indicates the SST difference at

t_{0}

compared to 1 day prior, and

U_{m a x}

is the surface current speed at

t_{0}

. The search radius is 300 km.

Table A1. Surface drifters captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinate, while

V_{m a x}

denotes the maximum sustained wind speed of the TC. ΔSST indicates the SST difference at

t_{0}

compared to 1 day prior, and

U_{m a x}

is the surface current speed at

t_{0}

. The search radius is 300 km.

Name	Drifter ID	$t_{0}$	$x_{0}$	$V_{\max}$	ΔSST	$U_{\max}$
		(YYYY-MM-DD HH)	(km)	(m/s)	(°C)	(m/s)
Sanvu	61399350	2023-04-22 06	—	—	0.06	0.19
Mawar	61394350	2023-05-31 08	−36	33.4	−0.24	0.39
	61399350	2023-05-23 19	−58	53.2	−0.60	0.88
	60428510	2023-06-02 08	−94	23.1	0.62	0.38
	61658910	2023-06-03 04	154	0.0	0.09	0.43
	60523120	2023-06-03 12	—	—	−0.01	0.02
	61286260	2023-06-01 10	−185	25.7	−0.03	0.26
	62363790	2023-06-02 21	−259	11.6	0.14	0.27
	63010310	2023-06-03 12	—	—	−0.59	0.25
	62364660	2023-06-01 20	278	25.7	−0.39	0.44
Guchol	60520160	2023-06-11 06	11	30.9	−0.94	0.61
	62364800	2023-06-11 10	31	29.2	−1.49	0.65
	62365390	2023-06-11 05	−53	31.3	−1.04	0.36
	61654920	2023-06-10 23	−103	33.9	−0.52	0.09
	61658910	2023-06-12 16	105	0.0	−0.47	1.10
	62129360	2023-06-06 00	—	—	0.14	0.07
	66813190	2023-06-11 04	174	31.7	−0.64	1.23
	63010310	2023-06-13 13	−178	0.0	−0.15	0.40
	62364660	2023-06-10 23	−179	33.9	−0.63	0.41
	60523120	2023-06-13 05	207	0.0	−0.52	0.50
	61081580	2023-06-13 10	281	0.0	−0.64	0.34
	61703450	2023-06-07 13	−286	23.6	−0.17	0.16
Talim	64640950	2023-07-16 06	−240	25.7	−0.53	0.68
	64134530	2023-07-16 05	−249	25.7	−0.49	0.63
Doksuri	61399350	2023-07-20 09	1	0.0	0.08	0.19
Khanun	67177170	2023-07-29 22	−42	31.7	−0.64	0.57
	62364660	2023-07-30 20	−150	41.2	−0.17	0.61
	61652570	2023-07-30 02	−165	34.3	−0.19	0.83
	61399350	2023-07-28 15	−226	19.3	−0.28	0.36
	62365390	2023-07-31 06	246	43.7	−0.59	0.59
Lan	61656610	2023-08-07 04	−11	0.0	−0.40	0.38
	62364410	2023-08-13 04	−50	38.6	−0.73	0.56
	61658910	2023-08-13 00	98	38.6	−0.48	1.09
	60753060	2023-08-16 23	−108	20.6	−0.33	0.39
	61654920	2023-08-13 11	−160	38.6	−0.25	0.59
	62364580	2023-08-16 19	180	20.6	0.36	0.31
	64305520	2023-08-10 00	−205	33.4	−0.22	0.08
	64305480	2023-08-09 12	−236	28.3	−0.10	0.24
	64304890	2023-08-09 16	−282	30.0	−0.04	0.07
	62364800	2023-08-10 18	−288	46.3	−0.07	0.24
Dora	61656750	2023-08-20 07	−23	0.0	−0.11	0.38
