Forecasts of tropical cyclones in the Bay of Bengal in a regional convection-permitting atmosphere-ocean coupled model

2021 ◽  
Author(s):  
Jennifer Saxby ◽  
Julia Crook ◽  
Cathryn Birch ◽  
Chris Holloway ◽  
Huw Lewis ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Rain Rate ◽  
Ocean Model ◽  
Small Scale ◽  
Good Representation ◽  
Position Errors ◽  
Rate Asymmetry ◽  
Model Configuration ◽  
The Impact

<p>Tropical cyclones (TCs) forming over the Bay of Bengal can cause devastation when they make landfall in India and Bangladesh; accurate prediction of their track and intensity is essential for disaster management. TC intensity is moderated by heat, momentum and moisture exchanges between the atmosphere and ocean. In recent years there have been significant improvements in the skill of TC forecasts due to the implementation of coupled atmosphere-ocean models and high-resolution models capable of explicitly resolving small-scale physical processes influencing storm development.</p><p> </p><p>This study evaluates the representation of six TCs in the Bay of Bengal from 2016 to 2019, using both a Met Office Unified Model atmosphere-only configuration (ATM) with 4.4 km grid spacing, and coupled to a 2.2 km resolution NEMO (Nucleus for European Models of the Ocean) ocean model (CPL). To determine the impact of coupling on wind-driven mixing and ocean-atmosphere heat exchange, forecast sea surface temperature (SST) is compared to observations. The impact of coupling on track position and storm intensity is evaluated using predictions of minimum sea level pressure (MSLP) and 10 m maximum sustained winds (MSW). Representation of TC dynamics is assessed by analysing storm structure, using radius of maximum winds and rain rate asymmetry.</p><p> </p><p>Results from the three most intense TC case studies (Fani, Titli, and Vardah) show that SSTs in ATM are too high, while SSTs in CPL are slightly too low, with an overestimation of the cooling response in TC wakes. TC track position errors are small, but intensity error metrics for MSLP and MSW show biases relative to observations. Peak intensity is overestimated for Titli and Vardah in the ATM model configuration; the CPL model configuration generally produces weaker storms than the ATM model configuration. Wind speeds outside the storm centre are high compared to observations, with a greater bias in the ATM model configuration.  Both model configurations produce accurate predictions of radius of maximum winds and rain rate asymmetry, suggesting a good representation of TC dynamics. Much of the variation in rain rate asymmetry in the forecasts can be explained by variations in wind shear.</p>

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

2021 ◽  
Author(s):  
Jennifer Saxby ◽  
Julia Crook ◽  
Simon Peatman ◽  
Cathryn Birch ◽  
Juliane Schwendike ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Rain Rate ◽  
Coupled Model ◽  
Good Representation ◽  
Grid Spacing ◽  
Wind Speeds ◽  
Rate Asymmetry ◽  
Rain Rates ◽  
Horizontal Grid

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.

scholarly journals The Impact of Tides on the Bay of Biscay Dynamics

2020 ◽  
Vol 8 (8) ◽  
pp. 617
Author(s):  
John Karagiorgos ◽  
Vassilios Vervatis ◽  
Sarantis Sofianos
Keyword(s):  
Vertical Mixing ◽  
Ocean Model ◽  
Open Ocean ◽  
Small Scale ◽  
Bay Of Biscay ◽  
English Channel ◽  
Tidal Forcing ◽  
Freshwater Transport ◽  
One Year ◽  
The Impact

The impact of tides on the Bay of Biscay dynamics is investigated by means of an ocean model twin-experiment, consisted of two simulations with and without tidal forcing. The study is based on a high-resolution (1/36∘) regional configuration of NEMO (Nucleus for European Modelling of the Ocean) performing one-year simulations. The results highlight the imprint of tides on the thermohaline properties and circulation patterns in three distinct dynamical areas in the model domain: the abyssal plain, the Armorican shelf and the English Channel. When tides are activated, the bottom stress is increased in the shelf areas by about two orders of magnitude with respect to the open ocean, subsequently enhancing vertical mixing and weakening stratification in the bottom boundary layer. The most prominent feature reproduced only when tides are modelled, is the Ushant front near the entrance of the English Channel. Tides appear also to constrain the freshwater transport of rivers from the continental shelf to the open ocean. The spectral analysis revealed that the tidal forcing contributes to the SSH variance at high frequencies near the semidiurnal band and to the open ocean mesoscale and small-scale features in the presence of summer stratification pattern.

