Forecasting tropical cyclones in the Bay of Bengal using quasi-operational WRF and HWRF modeling systems: an assessment study

Nadimpalli, Raghu; Osuri, Krishna K.; Mohanty, U. C.; Das, Abhimanyu; Ankur, Kumar; Sil, Sourav; Niyogi, Dev

doi:10.1007/s00703-019-00669-6

Cited by 30 publications

(18 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For TC Roanu the errors are 83 hours (ATM) or 78 hours (CPL). For similar lead times, landfall position errors are comparable to reported errors for Vardah and Roanu forecasted using atmosphere-only configurations of WRF and the Hurricane Weather Research and Forecasting (HWRF) model (Nadimpalli et al, 2020). Position errors also 555 compare favourably to global model simulations of TC Fani (Singh et al, 2021).…”

supporting

confidence: 65%

“…Both ATM and CPL underestimate the intensity of stronger TCs and overestimate the intensity of weaker TCs. Nadimpalli et al (2020) have highlighted a similar bias in the WRF model for Bay of Bengal cyclones. In general, CPL predicts less intense storms than ATM, consistent with the lower SSTs and overestimation of SST 560 cooling in cyclone wakes in CPL.…”

mentioning

confidence: 60%

“…Ocean coupling in mesoscale models generally improves TC track and intensity predictions (Greeshma et al, 2019;Srinivas et al, 2016;Yesubabu et al, 2020). Atmosphere-only (uncoupled) NWP models generally assume constant SST over the forecast, derived from ocean analysis systems, which has been the operational 80 practice for TC prediction over the Bay of Bengal (Mohanty et al, 2015;Osuri et al, 2017;Routray et al, 2017;Srinivas et al, 2013;Nadimpalli et al, 2020). Updating SST during simulations with SST observations has been shown to improve track and intensity predictions (Mohanty et al, 2019;Rai et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simulations of Bay of Bengal tropical cyclones in a regional convection-permitting atmosphere–ocean coupled model

Saxby

Crook

Peatman

et al. 2021

Preprint

View full text Add to dashboard Cite

Abstract. Tropical cyclones (TCs) in the Bay of Bengal can be extremely destructive when they make landfall in India and Bangladesh. Accurate prediction of their track and intensity is essential for disaster management. This study evaluates simulations of Bay of Bengal TCs using a regional convection-permitting atmosphere-ocean coupled model. The Met Office Unified Model atmosphere-only configuration (4.4 km horizontal grid spacing) is compared with a configuration coupled to a three-dimensional dynamical ocean model (2.2 km horizontal grid spacing). Simulations of six TCs from 2016–2019 show that both configurations produce accurate TC tracks for lead times of up to 6 days before landfall. Both configurations underestimate high wind speeds and high rain rates, and overestimate low wind speeds and low rain rates. The ocean-coupled configuration improves landfall timing predictions and reduces wind speed biases relative to observations outside the eyewall but underestimates maximum wind speeds in the eyewall for the most intense TCs. The coupled configuration produces weaker TCs than the atmosphere-only configuration, consistent with lower sea surface temperatures in the coupled model and an overestimated cooling response in TC wakes. Both model configurations accurately predict rain rate asymmetry, suggesting a good representation of TC dynamics. Much of the rain rate asymmetry variation in the simulations is related to wind shear variations, with a preference for higher rain rates in the down-shear left quadrant.

show abstract

supporting

confidence: 65%

mentioning

confidence: 60%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simulations of Bay of Bengal tropical cyclones in a regional convection-permitting atmosphere–ocean coupled model

Saxby

Crook

Peatman

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The analyses of axisymmetric and asymmetric TC rainfall structures have recently been receiving more attention because of its destructive flooding potential in especially the coastal regions (Jiang and Zipser, ; Villarini et al ., ). Present‐day numerical models are capable of producing realistic TC information regarding track, intensity, structure, and rainfall over the North Indian Ocean (NIO) basin (Osuri et al ., ; ; Nadimpalli et al ., ; ; Busireddy et al ., ) and other global TC basins (Yeh et al ., ; Chen et al ., ; Bassill, ; Matyas et al ., ). The NIO (comprises Bay of Bengal—BoB; and the Arabian Sea–AS) is one of the basins that are prone to TCs but lacks behind without good observational setup to comprehend the realistic TC rainfall characteristics.…”

Section: Introductionmentioning

confidence: 99%

On the relationship between intensity changes and rainfall distribution in tropical cyclones over the North Indian Ocean

Ankur

Busireddy

Osuri

et al. 2019

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

Using Tropical Rainfall Measuring Mission rain estimates the relationship between rainfall and intensity changes in tropical cyclones (TCs) over the North Indian Ocean (NIO) based on 71 TCs during 1997–2017 is investigated. The axisymmetric analyses revealed that climatologically the Bay of Bengal (BoB) TCs produce extremely heavy rainfall (~9–10 mm⋅hr−1) and Arabian Sea TCs produce very heavy rainfall (~7–8 mm⋅hr−1) in the storm inner core region (0–100 km). The inner‐core region receives three times higher rainfall than the outer region (100–300 km). The left‐forward sector experiences the maximum rainfall for any TC intensity over the NIO basin. A significant increase (decrease) in the rain rate is seen during normal to rapid intensification (weakening) phase. A notable decrease in rainfall of ~4.3 mm⋅hr−1 is observed for the rapidly weakening TCs. Slow‐moving TCs are generally stronger and produce heavy rainfall (2–4 mm⋅hr−1) up to ~300 km storm radius. As the translation speed increases, rainfall gradually shifts from rear to the forward sector of the TC. The asymmetry (wavenumber‐1) in TC rainfall structures revealed that rainfall maximum is located in the left‐forward sector for almost all intensity stages. The amplitude of wave number‐1 asymmetry in TC rainfall shows cyclonic shift as the TC intensity increases and is particularly prevalent in the BoB region. These analyses would be helpful as a baseline for evaluating the performance of numerical models and to identify the vulnerable areas for TC heavy rainfall.

show abstract

“…With the advancements in the dense observational network such as in-situ, satellite, radar, and other remote sensed platforms, the TC movement's prediction accuracy has been improved from the last few decades [12]. Significant improvements have been achieved in the prediction of the track of TC since the previous few years due to the advancements in numerical weather prediction models and data assimilation techniques over the NIO basin [6,7,18,20,21,23], 2015, 2017, [14][15][16], Mohanty et al, 2015Mohanty et al, ,2019, [2]. However, the intensity prediction is still a challenging task for the operational and research community due to their intensity changes such as rapid intensification (RI) 1 and rapid decay (RD) 2 over the basin [11,26], [27].…”

Section: Introductionmentioning

confidence: 99%

Understanding the characteristics of rapid intensity changes of Tropical Cyclones over North Indian Ocean

et al. 2021

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Forecasting tropical cyclones in the Bay of Bengal using quasi-operational WRF and HWRF modeling systems: an assessment study

Cited by 30 publications

References 28 publications

Simulations of Bay of Bengal tropical cyclones in a regional convection-permitting atmosphere–ocean coupled model

Simulations of Bay of Bengal tropical cyclones in a regional convection-permitting atmosphere–ocean coupled model

On the relationship between intensity changes and rainfall distribution in tropical cyclones over the North Indian Ocean

Understanding the characteristics of rapid intensity changes of Tropical Cyclones over North Indian Ocean

Contact Info

Product

Resources

About