	61394270	2023-08-17 15	−33	0.0	−0.20	0.13
	67543320	2023-08-21 21	52	0.0	−0.56	0.19
	61289590	2023-08-15 14	115	0.0	−0.34	0.42
	61381210	2023-08-21 07	149	0.0	−0.22	0.23
	61084090	2023-08-20 18	175	0.0	−0.22	0.19
	60842100	2023-08-12 18	212	38.6	0.02	0.11
	60716640	2023-08-20 18	215	0.0	−0.20	0.30
	60250900	2023-08-15 18	−221	0.0	−0.04	0.38
	61657770	2023-08-19 16	−227	0.0	0.12	0.94
Saola	61652570	2023-08-23 15	−52	0.0	−0.04	0.25
	64649970	2023-08-26 17	−84	48.4	−0.09	0.42
	64640950	2023-08-30 05	−245	54.0	−0.27	0.10
	64134530	2023-08-30 10	−257	54.0	−0.41	0.20
Damrey	67178190	2023-08-26 02	4	24.0	−0.51	0.24
	60428510	2023-08-29 04	42	7.7	−1.70	0.54
	63010400	2023-08-29 05	−62	3.9	−0.52	0.37
	63010310	2023-08-29 18	73	0.0	−0.05	0.46
	61287440	2023-08-24 23	75	18.0	−0.26	0.82
	67541910	2023-08-26 22	101	25.7	−0.78	0.94
	61089090	2023-08-30 05	117	0.0	0.10	0.49
	62159490	2023-08-29 20	−147	0.0	−0.43	0.29
	61081580	2023-08-27 01	−168	25.7	−0.31	0.13
	62027550	2023-08-29 21	−173	0.0	−0.04	0.15
	63011370	2023-08-28 00	−176	23.1	−0.38	0.24
	61383120	2023-08-28 16	215	25.7	−1.14	0.32
	60522170	2023-08-27 01	−221	25.7	−0.26	0.34
	61658860	2023-08-24 21	−231	18.0	−0.00	0.36
	62425200	2023-08-29 15	−240	0.0	−0.08	0.08
	61286150	2023-08-25 15	−245	20.6	−0.07	0.22
	60523100	2023-08-29 18	286	0.0	−0.00	0.42
	67876470	2023-08-25 13	288	20.6	−0.27	0.18
	61656610	2023-08-26 12	−293	25.7	0.67	0.11
Haikui	67177170	2023-08-29 11	−21	23.1	−0.96	0.63
	64304490	2023-08-28 07	−67	0.0	−0.22	0.07
	64304900	2023-08-28 01	−219	0.0	−0.04	0.31
	61652570	2023-09-02 04	−233	37.7	−0.20	0.30
	60092970	2023-08-27 06	—	—	−0.05	0.24
	60520160	2023-09-01 01	291	30.9	−0.63	0.24
Kriogi	61286150	2023-09-01 05	−9	21.0	−0.07	0.71
	62364410	2023-09-03 12	15	0.0	−0.39	0.18
	66710990	2023-09-01 13	18	20.6	−0.18	0.83
	61656610	2023-09-02 03	42	18.0	−0.75	1.04
	60253330	2023-09-01 10	66	20.6	−0.20	0.44
	66813190	2023-09-05 12	86	0.0	−0.16	0.94
	61287440	2023-08-31 19	99	23.1	−0.22	0.93
	61658860	2023-08-31 22	−113	23.1	0.02	0.16
	10826560	2023-08-30 02	119	0.0	−0.13	0.24
	64305520	2023-09-01 16	−197	20.6	−0.00	0.21
	61658910	2023-09-03 19	215	0.0	−0.30	0.56
	64305480	2023-09-01 13	−222	20.6	−0.05	0.20
	60522170	2023-09-02 12	246	18.0	−0.20	0.26
	61081580	2023-09-02 14	248	18.0	−0.01	0.14
	64305500	2023-09-01 18	−292	20.6	−0.01	0.38
Yum-yemg	61658910	2023-09-08 14	131	0.0	−0.31	0.89
	62364410	2023-09-07 06	284	20.6	0.01	0.17

