Sensitivity of Microphysical Schemes on the Simulation of Post-Monsoon Tropical Cyclones over the North Indian Ocean

Tropical Cyclones (TCs) are the most disastrous natural weather phenomenon, that have a significant impact on the socioeconomic development of the country. In the past two decades, Numerical Weather Prediction (NWP) models (e.g., Advanced Research WRF (ARW)) have been used for the prediction of TCs. Extensive studies were carried out on the prediction of TCs using the ARW model. However, these studies are limited to a single cyclone with varying physics schemes, or single physics schemes to more than one cyclone. Hence, there is a need to compare different physics schemes on multiple TCs to understand their effectiveness. In the present study, a total of 56 sensitivity experiments are conducted to investigate the impact of seven microphysical parameterization schemes on eight post-monsoon TCs formed over the North Indian Ocean (NIO) using the ARW model. The performance of the Ferrier, Lin, Morrison, Thompson, WSM3, WSM5, and WSM6 are evaluated using error metrics, namely Mean Absolute Error (MAE), Mean Square Error (MSE), Skill Score (SS), and average track error. The results are compared with Indian Meteorological Department (IMD) observations. From the sensitivity experiments, it is observed that the WSM3 scheme simulated the cyclones Nilofar, Kyant, Daye, and Phethai well, whereas the cyclones Hudhud, Titli, and Ockhi are best simulated by WSM6. The present study suggests that the WSM3 scheme can be used as the first best scheme for the prediction of post-monsoon tropical cyclones over the NIO.

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Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-0313.1 ◽

2013 ◽

Vol 52 (11) ◽

pp. 2476-2492 ◽

Cited By ~ 50

Author(s):

Krishna K. Osuri ◽

U. C. Mohanty ◽

A. Routray ◽

M. Mohapatra ◽

Dev Niyogi

Keyword(s):

High Resolution ◽

Indian Ocean ◽

Real Time ◽

Tropical Cyclones ◽

North Indian Ocean ◽

Track Forecast ◽

Forecast Errors ◽

The North ◽

Arw Model ◽

The Impact

AbstractThe performance of the Advanced Research version of the Weather Research and Forecasting (ARW) model in real-time prediction of tropical cyclones (TCs) over the north Indian Ocean (NIO) at 27-km resolution is evaluated on the basis of 100 forecasts for 17 TCs during 2007–11. The analyses are carried out with respect to 1) basins of formation, 2) straight-moving and recurving TCs, 3) TC intensity at model initialization, and 4) season of occurrence. The impact of high resolution (18 and 9 km) on TC prediction is also studied. Model results at 27-km resolution indicate that the mean track forecast errors (skill with reference to persistence track) over the NIO were found to vary from 113 to 375 km (7%–51%) for a 12–72-h forecast. The model showed a right/eastward and slow bias in TC movement. The model is more skillful in track prediction when initialized at the intensity stage of severe cyclone or greater than at the intensity stage of cyclone or lower. The model is more efficient in predicting landfall location than landfall time. The higher-resolution (18 and 9 km) predictions yield an improvement in mean track error for the NIO Basin by about 4%–10% and 8%–24%, respectively. The 9-km predictions were found to be more accurate for recurving TC track predictions by ~13%–28% and 5%–15% when compared with the 27- and 18-km runs, respectively. The 9-km runs improve the intensity prediction by 15%–40% over the 18-km predictions. This study highlights the capabilities of the operational ARW model over the Indian monsoon region and the continued need for operational forecasts from high-resolution models.

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Effect of tropical cyclones on the Stratosphere-Troposphere Exchange observed using satellite observations over north Indian Ocean

10.5194/acp-2015-988 ◽

2016 ◽

Cited By ~ 3

Author(s):

M. Venkat Ratnam ◽

S. Ravindra Babu ◽

S. S. Das ◽

Ghouse Basha ◽

B. V. Krishnamurthy ◽

...

Keyword(s):

Water Vapor ◽

Indian Ocean ◽

Tropical Cyclones ◽

Lower Stratosphere ◽

North Indian Ocean ◽

Satellite Observations ◽

Upper Troposphere ◽

North West ◽

The North ◽

The Impact

Abstract. Tropical cyclones play an important role in modifying the tropopause structure and dynamics as well as stratosphere-troposphere exchange (STE) process in the Upper Troposphere and Lower Stratosphere (UTLS) region. In the present study, the impact of cyclones that occurred over the North Indian Ocean during 2007–2013 on the STE process is quantified using satellite observations. Tropopause characteristics during cyclones are obtained from the Global Positioning System (GPS) Radio Occultation (RO) measurements and ozone and water vapor concentrations in UTLS region are obtained from Aura-Microwave Limb Sounder (MLS) satellite observations. The effect of cyclones on the tropopause parameters is observed to be more prominent within 500 km from the centre of cyclone. In our earlier study we have observed decrease (increase) in the tropopause altitude (temperature) up to 0.6 km (3 K) and the convective outflow level increased up to 2 km. This change leads to a total increase in the tropical tropopause layer (TTL) thickness of 3 km within the 500 km from the centre of cyclone. Interestingly, an enhancement in the ozone mixing ratio in the upper troposphere is clearly noticed within 500 km from cyclone centre whereas the enhancement in the water vapor in the lower stratosphere is more significant on south-east side extending from 500–1000 km away from the cyclone centre. We estimated the cross-tropopause mass flux for different intensities of cyclones and found that the mean flux from stratosphere to troposphere for cyclonic stroms is 0.05 ± 0.29 × 10−3 kg m−2 and for very severe cyclonic stroms it is 0.5 ± 1.07 × 10−3 kg m−2. More downward flux is noticed in the north-west and south-west side of the cyclone centre. These results indicate that the cyclones have significant impact in effecting the tropopause structure, ozone and water vapour budget and consequentially the STE in the UTLS region.

