Impact of Tropical Cyclones over the North Indian Ocean on Weather in China and Related Forecasting Techniques: A Review of Progress

A tropical cyclone (TC) is an intense cyclonic weather system that occurs mainly in the tropical oceans in six major sea areas: the western and eastern North Pacific, North Atlantic, South Pacific, South Indian Ocean, and North Indian Ocean (NIO; Gray, 1968). China is affected by TCs over the western North Pacific (including the South China Sea) and the NIO [including the Arabian Sea (AS) and the Bay of Bengal (BoB)], and is one of the countries with the most severe TC-related hazards globally (Fig. 1). The western North Pacific is the most frequently occurring sea area for TCs (commonly known as typhoons) in the world with an average of about 34 TCs per year generated during 1949–2016, of which about 9 TCs made landfall in China (He and Zeng, 2020), causing huge economic losses per year.

The generation frequency of TCs in the NIO (commonly known as cyclonic storms) is less, with an annual average number of about 5.1, i.e., about 1.6 and 3.5 in the AS and BoB, respectively (Zhang et al., 2016). However, the trumpet terrain of the gulf can trigger huge storm surges even with a moderate intensity storm, making it the most deadly TC occurring site in the world (Chen et al., 2002). For example, on 29 April 1991, a TC made landfall on the BoB coast, reducing a quarter of Bangladesh to an ocean and affecting nearly 10 million people (Shi, 1995). On 2 May 2008, TC Nargis made landfall at the mouth of the Irrawaddy River in Myanmar, causing more than 100,000 people dead or missing, making it the worst storm disaster in Myanmar since April 1991.

Although China has been spared from the tidal disaster caused by the direct landfall of NIO TCs, storm clouds can climb northwards to the Tibetan Plateau or Southwest China, causing snowstorms on the Tibetan Plateau or heavy rainfall in Southwest China and other regions (Zhang et al., 1988), seriously threatening local agricultural and livestock production and people’s lives. For example, in 2013, the strongest tropical storm in the world, Phailin (1302), triggered a heavy snowstorm in southwestern Tibet, with a daily precipitation amount of 64 mm at Nerar station. The peak landfall period for TCs in the western North Pacific is July–September, while there are two peak periods for TCs in the NIO in May–June and October–November, respectively. The staggered and frequent activities of TCs in the two oceans render China the hardest TC-hit area in the world.

Figure 1.  Distribution of TC tracks in the western North Pacific and NIO from 2001 to 2020 (The red box indicates the active area of TCs in the NIO including the Arabian Sea and the Bay of Bengal).

Extensive investigations has been conducted in China over a long time, and a wealth of knowledge has been gained on typhoon activity and its wind and rain mechanisms (Ding et al., 1977; Chen and Ding, 1979; Ding and Lite, 1983; Chen, 2006; Duan et al., 2014, 2020), and significant progress has been made in TC forecasting technology (Xu et al., 2010; Liang and Zhang, 2016). However, research on TCs in the NIO is relatively inadequate, and TC forecasting operation in this sea area was not launched officially in China until 2017. The reason is that, on the one hand, the generation frequency of NIO TCs is low and they do not make direct landfall in China, so their impact is not as intense as that of the TCs in the western North Pacific; while on the other hand, the NIO TC impacted area is mainly the complex terrain highland, where observations and scientific experiments are relatively insufficient.

However, the activity and influenced area of NIO TCs is a key area of China’s “One Belt, One Road” initiative, so it is important to understand the NIO TCs influencing mechanisms and improve the related forecast accuracy. This paper mainly reviews the advances of research on the influence mechanism of TCs over the NIO on China’s weather and associated forecast technology, including the NIO TCs activity pattern, weather features, impacting mechanism, and forecast technology; and summarizes the shortcomings and development needs in current research and operation, so as to provide a reference for further research on the mechanism and forecast technology of the NIO TCs.

International research on TC generation in the NIO started early (Koteswaram and George, 1958; Rao and Jayaraman, 1958). Gray (1968) found that the annual generation and development of TCs in the BoB accounted for 10% of the total global TCs, while TCs in the AS accounted for only 3%. TCs in the BoB are mainly generated in its central and northern sea areas (Tropical Weather Research Group of Department of Geophysics, Peking University et al., 1976), with a few moving in from the South China Sea (Dai, 1974). Bhardwaj and Singh (2020) showed that the most concentrated region for TC generation over the BoB covers the area of 8°–10°N, 88°–92°E, and the trajectory of its generation location largely follows the north–south movement of the subsolar point. The AS storm frequent area is 7°–20°N, 63°–73°E (Zhang et al., 2016), some of which can also come from the BoB westward (Lin et al., 2013), with the densest and most intense storms in its northeastern sea areas (Li et al., 2021).

