Ocean response to Tropical Cyclone “Asani”: Surface cooling restricted by Coastal Downwelling

Ocean response to Tropical Cyclone “Asani”: Surface cooling restricted by Coastal Downwelling | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Ocean response to Tropical Cyclone “Asani”: Surface cooling restricted by Coastal Downwelling Sthitapragya Ray, Sidha Sankalpa Moharana, Debadatta Swain This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2001209/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The severe cyclonic storm “Asani” formed in the southeastern Bay of Bengal on 6 th May 2022 and made landfall on the evening of 11 th May 2022 in Andhra Pradesh, India. The unique characteristic of this cyclone was its low TS from roughly 27 hours prior to its landfall resulting in a remarkably prolonged interaction with the coastal ocean. In this analysis, we examined the sea surface temperature (SST) response to the cyclone at three locations along its track and analyzed the temporal variation of the observed cyclone-driven SST cooling. Four different ocean processes (wind-stirred and buoyancy flux-driven mixing, windstress-curl and alongshore windstress driven upwelling) could be identified by the corresponding proxies as the drivers of this cooling. A SST cooling of 1.08 °C was observed over a two-day period around the genesis area. Ekman pumping and wind-stirred mixing illustrated high values over the maximum intensity region during the passage of the cyclone, resulting in a SST drop by 2.14 °C. The landfall area had a significantly longer duration of interaction with the cyclone, as its TS reduced from moderate to slow, exhibiting wind-stirred mixing values comparable to the other two regions. However, the SST drop was the lowest at ~0.65 °C. Coastal downwelling-favourable windstress associated with the leading edge of the cyclone was responsible for limiting the cooling that could have otherwise resulted from mixing and entrainment. This unique modification of cyclone-ocean interaction through coastal upwelling possibly delayed the dissipation of cyclone “Asani”. Cyclone Asani Coastal upwelling Ekman transport Downwelling Translational speed Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Tropical cyclones (TCs) are among the most destructive natural hazards (Pielke et. al. 2008 ). TCs are fueled by transfer of latent heat from the ocean surface which is also the primary source of energy driving these intense circulations (Emanuel 1999 ). Consequently, air-sea interactions play a crucial role in determining the intensity of TCs through positive and negative feedbacks. LHF being dependent on wind speed, increasing amounts of moisture gets evaporated from the sea surface as the cyclone intensifies. This in turn further intensifies the TC resulting in a positive feedback, usually dominant during the genesis phase. But as the storm intensifies, vertical mixing resulting from the high wind speed can also reduce the sea surface temperature (SST) thereby limiting the total heat flux into the cyclone and consequently weakening it, a negative feedback (Ginis 2002 ). However, coastal downwelling due to a TC approaching land can cause increase in air-sea enthalpy flux, enabling TC intensification (Gramer et al. 2022 ). TC “Asani” formed in the south-eastern Bay of Bengal (BoB) near the Little Andaman Islands on 6th May 2002. The well-marked low-pressure system moved north-westwards and gradually intensified into a severe cyclonic storm (SCS) with 3-min sustained wind speed of 55 kt during the early morning of 9th May till the noon of 10th. India Meteorological Department (IMD) forecasts had predicted a sharp recurvature as the cyclone neared the coast, aligning the track of the cyclone nearly parallel to the eastern coast of India (IMD 2022a). However, “Asani” deviated from this forecasted track and followed a north-westward trajectory instead. It also hovered near the coast until it weakened into a deep depression and made landfall between Machilipatnam and Naraspur (in Andhra Pradesh, India) with a very low TS in the evening of 11th May 2022. The system started dissipating as it weakened further to a well-marked low-pressure area and very low TS moving south-westward close to the coast on the morning of 12th May (IMD 2022b). Cyclone Asani illustrated moderate TS from the time of its genesis up to roughly 27 hours prior to landfall when it decelerated to a slow TS, following the IMD categorization of TS (Jangir et al 2021 , https://rsmcnewdelhi.imd.gov.in/ ). As a result of the remarkably low TS of the cyclone just prior to and after landfall (IMD 2022b), it interacted with the coastal ocean for an extended period of time which could have resulted in intense coastal cooling. In this analysis, we have examined the role of different air-sea interaction processes and the local ocean response at three different stages of cyclone “Asani”. 2. Data The present analysis was carried out utilizing cyclone track datasets from the International Best Track Archive for Climate Stewardship (IBTrACS) which included latitude, longitude and wind speed information at 3 hour intervals (Knapp et al. 2010 , 2018 ) and 1-min averaged wind and storm track information from U.S. warning agencies. An uncertainty of ± 10 kts in intensity and ~ 20–25 kms in position was reported for moderate intensity (60 kts < wind < 100 kts) storms in the North Indian Ocean basin (IBTrACS Technical Documentation, accessed on 27-05-2022). Geophysical parameters, such as SST, mean sea level pressure (MSLP), and 10 m surface wind components were obtained from Copernicus ERA5 climate reanalysis data archive (Hersbach et al. 2018 ) for the month of May 2022. This fifth generation ECMWF reanalysis follows data assimilation methods using model with observations from across the globe with uncertainty estimates