Table A2. Argo floats captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinate, while

V_{m a x}

denotes the maximum sustained wind speed of the TC. ΔSST and ΔMLD indicate the SST and MLD differences, respectively, at

t_{0}

compared to 1 day prior. The search radius is 300 km.

Table A2. Argo floats captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinate, while

V_{m a x}

denotes the maximum sustained wind speed of the TC. ΔSST and ΔMLD indicate the SST and MLD differences, respectively, at

t_{0}

compared to 1 day prior. The search radius is 300 km.

Name	Float ID	$t_{0}$	$x_{0}$	$V_{\max}$	ΔSST	ΔMLD
		(YYYY-MM-DD HH)	(km)	(m/s)	(°C)	(m/s)
Sanvu	5906718	2023-04-19 10	45	0.0	0.03	—
	2902806	2023-04-21 14	−80	19.7	−0.01	—
	2902815	2023-04-19 06	−133	0.0	−0.00	0.0
	2902803	2023-04-21 21	−163	9.0	−0.00	0.0
	5905867	2023-04-21 12	162	20.6	0.01	0.0
	5906720	2023-04-22 00	−191	0.0	−0.01	0.0
	5906722	2023-04-20 06	210	0.0	−0.02	—
	5904717	2023-04-22 03	219	0.0	0.00	—
	2902801	2023-04-19 18	−248	0.0	−0.02	—
	2902807	2023-04-19 00	—	0.0	0.04	0.0
Mawar	2902740	2023-05-24 06	7	48.9	−0.08	—
	2902757	2023-05-27 17	−10	43.7	−0.59	0.0
	5905864	2023-05-27 00	−14	54.0	−0.19	—
	2903717	2023-06-02 13	−21	23.1	0.05	—
	2902818	2023-05-27 23	−19	43.7	−0.41	0.0
	2903687	2023-06-02 03	−31	23.1	0.17	—
	5906968	2023-05-28 00	−38	43.7	−0.30	0.0
	2903674	2023-06-02 08	−47	23.1	0.02	—
	5906387	2023-05-26 15	−58	59.2	−0.66	10.3
	2903706	2023-06-02 08	69	23.1	0.09	—
	5902515	2023-05-23 11	−71	54.0	−0.09	—
	3902470	2023-05-27 16	−73	43.7	−0.23	0.0
	4901648	2023-06-02 22	72	7.7	0.10	0.0
	2903684	2023-06-03 10	−83	0.0	0.07	—
	2903709	2023-06-02 14	87	23.1	−0.32	0.0
	2903705	2023-06-02 01	92	23.1	−0.11	—
	2903716	2023-06-03 01	95	0.0	0.16	0.0
	2903712	2023-06-02 17	−107	23.1	—	—
	2902811	2023-05-21 18	−117	33.4	−0.07	—
	2903714	2023-06-03 12	—	0.0	0.04	0.0
	7901012	2023-05-27 11	143	44.6	−0.15	—
	2902754	2023-06-03 07	149	0.0	—	—
	3902012	2023-05-25 21	159	59.2	—	—
	5906392	2023-05-27 05	161	49.7	−0.41	0.0
	5905844	2023-05-27 12	165	43.7	−0.25	0.0
	2903708	2023-05-27 05	170	49.7	−0.50	—
	2903694	2023-05-31 17	−184	31.7	−0.30	—
	2903707	2023-06-02 09	184	23.1	0.22	—
	2902812	2023-05-21 21	−186	33.4	−0.08	0.0
	5906522	2023-06-03 00	196	0.0	0.05	0.0
	5906724	2023-05-23 00	188	48.9	−0.01	0.0
	2902817	2023-05-22 11	−199	38.2	−0.09	0.0
	2902816	2023-05-22 19	207	48.9	−0.01	0.0
	2903710	2023-06-02 13	207	23.1	0.23	—
	2902885	2023-06-03 12	—	0.0	—	—
	2903719	2023-06-02 23	229	3.9	−0.05	—
	3901304	2023-05-22 06	232	36.0	−0.02	0.0
	5906717	2023-05-20 06	−225	0.0	−0.02	0.0
	2903724	2023-06-02 11	238	23.1	—	—
	2903711	2023-06-03 09	240	0.0	0.11	0.0
	5906391	2023-05-28 00	−244	43.7	−0.12	—
	2903704	2023-06-03 03	−251	0.0	0.02	—
	2903647	2023-06-01 20	−256	25.7	0.13	—
	2903689	2023-06-03 12	—	0.0	0.56	—
	2903690	2023-06-02 14	262	23.1	−0.09	—
	2903653	2023-06-02 20	−265	15.4	−0.00	—
	2903657	2023-06-03 12	—	0.0	0.04	0.0
	2903718	2023-06-03 12	—	0.0	0.22	0.0
	5906385	2023-06-02 21	−283	11.6	0.17	—
	2901805	2023-05-27 12	−290	43.7	−0.02	0.0
	2903731	2023-06-03 12	—	0.0	0.38	0.0
Guchol	2903716	2023-06-12 12	−12	0.0	−0.15	0.0
	2903725	2023-06-13 14	12	0.0	—	—
	2903675	2023-06-10 15	−30	37.3	−0.09	—
	2903005	2023-06-13 18	24	0.0	0.17	—
	2903689	2023-06-13 12	−46	0.0	−0.00	—
	2903713	2023-06-11 12	−53	28.3	−0.05	—
	2903719	2023-06-12 04	54	26.6	−0.29	—
	2903649	2023-06-11 23	52	28.3	0.02	0.0
