Towards understanding the unusual Indian monsoon in 2009

The Indian summer monsoon season of 2009 commenced with a massive deficit in all-India rainfall of 48% of the average rainfall in June. The all-India rainfall in July was close to the normal but that in August was deficit by 27%. In this paper, we first focus on June 2009, elucidating the special features and attempting to identify the factors that could have led to the large deficit in rainfall. In June 2009, the phase of the two important modes, viz., El Niño and Southern Oscillation (ENSO) and the equatorial Indian Ocean Oscillation (EQUINOO) was unfavourable. Also, the eastern equatorial Indian Ocean (EEIO) was warmer than in other years and much warmer than the Bay. In almost all the years, the opposite is true, i.e., the Bay is warmer than EEIO in June. It appears that this SST gradient gave an edge to the tropical convergence zone over the eastern equatorial Indian Ocean, in competition with the organized convection over the Bay. Thus, convection was not sustained for more than three or four days over the Bay and no northward propagations occurred. We suggest that the reversal of the sea surface temperature (SST) gradient between the Bay of Bengal and EEIO, played a critical role in the rainfall deficit over the Bay and hence the Indian region. We also suggest that suppression of convection over EEIO in association with the El Niño led to a positive phase of EQUINOO in July and hence revival of the monsoon despite the El Niño. It appears that the transition to a negative phase of EQUINOO in August and the associated large deficit in monsoon rainfall can also be attributed to the El Niño.     

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.     

On the impacts of ENSO and Indian Ocean dipole events on sub-regional Indian summer monsoon rainfall

The relative impacts of the ENSO and Indian Ocean dipole (IOD) events on Indian summer (June–September) monsoon rainfall at sub-regional scales have been examined in this study. GISST datasets from 1958 to 1998, along with Willmott and Matsuura gridded rainfall data, all India summer monsoon rainfall data, and homogeneous and sub-regional Indian rainfall datasets were used. The spatial distribution of partial correlations between the IOD and summer rainfall over India indicates a significant impact on rainfall along the monsoon trough regions, parts of the southwest coastal regions of India, and also over Pakistan, Afghanistan, and Iran. ENSO events have a wider impact, although opposite in nature over the monsoon trough region to that of IOD events. The ENSO (IOD) index is negatively (positively) correlated (significant at the 95% confidence level from a two-tailed Student t-test) with summer monsoon rainfall over seven (four) of the eight homogeneous rainfall zones of India. During summer, ENSO events also cause drought over northern Sri Lanka, whereas the IOD events cause surplus rainfall in its south. On monthly scales, the ENSO and IOD events have significant impacts on many parts of India. In general, the magnitude of ENSO-related correlations is greater than those related to the IOD. The monthly-stratified IOD variability during each of the months from July to September has a significant impact on Indian summer monsoon rainfall variability over different parts of India, confirming that strong IOD events indeed affect the Indian summer monsoon.

Interannual variability of summer monsoon rainfall over Myanmar

Observed summer (May–October) rainfall in Myanmar for the period 1981–2010 was used to investigate the interannual variability of summer monsoon rainfall over Myanmar. Empirical orthogonal function, the sequential Mann-Kendall test, power spectrum analysis, and singular value decomposition (SVD) were deployed in the study. Results from spectral analysis showed that the variability of rainfall over Myanmar exhibits a 2- to 6-year cycle. An abrupt change in rainfall over the country was noted in 1992. There was a notable increasing rainfall trend from 1989. After the sudden change, the mean rainfall increased by 36.1 mm, compared with the mean rainfall before the sudden change, and was associated with a rise in temperature of about 0.2 °C. An increase in heavy rainfall days was observed from the early 1990s to 2010. IOD and ENSO play an important role in the interannual variability of the summer rainfall over Myanmar. The covariability between rainfall over Myanmar and Indian Ocean SST generally suggests that a positive IOD mode is associated with suppressed rainfall in the central and northern parts of Myanmar. During a negative IOD mode, nearly the whole Myanmar experiences enhanced rainfall, which is associated with devastating socioeconomic impacts. The covariability between the rainfall over Myanmar and the sea surface temperature in the Pacific Ocean in the first and second SVD modes was dominated by warming in the east and central Pacific—an El Niño-like pattern—resulting in dry conditions in central Myanmar.     