calculated from 10-member ensembles at 3-hour intervals. The meteorological and oceanographic parameter fields are available from 1951 to present and are at 1 hour temporal and 0.25° × 0.25° spatial resolutions on regular latitude – longitude grids. Two other foundation SST datasets were obtained from GHRSST Level 4 OSTIA global foundation SST analysis (Donlon et al. 2012 ; UK Met Office 2012 ) and GHRSST Level 4 Remote Sensing Systems (REMSS) Microwave-Infrared Optimally Interpolated (MW-IR OI) SST (Remote Sensing Systems 2017 ) for comparison and validation of ERA5 SST product. The OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis) SST is a daily gridded level 4 analysis product from the UK Met Office, provided on a 0.054° grid. The OSTIA analysis uses satellite observations from sensors such as the Advanced Very High Resolution Radiometer (AVHRR), the Spinning Enhanced Visible and Infrared Imager (SEVIRI), the Geostationary Operational Environmental Satellite (GOES) imager, the Infrared Atmospheric Sounding Interferometer (IASI), the Tropical Rainfall Measuring Mission Microwave Imager (TMI) and in situ data from ships, drifting and moored buoys (Donlon et al., 2012 ). The REMSS SST uses a diurnal model to generate a 0.09° resolution daily foundation SST combining the through-cloud capabilities of microwave sensors such as Global Precipitation Measurement (GPM), Microwave Imager (GMI), Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), the NASA Advanced Microwave Scanning Radiometer-EOS (AMSRE), and the Advanced Microwave Scanning Radiometer 2 (AMSR2). High spatial resolution and near-coastal capabilities of infrared SST sensors, such as that of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) were also included. The REMSS SST analysis however does not use any in situ observations (Remote Sensing Systems 2017 ). 3. Methodology The track and intensity of TC “Asani” from IBTrACS data was overlaid on the minimum ERA5 mean sea level pressure (Fig. 1 a). Three boxes (2° × 2°) were identified corresponding to the genesis, maximum intensity, and landfall regions of the cyclone. All subsequent analysis were carried out based on these selected areas. We then attempted to identify suitable proxy measures for each of the four primary air-sea interaction mechanisms driving the ocean response: wind-stirred mixing, buoyancy flux driven mixing, open ocean upwelling and coastal upwelling. The Monin-Obhukov similarity theory (Monin and Obhukov 1954) describes the comparison of the dynamic significance of buoyancy flux to wind-stirring in terms of their contribution to the turbulent kinetic energy (TKE) within the ocean boundary layer through the Monin-Obhukov length scale (L) (Zheng 2021), as: $$L= \frac{{u}_{*}^{3}}{\kappa {B}_{0}}$$ 1 where, \({u}_{*}\) is the friction velocity, \({B}_{0}\) is the surface buoyancy flux and \(\kappa =0.4\) is the Von Karman constant. The magnitude of L is an estimate of the depth at which buoyancy flux dominates over wind-stirring in TKE production. Based on this, we selected \({u}_{*}^{3}\) (which is proportional to the cube of surface wind speed) to be the proxy for wind-stirred production of TKE where, $${u}_{*}=\sqrt{{\tau }_{0}/{\rho }_{a}}$$ 2 \({\tau }_{0}\) being the surface windstress and \({\rho }_{a}\) being the surface air density. Different formulations of wind energy transfer at the surface use a similar dependence on the cube of surface wind speed; the total power dissipation is formulated by Emmanuel (2005) as a spatio-temporal integral involving the cube of surface wind speed. Niiler ( 1977 ) similarly quantified the wind-stirred TKE production within the ocean mixed layer as \({u}_{*}^{3}\) in the 1 dimensional bulk mixed layer theory. The surface buoyancy flux ( \({B}_{0}\) ) was considered to be the proxy for buoyant TKE production. As the density of seawater depends on temperature and salinity, both air-sea heat and moisture fluxes could alter the surface water density making the water column more or less buoyant. Following Cronin ( 2009 ), the buoyancy flux ( \({B}_{0}\) ) could be expressed in terms of the net surface heat flux ( \({Q}_{0}\) ), rate of evaporation ( \(E\) ) and precipitation ( \(P\) ) as: $${B}_{0}=-\frac{g\alpha }{\rho {c}_{p}}{Q}_{0}+g\beta {S}_{0}(E-P)$$ 3 where, g is the acceleration due to gravity, \({S}_{0}\) is the surface salinity, \(\rho\) is the density of sea water, \({c}_{p}\) is its specific heat, \(\alpha\) ( \(\alpha = -\frac{1}{\rho } \frac{\partial \rho }{\partial T}\) ) is the thermal expansion coefficient, and \(\beta\) ( \(\beta = \frac{1}{\rho }\frac{\partial \rho }{\partial S}\) ) is the haline contraction coefficient. A positive buoyancy flux due to heat loss or excess evaporation makes the surface waters less buoyant (more dense), decreases convective stability of the water column with the resultant overturning leading to the entrainment of deeper waters to the surface. The open ocean upwelling process is quantified in terms of the Ekman pumping velocity ( \({w}_{E}\) ) which is the vertical velocity produced at the base of the Ekman layer due to the divergence of surface currents resulting from a positive windstress curl at the surface. The Ekman pumping velocity is expressed as: $${w}_{E}=\frac{\overrightarrow{{\nabla }_{z}} \times \overrightarrow{{\tau }_{0}}}{\rho f}$$ 4 where, \({\tau }_{0}\) is the surface windstress, \(\rho\) is the density of water, and \(f\) is the Coriolis parameter (Smith 1968). In the vicinity of the coast, the alongshore windstress (AWS) could generate a divergence of surface currents along the coast, resulting in coastal upwelling (Smith 1968). This process is quantified in terms of the Ekman transport (M) which represents the horizontal flow of coastal waters in the cross-shore direction (Smith 1968; Varela et. al. 2015 ; Jayaram