	5906522	2023-06-12 06	56	25.7	−0.09	0.0
	2903684	2023-06-12 22	−53	0.0	−0.07	—
	2903718	2023-06-13 15	−57	0.0	−0.09	0.0
	2903680	2023-06-14 10	76	0.0	0.01	—
	2902754	2023-06-12 18	76	0.0	—	—
	2902878	2023-06-14 03	−79	0.0	—	—
	4901648	2023-06-12 05	−82	26.2	0.03	0.0
	3902470	2023-06-08 18	−86	38.6	−0.05	0.0
	2902818	2023-06-09 08	−89	38.6	−0.03	—
	2902881	2023-06-10 18	−94	36.0	0.10	—
	2903714	2023-06-13 08	−93	0.0	0.13	—
	5905844	2023-06-09 04	98	38.6	−0.17	—
	7901012	2023-06-09 02	100	38.6	0.06	0.0
	2903721	2023-06-10 23	−99	33.9	−0.04	0.0
	2903731	2023-06-13 10	−100	0.0	0.04	0.0
	2903679	2023-06-14 07	109	0.0	−0.06	0.0
	5906387	2023-06-06 21	121	19.3	−0.15	18.9
	2903657	2023-06-13 06	121	0.0	0.13	—
	5906393	2023-06-11 08	−127	30.0	−0.47	9.6
	5906510	2023-06-11 15	−133	28.3	−0.10	—
	2903685	2023-06-15 03	−138	0.0	−0.14	0.0
	2903708	2023-06-09 00	140	38.6	−0.33	0.0
	2903692	2023-06-14 03	141	0.0	−0.13	0.0
	2903422	2023-06-13 16	−142	0.0	0.08	0.0
	2903690	2023-06-11 17	−144	28.3	−0.26	0.0
	5906392	2023-06-09 00	147	38.6	−0.62	−3.6
	5905864	2023-06-07 07	158	21.0	0.12	—
	2902535	2023-06-14 08	165	0.0	0.02	0.0
	2903695	2023-06-11 00	−168	33.4	−0.10	0.0
	5906968	2023-06-09 04	−169	38.6	0.04	0.0
	2903360	2023-06-12 07	180	21.4	−0.12	—
	2903211	2023-06-14 08	−184	0.0	−0.09	0.0
	2903346	2023-06-12 00	184	28.3	—	—
	2903699	2023-06-13 12	183	0.0	−0.08	0.0
	2903399	2023-06-13 12	−188	0.0	0.03	—
	2903678	2023-06-13 13	−189	0.0	0.14	0.0
	2903693	2023-06-14 02	190	0.0	0.04	—
	2903711	2023-06-12 21	190	0.0	−0.24	0.0
	2901805	2023-06-08 06	−193	30.9	—	—
	2903703	2023-06-14 04	−197	0.0	0.09	—
	2903710	2023-06-11 19	−198	28.3	0.04	—
	2903403	2023-06-14 23	197	0.0	0.05	—
	2903712	2023-06-12 06	−199	25.7	—	—
	5905733	2023-06-06 00	—	0.0	−0.04	—
	2903724	2023-06-11 14	−226	28.3	—	—
	2902885	2023-06-13 03	257	0.0	—	—
	2903707	2023-06-11 12	−259	28.3	0.08	—
	2903610	2023-06-15 18	−263	0.0	0.08	—
	2903688	2023-06-11 18	278	28.3	0.21	0.0
	2903720	2023-06-11 21	287	28.3	−0.26	—
	2903358	2023-06-13 14	293	0.0	0.09	—
	2903722	2023-06-12 14	−298	0.0	—	—
	2903723	2023-06-13 14	296	0.0	0.00	0.0
Doksuri	2901805	2023-07-22 19	13	26.2	—	—
	5902519	2023-07-23 22	−119	37.7	−0.08	—
	3902470	2023-07-23 04	160	30.0	−0.08	0.0
	5902518	2023-07-20 06	—	0.0	−0.04	0.0
	5906968	2023-07-22 21	197	27.0	−0.04	—
	5906391	2023-07-24 09	211	45.0	−0.56	13.6
	5906392	2023-07-22 22	246	27.4	−0.41	7.0
	5905733	2023-07-20 06	—	0.0	−0.08	—
Khanun	2902818	2023-07-29 16	0	27.4	−0.05	0.0
	2903695	2023-08-01 02	−1	48.9	−0.30	—
	2903647	2023-08-09 09	−5	25.7	−0.12	0.0
	2903687	2023-08-07 21	−12	23.1	0.14	—
	2903690	2023-08-06 15	24	25.7	−0.09	—
	5906510	2023-08-06 15	32	25.7	−0.06	0.0
	5905883	2023-07-28 05	43	18.0	−0.03	0.0
	5905872	2023-07-27 02	−57	0.0	−0.05	—
	2903721	2023-07-31 20	−60	46.3	−0.26	0.0
	2903710	2023-07-31 18	102	46.3	−0.62	—
	2903706	2023-08-07 00	101	25.7	−0.11	—
	2903705	2023-08-01 06	−116	48.9	−0.26	—
	5906384	2023-07-27 06	−143	0.0	−0.08	0.0
	2902802	2023-07-26 18	—	0.0	−0.05	0.0
	2903649	2023-08-06 21	152	25.7	0.05	0.0
	5905864	2023-07-29 12	157	25.7	−0.05	—
	2902881	2023-07-31 09	−164	43.7	−0.08	0.0
	5905733	2023-07-27 12	−172	0.0	−0.08	—
	2903694	2023-08-03 12	92	36.0	−0.25	0.0
	2903709	2023-08-06 15	184	25.7	−0.20	0.0
	6990599	2023-08-10 02	188	15.4	—	—
	4903764	2023-08-10 01	193	19.3	0.04	—
	3902012	2023-07-28 12	256	18.0	—	—
	5906387	2023-07-29 11	264	25.3	−0.16	11.1