The TC activity in the NIO is featured with a distinct “bimodal” monthly frequency distribution, i.e., two peaks occurring respectively in May–June and October–November (which correspond to the monsoon transition season). This is distinctly different from the TC frequency in other oceanic areas, where a single peak of TC occurrence dominates the summer season (Gray, 1968; Camargo et al., 2007). Chen and Ding (1979) suggested that this is mainly related to the characteristics of monsoon activity and the vertical distribution of wind fields in South Asia. The low vertical wind shear during the alternating monsoon period provides favorable conditions for development of the storms. Wang and Wang (1988) pointed out that the presence of convergence zones and convergence centers in the lower troposphere over the BoB, as well as the control of high-pressure ridges in the upper layers, is also one of the reasons for the bimodal feature of the storm occurrence frequency in the BoB. During the northward advance of the monsoon trough in spring or its retreat to the south in autumn, barotropic instability caused by horizontal wind shear can trigger TC generation in the BoB (Krishnamurti et al., 1981; Mao and Wu, 2011).

Intraseasonal oscillation (ISO) events are also influential in the formation of TCs in the NIO during the monsoon transition (Yanase et al., 2010; Krishnamohan et al., 2012). Li et al. (2013) comprehensively analyzed large-scale environmental factors and concluded that the increasing relative humidity and the decreasing vertical wind shear are the dominant factors for the peak seasons of NIO TCs in April–May and October–November, respectively. While the higher oceanic heat content and a more variable ISO with northward propagation are the reasons for the tendency to have stronger TCs in April–May. During summer in the NIO, the location of the monsoon trough close to land hinders storm development, and the prevailing southwesterly and upper easterly winds cause strong vertical shear that also inhibits storm formation (Xian and Miller, 2008; Jadhav and Munot, 2009). Duan et al. (2021) analyzed environmental factors, atmospheric circulation, and generative potential indices for TC in the NIO (2021), and found that the BoB has more favorable TC-generating conditions than the AS, especially in October–November.

Fan et al. (2020) classified the TC tracks over the AS during 1977–2018 into three categories: westerly, northwesterly, and northeasterly, of which the westerly path accounted for about 38.8%, the northwesterly path for about 35.8%, and the northeasterly path for only about 25.4%; while the three types of TC tracks over the BoB accounted for a similar proportion, all about 33%. Duan et al. (2009) calculated the occurance frequency of TC tracks over the BoB from 1971 to 2006, indicating that 24.5%, 30.0%, and 30.9% of TCs landed with the west, northwest, and northeast tracks, respectively, while only 14.6% of TCs did not make landfall. Wang and Wang (1989) and Lin et al. (2013) pointed out that the moving track of TC is related to the region and seasons where it is generated. In May, when the South Asian monsoon breaks out, TCs tend to move northeastward along the southwesterly flow outside the subtropical high; in June and July, TCs tend to move westward when the Indian Peninsula is mostly monsoonal low pressure around the time of TC formation; in autumn and winter, the subtropical high retreats southward and extends westward to southern China and the northern Indo-China Peninsula, TCs east of 86°E mostly move northward, while those west of 86°E mostly move westward along the southern side of the subtropical high.

Liu et al. (2021) also suggested that the number of TCs with the northeasterly track in the BoB in May is the most, and TCs generated in the BoB north of 10°N tend to move northeast, while those generated south tend to move northwest, which is related to the different steering flow along the edge of the subtropical high pressure in the western Pacific. Han et al. (2010) found that BoB TCs tend to move westward when located at low latitudes, and often turn directions when moving to higher latitudes, with the turning point at the latitude of the top of the western Pacific subtropical high. Yamada et al. (2010) showed that during the northward movement of TC Nargis, the flow over the northern BoB was characterized as a northwesterly subtropical jet stream with low relative humidity in the mid-troposphere due to the sinking along the southern slope of the Tibetan Plateau, which caused it to shift from a northward track to an easterly track.

Global warming has a large impact on the frequency and intensity of TC extreme events, and the climate change of TC generation in the NIO has attracted much attention in recent years. Wang et al. (2002) and Duan et al. (2009) statistically analyzed the best track data provided by Joint Typhoon Warning Center (JTWC) and found that the frequency of BoB TCs showed a significant abrupt change in the 1970s, with an annual average of 12.4 during 1945–1976 and a sharp decrease to 3.7 during 1977–2008. Bhardwaj and Singh (2020) also noted an average of 3.30 BoB TCs per year during 1972–2017.

However, this drastic change may be related to the inconsistency in the observation means of meteorological data, which relied mainly on meteorological satellite and radar observations after the 1970s, using the Davorak for TC localization. Mohapatra et al. (2014) statistically found that the annual and seasonal variations of TC frequency in the BoB from 1891–1960 had an increasing trend in May and November, but a decreasing trend during 1961–2008. Based on JTWC data, Zhang et al. (2016) showed a decreasing trend in TC frequency in the BoB during 1977–2012, while TC frequency in the AS showed a significant increasing trend.

A recent statistical study by Fan et al. (2020) pointed out that the frequency and duration of TCs in the AS showed a significant increasing trend during 1977–2018, mainly due to the significant increase in the number of H1–H5 intensity grade cyclones, while an insignificant decreasing trend for TCs in the BoB, mainly due to a decrease in the number of tropical depression while still a slight increase in the number of H1–H5 intensity grades (Fig. 2).