and Kumar 2018 ), given by: \(M= \frac{{\tau }_{l}}{\rho f}\) (5) where, \({\tau }_{l}= {\rho }_{a}{c}_{d}{v}_{l}\sqrt{{u}^{2}+{v}^{2}}\) (6) where, \({v}_{l}= \pm (u\text{cos}\left(\theta -\frac{\pi }{2}\right)+v sin \left(\theta -\frac{\pi }{2}\right))\) (7) where, \({c}_{d}\) is the drag coefficient, \({\tau }_{l}\) is the alongshore windstress, \({v}_{l}\) is the alongshore wind speed, \(u\) is the zonal wind speed, \(v\) is the meridional wind speed, and \(\theta\) is the coastal angle, which is the angle subtended by the seaward normal to the coastline. The sign of \({v}_{l}\) is negative (positive) in the northern (southern) hemisphere. Three 2°× 2° boxes (as in Fig. 1 ) were selected along the track of the cyclone covering three different stages. The ERA5 SST and the first three proxy parameters, \({u}_{*}^{3}\) , \({B}_{0}\) , and \({w}_{E}\) were computed within each box over the period from 0000 UTC of 3rd May, 2022 to 2300 UTC on 15th May, 2022. The first box extended between 9 °N – 11 °N and 89.35 °E – 91.35 °E and covered the location of genesis and the earlier part of the intensification of the cyclone. The second box which spanned the location just prior to the cyclone reaching its maximum intensity extended between 12 °N – 14 °N and 86 °E – 88 °E. The third box extends between 14 °N – 16 °N and 80.5 °E – 82.5 °E and stretched over the final part of the TC trajectory where it started weakening and finally made landfall. In addition to the above three, the Ekman transport (M) associated with coastal upwelling was also computed for the third box which spanned the coastal region. For this, five coastal points that lay within this box area were selected and the coastal angle was computed at each of those points. The zonal and meridional wind speed were sampled at each of these five points for every time-step using a Cressman window (Cressman 1959 ) of 50 km radius, and the mean Ekman transport (M) over the five points were obtained. Further, ERA5 SST was also inter-compared with OSTIA SST and REMSS SST over each of these boxes to ascertain the performance of the SST products. 4. Results The Monin-Obukhov length (L) computed over each of the three areas is presented in Fig. 2 . The greatest variation of L is observed in the intensification area of the cyclone with minimum values less than 10 3 m observed in the period immediately prior to its genesis. During the period of influence of the cyclone, the value of L ranges between 10 4 – 10 9 m in all three areas. This implies that shear-driven TKE production dominates over buoyant TKE production within the depth of the surface mixed layer. The subsequent analysis therefore focuses on wind-stirred TKE production and upwelling as the key mechanisms regulating the oceanic response to the cyclone. The computed values of all the mixing parameters were plotted for the entire duration of the cyclone over the three 2° × 2° boxes and presented in Fig. 3 along with the corresponding SST values (from the ERA5, OISST and REMSS SST data sets). The largest SST drop was observed for the second box corresponding to the region just before TC “Asani” reached its maximum intensity (Fig. 3 b), while the lowest SST drop was surprisingly observed for the landfall area of the cyclone (Fig. 3 c). The eye of the cyclone passed over the box labelled genesis area between 0600 to 2100 hours UTC of 7th May 2022, the first 15 hours after its genesis. During this time, it gradually intensified from a sustained wind speed of 39 kt to 55 kt (Fig. 1 ). The TS of the cyclone was moderate, varying between 8–10 kt. The mixing parameter remained low in this region throughout the observed period (Fig. 3 a), reaching a maximum value of about 0.2 m 3 /s 3 between 1900 hours UTC of 7th May to 0000 hours UTC of 8th May 2022. A moderately low Ekman pumping value of less than 0.5 m/s was observed (Fig. 3 a) with a peak around 1800 hours UTC of 7th May. The ERA5 SST dropped by 0.22°C from 6th to 7th and by 0.862°C from 7th to 8th May 2022 (total of 1.08°C over two days). The second box covered the track of Cyclone “Asani”, where it reached its maximum intensity (64 kts) from 1200 to 1800 hours UTC (1730 to 2330 IST) of 8th May before weakening down to 54 kts. The cyclone began intensification again upon its center leaving this area. Interestingly, the cyclone slowed down at this point allowing enhanced LHF which again caused intensification (Fig. 1 ). The cyclone had a high TS of 9–12 kt while traversing this area. The proxy parameters for the different air-sea interaction processes show an interesting variation over this area: Ekman pumping velocity and wind-stirring based mixing parameter peaked in quick succession (Fig. 3 b). The Ekman pumping velocity began to rise in this area from 2200 hours UTC of 7th May, reaching a maximum value of over 1.7×10 − 4 m/s at 1600 hours UTC of 8th May (during the period of maximum intensity), before dropping again to about − 0.18×10 − 4 m/s on 0700 hours UTC of 9th May 2022. The mixing parameter rose sharply from 1800 hours UTC of 7th May reaching a maximum of 0.84 m 3 /s 3 between 2300 hours UTC on 8th May (5 hours after the maximum intensity period) and 0000 hours UTC of the following day. The mixing parameter also showed a second weaker peak of 0.82 m 3 /s 3 on 0700 hours UTC of 9th May and subsequently dropped below 0.1 m 3 /s 3 by 0200 hours UTC of 10th May. The ERA5 SST in this area dropped continuously from 7th to 12th May, with the sharpest falls of 0.74°C, 0.54°C, and 0.86°C observed on the 8th, 9th, and 10th of May, respectively. A total SST cooling of 2.14°C was observed in ERA5 SST in this area over the 3-day period. The final box, labelled landfall area, covered the final part of the cyclone from 0600 hours UTC of 10th May till landfall on 11th May and its subsequent weakening. While the cyclone