2023 Volume 101 Issue 4 Pages 347-365
Based on the vertical atmospheric sounding system carried by the FY-3D meteorological satellite (FY-3D/VASS) and the new wind radar instrument carried by the FY-3E meteorological satellite (FY-3E/WindRAD), a study of the potential application of research on the changes of temperature, humidity, and ocean wind vector (OWV) during the onset of the South China Sea summer monsoon (SCSSM) was conducted. The applications of these satellite datasets in SCSSM monitoring were evaluated, and the SCSSM onset process in 2022 was analyzed. The results showed that the mean bias of the FY-3D/VASS temperature and specific humidity at 850 hPa, compared with that of the fifth-generation ECMWF reanalysis, were −0.6 K and −0.53 g kg−1, respectively, and the pseudo-equivalent potential temperature (θse) was slightly lower, by 1–2 K; the distribution of θse was consistent with the seasonal advancement of the SCSSM. Compared with Metop-C/ASCAT, the mean bias of FY-3E/WindRAD zonal wind was positive, and that of meridional wind was negative. The correlation coefficient, mean bias, mean absolute error, and root-mean-square error of the wind speed were 0.79, −0.45, 1.56, and 2.03 m s−1, respectively. The distributions of OWV were consistent, and the region and intensity of strong wind speed were close to each other. The temperature, humidity, and wind reversal during the onset of the SCSSM in 2022 were well monitored by the FY-3D/E-derived θse and OWV dual indices, which are consistent with the SCSSM onset date, the third pentad in May, issued officially by the National Climate Center, China Meteorological Administration. Before the SCSSM's onset in 2022, the tropical storms' pumping effect in early May increased the westerly wind over the tropical ocean north of the equator. After the storm weakened, the southwesterly wind passed across the Indochina Peninsula and reached the South China Sea, causing the SCSSM's onset.
Asia and Australia are typical monsoon regions, forming the Asian–Australian monsoon system. The onset of the summer monsoon indicates that the atmospheric circulation changes from winter to summer. The Asian summer monsoon includes the tropical summer monsoon and the subtropical summer monsoon (Wu and Zhang 1998; Wu et al. 2013a, b). The onset of the Asian tropical summer monsoon generally passes through three stages. First, the Asian summer monsoon is established over the south of the Bay of Bengal. Then, in mid-May, it extends eastward through the Indochina Peninsula to the South China Sea summer monsoon (SCSSM) region. Finally, the onset of the South Asian summer monsoon arrives in June. The onset of the SCSSM indicates that the East Asian subtropical summer monsoon has begun to establish itself and the primary rainy season begins (Chen et al. 2022). In addition, this marks a major transition in the seasonal change of climate in Asia and can affect the weather and climate in other regions of the world through atmospheric teleconnection (Xu et al. 2019). Therefore, the South China Sea Monsoon Experiment was performed more than 20 years ago to conduct in-depth research on the onset and evolution of the SCSSM (Lau et al. 1998; Chan et al. 2002; Wang 2008).
The studies on the SCSSM mainly investigated the dynamics and triggering mechanisms of its onset, the characteristics and mechanisms of the multiple time-scale changes of the onset of the summer monsoon, and the monitoring indices. These studies demonstrated that during the onset of the SCSSM, the large-scale atmospheric circulation in Asia changes suddenly; the South Asia High jumps rapidly to the north, the tropospheric atmosphere in the southeast of the Tibet Plateau and the eastern parts of China warms rapidly, and the atmospheric heating source and water vapor sink increase significantly (Jiang and Luo 1995; Wang et al. 2018). An explosive vortex or cyclone storm in the Bay of Bengal or a tropical cyclone in the northwest Pacific is an important trigger factor for the onset of the SCSSM (Wu et al. 2011, 2012, 2013a, b; Ren et al. 2016). In addition, the southward motion of a middle- and high-latitude cold front can trigger the onset of the SCSSM (Ding and Liu 2001).