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The impact of satellite-derived wind data assimilation on track, intensity and structure of tropical cyclones over the North Indian Ocean

International Journal of Remote Sensing ◽

10.1080/01431161.2011.596849 ◽

2011 ◽

Vol 33 (5) ◽

pp. 1627-1652 ◽

Cited By ~ 39

Author(s):

Krishna K. Osuri ◽

U. C. Mohanty ◽

A. Routray ◽

M. Mohapatra

Keyword(s):

Indian Ocean ◽

Data Assimilation ◽

Tropical Cyclones ◽

North Indian Ocean ◽

Wind Data ◽

The North ◽

The Impact

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Effect of tropical cyclones on the stratosphere–troposphere exchange observed using satellite observations over the north Indian Ocean

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-8581-2016 ◽

2016 ◽

Vol 16 (13) ◽

pp. 8581-8591 ◽

Cited By ~ 11

Author(s):

M. Venkat Ratnam ◽

S. Ravindra Babu ◽

S. S. Das ◽

G. Basha ◽

B. V. Krishnamurthy ◽

...

Keyword(s):

Indian Ocean ◽

Water Vapour ◽

Tropical Cyclones ◽

Lower Stratosphere ◽

North Indian Ocean ◽

Satellite Observations ◽

Upper Troposphere ◽

The North ◽

The Impact ◽

Cyclonic Storms

Abstract. Tropical cyclones play an important role in modifying the tropopause structure and dynamics as well as stratosphere–troposphere exchange (STE) processes in the upper troposphere and lower stratosphere (UTLS) region. In the present study, the impact of cyclones that occurred over the north Indian Ocean during 2007–2013 on the STE processes is quantified using satellite observations. Tropopause characteristics during cyclones are obtained from the Global Positioning System (GPS) radio occultation (RO) measurements, and ozone and water vapour concentrations in the UTLS region are obtained from Aura Microwave Limb Sounder (MLS) satellite observations. The effect of cyclones on the tropopause parameters is observed to be more prominent within 500 km of the centre of the tropical cyclone. In our earlier study, we observed a decrease (increase) in the tropopause altitude (temperature) up to 0.6 km (3 K), and the convective outflow level increased up to 2 km. This change leads to a total increase in the tropical tropopause layer (TTL) thickness of 3 km within 500 km of the centre of cyclone. Interestingly, an enhancement in the ozone mixing ratio in the upper troposphere is clearly noticed within 500 km from the cyclone centre, whereas the enhancement in the water vapour in the lower stratosphere is more significant on the south-east side, extending from 500 to 1000 km away from the cyclone centre. The cross-tropopause mass flux for different intensities of cyclones is estimated and it is found that the mean flux from the stratosphere to the troposphere for cyclonic storms is 0.05 ± 0.29 × 10−3 kg m−2, and for very severe cyclonic storms it is 0.5 ± 1.07 × 10−3 kg m−2. More downward flux is noticed on the north-west and south-west side of the cyclone centre. These results indicate that the cyclones have significant impact in effecting the tropopause structure, ozone and water vapour budget, and consequentially the STE in the UTLS region.

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Extended Prediction of North Indian Ocean Tropical Cyclones

Weather and Forecasting ◽

10.1175/waf-d-11-00083.1 ◽

2012 ◽

Vol 27 (3) ◽

pp. 757-769 ◽

Cited By ~ 31

Author(s):

James I. Belanger ◽

Peter J. Webster ◽

Judith A. Curry ◽

Mark T. Jelinek

Keyword(s):

Tropical Cyclone ◽

Indian Ocean ◽

Tropical Cyclones ◽

North Indian Ocean ◽

Ensemble Prediction ◽

Tropical Cyclone Genesis ◽

Lead Times ◽

Prediction System ◽

Ensemble Prediction System ◽

The North

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.

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Seasonal Nature and Trends of Tropical Cyclone Frequency and Intensity over the North Indian Ocean

Current World Environment ◽

10.12944/cwe.15.3.16 ◽

2020 ◽

Vol 15 (3) ◽

pp. 526-534

Author(s):

Abhisek Pal ◽

Soumendu Chatterjee

Keyword(s):

Time Series ◽

Tropical Cyclone ◽

Indian Ocean ◽

Monsoon Season ◽

North Indian Ocean ◽

Post Monsoon ◽

The North ◽

Increasing Trend ◽

Post Monsoon Season ◽

Cyclone Frequency

Tropical cyclone (TC) genesis over the North Indian Ocean (NIO) region showed significant amount of both spatial and temporal variability.It was observed that the TC genesis was significantly suppressed during the monsoon (June-September) compared to pre-monsoon (March-May) and post-monsoon (October-December) season specifically in terms of severe cyclonic storms (SCS) frequency. The Bay of Bengal (BoB) was characterized by higher TC frequency but lower intensity compared to the Arabian Sea (AS). It was also observed that the TC genesis locations were shifted significantly seasonally.The movement of the TCs also portrayed some significant seasonal differences. The pre-monsoon and post-monsoon season was responsible for generating TCs with higher values of accumulated cyclone energy (ACE) compared to the monsoon. The time series of TC frequency showed a statistically significant decreasing trend whereas the time series of ACE showed astatistically significant increasing trend over the NIO.

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