entered this area with a TS of 11 kts, it dropped sharply varying between 1–6 kt for the remaining period. This remarkably slow TS resulted in the cyclone spending an unusually high amount of time in the near vicinity of the coast. The intensity of the cyclone also dropped during this period from 64 kt to 35 kt just prior to landfall (Fig. 1 ). Figure 3 c illustrates the Ekman pumping velocity to remain very low (magnitude < 0.15 ×10 − 4 m/s) here throughout the influence of the cyclone, reaching a value of around − 0.14 ×10 − 4 m/s on 0700 hours UTC of 9th May (prior to the entry of the eye of the cyclone into the region), and increasing to 0.11 ×10 − 4 m/s at 1800 hours UTC on the following day. The mixing parameter rose sharply from 1800 hours UTC of 9th May, reaching a maximum value of 1.16 m 3 /s 3 on 1500 hours UTC (2030 IST) of 10th May 2022, and then decreasing below 0.1 m 3 /s 3 by 1800 hours UTC the following day (6 hours after landfall). The mean Ekman mass transport (resulting from costal upwelling) also began to decrease from 1000 hours UTC of 9th May 2022 before attaining the maximum onshore Ekman transport of 4.28 m 2 /s on 1900 hours UTC of 10th May (17 hours before landfall). It increased subsequently to a weakly positive value of 1.05 m 2 /s on 1900 hours UTC of 11th May (7 hours after landfall) and dropped close to zero thereafter. Surprisingly, in spite of observed higher values of wind-stirred mixing parameter and buoyancy flux, the ERA5 SST in this region remained fairly constant and in fact rose by about 0.1°C between the 10th and 11th of May 2022, and a dropped hardly about 0.4°C between the 11th and 12th of May 2022. A comparison of the spatial extent of lowest surface pressure and SST cooling (Fig. 1 a and 1 b) also illustrates comparatively lower cooling in the low surface pressure area towards the coast in spite of the availability of adequate depth for mixing to occur. An intercomparison between the three SST products was carried out for the three selected grids to analyse the probable differences in the response of the three different data products as presented in Fig. 4 . The three SST datasets were found to compare fairly well with each other with the best agreement between the ERA5 and OSTIA SST (Fig. 4 ). The REMSS SST dropped more sharply than the other two SSTs over the period of influence of the cyclone, especially in the intensification and landfall stages (Figs. 4 b & c). Further, the REMSS SST values over the intensification box underestimated ERA5 SST by 0.21°C, 0.30°C, 1.05°C, and 0.57°C on 7th, 8th, 9th, and 10th May 2022, respectively. However, the total SST cooling observed in the REMSS SST data over the three-day period from 8th to 10th May was overestimated as 2.51°C as compared to 2.14°C for the ERA5 SST. The REMSS SST values observed over the landfall area were also relatively cooler than the other two SST products although the magnitude of the difference was less (< 0.5°C) than the values over intensification grid. Compared to the ERA5 dataset which illustrated a ~ 0.1°C rise of SST on 11th May 2022, REMSS SST showed a drop of ~ 0.4°C. The largest difference (of 0.65°C) between the two datasets was observed on 11th May 2022. A total cooling of 0.65°C was observed over 9–13th May 2022 in ERA5 SST while the corresponding cooling observed in the REMSS SST was 0.86°C. Irrespective of these differences, the SST cooling in the landfall area was observed to be significantly less than that observed over the intensification area in both the data sets (Fig. 4 ), even though the cyclone entered both the grids with a comparable intensity. The TC however spent a significantly longer duration within the landfall area due to a sharp decrease in its TS. The total SST cooling during this period of influence of the cyclone in the landfall area was ~ 30% of that observed in the intensification area in all three SST datasets. The difference between the ERA5 SST and OSTIA SST are typically between 0.01–0.02°C in the open ocean (genesis and intensification area). The corresponding difference in the landfall area (near the coast) can be slightly higher (0.04–0.06°C) with a maximum difference of 0.065°C observed on 12th May. 5. Discussions The upper-ocean temperature responds to the TC wind forcing in multiple ways; the wind-driven vertical mixing and upwelling play a dominant role especially at higher wind speeds (Jullien et al. 2012 ). For weaker winds, e.g. during cyclogenesis, surface heat fluxes (especially LHF) can play a more significant role (Vincent et al. 2012 , Chowdhury et al. 2020). Wind-stirring (measured in terms of the proxy mixing parameter) associated with cyclones can indirectly cool waters close to the ocean surface by inducing velocity shear, which leads to the deepening of the mixed layer through the entrainment (turbulent mass flux) of deeper colder waters into the surface-adjacent layer (Subrahmanyam et al. 2002 ; Byju and Kumar 2011). Along with these entrainment processes, Ekman pumping (quantified in terms of the proxy quantity Ekaman pumping velocity) resulting from the positive wind stress curl (and resultant surface current divergence) can upwell deeper waters into the surface layer (Vinayachandra and Mathew 2003; Byju and Kumar 2011; Suzuki et al. 2011 ) resulting in surface cooling. In addition to the aforementioned process, coastal upwelling driven by alongshore windstress (associated with the divergence of surface currents along the coast, and measured in terms of the proxy offshore Ekman transport) can also have a similar effect near the coast (Smitha et al. 2006 ; Zhao et al. 2015 ). The contribution of these forcing mechanisms largely depend on the TS of the cyclone and the underlying oceanographic conditions (Yablonsky and Ginnis 2009). Slow moving cyclones (TS 13.5 kt). Cyclone Asani initially illustrated