To study the characteristics of the onset of the SCSSM, it is necessary to define the monitoring indices. Most indices are established with single or multiple parameters of wind, temperature, precipitation, convection, and their derived parameters, forming a single or comprehensive index (Li and Zhang 1999). While the average onset dates produced by different indices are fairly consistent, due to the complexity of the onset process of the summer monsoon, they often produce different dates in a particular year. Zhang et al. (2003) defined the East Asian summer monsoon index by using zonal wind at 850 hPa, and Webster and Yang (1992) studied the Asian summer monsoon index by using the vertical zonal wind shear between the high and low troposphere. The satellite data regarding outgoing longwave radiation or blackbody brightness temperature (TBB), combined with the meteorological reanalysis data, are usually used to define the SCSSM indices, and two indices are generally used to determine summer monsoon activity (Ding and Li 1999; He et al. 1996; Liang et al. 1999; Guo et al. 1999; Liu et al. 1998; Jiang et al. 2006). In addition, Qian and Zhu (2001) and Zhu et al. (2001) studied the characteristics of deep convection before and after the onset of the Asian summer monsoon using the brightness temperature of the satellite water vapor channel in the upper troposphere and demonstrated that the critical value of deep convection is 244 K, indicating that meteorological satellite data can be used to monitor the characteristics of significant changes in atmospheric temperature and humidity during the onset of the SCSSM. Ren and Fang (2013) and Ren et al. (2018) studied the application of meteorological satellite-derived atmospheric motion vector (AMV) and TBB in summer monsoon monitoring, indicating that satellite AMV and TBB double indices can better describe the characteristics of the onset of the SCSSM than a single convective index. In addition, the operational monitoring indices and determination methods for real-time monitoring of the SCSSM, based on AMV and TBB and conducted in real time, have been implemented as a component of operational climate services at the National Satellite Meteorological Center (NSMC), Chinese Meteorological Administration (CMA) (Ren et al. 2017). In the National Climate Center (NCC), CMA, zonal wind, and pseudo-equivalent potential temperature (θse) at 850 hPa from the numerical prediction model, or reanalysis data, are used to calculate the SCSSM indices and the SCSSM intensity classification and conduct the prediction, monitoring, and impact assessment of the SCSSM (Shao et al. 2021).
The onset process of the Asian tropical summer monsoon occurs over the ocean with few conventional meteorological observations. The vertical atmospheric sounding system—including three instruments: the MicroWave Humidity Sounder (MWHS), MicroWave Temperature Sounder (MWTS), and Hyperspectral InfraRed Atmospheric Sounder (HIRAS)—carried by the FY-3D polar-orbiting meteorological satellites (FY-3D/VASS) can effectively observe the three-dimensional temperature and humidity of the atmosphere under all weather conditions (Gu et al. 2010; Guo et al. 2014; Zhang et al. 2021; Xian et al. 2021) and has played an important role in the monitoring of extreme weather events (Zhuang 2022; Ren et al. 2022). The application of this observation data in the monitoring of the SCSSM has great potential. The wind radar carried by the FY-3E meteorological satellite launched in 2021 can observe the global ocean surface wind field (FY-3E/WindRAD) (Zhang et al. 2022). Previous analysis has shown that, compared with the wind at 850 hPa, the surface wind can better describe the characteristics of the Asian monsoon (Wu et al. 2013b). Therefore, this paper will also evaluate the potential application of the FY-3E/WindRAD ocean surface wind in SCSSM monitoring.
This study will focus on the evaluation of the applications of the FY orbiting meteorological satellite's retrieval of temperature, humidity, and ocean surface wind data in SCSSM monitoring. First, the performance of satellite data was evaluated during the key period of the onset of the summer monsoon in the SCSSM region, and the summer monsoon indices retrieved by the satellites were compared to the operational indices of the NCC, CMA. Then, the SCSSM onset process in 2022 was studied using FY-3D/VASS and FY-3E/WindRAD data.
The FY-3D meteorological satellite was launched on 15 November 2017 (Gu et al. 2010; Guo et al. 2014; Zhang et al. 2021; Xian et al. 2021). In the present study, the temperature and humidity data retrieved by the FY-3D/VASS were used. Overall, there are three vertical atmospheric sounding instruments, including the 4-channel MWHS, the 5-channel MWTS, and the 1370-channel HIRAS. A package has been developed to retrieve the atmospheric temperature and humidity profiles, in both clear and cloudy atmospheres, from the VASS measurements. The algorithm that retrieves these parameters contains four steps: 1) cloud and precipitation detection, 2) bias adjustment for VASS measurements, 3) regression retrieval processes, and 4) a nonlinear iterative physical retrieval. The VASS temperature and humidity data cover the entire world, with a maximum spatial resolution of 16 km. There are 43 pressure layers, from 1013.25 to 0.1 hPa. The pressure layer selected in this paper is near 850 hPa.