Mandke and Bhide (2003) found that although the increase in SST after 1980 favored TC formation in the BoB, changes in other parameters such as 850-hPa relative vorticity, and horizontal and vertical shear of latitudinal winds favored a decrease in TC frequency. Dash et al. (2004) also noted that anomalies in wind shear, mean sea level pressure, water vapor content, and other conditions in the BoB led to a decrease in the frequency of monsoon storms and low pressure. Girishkumar and Ravichandran (2012) and Felton et al. (2013) emphasized that ENSO influences TC activity over the BoB through forced convection, low-level cyclonic vorticity, and tropical cyclone heat potential (TCHP). Increased environmental cyclonic vorticity, higher low-level relative humidity, and anomalous wind forcing increase sea surface evaporation during La Niña events, which are more favorable for cyclogenesis.

Figure 2.  Annual variations of (a) the number and (b) the average duration of TCs after z-score standardization over the Arabian Sea (AS; red lines) and Bay of Bengal (BoB; blue lines) during 1977–2018. Annual variation of TC frequencies in different intensity grades in the (c) AS and (d) BoB, including tropical depressions (TD; green lines), tropical storms (TS; blue lines), and hurricane grades H1–H5 (red lines) after z-score standardization. The dotted lines indicate the trends (Fan et al., 2020).

The climatic trends in the intensity of NIO TCs have also received much attention. Singh et al. (2000) analyzed data from the Indian Meteorological Department (IMD) for the period 1877–1998 and found that during the monsoon transition period (May and November), the frequency of TCs with a central maximum wind speed of 48 kt and above showed a significant increasing trend in the BoB, while there was no significant change in the AS. Duan et al. (2009) showed that although the frequency of BoB TCs declined after the mid-1980s, the number of years with super cyclonic storms increased significantly. For example, there was only one such TC in 1971–1986, compared with eight in 1987–2006. Evan and Camargo (2011) and Evan et al. (2011) suggested that the intensity of TCs in the AS has intensified significantly in May–June since 1997, and attributed this to a significant weakening of tropospheric vertical wind shear caused by increased anthropogenic emissions of black carbon and other aerosol particles, while Wang et al. (2012) suggested that it was caused by a significant advance (15 days) in TC occurrence due to an early onset of Asian summer monsoon. Wang and Yu (2011) found that the observed intensity of NIO TCs from 1982 to 2007 showed an increasing trend, which was the result of a combination of decreasing environmental vertical wind shear and increasing thermal control factors. Xiao and Duan (2015) also noted an increase in TC intensity in the BoB over the last 30 years.

Recently, Liu and Xu (2022) found that a significant increase in the number of super cyclonic storms generated in the NIO in autumn after 1998 was associated with higher sea surface temperatures and ocean heat content and weaker vertical wind shear and lower-level cyclonic vorticity transport. Liang et al. (2020) counted TCs over the NIO from 1990 to 2018 and found that very severe cyclonic storm (VSCS) and super cyclonic storm (SuperCS) class TCs were mainly generated in the central–eastern part of the BoB waters and the central part of the AS waters. Due to the inconsistency of the data, there is no consensus on the climate change trends of the frequency and intensity of NIO TCs under the background of global warming and their causes, and there are few studies on the impact of NIO TCs on climate change in China.

The NIO has a significant influence on China’s weather, especially the BoB, which is the sea area with frequent summer monsoon activity and the strongest precipitation in Asia, as well as an important source of moisture for China’s precipitation (Ding and Sun, 2002). The South Asian monsoon transports warm and humid air from the Indian Ocean downstream through the BoB, making the BoB a key area for southwesterly water vapor transport for flooding in China (Tao et al., 1999, 2000; Xu et al., 2002). The TC in BoB is one of the most active weather systems in this region, and its two peak periods in May and October–November largely coincide with the onset and retreat of the South Asian summer monsoon, and the two are closely related (Fig. 3; Liu and Li 2022). The onset of the summer monsoon in the Indo-China Peninsula and the northward movement of the BoB branch of the southwest monsoon are associated with the northward movement of storms in the BoB in early summer (Li, 1981). On average, the Asian summer monsoon breaks first in the BoB and is mostly accompanied by the development of tropical storms or monsoonal explosive cyclones (Wu et al., 2011, 2013). TCs are more likely (up to 80%) to occur in years with early summer monsoon onset in the BoB (Ren et al., 2016).

Once a tropical storm is generated over the BoB, its intensity and activity trajectory determine the direction of water vapor transport (Xu et al., 2002). The total water vapor transported by southwesterly flow in May is about twice as much as that in October–November (Duan and Zhang 2015). The southwesterly moisture transport from TCs in the BoB is an important influencing factor on the criteria for determining the start and end of the rainy season in the low-latitude highlands of Yunnan (Yan et al., 2013). Compared with climate averages, southwesterly moisture transport is more obvious in southeastern Qinghai–Tibetan Plateau, southwestern China, and southern China during the TC’s northward activity (Liu et al., 2016). The anomalous southwesterly water vapor channel transports more moisture from the BoB to the southeastern Tibetan Plateau, southwestern China, and even the middle and lower reaches of the Yangtze River, which is more stronger in May than that in October–November (Fig. 4; Liu and Li, 2022). It can be concluded that TCs in NIO are closely related to South Asian monsoon activity and have a significant impact on monsoon water vapor transport.