a moderate TS (TS between 7.56–13.50 kt) but decelerated to a slow TS (TS < 7.56 kt) roughly 27 hours prior to landfall, thereby allowing an extended period of interaction with the coast. Cyclone “Asani” induced SST cooling presented some interesting facts as emerged from the present study. On analyzing the four mechanisms which are key during a TC event and also generally responsible for the cyclone feedback with the ocean, contributions of each factor to SST cooling in the genesis area was found to be fairly straightforward. The first box covered the phase of initial intensification of the cyclone immediately following its genesis. Both, mixing parameter and the Ekman pumping velocity were relatively low in this area throughout the cyclone period. The region of high mixing parameter values remained diffused through most of the passage of the center of the cyclone through this box. By 2100 hours UTC of 7th May, mixing parameter values exceeding 0.3 are observed over a well-defined ring around the cyclone center with particularly high values observed behind the eye. Similar to the mixing parameter, the Ekman pumping is also initially observed as a diffused region of low positive pumping velocity values. With the intensification of the cyclone, as the center of the cyclone neared the north-western edge of the genesis area, high Ekman pumping velocities behind the eye of the cyclone (with magnitudes reaching 2.6 × 10 − 4 m/s) contributed to the peak of Ekamn pumping velocity observed at 1700 hours UTC of 7th May. However, in spite of the comparatively lower values of Ekamn pumping and mixing parameter observed here, a considerable SST cooling of 0.86°C is observed on the 7th of May 2022, corresponding to the date of maximum mixing parameter and Ekman pumping velocity values. The second area was selected to span a part of the cyclone where it displayed a strong intensity (64 kt) and moderately high TS, although both reduced partially as the center of the cyclone moved towards the north-west. The storm ‘Asani’ was categorized as a Severe Cyclonic Storm (maximum sustained wind speed between 48 to 63 kt) by IMD based on 3-min averaging of winds. However, the present analysis relied on 1-min sustained wind speeds available from IBTrACS. Since, 1-min averaging of winds overestimates the intensity when compared to a 3-min averaging; the IBTrACS sustained wind speeds are not expected to be comparable with IMD estimated winds. The cyclone intensity rose again upon leaving this area. The Ekman pumping velocity, and mixing parameter peaked in quick succession; the Ekman pumping at 1600 hours UTC, and the mixing parameter at 2300 hours UTC of 8th May 2022. The region of maximum Ekman pumping velocity was concentrated around the center of the cyclone with a large cross-track spread. Therefore, its peak coincided with the center traversing the box. The mixing parameter value also increased as the storm moved through the box while slowing down in TS. However, unlike the buoyancy flux, the mixing parameter value was the strongest behind the eye, on either side of the cyclone center. Consequently, the mixing peak appeared later as it corresponded with the entry of the high mixing region behind the eye into the box. The increase in heat flux parameters as the center exited the box and slowed down might have contributed to the strengthening of the cyclone at this stage. The strongest cooling was observed between 7th and 8th (> 1.5°C/day around the storm center), followed by that between 9th and 10th May 2022 (> 1.0°C/day). These periods also corresponded to a low TS of the cyclone. The cooling between 8th and 9th May was weak (< 0.5°C/day) and largely restricted to the rear and right of the cyclone track. TC “Asani” moved into the third region selected for analysis during its final phase of weaking and subsequent landfall as a deep depression. Therefore, the observations from this area allowed us to analyze the interaction of the cyclone with the coastal ocean, the primary focus of this analysis. The intensity and TS of the cyclone dropped steadily just as it entered this area. During this time, the spread of high mixing parameter values decreased considerably due to the weakening of the cyclone. This was also the time when the area of high mixing parameter values (around the center of the cyclone) entered the box. The peak values of this parameters within the box occurred at 1500 hours UTC of 10th May 2022, respectively. The peak value of mixing parameter was greater in this box compared to the previous one. Moderate to high values of both this parameter persisted in the region from 0600 hours UTC of 10th May till 1200 hours UTC on 11th May, 2022. However, the most significant observation in this region was the incredibly low SST cooling induced by cyclone “Asani”. On the day of peak mixing parameters, a minor warming of coastal SST (~ 0.1°C) was observed between 10th and 11th May (in the ERA5 SST data). The anticlockwise winds associated with the leading (ahead/east of eye) edge of the cyclone provided downwelling-favourable along-shore windstress (− 4.3 m 2 /s), and onshore Ekman transport. This downwelling favouring forcing could have easily counteracted the shear driven entrainment, thereby leading to a limited cooling or net warming. Eventually, as the cyclone center made landfall and the cyclone moved inland, the coast came under the influence of the trailing (west of/behind eye) edge of the cyclone which provided a moderately positive (offshore) Ekman transport (+ 1.0 m 2 /s) accompanied by a coastal SST cooling of 0.39°C. As cyclone “Asani” hovered around the coast (TS between 1–6 kt) both before and after landfall, a significant amount of weakening occurred between the interaction of the leading edge with the coast and the interaction of the trailing edge. Consequently, the