	2903707	2023-08-08 03	277	23.1	0.03	0.0
	4903636	2023-08-10 03	280	11.6	−0.08	—
	3902565	2023-08-04 21	−254	28.3	−0.01	—
	4903637	2023-08-10 02	297	15.4	0.48	—
Lan	2903734	2023-08-14 19	24	30.9	—	—
	2903728	2023-08-14 09	25	33.4	—	—
	5905880	2023-08-09 10	−27	27.4	−0.18	0.0
	2901801	2023-08-16 09	43	20.6	−0.12	—
	5906522	2023-08-13 06	−72	38.6	0.02	0.0
	5905847	2023-08-09 23	−83	33.0	−0.11	—
	2902882	2023-08-08 03	84	19.3	—	—
	3902014	2023-08-07 04	86	0.0	—	—
	4901648	2023-08-14 08	87	33.4	−0.05	0.0
	2903704	2023-08-13 22	−117	36.0	−0.20	—
	2903716	2023-08-12 13	120	40.7	−0.50	0.0
	2901804	2023-08-16 23	121	20.6	−0.02	—
	2903733	2023-08-14 09	122	33.4	—	—
	2901792	2023-08-16 05	122	20.6	−0.05	—
	2903719	2023-08-13 18	145	36.0	−0.35	0.0
	5904979	2023-08-18 12	—	0.0	−0.15	0.0
	5904978	2023-08-18 12	—	0.0	−0.08	—
	2903712	2023-08-12 10	183	42.0	—	—
	5906513	2023-08-12 13	−205	40.7	−0.01	0.0
	2903724	2023-08-14 06	−210	33.4	—	—
	4902088	2023-08-18 12	—	0.0	−0.08	—
	2903425	2023-08-11 09	227	46.3	—	—
	4903637	2023-08-15 12	−239	23.1	0.14	0.0
	5906762	2023-08-07 18	212	0.0	—	—
	2903711	2023-08-12 00	242	43.7	−0.30	0.0
	2903360	2023-08-12 18	−243	38.6	−0.04	0.0
	2903402	2023-08-18 12	—	0.0	0.29	0.0
	2901806	2023-08-15 18	−260	20.6	0.24	—
	5906393	2023-08-14 03	−279	36.0	−0.13	1.1
	2903707	2023-08-14 18	−255	30.9	−0.22	0.0
	4903636	2023-08-15 14	−292	22.3	0.09	0.0
Dora	5906512	2023-08-16 20	−11	0.0	0.06	0.0
	5905794	2023-08-13 08	30	31.7	−0.00	—
	5906506	2023-08-21 02	42	0.0	0.03	—
	5902509	2023-08-14 01	48	23.1	−0.09	—
	5904934	2023-08-14 14	55	21.4	−0.02	—
	4903292	2023-08-13 13	−64	27.9	0.04	0.0
	5906104	2023-08-14 04	−67	23.1	−0.00	—
	5906761	2023-08-16 10	78	0.0	0.02	—
	2903702	2023-08-21 12	−79	0.0	0.04	0.0
	5906358	2023-08-13 05	−84	33.9	0.01	0.0
	2903659	2023-08-21 09	102	0.0	−0.06	0.0
	2903664	2023-08-15 23	−131	0.0	0.07	—
	5905231	2023-08-16 05	130	0.0	0.01	—
	5905874	2023-08-18 22	135	0.0	0.00	0.0
	2903617	2023-08-18 06	−140	0.0	0.10	—
	5906588	2023-08-13 05	−184	33.9	0.03	0.0
	2903730	2023-08-17 04	190	0.0	−0.01	0.0
	5905792	2023-08-13 07	197	32.6	−0.04	—
	4902987	2023-08-21 03	202	0.0	−0.02	—
	5906802	2023-08-17 19	−214	0.0	0.09	0.0
	2903351	2023-08-21 08	221	0.0	—	—
	5906390	2023-08-16 04	−246	0.0	—	—
	2903428	2023-08-16 13	261	0.0	0.07	—
	5905861	2023-08-13 16	277	26.6	0.01	—
Saola	2903708	2023-08-22 11	−39	0.0	−0.11	0.0
	5906391	2023-08-23 00	−97	0.0	−0.40	−1.1
	7901012	2023-08-22 00	—	0.0	0.05	0.0
	5905844	2023-08-22 00	—	0.0	0.02	0.0
	5906392	2023-08-22 00	—	0.0	−0.10	−5.3
	2903705	2023-08-24 06	259	18.0	−0.01	0.0
	3902470	2023-08-22 00	—	0.0	0.02	0.0
Damrey	5906763	2023-08-24 20	−1	18.0	—	—
	2903691	2023-08-27 02	−2	25.7	−0.03	—
	2903697	2023-08-27 02	−15	25.7	−0.08	0.0
	2903005	2023-08-28 15	27	25.7	−0.36	—
	2903722	2023-08-27 06	33	25.7	—	—
	2903698	2023-08-29 02	−38	15.4	−0.18	—
	2902887	2023-08-26 21	−41	25.7	—	—
	2903610	2023-08-30 00	37	0.0	−0.07	—
	4903498	2023-08-29 04	−38	7.7	−0.14	—
	5905873	2023-08-29 20	17	0.0	0.03	0.0
	2903685	2023-08-29 20	−21	0.0	0.05	0.0
	2902886	2023-08-28 18	52	25.7	—	—
	2903737	2023-08-28 00	−50	23.1	—	—
	4903291	2023-08-30 00	41	0.0	−0.02	0.0
	2903678	2023-08-27 09	56	25.7	−0.44	0.0
	2903703	2023-08-29 12	−69	0.0	−0.26	—
	2903726	2023-08-29 03	84	11.6	—	—
	2903424	2023-08-26 21	−100	25.7	—	—
	3902013	2023-08-24 11	−102	0.0	—	—
	2903727	2023-08-27 19	−107	23.1	—	—
	2903612	2023-08-26 19	−122	25.7	0.00	—