Tropical cyclones over north Indian Ocean during El-Niño Modoki years

Tropical cyclones are the most hazardous weather systems, which form over warm ocean waters. The frequencies of tropical cyclones show variabilities over all the oceanic basins, during the El-Niño and El-Niño Modoki years. Recent studies have shown significant impact of air–sea interaction processes like El-Niño and El-Niño Modoki on the cyclone activity over different ocean basins. The results suggest in most cases, El-Niño events suppress the formation of cyclones over various basins. A recent study indicated that concurrent occurrence of El-Niño Modoki and positive Indian Ocean dipole (IOD) events can generate more cyclones over north-west Pacific. We propose to study the impact of El-Niño Modoki events on the formation of tropical cyclones over north Indian Ocean (NIO). Our present study suggests that the cyclogenesis over the NIO is a complex phenomenon, as it is influenced by several coupled ocean atmospheric phenomena such as El-Niño, El-Niño Modki, IOD and Madden–Julian oscillation.     

Seasonal forecasting of tropical cyclogenesis over the North Indian Ocean

Over the North Indian Ocean (NIO) and particularly over the Bay of Bengal (BoB), the post-monsoon season from October to December (OND) are known to produce tropical cyclones, which cause damage to life and property over India and many neighbouring countries. The variability of frequency of cyclonic disturbances (CDs) during OND season is found to be associated with variability of previous large-scale features during monsoon season from June to September, which is used to develop seasonal forecast model of CDs frequency over the BoB and NIO based on principal component regression (PCR). Six dynamical/thermodynamical parameters during previous June–August, viz., (i) sea surface temperature (SST) over the equatorial central Pacific, (ii) sea level pressure (SLP) over the southeastern equatorial Indian Ocean, (iii) meridional wind over the eastern equatorial Indian Ocean at 850 hPa, (iv) strength of upper level easterly, (v) strength of monsoon westerly over North Indian Ocean at 850 hPa, and (vi) SST over the northwest Pacific having significant and stable relationship with CDs over BoB in subsequent OND season are used in PCR model for a training period of 40 years (1971–2010) and the latest four years (2011–2014) are used for validation. The PCR model indicates highly significant correlation coefficient of 0.77 (0.76) between forecast and observed frequency of CD over the BoB (NIO) for the whole period of 44 years and is associated with the root mean square error and mean absolute error ≤ 1 CD. With respect to the category forecast of CD frequency over BoB and NIO, the Hit score is found to be about 63% and the Relative Operating Curves (ROC) for above and below normal forecast is found to be having much better forecast skill than the climatology. The PCR model performs very well, particularly for the above and below normal CD year over the BoB and the NIO, during the test period from 2011 to 2014.     

东北印度洋源汇过程及古环境与古季风演化

东北印度洋地理位置独特,其沉积物记录了青藏高原隆升及孟加拉扇的“源-汇”过程、印度季风与东亚季风的“海-气”交互作用、印-太暖池热传输的演变与高纬气候之间的相位关系等关键信息,是喜马拉雅地区“构造-气候-沉积”耦合演化的良好记录载体,是探讨多圈层相互作用、探索古气候与古环境演化的理想“窗口”。本文系统总结了近年来有关东北印度洋季风与表层环流特征、沉积物组成及物源、气候环境演化以及环境磁学记录等方面的研究进展。分析表明,东北印度洋为典型的季风风场,表层环流受季风影响强烈,夏季和冬季环流差异明显。沉积物类型丰富,包括河流输运而来的陆源碎屑、钙质和硅质为主的生物沉积以及火山物质等。但目前对于该区域的沉积物的具体组成、“源-汇”过程、迁移历史、季风演化与青藏高原隆升、高纬气候变化之间相互关系等方面的认识尚存在较大的分歧。同时,受样品获取难度大、磁学信号稀释严重等因素的限制,环境磁学作为一种在示踪沉积物物质来源、恢复古气候和古环境等方面被普遍认可的技术手段,在东北印度洋区并没有得到充分的发挥与应用。因此,未来需要在前人研究的基础上,将目光向东北印度洋更南、更深处延伸,对其“源-汇”过程进行全面分析。在研究方法上进一步拓展,采用更高精度的技术手段提取磁学信号,加大环境磁学的应用,寻找有效的替代性指标,解决该地区季风演化、古海洋环境变化等气候环境问题,为该地区环境气候研究提供新认识。并尝试开展地磁场长期变化(paleosecular variation, PSV)研究,建立东北印度洋的PSV记录,辅助修正全球地磁场模型,探究地球深部动力过程。     