Figure 3.  Inter-pentad variations of regional average (a) OLR (blue line; W m⁻²), and (b) zonal winds at 850 hPa (blue line; m s⁻¹) and 100 hPa (orange line; m s⁻¹) and the frequency of BoB TC genesis (gray bars; right-hand axis) in the South Asian monsoon region (Liu and Li, 2022).

Figure 4.  Anomalies of the whole-layer-average water vapor flux (shading and contours) and the anomalous water vapor flux vectors (arrows; kg s⁻¹ m⁻¹) in (a) May and (b) October–November during 1979–2018. The anomaly fields with stippled small black dots and the fields with heavily plotted vectors of water vapor fluxes are significantly different from 0 at the 0.05 level using a Student’s t-test (Liu and Li, 2022).

The impact of TC is mainly reflected in the three aspects of wind, precipitation, and storm surge that it causes. Due to the topographic blocking of the Tibetan Plateau and the Yunnan–Guizhou Plateau on the northern side of the NIO, the impact of storms on China’s weather is mainly reflected in precipitation. Tropical Weather Research Groups from Department of Geophysics of Peking University and State Oceanic Administration (1976) found that 17 (about 74%) of the 23 BoB TCs that occurred during the early summer and autumn–winter seasons of 1969–1973 had an impact on China’s weather. In fact, the precipitation amount in the Tibetan Plateau, Southwest China, and even the middle and lower reaches of the Yangtze River in China is closely linked to the impact of TCs in the BoB (He et al., 1984). Many studies (Chen and Zhu, 1985; Wang and Wang, 1988; Wang et al., 2007, 2010; Jin et al., 2010; Zhou G. L. et al., 2011; Zhou S. W. et al., 2011; Lyu et al., 2013; Liu et al., 2015; Xie et al., 2015; Da et al., 2019) showed that TCs in the BoB in early summer and autumn peak seasons often trigger heavy rainfall or snowstorms in the Tibetan Plateau and Southwest China.

Lin et al. (2013) statistically analyzed the tracks and impacts of 131 BoB TCs between 1972 and 2011 and pointed out that TCs with northward tracks generated in the central BoB (56.6%) had the greatest impact on precipitation in Tibet. Xiao and Duan (2015; Fig. 5) defined their precipitation influence range by 10 latitudes and longitudes from the TC center, and studied the impact of BoB TCs on precipitation on the Tibetan Plateau in different seasons from 1981 to 2011, finding that an average of about 1.35 TCs affected the plateau annually, and their precipitation range could cover the main precipitation areas over the Tibetan Plateau. The maximum precipitation caused by the TCs can exceed 50% of the local monthly precipitation and account for 20% of the whole season. According to Duan and Duan (2015), among the landfall tracks of BoB TCs, the northeast track has the greatest impact on precipitation in the Yunnan–Guizhou Plateau and the southeastern Tibetan Plateau; the TCs with the northwest track mainly affect southern Tibetan Plateau whereas the TCs with the westward track has the least impact on the plateau.

Liu et al. (2016) synthetically analyzed the precipitation distribution in China during 17 northward storms in May 1979–2013 and found that the precipitation distribution in China in early summer was similar to the climatic mean, but precipitation was abnormally enhanced on the southern side of the Tibetan Plateau, western Yunnan, and in Guangdong and Jiangxi. Yuan et al. (2018) statistically found that about 19% of cyclones in the BoB produced long-range precipitation in Yunnan, Guizhou, and Sichuan provinces. Fan (2021) found that the direct precipitation produced by the convective cloud clusters related to the storms in the BoB is mainly distributed in the Tibetan Plateau and Southwest China; while the indirect precipitation associated with the long distant water vapor transport from the storms is located in Southwest China and the south Yangtze River. The average annual days and amount of precipitation as well as the intensity of precipitation in China under the impact of TCs in May are generally greater than that in autumn, except for the stations in the southern Tibetan Plateau. It is also noted that BoB TCs mainly trigger heavy precipitation in China in early summer/autumn through the “northern trough with a southern TC/convergence of two high pressure systems” circulation pattern.

It is also noted that BoB TCs mainly trigger heavy precipitation in China in early summer/autumn through the “northern trough with a southern TC/convergence of two high pressure systems” circulation pattern. It is noteworthy that storms in autumn/winter tend to cause snowfall on the Tibetan Plateau, and when the trough over the plateau meets with BoB TCs, the snowstorms may be more severe (Tao and Ding, 1981; Pu et al., 1998). Although the annual frequency of TCs over the BoB is low, precipitation in the highland areas of China under their impact is stronger, which tends to trigger consecutive precipitation anomalies at certain spatial and temporal scales. The anomalous characteristics at different spatial and temporal scales and the mechanisms of rainfall or snowfall on the plateau caused by TCs over the BoB are topics that still need to be explored in depth.

Figure 5.  Distributions of the weather stations impacted by BoB TCs over the Tibetan Plateau (solid dots), the corresponding frequency (shaded; times per year), and the tracks of BoB TCs (blue lines) in (a) April–June (AMJ) and (b) September–December (SOND). The purple solid line indicates the topography of 3000-m altitude above the sea level (Xiao and Duan, 2015).

