Is an onset vortex important for monsoon onset over Kerala?

Kumar, M. R. Ramesh; Sankar, Syam; Reason, C. J. C.

doi:10.1007/s00704-012-0598-x

Cited by 7 publications

(5 citation statements)

References 23 publications

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“…At lag-3 and monsoon onset date, confined upper (lower) level divergence (convergence) can be marked over southern AS, which can be related to the monsoon onset vortex 7 . A study by 49 suggests that monsoon onset vortex builds up moisture and strengthening of westerlies over AS needed for setting up of MoK. The positive and negative VP200 anomalies show further eastward movement over Pacific.…”

Section: Resultsmentioning

confidence: 99%

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance

Pradhan

Rao

Srivastava

et al. 2017

Sci Rep

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Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2–3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

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Section: Resultsmentioning

confidence: 99%

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance

Pradhan

Rao

Srivastava

et al. 2017

Sci Rep

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“…This shows that anomalously warm SSTs although important, may not be the only governing factor controlling the genesis of cyclone during the onset phase of ISM. This is in line with previous studies which show that SST alone may not play a dominant role in the genesis of the cyclone (Sikka and Vihar, 2005; Ramesh Kumar et al ., 2012). It signifies our findings from the earlier discussion that the changes in atmospheric circulation play an important role in the genesis of the cyclone during the onset phase of ISM.…”

Section: Resultsmentioning

confidence: 99%

Tropical cyclones over the Arabian Sea during the monsoon onset phase

Dhavale

Mujumdar

Roxy

et al. 2021

Intl Journal of Climatology

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Generally, monsoon conditions are unfavourable for cyclogenesis in the Arabian Sea due to the strong vertical wind shear present over the basin which prevents the vertical development of cyclones. However, there are instances where tropical cyclones form over the basin during the onset phase of the Indian summer monsoon (ISM). The current study examines the evolution of the synoptic conditions in the years during 1979–2019 in which a cyclone forms during the onset phase of the ISM. The effect of various atmospheric and oceanic factors, the modulation of wind circulation over the Indian subcontinent and the north Indian Ocean region due to the possible influence of tropical and extratropical weather systems has been taken into consideration. Our analysis indicates that a weak mean monsoonal wind circulation caused by the southward intrusion of subtropical westerlies (at 200 hPa) is conducive for cyclogenesis over the Arabian Sea during the monsoon onset phase. Such a weak onset phase of the monsoon, coupled with the seasonal warm SSTs, may lead to cyclone formation in the Arabian Sea.

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“…Moreover, the absence of a warm SST region can preclude the formation and maintenance of MOV even if the environment is favourable (Deepa et al, 2012). Similarly, Kumar et al (2012) showed that the presence of the mini-warm-pool is not a sufficient condition for the formation of MOV in the Arabian Sea. Interestingly, the frequency of MOV occurrences has been decreasing in recent decades despite the increase in the global SST (Deepa and Oh, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, Kumar et al . (2012) showed that the presence of the mini‐warm‐pool is not a sufficient condition for the formation of MOV in the Arabian Sea. Interestingly, the frequency of MOV occurrences has been decreasing in recent decades despite the increase in the global SST (Deepa and Oh, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Subsequent studies on BoB MOVs have adopted this definition (Li et al, 2016). However, there is a difference in the number of MOVs over the Arabian Sea, as seen in studies such as Kumar et al (2012) and Deepa and Oh (2014) for the same period of 1988-2005 (refer to Table 1 of Kumar et al, 2012;Deepa and Oh, 2014). This indicates a lack of consistency while defining/identifying the MOVs over the Arabian Sea which led to differences in number of MOVs from study to study.…”

Section: Introductionmentioning

confidence: 99%

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Machine learning and dynamics based error‐index method for the detection of monsoon onset vortex over the Arabian Sea: Climatology and composite structures

Sasanka

Osuri

Niyogi

2023

Quart J Royal Meteoro Soc

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Monsoon onset vortex (MOV) forms over the Arabian Sea near the northern flank of the low-level jet during the monsoon onset over Kerala (MOK). The study concerns the development and evaluation of an algorithm for detecting and tracking MOVs in regional/global analyses. The first step involves preparing the first-guess database of MOV locations based on geopotential height, surface and 850 hPa wind magnitude and circulation from ERA5 reanalysis for 1982-2020. Three different approaches: (a) error-index of MOV, (b)machine-learning (ML), and (c) combination of error-index and ML models, are employed to detect MOV. The error-index method, in which the detected vortex is compared with the idealized vortex, achieves an accuracy of 0.6 with a 0.95 true-positive-rate and 0.55 false-positive-rate. The best ML models can identify the MOVs in the training samples with maximum accuracy of 0.99. However, their accuracy is limited in tracking the MOVs continuously in the global analyses as they are not trained with wind circulation. The combined error-index and ML models could detect all the 27 observed MOVs in the ERA5 reanalysis with 5 false-positives. This approach is tested on IMDAA reanalysis, and the success rate is 0.79 with 6 false-positives. Temporal analyses show that ∼95% of the MOVs occur during −10 to +20 days from MOK. Composite structures indicate that the MOVs exhibit higher sea-surface temperatures (>0.3 • C) in the forward sector with 85% cloud cover in the left-rear sector. Rainfall of 4-5 mm⋅hr −1 is seen in the left sector. Upper-level (700-200 hPa) warm core (>3.5 • C) and lower-level (1000-700 hPa) cold-core (<1 • C) is evident. The composite structures of MOVs are almost similar to that of monsoon depressions with higher asymmetry in the forward-rear sectors. This study may help explore future projections of MOV activity from climate models and its relationship with monsoon rainfall activity.

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Is an onset vortex important for monsoon onset over Kerala?

Cited by 7 publications

References 23 publications

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance

Tropical cyclones over the Arabian Sea during the monsoon onset phase

Machine learning and dynamics based error‐index method for the detection of monsoon onset vortex over the Arabian Sea: Climatology and composite structures

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