North Indian Ocean (NIO), which comprises of Bay of Bengal (BoB) and Arabian Sea (AS) basins, is one of the highly potential regions for Tropical Cyclones (TCs) in the world. Significant improvements have been achieved in the prediction of the movement of TCs, since the last decade. However, the prediction of sudden intensity changes becomes a challenging task for the research and operational meteorologists. Hence, the present study focuses on finding the climatological characteristics of such intensity changes over NIO regions. Rapid Intensification (RI) is defined as the 24-h maximum sustained surface wind speed rate equal to 30 knots (15.4 ms−1). The results suggest that the TCs formed over the NIO basin are both seasonal and basin sensitive. Since 2000, a significant trend is observed in RI TCs over the basin. At least one among three cyclones getting intensified is of RI category. More number of RI cases have been identified in the BoB basin than the AS. The post-monsoon season holds more RI and rapid decay cases, with 63% and 90% contribution. Most of the TCs are attaining RI onset in their initial stage. Further, India is receiving more landfalling RI TCs, followed by Bangladesh and Oman. The east coast of India, Tamil Nadu, and Andhra Pradesh are the most vulnerable states to these RI TCs. The cyclogenesis locations associated with RI cases hold higher moisture, and sea surface temperature as compared to the Non-RI cases.
This study aimed to understand the microphysical processes that affect rapid intensity changes of tropical cyclones (TCs) over the Bay of Bengal (BoB). Four representative TCs were simulated using the Weather Research and Forecasting model with storm tracking nested configuration (at 9‐km and 3‐km resolution). Results indicate that the inner‐core heating strongly correlated (r > 0.85) with the precipitated compared to non‐precipitated hydrometeors. Furthermore, the vertical distribution of hydrometeors and heating is dependent on inner‐core updrafts and relative humidity. A novel composite analysis of microphysical processes indicates that the warmer (2 K) inner core is close to saturation (>90%) with excess water vapor (>2–3 × 10−3 kg·kg−1), which enhances the latent heat release (LHR) through condensation below the freezing level during the rapid intensification (RI) onset. In addition, during RI, strong updrafts transport the water vapor (>2 × 10−3 kg·kg−1) and cloud liquid water (2.5 × 10−4 kg·kg−1) to above freezing level, and enhance the LHR because of deposition and freezing respectively. The increased precipitating particles in the saturated inner core also enhance LHR. The symmetric convection structured by the atmospheric moisture causes the formation of prolonged RI episodes, as seen in TC Phailin. During rapid weakening (RW), asymmetric and relatively fewer hydrometeors are evident, along with the presence of weak updrafts and strong shear. The dry‐air intrusion into the inner core also causes the cooling processes (evaporation and sublimation). The enhancement or reduction of moist static energy and potential vorticity is associated with increased or reduced LHR in the TC rapid intensity changes.
The present study focuses on the performance-based comparison of simulations carried out using nudging (NUD) technique and three-dimensional variational (3DVAR) data assimilation system (3DV) of a heavy rainfall event occurred during 25-28 June 2005 along the west coast of India. The Indian conventional and nonconventional observations are used in the 3DV experiment. Three numerical experiments are conducted using WRF modeling system, the model is integrated upto 54 hours from the initial time 0000 UTC of 25 June 2005. It is noticed that the meteorological parameters are improved in the resulting high-resolution analyses prepared by NUD and 3DV compared to without data assimilation experiment (i.e., called CNTL experiment). However, after the successful inclusion of observations using the 3DVAR data assimilation technique, the model is able to simulate better structure of the convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC) than the NUD experiment and well correlated with the observations. The simulated location and intensity of rainfall is also improved in 3DV simulation as compared with other experiments. Similar results are noticed in the root mean squar errors, correlation coefficients, and Equitable Threat Scores between TRMM and model simulated rainfall for all the three experiments.
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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