Early prediction of onset of south west monsoon from ERS-1 scatterometer winds

Detailed analysis of the surface winds over the Indian Ocean derived from ERS-1 scatterometer data during the years 1993 and 1994 has been used to understand and unambiguously identify the onset phase of south-west monsoon. Five day (pentad) averaged wind vectors for the period April to June during both years have been examined to study the exact reversal of wind direction as well as the increase in wind speed over the Arabian Sea in relation to the onset of monsoon over the Indian west coast (Kerala). The related upper level humidity available from other satellites has also been analysed. The results of our analysis clearly show a consistent dramatic reversal in wind direction over the western Arabian Sea three weeks in advance of the onset of monsoon. The wind speed shows a large increase coinciding with the onset of monsoon. These findings together show the dominant role of sea surface winds in establishing the monsoon circulation. The study confirms that the cross equatorial current phenomenon becomes more important after the onset of monsoon.     

Evaluation of operational tropical cyclone intensity forecasts over north Indian Ocean issued by India Meteorological Department

India Meteorological Department (IMD) introduced the objective tropical cyclone (TC) intensity forecast valid for next 24 h over the north Indian Ocean (NIO) in 2003 and extended up to 72 h in 2009. In this study, an attempt is made to evaluate the TC intensity forecast issued by IMD during 2005–2011 (7 years) by calculating the absolute error (AE), root mean square error (RMSE) and skill in intensity forecast in terms of maximum sustained surface wind (MSW). The accuracy of TC intensity forecast has been analysed with respect to basin of formation (Bay of Bengal, Arabian Sea and NIO as whole), season of formation (pre-monsoon and post-monsoon seasons), intensity of TCs (cyclonic storm and severe cyclonic storm or higher intensities) and type of track of TCs (climatological/straight moving and recurving/looping type). The study shows that the average AE (RMSE) in intensity forecast is about 11(14), 14(19) and 20(26) knots, respectively, for 24-, 48- and 72-h forecasts over the NIO as a whole during 2009–2011. The skill of intensity forecast is about 44 %(48 %), 60 %(58 %) and 60 %(65 %) for 24-, 48- and 72-h forecasts during 2009–2011 with respect to AE (RMSE). There is no significant improvement in terms of reduction in AE and RMSE of MSW forecast over the NIO like that over the northwest Pacific and northern Atlantic Oceans during 2005–2011. However, the skill in intensity forecast compared to persistence method has significantly improved by about 6 %(10 %) and 9 %(8 %) per year, respectively, for 12- and 24-h forecasts considering the AE (RMSE) during 2005–2011. There is also significant increasing trend in percentage of 24-h intensity forecasts with error of 10 knots or less during 2005–2011.     

Medium-range forecast of cyclogenesis over North Indian Ocean with multilayer perceptron model using satellite data

An attempt is made in this study to develop a model to forecast the cyclonic depressions leading to cyclonic storms over North Indian Ocean (NIO) with 3 days lead time. A multilayer perceptron (MLP) model is developed for the purpose and the forecast quality of the model is compared with other neural network and multiple linear regression models to assess the forecast skill and performances of the MLP model. The input matrix of the model is prepared with the data of cloud coverage, cloud top temperature, cloud top pressure, cloud optical depth, cloud water path collected from remotely sensed moderate resolution imaging spectro-radiometer (MODIS), and sea surface temperature. The input data are collected 3 days before the cyclogenesis over NIO. The target output is the central pressure, pressure drop, wind speed, and sea surface temperature associated with cyclogenesis over NIO. The models are trained with the data and records from 1998 to 2008. The result of the study reveals that the forecast error with MLP model varies between 0 and 7.2 % for target outputs. The errors with MLP are less than radial basis function network, generalized regression neural network, linear neural network where the errors vary between 0 and 8.4 %, 0.3 and 24.8 %, and 0.3 and 32.4 %, respectively. The forecast with conventional statistical multiple linear regression model, on the other hand, generates error values between 15.9 and 32.4 %. The performances of the models are validated for the cyclonic storms of 2009, 2010, and 2011. The forecast errors with MLP model during validation are also observed to be minimum.     

