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 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.

scholarly journals Optimization of physical schemes in WRF model on cyclone simulations over Bay of Bengal using one-way ANOVA and Tukey’s test

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Meenakshi Shenoy ◽  
P. V. S. Raju ◽  
Jagdish Prasad
Keyword(s):  
Boundary Layer ◽  
Tropical Cyclones ◽  
Planetary Boundary Layer ◽  
Bay Of Bengal ◽  
Wrf Model ◽  
India Meteorological Department ◽  
Cloud Microphysics ◽  
Optimal Combination ◽  
Cumulus Convection ◽  
Elimination Method

AbstractEvaluation of appropriate physics parameterization schemes for the Weather Research and Forecasting (WRF) model is vital for accurately forecasting tropical cyclones. Three cyclones Nargis, Titli and Fani have been chosen to investigate the combination of five cloud microphysics (MP), three cumulus convection (CC), and two planetary boundary layer (PBL) schemes of the WRF model (ver. 4.0) with ARW core with respect to track and intensity to determine an optimal combination of these physical schemes. The initial and boundary conditions for sensitivity experiments are drawn from the National Centers for Environmental Prediction (NCEP) global forecasting system (GFS) data. Simulated track and intensity of three cyclonic cases are compared with the India Meteorological Department (IMD) observations. One-way analysis of variance (ANOVA) is applied to check the significance of the data obtained from the model. Further, Tukey’s test is applied for post-hoc analysis in order to identify the cluster of treatments close to IMD observations for all three cyclones. Results are obtained through the statistical analysis; average root means square error (RMSE) of intensity throughout the cyclone period and time error at landfall with the step-by-step elimination method. Through the elimination method, the optimal scheme combination is obtained. The YSU planetary boundary layer with Kain–Fritsch cumulus convection and Ferrier microphysics scheme combination is identified as an optimal combination in this study for the forecasting of tropical cyclones over the Bay of Bengal.

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.

Simulation of Bay of Bengal Tropical Cyclones with WRF Model: Impact of Initial and Boundary Conditions

2010 ◽  
Vol 33 (4) ◽  
pp. 294-314 ◽  
Author(s):  
U. C. Mohanty ◽  
Krishna K. Osuri ◽  
A. Routray ◽  
M. Mohapatra ◽  
Sujata Pattanayak
Keyword(s):  
Boundary Conditions ◽  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Wrf Model ◽  
Initial And Boundary Conditions

scholarly journals Recent very severe tropical cyclones over the Bay of Bengal : Analysis with satellite data

MAUSAM ◽  
2021 ◽  
Vol 57 (1) ◽  
pp. 37-46
Author(s):  
B. R. LOE ◽  
B. L. VERMA ◽  
R. K. GIRI ◽  
S. BALI ◽  
L. R. MEENA
Keyword(s):  
Tropical Cyclones ◽  
Satellite Data ◽  
Bay Of Bengal ◽  
Wave Radiation ◽  
Cyclonic Storm ◽  
The Difference ◽  
Remote Sensing Techniques ◽  
Pseudo Color ◽  
The Impact ◽  
Cyclonic Storms

lkj & bl 'kks/k&i= esa caxky dh [kkM+h ds m".kdfVca/kh; pØokrksa dh rhozrk dk vkdyu vkSj pØokr ds ekxZ dk iwokZuqeku yxkus esa mixzg ds vk¡dM+ksa ls cus izHkko dks n’kkZ;k x;k gSA bl 'kks/k&i= esa ys[kdksa us pØokrh rwQkuksa ds ekxZ dk] pØokr ds cuus dk vkSj pØokr dh xfrfof/k;ksa dk irk yxkus esa mixzg ds vk¡dM+ksa ds mi;ksx dks vuqdwy cukus esa lqnwj laosnh rduhdksa dh gky gh esa feyh lQyrk vkSj mlds mi;ksx dh izxfr ij fo’ks"k :Ik ls /;ku dsfUnzr fd;k gSA nks pØokrksa dk fo’ys"k.k fd;k x;k gS & 16 ls 19 ebZ 2004 esa E;kaekj esa vk;k izpaM pØokrh rwQku vkSj nwljk 26 ls 31 vDrwcj 1999 esa mM+hlk esa vk;k pØokrA pØokrh rwQkuksa ds cuus vkSj muds vkxs c<+us ds iwokZuqeku esa vfr mPp foHksnu jsfM;ksehVj ¼oh- ,p- vkj- vkj-½ vk¡dM+ksa] LdsVªksehVj iouksa vkSj cfgxkZeh nh?kZrjax fofdj.k ¼vks- ,y- vkj-½ ds pØokrksa ds vkl&ikl Ñf=e o.kZ esa n’kkZ, x, vk¡dM+ksa dk mi;ksx djrh gqbZ mixzg ij vk/kkfjr rduhd cgqr vf/kd mi;ksxh ikbZ xbZ gSA bl v/;;u esa caxky dh [kkM+h esa vk, nks pØokrksa ds cuus vkSj muds vkxs c<+us dh vlekurk dks fo’ks"k :Ik ls crk;k x;k gSA This paper shows the impact made by the satellite data in the intensity estimation and track prediction of tropical cyclones of Bay of Bengal. The authors in this paper have focused on the recent accomplishment and advances in the remote sensing techniques to optimize the use of satellite data in tracking, formation and movement of cyclonic storms. Two cyclones - firstly the Myanmar severe cyclonic storm of 16 to 19 May 2004 and secondly the          26 – 31 October 1999 Orissa cyclone have been analysed. Satellite based technique using Very High Resolution Radiometer (VHRR) data, scatterometer winds and outgoing long wave radiation (OLR) data in pseudo color around the cyclones have been found to be more useful in predicting formation and movement of cyclonic storms. The present study has significantly brought out the difference in formation and movement of the two cyclones formed over the Bay of Bengal.

scholarly journals Examining the Impact of Tropical Cyclones on Air‐Sea CO2Exchanges in the Bay of Bengal Based on Satellite Data and In Situ Observations

2019 ◽  
Vol 124 (1) ◽  
pp. 555-576 ◽  
Author(s):  
Haijun Ye ◽  
Jinyu Sheng ◽  
Danling Tang ◽  
Evgeny Morozov ◽  
Muhsan Ali Kalhoro ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Satellite Data ◽  
Bay Of Bengal ◽  
In Situ Observations ◽  
The Impact

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

&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;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. &amp;#160;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.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document