Because it is affected by hydrometeors, temperature and humidity estimation accuracy may be relatively low. The FY-3D/VASS temperature and humidity datasets provide a data quality flag (quality flag is 0 or 1; 0 is for good); the data with quality flag number 0 were selected in this research.
2.2 FY-3E/WindRAD ocean wind vectorThe FY-3E, the world's first early morning orbit meteorological satellite, was successfully launched in July 2021. The satellite is equipped with 11 remote sensing instruments, including 3 that are newly developed, 7 that have been upgraded, and 1 that is inherited (Zhuang 2022; Zhang et al. 2022). The FY-3E is capable of an active and passive combination of ocean surface wind detection capability and has now added dual-frequency wind radar using C-band (5.3 GHz) and Ku-band (13.265 GHz), the first active remote sensing instrument loaded on the FY series meteorological satellite. This instrument can provide high-precision measurements of global ocean surface wind, including wind speed and wind direction. The ocean wind vector (OWV) from FY-3E/WindRAD has been a stable operational product since 1 March 2022.
The daily OWV selected in this paper is divided into ascending and descending orbits. The spatial resolution is 0.25° (latitude) × 0.25° (longitude), covering the global ocean surface. In the present study, the daily ascending and descending orbit data are processed into daily averages. The satellite observation times of the SCSSM region are approximately 1000 UTC and 2200 UTC.
2.3 Metop/ASCAT OWVThe Advanced SCATterometer (ASCAT) is one of the instruments carried onboard the Meteorological Operational (Metop) polar satellites launched by the European Space Agency and operated by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) (Verhoef et al. 2012; Verspeek et al. 2019). Metop-C was launched on 7 November 2018. The horizontal stress-equivalent wind vector was measured at 10 m height and included wind speed and wind direction. Wind speed was measured in m s−1. The wind speed range was from 0 to 50 m s−1, but wind speeds exceeding 25 m s−1 are generally less reliable (OSI SAF/EARS Winds Team 2021). The accuracy should be better than 2 m s−1 in wind component standard deviation, with a bias of less than 0.5 m s−1 in wind speed. The spatial resolution was approximately 12.5 km, observed twice each day. In the present study, the data were processed into daily averages, with a spatial resolution of 0.25° (latitude) × 0.25° (longitude). The satellite observation times of the SCSSM region were approximately 0200 UTC and 1400 UTC.
2.4 ERA5 reanalysis dataThe temperature, humidity, and wind data used in this paper are from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5), which combines numerical model and global observation data, with a horizontal spatial resolution of 0.25° (longitude) × 0.25° (latitude) and a temporal resolution of 1 h. In the present study, the daily average data are processed, and the pressure layer used is 850 hPa (Hersbach et al. 2020).
2.5 Calculation method of the SCSSM indexThis paper conducts an evaluation of FY-3D/VASS and FY-3E/WindRAD applications in SCSSM monitoring based on the indices operated by the NCC, CMA, including the regional average pseudo-equivalent potential temperature index and the regional average zonal wind index (Shao et al. 2021). The pseudo-equivalent potential temperature was calculated using Eqs. (1)–(4) (Bolton 1980):
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The region of the SCSSM is [10–20°N, 110–120 °E], and the pseudo-equivalent potential temperature index is its regional average at 850 hPa. The wind index is the zonal wind regional average at 850 hPa used by the NCC, CMA. In the present study, the zonal components of OWV from FY-3E/WindRAD were used as a replacement of the zonal wind at 850 hPa in the SCSSM wind index.
2.6 Evaluation methodThe mean bias (MB), mean absolute error (MAE), root-mean-square error (RMSE), and correlation coefficient (CC) were calculated from Eqs. (5)–(8):
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In the present study, the evaluation of the FY-3D meteorological satellite data was conducted for the 850 hPa pseudo-equivalent potential temperature index of the SCSSM, including temperature, humidity, and the pseudo-equivalent potential temperature calculated by Eqs. (1)–(4).
The scatter density and evaluation indices of the temperature at 850 hPa between FY-3D/VASS and ERA5 in the SCSSM region [10–20°N, 110–120°E] in April, May, and June 2022 show that the matching sample number is approximately 80000 and the maximum matching sample number is approximately 86000 in May (Fig. 1). The lowest MB and MAE measurements in 3 months occurred in April, which are −0.39 K and 1.02 K, respectively. The maximum CC was 0.46, which was also in April (Fig. 1a). The average MB in May was −0.73 K, the MAE was 1.11 K, and the minimum RMSE was approximately 1.54 K (Fig. 1b). The minimum CC was 0.27 in June (Fig. 1c). Overall, the scatter density distribution from April to June shows that the FY-3D/VASS temperature at 850 hPa was abnormally high or low at some points. In these 3 months, the average MB was −0.64 K, the MAE was 1.09 K, and the RMSE was 1.61 K (Fig. 1d).