Relative role of sea surface temperature and snow on Indian summer monsoon seasonal simulation using a GCM

Indian summer monsoon is a global scale phenomenon controlled by different land, ocean, and atmospheric parameters. Sea surface temperature (SST) and snow are two of the major parameters, which may alter the spatial and temporal patterns of circulation and rainfall during Indian summer monsoon. In the current paper, we study the monsoon variability using long integrations (20 years) of the Indian Institute of Technology Delhi (IITD) Spectral model at T80L18 resolution with observed and climatological SST and snow. Study shows response of IITD GCM in simulating the Indian summer monsoon rainfall and circulation relative to the snow and SST as boundary conditions. The model’s response to SST and snow is examined by conducting four types of experiments by varying observed and climatological values of snow and SST. This paper discusses the seasonal total rainfall for country as a whole and 850 and 200 hPa wind for the period of 20 years starting from 1985 to 2004. The model has been integrated in the ensemble mode with five different initial conditions from the last week of April and first week of May. The model is able to capture the climatological patterns of seasonal total rainfall and averaged wind at lower and upper levels. Observed snow in the presence of climatological SST as a boundary condition shows much impact on rainfall and circulation than observed SST in the presence of climatological snow. Model performance is good in simulating the normal and excess monsoon conditions; it shows poor skill in capturing deficit monsoon years.     

Potential predictability of wet/dry spells transitions during extreme monsoon years: optimism for dynamical extended range prediction

The duration and extreme fluctuations of prolonged wet or dry spells associated with intraseasonal variability during extreme monsoon have devastating impacts on agrarian-based economy over Indian subcontinent. This study examines the potential predictability limit of intraseasonal transitions between rainy to non-rainy phases (i.e., active to break phases) or vice versa over central Indian region during extreme monsoon using very high-resolution (0.25° × 0.25°) daily rainfall datasets. The present study reveals that the transitions from both active to break and break to active conditions are more predictable by ~8 days during the weak monsoon (WM) years compared to the strong monsoon (SM) years. Such asymmetric behavior in the limit of predictability could be linked to the distinct differences in the large-scale seasonal mean background instability during SM and WM years. The achievability of such predictability is further evaluated in a state-of-the-art climate model, the climate forecast system (CFSv2). It is demonstrated that the observed asymmetry in predictability limit could be reproducible in the CFSv2 model, irrespective of its spatial resolution. This study provides impetus for useful dynamical prediction of wet/dry spells at extended range during the extreme monsoon years.     

Unusual circulation pattern during Indian summer monsoon failure in July 2002 and June 2009

The circulation patterns over the Indian Ocean and the surrounding continents have been studied during June 2009 and July 2002 to explain the failure of Indian summer monsoon (ISM) rainfall. This study presents evidences that the failure of the ISM during these 2?months was probably due to the development of cyclonic circulation anomaly over the Western Asia and anticyclonic circulation anomalies downstream of Eastern Asia. These circulation anomalies were associated with the equatorward advection of cold air up to 10°N. This may be due to the equatorward intrusion of midlatitude Rossby waves. We hypothesize that the intrusion of midlatitude Rossby wave is responsible for breaking the east?Cwest circulation cell over the Indian region into two cells and weakening it. The weak east?Cwest cell reduces the strength of the easterly wind field usually present over the monsoonal region, thus reducing the cross-equatorial moisture transport into the Indian subcontinent and decreasing monsoon rainfall.     

Simulation of a flood producing rainfall event of 29 July 2010 over north-west Pakistan using WRF-ARW model

Simulation of a flood producing rainfall event of 29 July 2010 over north-west Pakistan has been carried out using the Weather Research and Forecasting (WRF) model. This extraordinary rainfall event was localized over north-west Pakistan and recorded 274 mm of rainfall at Peshawar (34.02°N, 71.58°E), within a span of 24 h on that eventful day where monthly July normal rainfall is only 46.1 mm. The WRF model was run with the triple-nested domains of 27, 9, and 3 km horizontal resolution using Kain–Fritsch cumulus parameterization scheme having YSU planetary boundary layer. The model performance was evaluated by examining the different simulated parameters. The model-derived rainfall was compared with Pakistan Meteorological Department–observed rainfall. The model suggested that this flood producing heavy rainfall event over north-west region of Pakistan might be the result of an interaction of active monsoon flow with upper air westerly trough (mid-latitude). The north-west Pakistan was the meeting point of the southeasterly flow from the Bay of Bengal following monsoon trough and southwesterly flow from the Arabian Sea which helped to transport high magnitude of moisture. The vertical profile of the humidity showed that moisture content was reached up to upper troposphere during their mature stage (monsoon system usually did not extent up to that level) like a narrow vertical column where high amounts of rainfall were recorded. The other favourable conditions were strong vertical wind shear, low-level convergence and upper level divergence, and strong vorticity field which demarked the area of heavy rainfall. The WRF model might be able to simulate the flood producing rainfall event over north-west Pakistan and associated dynamical features reasonably well, though there were some spatial and temporal biases in the simulated rainfall pattern.     