scholarly journals Effects of Tropical Cyclones on Sea Surface Salinity in the Bay of Bengal Based on SMAP and Argo Data

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2975
Author(s):  
Huabing Xu ◽  
Rongzhen Yu ◽  
Danling Tang ◽  
Yupeng Liu ◽  
Sufen Wang ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Vertical Mixing ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Ekman Pumping ◽  
Surface Salinity ◽  
Argo Data ◽  
Before And After ◽  
The Impact

This paper uses the Argo sea surface salinity (SSSArgo) before and after the passage of 25 tropical cyclones (TCs) in the Bay of Bengal from 2015 to 2019 to evaluate the sea surface salinity (SSS) of the Soil Moisture Active Passive (SMAP) remote sensing satellite (SSSSMAP). First, SSSArgo data were used to evaluate the accuracy of the 8-day SMAP SSS data, and the correlations and biases between SSSSMAP and SSSArgo were calculated. The results show good correlations between SSSSMAP and SSSArgo before and after TCs (before: SSSSMAP = 1.09SSSArgo−3.08 (R2 = 0.69); after: SSSSMAP = 1.11SSSArgo−3.61 (R2 = 0.65)). A stronger negative bias (−0.23) and larger root-mean-square error (RMSE, 0.95) between the SSSSMAP and SSSArgo were observed before the passage of 25 TCs, which were compared to the bias (−0.13) and RMSE (0.75) after the passage of 25 TCs. Then, two specific TCs were selected from 25 TCs to analyze the impact of TCs on the SSS. The results show the significant SSS increase up to the maximum 5.92 psu after TC Kyant (2016), which was mainly owing to vertical mixing and strong Ekman pumping caused by TC and high-salinity waters in the deep layer that were transported to the sea surface. The SSSSMAP agreed well with SSSArgo in both coastal and offshore waters before and after TC Roanu (2016) and TC Kyant (2016) in the Bay of Bengal.

The impact of northern Indian Ocean rivers on the Bay of Bengal using NEMO global ocean model

2020 ◽  
Vol 39 (3) ◽  
pp. 45-55
Author(s):  
Atul Srivastava ◽  
Anitha Gera ◽  
Imran M. Momin ◽  
Ashis Kumar Mitra ◽  
Ankur Gupta
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Ocean Model ◽  
Global Ocean ◽  
Northern Indian Ocean ◽  
The Impact

scholarly journals NUMERICAL SIMULATION OF TROPICAL CYCLONES AND STORM SURGES IN THE ARABIAN SEA

2018 ◽  
pp. 11
Author(s):  
Mohsen Soltanpour ◽  
Zahra Ranji ◽  
Tomoyo Shibayama ◽  
Sarmad Ghader ◽  
Shinsaku Nishizaki
Keyword(s):  
Tropical Cyclones ◽  
Persian Gulf ◽  
Arabian Sea ◽  
Storm Surges ◽  
Ocean Model ◽  
Gulf Of Oman ◽  
The Persian Gulf ◽  
The Impact ◽  
Landfall Location ◽  
Good Agreement

Winds, waves and storm surges of Gonu and Ashobaa, as two recent cyclones in the Arabian Sea and Gulf of Oman, are simulated by a system of WRF-FVCOM-SWAN. The employed models are separately calibrated using the available data. Surges are found to be highly dependent on coastal geometry and landfall location, rather than the storm intensity. Comparisons at different stations reveal that the results of models are in a good agreement with measured parameters. Negative surges are also observed in the enclosed basins of the Persian Gulf and Red Sea. The calibrated atmosphere-wave-ocean model can be utilized for the prediction of extreme events, expected to increase in future due to the impact of the climate change.

scholarly journals The Impact of the Madden–Julian Oscillation on Cyclone Amphan (2020) and Southwest Monsoon Onset