	2902878	2023-08-29 04	143	7.7	—	—
	2902754	2023-08-27 06	−149	25.7	—	—
	2903349	2023-08-27 12	−157	25.7	−0.00	0.0
	5906386	2023-08-24 17	162	15.0	−0.06	—
	2903422	2023-08-28 03	165	23.1	−0.04	0.0
	2903427	2023-08-26 15	−173	25.7	—	—
	2903676	2023-08-26 18	−175	25.7	−0.06	—
	2903211	2023-08-29 11	176	0.0	−0.04	0.0
	5906515	2023-08-26 10	178	25.7	0.04	—
	5906818	2023-08-23 20	−196	0.0	−0.07	0.0
	5906190	2023-08-29 17	−210	0.0	0.03	0.0
	2903605	2023-08-30 05	214	0.0	−0.05	—
	5906762	2023-08-26 00	−216	23.1	—	—
	2903397	2023-08-26 23	−221	25.7	−0.04	0.0
	5906518	2023-08-26 18	222	25.7	0.03	0.0
	5906503	2023-08-25 03	−225	19.3	−0.03	0.0
	2903692	2023-08-29 05	234	3.9	−0.21	—
	5904056	2023-08-29 23	235	0.0	−0.04	0.0
	2903689	2023-08-28 19	243	25.3	−0.56	—
	2903736	2023-08-28 08	259	24.0	—	—
	2902885	2023-08-27 02	−272	25.7	—	—
	2903684	2023-08-27 10	−275	25.7	0.03	—
	2903403	2023-08-29 20	290	0.0	0.01	—
Haikui	2902881	2023-08-31 20	21	29.2	−0.07	0.0
	2903705	2023-09-02 03	−64	37.3	−0.29	—
	5906519	2023-08-30 12	164	23.1	−0.09	0.0
	5906594	2023-08-30 12	149	23.1	−0.19	−0.1
	2902818	2023-08-29 12	−201	23.1	−0.18	0.0
	5906387	2023-08-29 04	−222	22.3	−0.42	8.2
	2903721	2023-09-01 03	228	30.9	−0.21	—
	2903688	2023-08-30 10	245	23.1	−0.18	0.0
Kriogi	5906763	2023-08-31 13	14	23.1	—	—
	5906386	2023-08-31 06	10	23.1	0.00	—
	3902014	2023-09-01 09	−19	20.6	—	—
	2903704	2023-09-03 19	31	0.0	−0.04	0.0
	2903716	2023-09-03 03	−34	0.0	—	—
	2903734	2023-09-04 06	35	0.0	—	—
	5904717	2023-08-29 20	−38	0.0	0.02	—
	2903728	2023-09-04 03	40	0.0	—	—
	2903425	2023-09-02 10	44	18.0	—	—
	2903738	2023-09-04 05	45	0.0	—	—
	5906503	2023-08-31 22	81	23.1	0.01	0.0
	5906522	2023-09-03 15	−82	0.0	−0.06	0.0
	3902013	2023-08-31 18	−90	23.1	—	—
	2903712	2023-09-03 08	100	0.0	—	—
	2902882	2023-09-01 20	103	19.7	—	—
	2903707	2023-09-03 17	−117	0.0	0.00	0.0
	2903711	2023-09-02 19	119	15.0	−0.20	—
	5905867	2023-08-30 06	132	0.0	−0.09	—
	2903687	2023-09-05 06	149	0.0	—	—
	5906393	2023-09-04 09	−156	0.0	−0.23	−7.9
	2903719	2023-09-03 19	162	0.0	−0.06	—
	2903397	2023-09-02 12	184	18.0	−0.02	0.0
	5905880	2023-09-02 02	−188	18.0	0.03	0.0
	5906762	2023-09-01 06	196	20.6	—	—
	2903724	2023-09-03 18	−194	0.0	—	—
	4901648	2023-09-04 00	198	0.0	−0.07	0.0
	2903676	2023-09-02 07	228	18.0	0.10	—
	2903427	2023-09-02 03	230	18.0	—	—
	5906818	2023-08-31 20	−238	23.1	−0.04	—
	2902885	2023-09-02 17	240	18.0	—	—
	2903717	2023-09-05 09	250	0.0	—	—
	2903739	2023-09-04 04	−260	0.0	—	—
	2903612	2023-09-02 08	284	18.0	−0.02	—
	5906590	2023-08-30 12	−288	18.0	−0.01	—
Yum-yemg	2903739	2023-09-06 22	−16	20.6	—	—
	4901648	2023-09-08 12	−34	0.0	0.08	—
	2903710	2023-09-06 00	−35	18.0	—	—
	2903728	2023-09-07 14	−60	20.6	—	—
	2903724	2023-09-07 01	61	20.6	—	—
	2903704	2023-09-08 06	64	18.0	—	0.0
	2903738	2023-09-07 14	−85	20.6	—	—
	5906393	2023-09-07 01	−96	20.6	−0.03	9.4
	2903734	2023-09-07 14	−100	20.6	—	—
	2902881	2023-09-04 23	−107	0.0	0.05	0.0
	2903713	2023-09-06 00	−128	18.0	—	0.0
	2903719	2023-09-08 09	131	9.0	—	0.0
	2903707	2023-09-07 04	140	20.6	—	0.0
	5906522	2023-09-07 05	171	20.6	0.04	—
	2903717	2023-09-06 16	−213	20.6	—	0.0
	5906392	2023-09-04 06	—	0.0	−0.23	7.7
	2903690	2023-09-06 01	−232	18.4	—	—
	7901012	2023-09-04 06	—	0.0	0.14	—
	5905844	2023-09-04 06	—	0.0	−0.02	0.0
	2903721	2023-09-05 14	−280	18.0	0.07	—
	2903709	2023-09-05 20	−281	18.0	—	0.0
	2903360	2023-09-06 16	285	20.6	0.04	0.0