Relationship between atmospheric conditions at Dhaka, Bangladesh, and rainfall at Cherrapunjee, India

To improve flood forecasting, the understanding of the atmospheric conditions associated with severe rainfall is crucial. We analysed the atmospheric conditions at Dhaka, Bangladesh, using upper-air soundings. We then compared these conditions with daily rainfall variations at Cherrapunjee, India, which is a main source of floodwater to Bangladesh, and a representative sample of exceptionally heavy rainfall events. The analysis focussed on June and July 2004. June and July are the heaviest rainfall months of the year at Cherrapunjee. July 2004 had the fourth-heaviest monthly rainfall of the past 31 years, and severe floods occurred in Bangladesh. Active rainfall periods at Cherrapunjee corresponded to “breaks” in the Indian monsoon. The monsoon trough was located over the Himalayan foothills, and strong westerly winds dominated up to 7 km at Dhaka. Near-surface wind below 1 km had southerly components, and the wind profile had an Ekman spiral structure. The results suggest that rainfall at Cherrapunjee strongly depends on the near-surface wind speed and wind direction at Dhaka. Lifting of the near-surface southerly airflow by the Meghalaya Plateau is considered to be the main contributor to severe rainfall at Cherrapunjee. High convective available potential energy (CAPE) also contributes to intense rainfall.     

Meteorological features associated with unprecedented precipitation over India during 1st week of March 2015

Unprecedented precipitation along with heavy falls occurred over many parts of India from 28th February to 2nd March 2015. Many of the stations of northwest and central India received an all time high 24 hr cumulative precipitation of March during this period. Even the national capital, New Delhi, broke all the previous historical 24 hr rainfall records of the last 100 years to the rainfall record in March 2015. Due to this event, huge loss to agricultural and horticultural crops occurred in several parts of India. In the present study, an attempt is made to understand the various meteorological features associated with this unprecedented precipitation event over India. It occurred due to the presence of an intense western disturbance (WD) over Afghanistan and neighbouring areas in the form of north–south oriented deep trough in westerlies in middle and upper tropospheric levels with its southern end deep in the Arabian Sea, which pumped huge moisture feed over Indian region. Also, there was a jet stream with core wind speed up to 160 knots that generated high positive divergence at upper tropospheric level over Indian region; along with this there was high magnitude of negative vertical velocity and velocity convergence were there at middle tropospheric level. It caused intense upward motion and forced lower levels air to rise and strengthen the lower levels cyclonic circulations (CCs)/Lows. Moreover, the induced CCs/Lows at lower tropospheric levels associated with WD were more towards south of its normal position. Additionally, there was wind confluence over central parts of India due to westerlies in association with WD and easterlies from anticyclone over north Bay of Bengal. Thus, intense WD along with wind confluence between westerlies and easterlies caused unprecedented precipitation over India during the 1st week of March 2015.     

Monthly-mean wind stress along the coast of the north Indian Ocean

Monthly-mean wind stress and its longshore and offshore components have been computed using the bulk aerodynamic method for each of a string of 36 two-degree-latitude by two-degree-longitude squares along the coast of the north Indian Ocean. The data source for the computation is the sixty-year mean resultant winds of Hastenrath and Lamb. The main features exhibited by the components, taking the longshore components as positive (negative) when the Ekman transport is away from (towards) the coast, are: (1) Along the coasts of Somalia and Arabia, the magnitude of the wind stress is among the highest in the north Indian Ocean, and its direction is generally parallel to the coastline. This results in a longshore component which is large (as high as 2·5 dyne/cm²) and positive during the southwest monsoon, and weaker (less than 0·6 dyne/cm²) and negative during the northeast monsoon. (2) Though weak (less than 0·2 dyne/cm²) during the northeast monsoon, the monthly-mean longshore component along the west coast of India remains positive throughout the year. The magnitude of the offshore component during the southwest monsoon is much larger than that of the longshore component. (3) The behaviour of the wind stress components along the east coast of India is similar to that along the Somalia-Arabia coast, but the magnitudes are much smaller.     