upwelling-favouring forcing was significantly weaker than the downwelling favouring one. As entrainment caused cooling simultaneously with both of these processes, the SST response to the downwelling-favourable alongshore windstress was less than the response to upwelling-favouring alongshore wind stress. Similar observations of limited coastal SST cooling (resulting from the absence of upwelling-favouring winds) due to the partial interaction of a cyclone with a coast was also observed by Scorsati (2020) for cyclone “Dorian” along the western part of Nova Scotia. Wang and Zhang ( 2021 ) had also observed two instances of decline in biological activity (typically associated with downwelling, or reduced upwelling) resulting from onshore Ekman transport (driven by a negative alongshore windstress) during the interaction of typhoon “Linfa” with the coast of China. Gramer et al. ( 2022 ) used a coupled TC model (HWRF-B) and in situ ocean observations to show the development of coastal downwelling when 3 TCs approached land in 2020, illustrating the increase in air-sea enthalpy influencing the intensification of TCs. These past analyses (in addition to the present one) highlight an important mechanism by which TCs could limit the coastal temperature decline through partial interaction with a coastline (as a consequence of low TS or even the orientation of the track with respect to the coast). The present analysis establishes that coastal downwelling mediated restriction of SST cooling significantly influenced the intensity of TC Asani around the time of landfall. It is also highly possible that this restricted coastal cooling would in turn restrict the weakening of the cyclone just prior to its landfall. 6. Conclusions Ocean mixing driven by wind-stirring and buoyancy flux as well as open-ocean and coastal upwelling were all found to have significant variations through the course of cyclone “Asani”. As the intensity (wind speed) was not sufficiently strong just after genesis, buoyancy flux driven mixing appeared to play an important role in driving SST cooling during this phase. With the intensification of the cyclone, windstress curl increased near the center of the cyclone and the mixing parameter (wind-stirred) values increased behind the eye of the cyclone. This played an important role in extending the period of SST cooling as well as its intensity. The unique feature of Cyclone “Asani” was its extended interaction with the coast as result of its low TS during this phase. Around the time of landfall, in addition to the mechanisms already discussed, coastal downwelling-favouring alongshore windstress was found to play a pivotal role in restricting SST cooling. The leading part of the cyclone (north-west of the eye/ ahead of the eye) generated a coastal downwelling favourable forcing that was counteracted but only in part by shear-driven mixing and entrainment arising from wind-stirring. However, this limited the coastal SST cooling while the coasts were under the influence of the leading edge of the cyclone. On the other hand, the trailing edge of the cyclone (south-east of eye/ behind eye) could provide coastal upwelling-favourable forcing leading to significant weakening of cyclone “Asani” by this time due to its remarkably low TS prior to and after landfall. Thus, despite demonstrating the highest values of wind-stirred mixing parameter, the landfall region showed the lowest cooling compared to the genesis and intensification regions of the ocean for TC “Asani”. This phenomenon of restricted cooling of coastal SST (due to coastal downwelling), resulting from the partial interaction of the cyclone with the coast could be a significant mechanism influencing the intensity of slow moving cyclones close to the coast and needs to be investigated for other such TCs in the global oceans as well. Declarations Acknowledgements All authors acknowledge Indian Institute of Technology Bhubaneswar for providing necessary support for carrying out the present work. SSM acknowledges the Council of Scientific & Industrial Research (CSIR), Govt. of India for the Junior Research Fellowship. Funding No specific funding was received for carrying out this work Conflict of Interest The authors declare that they have no known conflict of interest. Author's contribution SR, SSM and DS have conceptualized the work; SR and SSM has carried out the analysis. SR, SSM and DS have written the manuscript. 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Front Mar Sci, 7. https://www.frontiersin.org/article/ 10.3389/fmars.2020.00651 Singh VK, Roxy MK (2022) A review of ocean-atmosphere interactions during tropical cyclones in the north Indian Ocean. Earth-Sci Rev 226, 103967. Smitha A, Rao KH, Sengupta D (2006) Effect of May 2003 tropical cyclone on physical and biological processes in the Bay of Bengal. Int J Remote Sens 27(23), 5301–5314. https://doi.org/10.1080/01431160600835838 Subrahmanyam B, Rao KH, Rao NS, Murty VSN, Sharp RJ (2002) Influence of a tropical cyclone on Chlorophyll-a Concentration in the Arabian Sea. Geophys Res Lett 29(22), 22–24. https://doi.org/10.1029/2002GL015892 Suzuki S, Niino H, Kimura R (2011) The mechanism of upper-oceanic vertical motions forced by a moving typhoon. Fluid Dyn Res 43, 025504. https://doi.org/10.1088/0169-5983/43/2/025504 UK Met Office (2012) OSTIA L4 SST Analysis (GDS2). Ver. 2.0. PO.DAAC, CA, USA. Dataset accessed 2022-05-29 at https://doi.org/10.5067/GHOST-4FK02 Varela R, Álvarez I, Santos F, DeCastro M, Gómez-Gesteira M (2015) Has upwelling strengthened along worldwide coasts over 1982–2010? Sci Rep 5(1), 1–15. Vinayachandran PN, Mathew S (2003) Phytoplankton bloom in the Bay of Bengal during the northeast monsoon and its intensification by cyclones. Geophys Res Lett 30(11). https://doi.org/10.1029/2002GL016717 Vincent EM, Lengaigne M, Madec