The scatter density and evaluation indices of temperature at 850 hPa between FY-3D/VASS and ERA5 in the SCSSM region [10–20°N; 110–120°E] in (a) April, (b) May, (c) June, and (d) the average of April, May, and June 2022.
The scatter density and evaluation indices of the specific humidity at 850 hPa between FY-3D/VASS and ERA5 in the SCSSM region [10–20°N, 110–120 °E] in April, May, and June 2022 show that, compared with those of temperature, the CC of the specific humidity is less and the scatter points are not very consistent (Fig. 2). More samples of the FY-3D/VASS specific humidity with abnormally high or low readings appeared in April and June, and the specific humidity value was low on average. In May and June, the CC was low, and the high scatter density was distributed below the regression line. The MB in June was relatively low: −0.15 g kg−1 (Fig. 2c). From April to June, the average MB was −0.53 g kg−1, the MAE was 2.25 g kg−1, and the RMSE was 2.97 g kg−1 (Fig. 2d).
The scatter density and evaluation indices of specific humidity at 850 hPa between FY-3D/VASS and ERA5 in the SCSSM region [10–20°N; 110–120°E] in (a) April, (b) May, (c) June, and (d) the average of April, May, and June 2022.
The study shows that the 340 K of the regional average pseudo-equivalent potential temperature at 850 hPa is the threshold of the onset of the SCSSM (Shao et al. 2021). The FY-3D/VASS temperature and specific humidity at 850 hPa in the SCSSM region were a little bit lower than those of ERA5, on average, from April to June. The distribution of equivalent potential temperature at 850 hPa from FY-3D/VASS and ERA5 shows that, during the onset of the SCSSM in 2022 from April to June, the pseudo-equivalent potential temperature from FY-3D/VASS is slightly lower (1–2 K; Fig. 3). Before the onset of the SCSSM in April (Figs. 3a1, a2), the pseudo-equivalent potential temperature in the SCSSM region was lower than 340 K, and in May, the pseudo-equivalent potential temperature higher than 340 K controls the SCSSM region and the Bay of Bengal (Figs. 3b1, b2). In June, it further advances northward and reaches South China (Figs. 3c1, c2). The seasonal distribution and advancement of the pseudo-equivalent potential temperature higher than 340 K of FY-3D/VASS and ERA5 are consistent with each other. FY-3D/VASS data can be used to monitor, to a certain extent, the characteristics of wide air temperature and humidity changes during the onset of the SCSSM.
The monthly mean θse (K) at 850 hPa from (a1, b1, c1) ERA5 and (a2, b2, c2) FY-3D/VASS in April, May, and June 2022.
To analyze its applicability in the monitoring of the SCSSM, FY-3E/WindRAD OWV data were compared with the OWV from EUMETSAT's ASCAT on the Metop-C satellite. The period selected was from 1 April to 30 June 2022, covering the entire process of the onset of the SCSSM. Because the observation times of the two satellites were different, the observation times were approximately 2200 UTC and 1000 UTC for FY-3E and approximately 0200 UTC and 1400 UTC for Metop-C in the SCSSM region. Therefore, the data are all processed into daily averages data for evaluation, and the daily averages data are matched with spatial grid points in the SCSSM region.
In the monitoring of the SCSSM, attention is paid not only to the wind speed but also to the meridional wind and zonal wind components. Therefore, these three parameters are evaluated separately. The monthly matching sample number from April to June 2022 was approximately 20000. The evaluation of zonal wind shows that the CCs in April and May were 0.66 and 0.62, respectively (Fig. 4), and the CC in June was relatively lower at 0.52. The scattered high-density area in April was distributed between −5 m s−1 and 0 m s−1, indicating that the SCSSM region was dominated by an easterly wind. The scattered high-density area was distributed between −5 m s−1 and 5 m s−1 in May, changing to 0–5 m s−1 in June, indicating the transformation of the zonal wind before and after the onset of the SCSSM. From April to June 2022, on average, the MB of zonal wind was 0.58 m s−1, the MAE was 2.29 m s−1, the RMSE was 3.01 m s−1, and the CC was 0.70 (Fig. 4d). The evaluation of meridional wind shows that the monthly CC from April to June was above 0.75 (Fig. 5), the average CC was 0.85 in 3 months, and the MB is negative, indicating that the north wind component is slightly stronger than that of Metop-C/ASCAT. The greatest MB was in June. The MAE and RMSE of meridional wind are lower than those of zonal wind, and the difference before and after the onset of the summer monsoon is low. The average MB from April to June was −0.52 m s−1, the MAE was 2.01 m s−1, and the RMSE was 2.70 m s−1. The wind speed evaluation shows that the maximum CC was 0.87 in April (Fig. 6), the average CC from April to June was 0.79, the MB was −0.45, the MAE was 1.56, and the RMSE was 2.03 m s−1.