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Figure 1. Best tracks of TCs in the western North Pacific during 2023. The best track data were provided by JMA. The first 13 TCs in this year were considered.

Figure 2. Surface drifters captured by TCs in the year 2023. Magenta solid lines represent the best tracks of TCs, while the blue solid lines depict the trajectories of surface drifters.

N_{d}

denotes the number of surface drifters, and a search radius of 300 km is utilized. The best tracks of TCs are sourced from JMA.

Figure 2. Surface drifters captured by TCs in the year 2023. Magenta solid lines represent the best tracks of TCs, while the blue solid lines depict the trajectories of surface drifters.

N_{d}

denotes the number of surface drifters, and a search radius of 300 km is utilized. The best tracks of TCs are sourced from JMA.

Figure 3. Argo floats captured by TCs in the year 2023. Magenta solid lines represent the best tracks of TCs, while the blue solid lines depict the trajectories of Argo floats.

N_{f}

denotes the number of Argo floats, and a search radius of 300 km is utilized. The best tracks of TCs are sourced from JMA.

Figure 3. Argo floats captured by TCs in the year 2023. Magenta solid lines represent the best tracks of TCs, while the blue solid lines depict the trajectories of Argo floats.

N_{f}

denotes the number of Argo floats, and a search radius of 300 km is utilized. The best tracks of TCs are sourced from JMA.

Figure 4. Argo observation of ocean response to typhoon Guchol. Time series of (a) SST and (b) SSS and profiling of (c) temperature and (d) salinity. Float ID: 5906387; distance from typhoon: 121 km. The variable t represents time, and

t_{0}

is the typhoon’s arrival time (2023-06-06 21:00:00). In (c,d), black solid lines are the mixed-layer depths.

Figure 4. Argo observation of ocean response to typhoon Guchol. Time series of (a) SST and (b) SSS and profiling of (c) temperature and (d) salinity. Float ID: 5906387; distance from typhoon: 121 km. The variable t represents time, and

t_{0}

is the typhoon’s arrival time (2023-06-06 21:00:00). In (c,d), black solid lines are the mixed-layer depths.

Table 1. Best tracks of TCs in 2023.

ID	Name	Affil.	Genesis Date	Life Cycle	$P^{\min}$
			(YYYY-MM-DD HH)	(Days)	(hPa)
1	Sanvu	JMA	2023-04-19 00	3.25	996
		JTWC	2023-04-19 12	2.75	999
		CMA	2023-04-19 00	3.50	995
2	Mawar	JMA	2023-05-19 18	14.75	900
		JTWC	2023-05-20 00	14.25	897
		CMA	2023-05-19 18	14.75	905
3	Guchol	JMA	2023-06-06 00	10.75	960
		JTWC	2023-06-06 00	6.75	956
		CMA	2023-06-06 00	11.25	960
4	Talim	JMA	2023-07-13 06	5.50	970
		JTWC	2023-07-14 12	3.25	971
		CMA	2023-07-13 06	5.50	960
5	Doksuri	JMA	2023-07-20 06	10.25	925
		JTWC	2023-07-21 12	6.75	926
		CMA	2023-07-20 12	10.50	915
6	Khanun	JMA	2023-07-26 18	16.00	930
		JTWC	2023-07-27 06	14.25	928
		CMA	2023-07-26 06	16.25	930
7	Lan	JMA	2023-08-07 00	11.50	940
		JTWC	2023-07-28 18	17.75	942
		CMA	2023-08-07 06	10.75	930
8	Dora	JMA	2023-08-12 00	10.25	975
		JTWC	2023-08-07 18	9.50	936
		CMA	2023-08-01 00	21.25	940
9	Saola	JMA	2023-08-22 00	12.50	920
		JTWC	2023-08-23 06	5.25	977
		CMA	2023-08-23 00	12.00	915
10	Damrey	JMA	2023-08-23 18	6.75	974
		JTWC	2023-08-23 18	10.75	921
		CMA	2023-08-23 00	6.75	985
11	Haikui	JMA	2023-08-27 06	9.75	945
		JTWC	2023-08-28 12	7.25	947
		CMA	2023-08-27 06	14.25	945
12	Kriogi	JMA	2023-08-29 18	7.75	994
		JTWC	2023-08-30 00	5.25	991
		CMA	2023-08-30 00	7.25	985
13	Yum-yemg	JMA	2023-09-04 06	4.50	998
		JTWC	2023-09-05 18	3.00	992
		CMA	2023-09-05 00	3.75	995

Table 2. Surface drifters captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinate, while

V_{\max}

denotes the maximum sustained wind speed of the TC. ΔSST indicates the SST difference at

t_{0}

compared to 1 day prior, and

U_{\max}

is the surface current speed at

t_{0}

. The search radius is 300 km. See also Table A1 for the full record.

Table 2. Surface drifters captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinate, while

V_{\max}

denotes the maximum sustained wind speed of the TC. ΔSST indicates the SST difference at

t_{0}

compared to 1 day prior, and

U_{\max}

is the surface current speed at

t_{0}

. The search radius is 300 km. See also Table A1 for the full record.