G, Vialard J, Samson G, Jourdain NC, Menkes CE, Jullien, S (2012) Processes setting the characteristics of sea surface cooling induced by tropical cyclones. J Geophys Res: Oceans 117(C2). https://doi.org/10.1029/2011JC007396 Wang T, Zhang S (2021) Effect of Summer Typhoon Linfa on the Chlorophyll-a Concentration in the Continental Shelf Region of Northern South China Sea. J Mar Sci Engg 9(8), 794. Yablonsky RM, Ginis I (2009) Limitation of One-Dimensional Ocean Models for Coupled Hurricane–Ocean Model Forecasts. Mon Weather Rev 137(12), 4410–4419. https://doi.org/10.1175/2009MWR2863.1 Zhao H, Shao J, Han G, Yang D, Lv J (2015) Influence of Typhoon Matsa on Phytoplankton Chlorophyll-a off East China. PLoS One 10(9), e0137863. https://doi.org/10.1371/journal.pone.0137863 Zheng Z, Harcourt RR, D’Asaro EA (2021) Evaluating Monin–Obukhov Scaling in the Unstable Oceanic Surface Layer. J Phys Ocean 51(3), 911–930. https://doi.org/10.1175/JPO-D-20-0201.1 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2001209","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":133044801,"identity":"71f2649d-df5a-4a71-bf28-882d50333c06","order_by":0,"name":"Sthitapragya Ray","email":"","orcid":"","institution":"Indian Institute of Technology Bhubaneswar","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sthitapragya","middleName":"","lastName":"Ray","suffix":""},{"id":133044802,"identity":"f3b947a4-dd08-4277-854d-b580aa289707","order_by":1,"name":"Sidha Sankalpa Moharana","email":"","orcid":"","institution":"Indian Institute of Technology Bhubaneswar","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sidha","middleName":"Sankalpa","lastName":"Moharana","suffix":""},{"id":133044804,"identity":"ab61cc80-fbe4-4298-97d6-e1ced8e901d8","order_by":2,"name":"Debadatta Swain","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYDCCA0CcwGDDw8YARGDATJyWNB42NpK0MDAcZmCAayEE+M6fMfzwcMd5GT753mMPfzDYyTOw8x7Aq0XyRo6xROKZ20CH8aUb8zAkGzYw8yXg1WJwg3eDRGIbSAuPmTTQIwkMzDwG+LWcP7v5R2LbObAWyR8M9URoOZC7DWjLAbAWCR6Gw4S1SN7I/2aR2JYM1JIH9IvBccM2Qlr4zh9Lvvmzzc5evvksMMQqquX5+c/g14LuTmD8kKJ+FIyCUTAKRgF2AABDSzkEuGK78AAAAABJRU5ErkJggg==","orcid":"","institution":"Indian Institute of Technology Bhubaneswar","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Debadatta","middleName":"","lastName":"Swain","suffix":""}],"badges":[],"createdAt":"2022-08-26 10:29:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2001209/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2001209/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":25949838,"identity":"871602c8-4904-42b8-ba24-d431b6fbd534","added_by":"auto","created_at":"2022-09-01 19:30:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":318605,"visible":true,"origin":"","legend":"\u003cp\u003ea) Track of Tropical Cyclone “Asani” (white line), intensity (coloured dots), minimum mean sea level pressure (background colour), and study locations (magenta boxes) b) Total change in mean daily SST between 5\u003csup\u003eth\u003c/sup\u003e and 13\u003csup\u003eth\u003c/sup\u003e May (background color) with cyclone track (green line,) contours of bathymetry (black lines) and study locations (yellow boxes)\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2001209/v1/5670bde6bbd48d135fcbc130.png"},{"id":25949840,"identity":"385bf5f6-fc87-4266-808e-8b5afbd278c3","added_by":"auto","created_at":"2022-09-01 19:30:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":125713,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal variation of Monin-Obukhov Length over the genesis, intensification and landfall area\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2001209/v1/42096cdfabb828b95bb480d3.png"},{"id":25949839,"identity":"9df5813d-7840-4c2f-ae9e-b5901132b2bd","added_by":"auto","created_at":"2022-09-01 19:30:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":206451,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal variation of ERA5 SST, mixing parameter (proxy for wind-stirred mixing), Ekman pumping velocity (proxy for windstress curl driven open ocean upwelling), and Ekman transport (proxy for AWS driven coastal upwelling) over the (a) genesis, (b) maximum intensification and (c) landfall areas. The time of the genesis and landfall of the TC are marked with vertical orange lines (based on data from IBTrACS).\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2001209/v1/7bf768fe473be0d6ffbfd7b4.png"},{"id":25949841,"identity":"de515747-9f84-4376-a1ed-9d822eb0f6e8","added_by":"auto","created_at":"2022-09-01 19:30:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":182029,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal variation of ERA5 SST, OSTIA SST, and REMSS SST in the (a) genesis, (b) intensification, and (c) landfall area, along with the time of the cyclogenesis and landfall from IBTrACS marked as vertical orange lines.\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2001209/v1/d45f6f190110333b3092046b.png"},{"id":30016184,"identity":"abfc5c87-ceb7-496f-93ac-27e9123558c9","added_by":"auto","created_at":"2022-12-07 15:44:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1033201,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2001209/v1/bdc079e0-cb96-49e8-92c2-901eb7c2415f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ocean response to Tropical Cyclone “Asani”: Surface cooling restricted by Coastal Downwelling","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTropical cyclones (TCs) are among the most destructive natural hazards (Pielke et. al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). TCs are fueled by transfer of latent heat from the ocean surface which is also the primary source of energy driving these intense circulations (Emanuel \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Consequently, air-sea interactions play a crucial role in determining the intensity of TCs through