Due to their special geographical location, the impact of NIO storms on China’s weather is closely linked to the topography of the Tibetan Plateau. The Tibetan Plateau, which is the largest, highest, and most complex terrain in the world, dwells at the midlatitude to the north of NIO, and its dynamical and thermal forcing affect not only the regional circulation but also the atmospheric circulation in Asia and the globe. On the one hand, the Qinghai–Tibetan Plateau acts as an airborne “heat island,” and its thermal forcing can influence the structure of the atmospheric circulation (Huang, 1985; Huang and Yan, 1987) as well as the low-latitude monsoon activity (Wu and Zhang, 1998; Ding and Sun, 2002). Xu et al. (2014) suggested that the Qinghai–Tibetan Plateau is thermally driven by a large-scale TC-like CISK mechanism in a two-step process that transports warm and humid airflow to the plateau in a “relay” mode. Wang et al. (2015) showed that the plateau can continuously attract anomalous warm and humid airflow from the lower latitudes of the Indian Ocean and the South China Sea to the south through the “heat pump” effect.

However, the influence of the thermal effect of the Tibetan Plateau on NIO storm activity and its circulation has been less discussed. On the other hand, the topographic dynamic forcing effect of the Tibetan Plateau has a non-negligible role in storms and their precipitation. According to Wang et al. (1986, 1996), after the landfall of a storm in the coastal BoB, the middle and upper layers in the northern part of the storm are mainly divergent, while the whole layer in the southern part is almost convergent due to the large orographic lifting effect, which is conducive to transporting water vapor to the plateau. Zhu et al. (1998) suggested that the topographic blocking effect of the Qinghai–Tibetan Plateau is limited and has no blocking effect on the northward advance of cirrus clouds at the front of the storm, so the storm cloud systems can reach over the plateau forming precipitation conditions. Wang et al. (2010) showed that as the terrain rises, the vorticity, moisture flux convergence, and upward motion generally inten-sify, and precipitation occurred, with its center formed between the terrain peak and the terrain-forced vertical motion maximum.

There are also significant changes in TC structure under the plateau topographic forcing. Xu et al. (2006) showed that the structure of the BoB TC under study evolved from essentially symmetric to baroclinic asymmetric before and after landfall, similar to the transition phase of landfalling typhoons. Wang et al. (2009, 2011) found that compared with the typhoon structure, the height of the cyclonic outflow of the TCs in the BoB was significantly lower, and the upper vorticity field and divergent field were both tilted in the direction of movement, and this structural feature has some significance for TC track forecasting. Duan and Zhang (2014) studied the structures of landfalling storms with the northeast tracks and pointed out that except for the enhanced airflow convergence in the near-surface layer due to topographic friction at landfall, the convergence in the middle and upper troposphere and the divergence at upper-level were weakened.

Due to the blockage and dissipation effects of the Tibetan Plateau topography, the vast majority of BoB storms cannot move into China; the way that they affect China’s weather is different from the direct impact of a normal landfalling typhoon. Chen and Ding (1979) pointed out that when a BoB storm moves in a northerly direction, its leading edge can reach the Tibetan Plateau, and bring about strong snowfall (rainfall) there. Zhang et al. (2006) showed that the BoB storm affected Yunnan by splitting into mesoscale convective cloud clusters and peripheral cloud systems, and by continuous northward movement after landfall. Lyu (2013) tracked the convective cloud clusters of the BoB TCs from 2001 to 2011 and found that about 39% of the TCs were able to produce splitted cloud clusters to climb up to the Tibetan Plateau or the Yunnan–Guizhou Plateau, and strengthen the cloud systems in front of a trough to trigger heavy precipitation.

Liu et al. (2015) also pointed out that when it was weakened after landfall, the BoB storm “Phailin (1302)” split off mesoscale convective cloud clusters that moved up to the plateau, under the influence of the southern branch trough, which possibly led to a heavy snowstorm in Tibet. Many studies (Li et al., 2003a, b; Duan et al., 2004; Lu et al., 2006; Xu et al., 2007) have found that under certain atmospheric circulation conditions, BoB TCs can “directly” affect the plateau by splitting off mesoscale convective cloud clusters, peripheral cloud systems, or weakened remnant cloud systems to the north; on the other hand, they can also affect the plateau “indirectly” by transporting warm and humid airflow over a long distance through the southwesterly low-level jets, which can alter the thermodynamic conditions for the rainfall in the downstream region.