Name	Drifter ID	$t_{0}$	$x_{0}$	$V_{\max}$	ΔSST	$U_{\max}$
		(YYYY-MM-DD HH)	(km)	(m/s)	(°C)	(m/s)
Sanvu	61399350	2023-04-22 06	—	—	0.06	0.19
Mawar	61394350	2023-05-31 08	−36	33.4	−0.24	0.39
	61399350	2023-05-23 19	−58	53.2	−0.60	0.88
	60428510	2023-06-02 08	−94	23.1	0.62	0.38
	61658910	2023-06-03 04	154	0.0	0.09	0.43
	60523120	2023-06-03 12	—	—	−0.01	0.02
	61286260	2023-06-01 10	−185	25.7	−0.03	0.26
	62363790	2023-06-02 21	−259	11.6	0.14	0.27
	63010310	2023-06-03 12	—	—	−0.59	0.25
	62364660	2023-06-01 20	278	25.7	−0.39	0.44
Guchol	60520160	2023-06-11 06	11	30.9	−0.94	0.61
	62364800	2023-06-11 10	31	29.2	−1.49	0.65
	62365390	2023-06-11 05	−53	31.3	−1.04	0.36
	61654920	2023-06-10 23	−103	33.9	−0.52	0.09
	61658910	2023-06-12 16	105	0.0	−0.47	1.10
	62129360	2023-06-06 00	—	—	0.14	0.07
	66813190	2023-06-11 04	174	31.7	−0.64	1.23
	63010310	2023-06-13 13	−178	0.0	−0.15	0.40
	62364660	2023-06-10 23	−179	33.9	−0.63	0.41
	60523120	2023-06-13 05	207	0.0	−0.52	0.50
	61081580	2023-06-13 10	281	0.0	−0.64	0.34
	61703450	2023-06-07 13	−286	23.6	−0.17	0.16

Table 3. Argo floats captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinates, while

V_{m a x}

denotes the maximum sustained wind speed of the TC. ΔSST and ΔMLD indicate the SST and MLD differences, respectively, at

t_{0}

compared to 1 day prior. The search radius is 300 km. See also Table A2 for the full record.

Table 3. Argo floats captured by TCs in the western North Pacific during 2023:

t_{0}

is the arrival time of the TC. At this time,

x_{0}

represents the cross-track coordinates, while

V_{m a x}

denotes the maximum sustained wind speed of the TC. ΔSST and ΔMLD indicate the SST and MLD differences, respectively, at

t_{0}

compared to 1 day prior. The search radius is 300 km. See also Table A2 for the full record.

Name	Float ID	$t_{0}$	$x_{0}$	$V_{\max}$	ΔSST	ΔMLD
		(YYYY-MM-DD HH)	(km)	(m/s)	(°C)	(m)
Sanvu	5906718	2023-04-19 10	45	0.0	0.03	—
	2902806	2023-04-21 14	−80	19.7	−0.01	—
	2902815	2023-04-19 06	−133	0.0	−0.00	0.0
	2902803	2023-04-21 21	−163	9.0	−0.00	0.0
	5905867	2023-04-21 12	162	20.6	0.01	0.0
	5906720	2023-04-22 00	−191	0.0	−0.01	0.0
	5906722	2023-04-20 06	210	0.0	−0.02	—
	5904717	2023-04-22 03	219	0.0	0.00	—
	2902801	2023-04-19 18	−248	0.0	−0.02	—
	2902807	2023-04-19 00	—	0.0	0.04	0.0
Mawar	2902740	2023-05-24 06	7	48.9	−0.08	—
	2902757	2023-05-27 17	−10	43.7	−0.59	0.0
	5905864	2023-05-27 00	−14	54.0	−0.19	—
	2903717	2023-06-02 13	−21	23.1	0.05	—
	2902818	2023-05-27 23	−19	43.7	−0.41	0.0
	2903687	2023-06-02 03	−31	23.1	0.17	—
	5906968	2023-05-28 00	−38	43.7	−0.30	0.0
	2903674	2023-06-02 08	−47	23.1	0.02	—
	5906387	2023-05-26 15	−58	59.2	−0.66	10.3

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He, H.; Tian, R.; Lyu, X.; Ling, Z.; Sun, J.; Cao, A. Annual Review of In Situ Observations of Tropical Cyclone–Ocean Interaction in the Western North Pacific during 2023. Remote Sens. 2024, 16, 1990. https://doi.org/10.3390/rs16111990

AMA Style

He H, Tian R, Lyu X, Ling Z, Sun J, Cao A. Annual Review of In Situ Observations of Tropical Cyclone–Ocean Interaction in the Western North Pacific during 2023. Remote Sensing. 2024; 16(11):1990. https://doi.org/10.3390/rs16111990

Chicago/Turabian Style

He, Hailun, Ruizhen Tian, Xinyan Lyu, Zheng Ling, Jia Sun, and Anzhou Cao. 2024. "Annual Review of In Situ Observations of Tropical Cyclone–Ocean Interaction in the Western North Pacific during 2023" Remote Sensing 16, no. 11: 1990. https://doi.org/10.3390/rs16111990

APA Style

He, H., Tian, R., Lyu, X., Ling, Z., Sun, J., & Cao, A. (2024). Annual Review of In Situ Observations of Tropical Cyclone–Ocean Interaction in the Western North Pacific during 2023. Remote Sensing, 16(11), 1990. https://doi.org/10.3390/rs16111990

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Annual Review of In Situ Observations of Tropical Cyclone–Ocean Interaction in the Western North Pacific during 2023

Abstract

1. Introduction

2. Materials and Method

2.1. Tracks of TCs

2.2. Surface Drifter Data

2.3. Argo Float Data

3. Results

3.1. Tracks of TCs

3.2. Surface Drifters

3.3. Argo Profiling

4. Summary

Author Contributions

Funding

Data Availability Statement

Conflicts of Interest

Appendix A

References

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