Characteristics of certain surface meteorological parameters in relation to the interannual variability of Indian summer monsoon

With an objective to understand the influence of surface marine meteorological parameters in relation to the extreme monsoon activity over the Indian sub-continent leading to flood/drought, a detailed analysis of the sea level pressure over the Southern Hemisphere and various surface meteorological parameters over the Indian seas is carried out. The present study using the long term data sets (Southern Hemispheric Sea Level Pressure Analysis; Comprehensive Ocean Atmospheric Data Set over the Indian Seas; Surface Station Climatology Data) clearly indicates that the sea surface temperature changes over the south eastern Pacific (El Ninõ/La Niña) have only a moderate impact (not exceeding 50% reliability) on the Indian summer monsoon activity. On the other hand, the sea level pressure anomaly (SOI) over Australia and the south Pacific has a reasonably high degree of significance (more than 70%) with the monsoon activity over India. However, these two parameters (SLP and SST) do not show any significant variability over the Indian seas in relation to the summer monsoon activity. Over the Indian seas, the parameters which are mainly associated with the convective activity such as cloud cover, relative humidity and the surface wind were found to have a strong association with the extreme monsoon activity (flood/drought) and thus the net oceanic heat loss over the Indian seas provides a strong positive feed-back for the monsoon activity over India.     

Global features of sea-level pressure distribution in April and July associated with contrasting situations of Indian summer monsoon

Global sea-level pressure distribution has been analysed for the months of April and July for 5 years of contrasting situations of Indian summer monsoon, comprising of two drought years (1972 and 1974), a flood year (1975) and two normal monsoon years (1970 and 1973). Mean monthly sea-level pressure data at about 400 stations have been used in the study. Prominent features of pressure departures from long-term normals have also been noted. It is observed that the month of April shows more prominent contrasting features than July. In April, the high pressure centres over USSR and the North Pacific move considerably eastward during poor monsoon years, while a breakaway cell of Icelandic Low goes deep south. Both the high pressure areas over south Indian Ocean and Australia are stronger in good monsoon years. In July, the subtropical high pressure zone over the southern Indian Ocean is stronger and the Australian high is more eastward, in good monsoon years.     

Storm surges in the Singapore Strait due to winds in the South China Sea

Among the semi-enclosed basins of the world ocean, the South China Sea (SCS) is unique in its configuration as it lies under the main southwest-northeast pathway of the seasonal monsoons. The northeast (NE) monsoon (November–February) and southwest (SW) monsoon (June–August) dominate the large-scale sea level dynamics of the SCS. Sunda Shelf at the southwest part of SCS tends to amplify Sea Level Anomalies (SLAs) generated by winds over the sea. The entire region, bounded by Gulf of Thailand on the north, Karimata Strait on the south, east cost of Peninsular Malaysia on the west, and break of Sunda Shelf on the east, could experience positive or negative SLAs depending on the wind direction and speed. Strong sea level surges during NE monsoon, if coincide with spring tide, usually lead to coastal floods in the region. To understand the phenomena, we analyzed the wind-driven sea level anomalies focusing on Singapore Strait (SS), laying at the most southwest point of the region. An analysis of Tanjong Pagar tide gauge data in the SS, as well as satellite altimetry and reanalyzed wind in the region, reveals that the wind over central part of SCS is arguably the most important factor determining the observed variability of SLAs at hourly to monthly scales. Climatological SLAs in SS are found to be positive, and of the order of 30 cm during NE monsoon, but negative, and of the order of 20 cm during SW monsoon. The largest anomalies are associated with intensified winds during NE monsoon, with historical highs exceeding 50 cm. At the hourly and daily time-scales, SLA magnitude is correlated with the NE wind speed over central part of SCS with an average time lag of 36–42 h. An exact solution is derived by approximating the elongated SCS shape with one-dimensional two-step channel. The solution is utilized to derive simple model connecting SLAs in SS with the wind speeds over central part of SCS. Due to delay of sea level anomaly in SS with respect to the remote source at SCS, the simplified solutions could be used for storm surge forecast, with a lead time exceeding 1 day.