The scatter density and evaluation indices of ocean surface zonal wind between FY-3E/WindRAD and Metop-C/ASCAT in the SCSSM region [10–20°N; 110–120°E] in (a) April, (b) May, (c) June, and (d) the average of April, May, and June 2022.
The scatter density and evaluation indices of ocean surface meridional wind between FY-3E/WindRAD and Metop-C/ASCAT in the SCSSM region [10–20°N; 110–120°E] in (a) April, (b) May, (c) June, and (d) the average of April, May, and June 2022.
The scatter density and evaluation indices of ocean surface wind speed between FY-3E/WindRAD and Metop-C/ASCAT in the SCSSM region [10–20°N; 110–120°E] in (a) April, (b) May, (c) June, and (d) the average of April, May, and June (d) 2022.
According to the monthly average of the ocean surface wind field from April to June 2022 (Fig. 7), the distribution of the ocean surface wind from FY-3E/WindRAD and Metop-C/ASCAT was consistent, and the location and intensity of high wind speed areas were similar. In April (Figs. 7a1, a2), before the onset of the Asian summer monsoon, there was a northeast wind in the SCSSM region. The wind speed in the northeast of the SCS and the ocean east of the Philippines was relatively high, and the wind speed from FY-3E/WindRAD was slightly weaker by 1 m s−1. At this time, the cross-equatorial flow along the east coast of Africa had not been established. The Arabian Sea was controlled by an anticyclone, and the southwest wind began to appear in the ocean south of India, extending to the southwest of the Bay of Bengal. In May (Figs. 7b1, b2), during the process of the successive onset of the Asian summer monsoon in different regions, the cross-equatorial flow along the east coast of Africa was strong and turned westerly or southwesterly in the 0–10°N region, extending to the Indochina Peninsula and the northern SCS. The Bay of Bengal summer monsoon and the SCSSM were initiated. It can be seen from the distribution of the wind speed maximum area that the wind speed of FY-3E/WindRAD was slightly lower by 1 m s−1. In June (Figs. 7c1, c2), the cross-equatorial flow was further strengthened. The maximum wind speed in the Asian summer monsoon area appeared in the southwest of the Arabian Sea; this was above 11 m s−1. The Asian tropical summer monsoon region was controlled by westerly and southwesterly winds.
Monthly mean OWV wind stream and wind speed (m s−1) from (a1, b1, c1) Metop-C/ASCAT and (a2, b2, c2) FY-3E/WindRAD in April, May, and June 2022.
It can be seen from the average ocean surface wind speed difference from April to June between FY-3E/WindRAD and Metop-C/ASCAT that the average difference is negative in most areas of the Asian summer monsoon region (Fig. 8a), including the tropical Indian Ocean, south of the equator, and the western Northwest Pacific, partly because of the system deviation caused by the different observation times of the two satellites. The relatively large wind speed difference (approximately −1.4 m s−1) in the Asian summer monsoon region occurs on the ocean surfaces east of the Philippines, on the western coast of the Bay of Bengal, and in the northern Arabian Sea, and the wind speed difference is relatively small, within the range of 0–10°N. Using the hourly averaged ERA5 10-m wind speed from 1 April to 30 June 2022, the diurnal variation of wind speed in the SCSSM region shows that there is a distinct diurnal variation of wind speed ranging from approximately 3 m s−1 to 4 m s−1 (Fig. 8b). At approximately 0200 UTC and 1400 UTC, when Metop-C/ASCAT scans the SCSSM region, the wind speeds are 3.80 m s−1 and 3.60 m s−1 (3.70 m s−1 on average), and at approximately 1000 UTC and 2200 UTC, when FY-3E/WindRAD scans the SCSSM region, the wind speeds are 3.06 m s−1 and 3.53 m s−1 (3.30 m s−1 on average), which is less, by approximately 0.40 m s−1, than that at Metop-C/ASCAT observation time. Therefore, the negative wind speed difference of FY-3E/WindRAD is partly because of the system deviation caused by the different observation times of the two satellites.