The mechanism for the impact of the NIO TCs on precipitation in China is mainly related to the interaction of the TCs with the midlatitude plateau circulation system. Dai (1974) found that without significant cold air invasion over the northern Tibetan Plateau, precipitation under the influence of BoB TCs mainly occurs in the southern or southeastern plateau; conversely, when cold air enters northern plateau, region-wide precipitation occurs, accompanying the northward extension of the cloud belt. Wang and Wang (1989) summarized three types of circulations in which TCs induce precipitation in Tibet: TCs are joined with southern branch troughs, TCs are under neutral stratification environments, and TCs are associated with meridional circulation. Yang et al. (2000) compared the effects of two BoB TCs on precipitation in China and found that the differences in precipitation areas and intensities depend mainly on midlatitude cold air activity as well as the interaction of the storms with mid- and low-latitude weather systems. Chen et al. (2003) and Duan et al. (2004) showed that the location and intensity of TCs, subtropical high, and the southern branch trough have a strong influence on precipitation in the low-latitude highlands. Xu (2007) categorized the environmental circulation system for the BoB TCs to induce heavy rainfall in Southwest China into three types: a transverse trough coupled with a shear line, the southern branch trough, and the western North Pacific subtropical high. The transverse trough, low vortex, or shear line in the plateau are significant disturbances favoring water vapor transport from the BoB TCs, promoting development of the TC cloud systems to the north, and producing heavy precipitation in Yunnan (Zhang et al., 2006).

Due to topography and cold air activity, the landfalling storms may enhance low and middle tropospheric fronts, leading to convective instability, baroclinic instability or conditional symmetric instability (Wang et al., 2010). The southern branch trough maintained over the BoB is conducive to water vapor transport from the BoB TCs to the plateau, meanwhile the moisture transport from the BoB storm can enhance the plateau shear line, thus facilitating increased precipitation (Suo and Ding, 2014). The interaction between the low pressure (trough) system and high- and low-level jets after the weakening of “Fani” in the BoB in May 2019 provided moisture and heat as well as dynamic uplift conditions for heavy precipitation in southern and southeastern Tibet (Ci et al., 2019).

Due to the interactions among midlatitude systems, the precipitation over the plateau under the influence of BoB storms is sometimes markedly baroclinic. The impact of the storms on China’s weather involves the interaction between low-latitude marine TC systems and midlatitude plateau circulation systems in the context of plateau topography, and investigation on the related complex mechanisms needs to be carried out extensively and deeply to address such questions as, what is the dynami-cal mechanism for the storm moisture to climb up the Tibetan Plateau; what are the responsible physical processes for the storm interaction with the plateau shear lines, plateau vortex, and other systems; and how do the resulting anomalous dynamic and thermal circulations impact on the precipitation.

Numerical weather prediction serves as a very important scientific and technical support for TC forecasting. Since the 21st century, due to the development of computer science and technology and the trend of sharing global resources, a large number of numerical models have been applied to TC forecasting in the NIO, such as the IMD Global Forecast System (GFS), the WRF model of the NCAR, and the HWRF model system of the NOAA; some numerical forecast products from such as the NCEP GFS, the ECMWF, the United Kingdom Meteorological Office (UKMO), the Japan Meteorological Agency (JMA) GFS, and the cloud-resolved version of NOAA’s HWRF model are also readily available to forecasters (Mohanty et al., 2015). Improvements and sharing of models have led to significant improvements in global TC forecast operations, but forecast accuracy and time efficiency need to be further enhanced.

The ECMWF Variable Ensemble Prediction System (VarEPS) has shown low false alarm rates in terms of storm generation, track, and intensity, providing more accurate TC track forecasts for period validity greater than 12 h (Belanger et al., 2012). Experts have also successfully forecasted the track of Storm Laila (1001) westward and then backward by using the Advanced Research version of the WRF model (ARW) and an improved Doppler weather radar data assimilation procedure (Osuri et al., 2015). The prediction of storms has been improving due to improvements in numerical forecasting systems and the increase of the model resolution. It can be seen a significant increasing trend in the accuracy of the 24-h intensity prediction of storms during 2005–2011, with errors below 10 knots (Mohapatra et al., 2013a). The mean error of the 24-h track prediction of the TCs in the NIO during 2003–2011 decreased at a rate of ~7.3 km yr⁻¹ (Mohapatra et al., 2013b), and the mean error in 24-h landfall predictions decreased at a rate of 14.5 km yr⁻¹ during 2003–2013 (Mohapatra et al., 2015).

Mesoscale numerical model assimilation and forecasting techniques have also been successfully applied to the prediction of BoB TCs. Mohanty et al. (2004) used the atmospheric research mesoscale model (MM5) to simulate Super Cyclonic Storm Orissa in 1999. Pattanayak et al. (2012) used the HWRF model to simulate the BoB TC Mala (2006), which successfully described most of the characteristics of the storms. The simulation of TCs has been further improved by data assimilation techniques. Srivastava et al. (2011) used radar 3D Var assimilation data to simulate Storm Ogni (0606), which can represent the generation, structure, and movement of the storm in a short time. Singh et al. (2012) used the WRF-ARW model to study the impact of assimilated satellite data Advanced Microwave Sounding Unit-A (AMSU-A) on BoB TCs and found that the simulation was improved after data assimilation.

In terms of improvements in model forecasting techniques, more appropriate physical process parameterization schemes are used to make the forecasts more credible, taking into account the physical processes of storm-affected weather in the BoB. For example, Akter (2015) simulated the track and intensity of four TCs before and after the monsoon season in 2007 and 2010 by using an improved WRF model (AHW) with the Kain–Fritsch cumulus parameterization scheme, the Ferrier microphysics scheme, and the Monin–Obukhovs scheme (for physical processes at the sea surface). The results of these simulations were used to examine the environmental conditions for the formation of TCs, development of associated convective systems, and variations of TC occurrence frequency relevant to the bimodal distribution of the NIO TCs, and improved understanding was obtained.