2020 ◽  
Vol 12 (18) ◽  
pp. 3011
Author(s):  
Heather L. Roman-Stork ◽  
Bulusu Subrahmanyam
Keyword(s):  
Bay Of Bengal ◽  
Heat Content ◽  
Southwest Monsoon ◽  
Ocean Model ◽  
Madden Julian Oscillation ◽  
Atmospheric Conditions ◽  
Kelvin Wave ◽  
Upper Ocean Heat Content ◽  
Southeastern Arabian Sea ◽  
The Impact

Cyclone Amphan was an exceptionally strong tropical cyclone in the Bay of Bengal that achieved a minimum central pressure of 907 mb during its active period in May 2020. In this study, we analyzed the oceanic and surface atmospheric conditions leading up to cyclogenesis, the impact of this storm on the Bay of Bengal, and how the processes that led to cyclogenesis, such as the Madden–Julian Oscillation (MJO) and Amphan itself, in turn impacted southwest monsoon preconditioning and onset. To accomplish this, we took a multiparameter approach using a combination of near real time satellite observations, ocean model forecasts, and reanalysis to better understand the processes involved. We found that the arrival of a second downwelling Kelvin wave in the equatorial Bay of Bengal, coupled with elevated upper ocean heat content and the positioning of the convective phase of the MJO, helped to create the conditions necessary for cyclogenesis, where the northward-propagating branch of the MJO acted as a trigger for cyclogenesis. This same MJO event, in conjunction with Amphan, heavily contributed atmospheric moisture to the southeastern Arabian Sea and established low-level westerlies that allowed for the southwest monsoon to climatologically onset on June 1.

The impact of assimilating MeghaTropiques SAPHIR radiances in the simulation of tropical cyclones over the Bay of Bengal using the WRF model

2016 ◽  
Vol 37 (13) ◽  
pp. 3086-3103 ◽  
Author(s):  
M. Dhanya ◽  
Deepak Gopalakrishnan ◽  
A. Chandrasekar ◽  
Sanjeev Kumar Singh ◽  
V.S. Prasad
Keyword(s):  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Wrf Model ◽  
The Impact

scholarly journals Observation-Based Estimates of Surface Cooling Inhibition by Heavy Rainfall under Tropical Cyclones

2013 ◽  
Vol 43 (1) ◽  
pp. 205-221 ◽  
Author(s):  
Nicolas C. Jourdain ◽  
Matthieu Lengaigne ◽  
Jérome Vialard ◽  
Gurvan Madec ◽  
Christophe E. Menkes ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Cold Water ◽  
Mixed Layer Depth ◽  
Vertical Mixing ◽  
Dilution Effect ◽  
Global Scale ◽  
Surface Cooling ◽  
Ocean Reanalysis ◽  
The Impact

Abstract Tropical cyclones drive intense ocean vertical mixing that explains most of the surface cooling observed in their wake (the “cold wake”). In this paper, the authors investigate the influence of cyclonic rainfall on the cold wake at a global scale over the 2002–09 period. For each cyclone, the cold wake intensity and accumulated rainfall are obtained from satellite data and precyclone oceanic stratification from the Global Eddy-Permitting Ocean Reanalysis (GLORYS2). The impact of precipitation on the cold wake is estimated by assuming that cooling is entirely due to vertical mixing and that an extra amount of energy (corresponding to the energy used to mix the rain layer into the ocean) would be available for mixing the ocean column in the hypothetical case with no rain. The positive buoyancy flux of rainfall reduces the mixed layer depth after the cyclone passage, hence reducing cold water entrainment. The resulting reduction in cold wake amplitude is generally small (median of 0.07 K for a median 1 K cold wake) but not negligible (>19% for 10% of the cases). Despite similar cyclonic rainfall, the effect of rain on the cold wake is strongest in the Arabian Sea and weak in the Bay of Bengal. An analytical approach with a linearly stratified ocean allows attributing this difference to the presence of barrier layers in the Bay of Bengal. The authors also show that the cold wake is generally a “salty wake” because entrainment of subsurface saltier water overwhelms the dilution effect of rainfall. Finally, rainfall temperature has a negligible influence on the cold wake.

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