(a) Average OWV wind speed difference (m s−1) between FY-3E/WindRAD and Metop-C/ASCAT from April to June 2022 and (b) the average diurnal variation of 10-m wind speed from ERA5 in April, May, and June 2022 in the SCSSM region [10–20°N; 110–120°E]; the blue and red numbers indicate Metop-C/ASCAT and FY-3E/WindRAD observation times, respectively.
The SCSSM regional daily average pseudo-equivalent potential temperature at 850 hPa shows that the value of ERA5 is slightly higher than that of FY-3D as a whole (Fig. 9a) and it is significantly higher from mid-March to mid-April. The regional average pseudo-equivalent potential temperature at 850 hPa of ERA5 in mid-March and late March exceeded 340 K. After 28 April, except for 11 and 12 May, it was greater than 340 K, meeting one of the operational indices of the onset of the SCSSM from the NCC, CMA (Shao et al. 2021). The regional average daily pseudo-equivalent potential temperature at 850 hPa of FY-3D/VASS also began to exceed 340 K on 28 April, but decreased back to below 340 K after 1 May, fluctuated from 8 to 9 May, and remained relatively stable above or near 340 K after 17 May.
The time series of daily mean (a) θse (K) at 850 hPa from FY-3D/VASS and ERA5 and (b) ocean surface zonal wind (m s−1) from FY-3E/WindRAD, Metop-C/ASCAT, and ERA5 in the SCSSM region from 1 March to 30 September 2022.
The operational monitoring index of the SCSSM of the NCC, CMA uses regional [10–20°N, 110–120°E] average zonal wind at 850 hPa. Figure 9b shows the time series of the regional average zonal wind from 1 March to 30 September 2022. It can be seen that the developing trend of the SCSSM index of FY-3E/WindRAD and Metop-C/ASCAT is consistent (10 May), and the onset date of the SCSSM is 1 day later than that of ERA5 (11 May). The zonal wind direction change during the onset of the SCSSM in 2022 was well monitored by FY-3E/WindRAD and the combined results of FY-3E/WindRAD and Metop-C/ASCAT.
The previous study shows that surface wind can be a better indicator of the onset of the Asian Summer Monsoon system than the wind at 850 hPa (Wu et al. 2013b). From the comparison of FY-3E/WinRAD OWV and ERA5 wind at 850 hPa during the onset of the SCSSM in May 2022 (Fig. 10), it can be seen that there is northeast wind near the ocean surface north of the SCSSM in the third pentad of May, during the onset of the SCSSM, but that was not seen in the wind at 850 hPa (Fig. 10a). The definition of a monsoon is generally a stable reversal of wind direction and precipitation. The northeast wind monitored by the OWV in the north of the SCS has important indicative significance for the convective activities in the summer monsoon region. In the fourth pentad of May (Fig. 10b), the southwest flow in the north of the SCSSM region is weaker than that in the third pentad of May, but the southwest wind still controls the southern part of the SCSSM region. Similarly, OWV has monitored the ocean surface's strong northeast wind, which provides important information for the convective monsoon precipitation in the north of the SCS and for determining the onset of the summer monsoon.
Average wind vectors in (a) the third pentad of May and (b) the fourth pentad of May 2022 from (red) FY-3E/WindRAD OWV and (blue) ERA5 wind at 850 hPa.
According to the NCC, CMA, the SCSSM broke out in the third pentad of May, slightly earlier than normal (the fourth pentad in May), and the intensity was close to normal or a little bit weak (note: each pentad is 5 days; e.g., the third pentad in May was from 11 to 15 May; http://cmdp.ncc-cma.net). The SCSSM monitoring indices of pseudo-equivalent potential temperature and ocean surface wind by the FY-3 meteorological satellite also showed that the onset of the SCSSM occurred in the third pentad in May. The characteristics of atmospheric parameters and the onset process of the SCSSM, before and after the onset, were analyzed using FY-3 satellites.