As the World Meteorological Organization (WMO)’s Regional Specialized Meteorological Centre for Tropical Cyclones in the NIO, Indian Meteorological Department (IMD) is responsible for providing guidance products on the generation, track, and intensity of storms and storm surge forecasts in the NIO to its members in the region. IMD has introduced the NCEP GFS and runs regional numerical weather models such as WRFDA and HWRF, of which HWRF is coupled with the Princeton Ocean Model (POM) and the HYbrid Coordinate Ocean Model (HYCOM), with functions such as vortex initialization, regional data assimilation, multiple nested grids, and so on (World Meteorological Organization, 2020).

At the same time, IMD has developed objective TC forecasting methods based on NWP models, including cyclone genesis potential parameter forecast, multi-model ensemble forecast for TC track and intensity, forecast of intensity decay after TC landfall, and quantitative TC precipitation probability forecasting products.

Just as TCs in other oceanic areas of the world, the TCs in the BoB also undergo rapid intensification, and researchers have developed the TC Rapid Intensification Index (Kotal and Bhowmick, 2013), the basic idea of which is to select characteristic physical quantities including the initial latitude of the TC, the change in TC intensity over the past 12 hours, the current intensity of the TC, 850-hPa vorticity, 200-hPa divergence, vertical wind, etc., by comparing individual cases of rapid intensification and non-rapid intensification. These physical quantities are selected and set as thresholds and combinations based on statistical analysis to provide a reference for forecasting TC rapid intensification. Due to the special topography of the Ganges Delta on the north coast of the BoB, storm surge forecasting is of great interest to India and other neighboring countries, and IMD has developed a storm surge forecasting model and a coastal flood forecasting model.

Apart from the IMD, other members of the NIO Panel on Tropical Cyclones, including the meteorological departments of Bangladesh, Maldives, Myanmar, Oman, Pakistan, Sri Lanka, Thailand, and the United Arab Emirates, also carry out monitoring and warning operations for TCs in the BoB according to their respective responsibilities. For example, to identify and track the storms based on surface observations (including automatic stations), air soundings, ships and radar, satellite observations, etc., to make forecasts on TC’s track, intensity, precipitation, gale, and storm surge, by reference to models such as EC, NCEP, and their own numerical weather forecasts, and combined with Tropical Cyclone Regional Meteorological Centre guidance products. Some members also issue storm impact forecasts for ports and sea areas, and do warnings based on color classes.

China attaches great importance to the monitoring and forecasting of TCs in the BoB. Especially, under the implementation of China’s “maritime power strategy” and the “Belt and Road” initiatives, China Meteorological Administration (CMA) has gradually expanded their operational forecasting of TCs over the NIO. Since 2003, Central Meteorological Observatory (CMO) of CMA has carried out operational TC monitoring over the NIO, including TC’s name and number, center location and intensity, TC’s future track, intensity, change trend, etc. The Bulletin on Tropical Cyclone Monitoring in the NIO is published twice a day (0000 and 0600 UTC) to meet the needs of different users. In recent years, with the successful upgrading of China’s meteorological satellite, especially the drifting of FY-2H over the Indian Ocean (79°E) in 2018, favorable conditions have been created for China to carry out TC monitoring in the NIO. CMA Earth System Modeling and Prediction Centre has modified the regional typhoon model CMA-TYM, extended the western boundary of the model from 90° to 40°E, and established the initialization process for NIO TCs, which can provide real-time numerical forecast guidance products on TC track, intensity, precipitation, sea level pressure, wind shear, etc., thus strongly supporting the development of BoB TC forecasting in China.

In the past five years, CMA has continued to expand the functions of its operational platform by developing a global TC database and forecasting platform including the NIO TCs, while adapting the Typhoon Track Objective Forecasting Method based on ensemble forecast revisions to make it applicable to NIO TC forecasting (Qian et al., 2014). CMO formally launched the operational forecasts for TCs in NIO in 2017, issuing NIO TC track and intensity forecasts four times a day (0000, 0600, 1200, and 1800 UTC). The mean errors of the 24–72-h track forecasts of NIO TCs by CMO from 2017 to 2021 are 66, 101, and 151 km, respectively, which are comparable to the forecast skill level of IMD (Fig. 6).

In addition, CMO has developed an ensemble forecast optimal percentile precipitation forecasting technique and introduced probability matching and frequency revision techniques in an attempt to improve the precipitation forecasting capability for TCs in NIO. Forecasting tests conducted in China have shown that this method can improve the forecast accuracy of TC rainfall areas to a large extent and it also shows a significant improvement in TC intensity forecasting, with better performance in both TS and BIAS scores, and the TS score for rainstorm can be improved by more than 5%–8% compared to the ECMWF model.

At present, a systematic quantitative assessment of TC precipitation in the NIO has not been carried out due to the limitation of foreign precipitation data. However, it can be speculated that by introducing ensemble optimal percentiles and other precipitation forecast calibration methods, the precipitation forecast capability for the NIO TCs can be improved, especially in terms of the forecast capability of TC rainfall areas and magnitudes. There is still an urgent need to develop numerical models and forecasting systems for the BoB TCs, through focusing on the forecasting capability of the circulation system and precipitation over the Tibetan Plateau and its surrounding areas, and improving the forecasting and warning technology for the NIO storms affecting China’s weather.

Figure 6.  (a) The track and intensity forecast over 1400 BT 2–0200 BT 5 May 2019 for the BoB TC “Fani” published by the National Meteorological Centre of China and (b) comparison of 24-, 48-, and 72-h forecast errors averaged over 2017–2021 for TC tracks in the NIO between the China Meteorological Administration (purple columns) and the Indian Meteorological Department (orange columns).

The NIO TC occupies an important position in China’s weather influence systems. In particular, the BoB is a source of water vapor for China’s precipitation and a key area for the South Asian monsoon onset, so the TC activity in the BoB has a very important impact on China’s precipitation. This study describes the research results and progress in the activity characteristics, weather impact, precipitation mechanism, and forecasting technology of TC in the NIO, and the main conclusions are as follows.

(1) NIO TCs are active in the early summer and autumn–winter and are closely associated with Asian summer monsoon activity. It has an impact on precipitation over a wide area of the Tibetan Plateau, Southwest China, and even the middle and lower reaches of the Yangtze River. They play an important role in precipitation anomalies on the Tibetan Plateau and in extremely heavy rainfall (snow). Under the background of global warming, the annual change in the frequency of TCs in the AS is on an increasing trend, while TCs in the BoB show an insignificant decreasing trend, but the number of strong TCs still increases slightly and the probability of their occurrence increases.

(2) The BoB TCs uniquely affect our weather, mainly by splitting convective cloud clusters northwards, by the northward movement of peripheral or remnant cloud systems to trigger precipitation, or by forming southwesterly low-level jet that provide moisture and heat to induce long distance precipitation in downstream areas. The key situation in which TCs affect precipitation in China is the formation of southwesterly low-level moisture jets collaborated with the southern branch trough or subtropical high pressure, which produces precipitation in China through the interaction of warm and moisture flows with midlatitude systems. In the BoB TC activity, the role of the Tibetan Plateau topography cannot be ignored, mainly in terms of its influence on water vapor transport and storm structure changes.

(3) The operational forecasting technology of TC in the NIO has also made great progress. The sharing of forecast system products, the application of ensemble forecasting techniques, the improvement of the resolution of mesoscale numerical models, the development of the parameterization scheme for physical processes, and the application of assimilation techniques have led to more accurate forecasts on the track, landfall, and intensity of the BoB TCs. In recent years, China’s forecast operations for the NIO TC have been fully developed, numerical forecast systems, databases, and forecast platforms have been established, and the level of forecasting of the BoB TCs affecting China’s weather has gradually improved.

In addition, there are still weaknesses in the research on mechanisms and forecasting techniques of TC in the NIO, and the following issues deserve further discussion.

(1) Trends in climate change. Under the background of global warming, changes in TC frequency and intensity in various seas have become a hot topic of concern for the international TC research community. The results of climate change studies on TC frequency and intensity in the NIO are divergent due to data inconsistency.

(2) Impacts on China. The researches mainly focus on the impact of TCs in the BoB, while the impact of TCs in the AS is rarely studied. In turn, most of the studies on BoB TCs focus on the impact of TCs on precipitation in the southwest in early summer, with insufficient studies on the impact on other regions, and also few studies on the peak period of TC activity in autumn. There is a lack of understanding on the activity pattern of the NIO TCs affecting China, and a lack of systematic, long-term statistics and analysis. In addition, the Tibetan Plateau does not receive much annual precipitation, while TC-induced precipitation is usually intense, and its contribution to precipitation anomalies or extremes in different temporal scales on the Tibetan Plateau deserves attention.

(3) The specificity of the impact mechanism on China’s weather. The storm impact mechanism on China’s weather involves the complex interaction between the low-latitude marine storm system and the midlatitude plateau circulation system under the topography of the Qinghai–Tibetan Plateau, and the special way and physical process of its impact on China need to be studied in depth. The activity characteristics, structural changes, and topographic forcing mechanisms of storms in the BoB under the special dynamical and thermal effects of the Qinghai–Tibetan Plateau are still issues of concern in the study of storm impact mechanisms.

(4) Observational studies. The BoB TC mainly affects the plateau areas of China, where observation data from surface or radar stations are scarce, leading to deficiency on observational studies of TC-influenced weather. There is also a lack of monitoring and observational analysis of the BoB TC itself. The analysis of the applicability of multi-source data such as satellite remote sensing and reanalysis data in highland areas under the influence of the storms is not yet to be fully carried out.

(5) Numerical forecasting. The Qinghai–Tibetan Plateau and its surroundings are one of the most difficult regions for numerical forecasting models to simulate in the world, and the development of stable and refined numerical forecasting techniques for this region is an important aspect of improving storm forecasting. China initially developed a numerical forecasting system and forecasting platform for the BoB TCs, but still needs to greatly improve its numerical forecasting capability and forecasting technology for the BoB TCs.