Previous studies show that the outbreak vortex or cyclone storm in the Bay of Bengal can trigger the onset of the SCSSM in many years (Wu et al. 2011; Ren et al. 2016; Ding and Liu 2001). Before the onset of the SCSSM in 2022, there was tropical storm activity in the Bay of Bengal of the north Indian Ocean. This severe cyclonic storm was named Asani and numbered BOB 03 by the Indian Meteorological Department and 02B by the Joint Typhoon Warning Center, USA (Figs. 11, 12). There was a tropical depression in the Bay of Bengal on 5 May. It intensified into a tropical storm, was named on 8 May, and then gradually moved to the northwest. It landed on the coast of the state of Andhra Pradesh, India, on 11 May, and then gradually weakened and dissipated. The maximum intensity reached the Category 1 tropical cyclone intensity recognized by the Joint Typhoon Warning Center and the strong cyclone intensity recognized by the Indian Meteorological Department and CMA. Asani brought strong wind and rainfall to India and Bangladesh, causing at least three deaths, but it failed to significantly alleviate the extreme hot weather in South Asia that began in the middle of March and was still developing in early May.
Tracks of Indian Ocean tropical cyclones (red) Asani and (blue) Karim in May 2022 and elevation (shaded, unit: m); the numbers indicate the times of tropical cyclone activity (e.g., 0506–1200 indicates 1200 UTC 6 May).
FY-3E/WindRAD OWV on (a1) 3 May and (b1) 8 May; the combined result of FY-3E/WindRAD and Metop/ASCAT OWV on (a2) 3 May and (b2) 8 May; and FY-4A satellite images of Indian Ocean cyclones Asani and Karim on (c) 3 May and (d) 8 May 2022 (shaded: wind speed, m s−1).
Before the onset of the SCSSM, tropical cyclone activity also occurred in the south Indian Ocean (Figs. 11, 12). A tropical low formed in the central Indian Ocean on 5 May. The system gradually developed and was named Karim on 7 May. Karim tracked southeast, entered the Australian region on 8 May, and intensified, further reaching Category 2 on the intensity scale, with 95 km h−1 sustained wind speeds, at 0600 UTC on 8 May. Karim maintained Category 2 intensity during 9 May as the system tracked steadily southward. On 10 May, Karim reached peak sustained wind speeds of 110 km h−1, just below Category 3 intensity. Early on 11 May, Karim transitioned to a subtropical system but continued to produce storm-force winds and gales, aided by the strong pressure gradient between the system and a high ridge to the south.
The combined influence of tropical cyclones Karim and Asani increased the intensity of the westerly wind over the Indian Ocean between the two cyclones, and the wind speed over the ocean to the south of the Bay of Bengal was more than 10 m s−1 in some areas, which promotes a later summer monsoon in the SCS.
Before and after the onset of the SCSSM, the distribution of the average pentad of pseudo-equivalent potential temperature of FY-3D/VASS and ocean surface wind of FY-3E/WindRAD shows that in the first pentad of May (Fig. 13), the cross-equatorial flow over the ocean surface along the east coast of Africa was established. Within the latitude range of 0–5°N, there were westerlies in the Indian Ocean and southerlies in the west of the Bay of Bengal. At this time, the SCS was controlled by the northeast wind or easterlies. The wind speed in the northern part of the SCS was strong, and there was a low-pressure circulation in the tropical area near 90–100°E south of the equator. The low-pressure circulation strengthened the westerly wind to its north. In the second pentad of May, the most typical feature was that in the Bay of Bengal and on the southern hemisphere's ocean surface. There were two tropical cyclones, named Asani and Karim, which gradually formed and developed. Affected by the strong storm Asani in the Bay of Bengal, there were easterlies or southeasterlies over the ocean to the south of the SCS and the Indochina Peninsula, merging into the storm Asani. In the third pentad of May, the tropical storm Asani in the Bay of Bengal landed and disappeared; the most obvious feature was that the pseudo-equivalent potential temperature increased in the Indian Peninsula, Bay of Bengal, and Indochina Peninsula. At the same time, the cross-equatorial flow was pulled much stronger by Asani than in the second pentad. The southwest wind controlled the Bay of Bengal and extended eastward to the SCSSM region, causing the onset of the SCSSM. In the fourth pentad of May, the southern part of the SCSSM region was continuously controlled by the southwest wind, whereas the northern part was affected by the cold air of the northeast wind. The pseudo-equivalent potential temperature in most regions was higher than 340 K.
Average pentad of FY-3D/VASS θse at 850 hPa (shaded, unit: K) and FY-3E/WindRAD OWV (vector) from (a–f) the first to sixth pentads of May 2022.
The storm in the Bay of Bengal had a pumping effect on the cross-equatorial flow, which made the westerly wind over the tropical ocean north of the equator stronger. After the cyclone storm weakened and disappeared, the strong southwest monsoon crossed the Indochina Peninsula to the SCS, causing the onset of the SCSSM. Although affected by cold air, a northeasterly wind appeared in the northern part of the SCS in the fourth pentad of May, and the strong southwesterly wind in the north Indian Ocean led the stable southwesterly wind to control the whole SCSSM region after the cold air activity. In the fifth pentad of May, the pseudo-equivalent potential temperature reached higher than 340 K, representing a warm and moist airmass that advanced to South China. Generally, a pseudo-equivalent potential temperature higher than 340 K is classified as the first sign of the summer monsoon. The entire SCS was affected by the southwest summer monsoon, and the southwest and northeast winds met over the ocean to the south of Taiwan. In the sixth pentad of May, the SCS was continuously controlled by the southwest summer monsoon, and the warm and moist airmass was further pushed northward to the Yangtze River basin.
According to the demands of the SCSSM operational monitoring service, in this paper, we conducted an evaluation of FY-3D/VASS temperature and humidity and FY-3E/WindRAD ocean surface wind data in the SCSSM region from April to June. The differences between the atmospheric parameters retrieved by the FY satellites, ERA5, and Metop-C/ASCAT were analyzed. In addition, the SCSSM operational monitoring indices were evaluated. The detailed process of the onset of the SCSSM in 2022 was shown by FY-3 satellite data. The main conclusions are as follows:
In this paper, based on the multiple vertical sounding instruments loaded on the FY polar-orbiting meteorological satellite, the changing characteristics of atmospheric temperature and humidity, before and after the onset of the SCSSM, were monitored. Based on the OWV from the new wind radar instrument on the FY-3E meteorological satellite, the wind field reversal, before and after the onset of the SCSSM, was also monitored. The application ability of the two types of satellite data in the climate monitoring of the SCSSM was demonstrated through various means of verifying the data. In addition to the real-time monitoring of atmospheric parameter changes in the SCSSM region, the polar-orbiting meteorological satellite, with global coverage, can monitor the cross-equatorial flow, warm and moist air transport, tropical depressions or cyclones in the south Indian Ocean, explosive vortices or tropical storms in the Bay of Bengal, and the triggering effect of synoptic scale systems on the onset of the summer monsoon, which are all important indicators for the establishment of the Asian summer monsoon before the onset of the SCSSM.
According to the present study, the operational climate monitoring and forecast of the SCSSM can be conducted using FY meteorological satellites, which can mutually corroborate the results from the meteorological numerical model or reanalysis data, even providing more detailed, near-real-time observation information of the SCSSM's activities. On 1 December 2022, the CMA announced that after 6 months of trial operation and the “practical” test of this year's flood season, FY-3E and its ground application systems were officially put into operation. FY-3E, together with FY-3D, will provide higher frequency and more stable observation data for the monitoring and research of the SCSSM.
Currently, NSMC, CMA FY-4A satellite datasets are used to monitor the SCSSM in operational work (Yang et al. 2017). The FY-4A AMV is used as the index to monitor the upper troposphere zonal wind direction reversal, and TBB is used to monitor the convective activities during the summer monsoon season. The addition of the FY-3E/WindRAD and FY-3D/VASS data increases the effectiveness of the monitoring of the lower-level wind field and the atmospheric temperature and humidity fields. After being applied to the operational summer monsoon monitoring, these data will improve the comprehensive monitoring capability of satellite remote sensing of the summer monsoon, including the monitoring capability of high- and low-layer dynamics, thermodynamics, and precipitation, providing more information for summer monsoon activities.
FY-3D/VASS and FY-3E/WindRAD data were provided by the China National Satellite Meteorological Center, CMA. The Metop-C/ASCAT ocean wind vector data were provided by EUMETSAT, available at https://www.eumetsat.int/. The ERA5 reanalysis data were provided by ECMWF, available at https://cds.climate.copernicus.eu, and the operational monitoring indices of the SCSSM in NCC, CMA, available at http://cmdp.ncc-cma.net/climate/monsoon.php.
We thank the anonymous reviewers for their helpful suggestions for further improving this manuscript. This research is supported by the National Key Research and Development Program of China (2021YFB 3900400) and the National Natural Science Foundation of China (42175014). We acknowledge EUMETSAT and ECMWF for providing the data.