positive and negative feedbacks. LHF being dependent on wind speed, increasing amounts of moisture gets evaporated from the sea surface as the cyclone intensifies. This in turn further intensifies the TC resulting in a positive feedback, usually dominant during the genesis phase. But as the storm intensifies, vertical mixing resulting from the high wind speed can also reduce the sea surface temperature (SST) thereby limiting the total heat flux into the cyclone and consequently weakening it, a negative feedback (Ginis \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). However, coastal downwelling due to a TC approaching land can cause increase in air-sea enthalpy flux, enabling TC intensification (Gramer et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTC \u0026ldquo;Asani\u0026rdquo; formed in the south-eastern Bay of Bengal (BoB) near the Little Andaman Islands on 6th May 2002. The well-marked low-pressure system moved north-westwards and gradually intensified into a severe cyclonic storm (SCS) with 3-min sustained wind speed of 55 kt during the early morning of 9th May till the noon of 10th. India Meteorological Department (IMD) forecasts had predicted a sharp recurvature as the cyclone neared the coast, aligning the track of the cyclone nearly parallel to the eastern coast of India (IMD 2022a). However, \u0026ldquo;Asani\u0026rdquo; deviated from this forecasted track and followed a north-westward trajectory instead. It also hovered near the coast until it weakened into a deep depression and made landfall between Machilipatnam and Naraspur (in Andhra Pradesh, India) with a very low TS in the evening of 11th May 2022. The system started dissipating as it weakened further to a well-marked low-pressure area and very low TS moving south-westward close to the coast on the morning of 12th May (IMD 2022b). Cyclone Asani illustrated moderate TS from the time of its genesis up to roughly 27 hours prior to landfall when it decelerated to a slow TS, following the IMD categorization of TS (Jangir et al \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rsmcnewdelhi.imd.gov.in/\u003c/span\u003e\u003cspan address=\"https://rsmcnewdelhi.imd.gov.in/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). As a result of the remarkably low TS of the cyclone just prior to and after landfall (IMD 2022b), it interacted with the coastal ocean for an extended period of time which could have resulted in intense coastal cooling. In this analysis, we have examined the role of different air-sea interaction processes and the local ocean response at three different stages of cyclone \u0026ldquo;Asani\u0026rdquo;.\u003c/p\u003e"},{"header":"2. Data","content":"\u003cp\u003eThe present analysis was carried out utilizing cyclone track datasets from the International Best Track Archive for Climate Stewardship (IBTrACS) which included latitude, longitude and wind speed information at 3 hour intervals (Knapp et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and 1-min averaged wind and storm track information from U.S. warning agencies. An uncertainty of \u0026plusmn;\u0026thinsp;10 kts in intensity and ~\u0026thinsp;20\u0026ndash;25 kms in position was reported for moderate intensity (60 kts\u0026thinsp;\u0026lt;\u0026thinsp;wind\u0026thinsp;\u0026lt;\u0026thinsp;100 kts) storms in the North Indian Ocean basin (IBTrACS Technical Documentation, accessed on 27-05-2022).\u003c/p\u003e \u003cp\u003eGeophysical parameters, such as SST, mean sea level pressure (MSLP), and 10 m surface wind components were obtained from Copernicus ERA5 climate reanalysis data archive (Hersbach et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) for the month of May 2022. This fifth generation ECMWF reanalysis follows data assimilation methods using model with observations from across the globe with uncertainty estimates calculated from 10-member ensembles at 3-hour intervals. The meteorological and oceanographic parameter fields are available from 1951 to present and are at 1 hour temporal and 0.25\u0026deg; \u0026times; 0.25\u0026deg; spatial resolutions on regular latitude \u0026ndash; longitude grids.\u003c/p\u003e \u003cp\u003eTwo other foundation SST datasets were obtained from GHRSST Level 4 OSTIA global foundation SST analysis (Donlon et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; UK Met Office \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and GHRSST Level 4 Remote Sensing Systems (REMSS) Microwave-Infrared Optimally Interpolated (MW-IR OI) SST (Remote Sensing Systems \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) for comparison and validation of ERA5 SST product. The OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis) SST is a daily gridded level 4 analysis product from the UK Met Office, provided on a 0.054\u0026deg; grid. The OSTIA analysis uses satellite observations from sensors such as the Advanced Very High Resolution Radiometer (AVHRR), the Spinning Enhanced Visible and Infrared Imager (SEVIRI), the Geostationary Operational Environmental Satellite (GOES) imager, the Infrared Atmospheric Sounding Interferometer (IASI), the Tropical Rainfall Measuring Mission Microwave Imager (TMI) and in situ data from ships, drifting and moored buoys (Donlon et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The REMSS SST uses a diurnal model to generate a 0.09\u0026deg; resolution daily foundation SST combining the through-cloud capabilities of microwave sensors such as Global Precipitation Measurement (GPM), Microwave Imager (GMI), Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), the NASA Advanced Microwave Scanning Radiometer-EOS (AMSRE), and the Advanced Microwave Scanning Radiometer 2 (AMSR2). High spatial resolution and near-coastal capabilities of infrared SST sensors, such as that of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) were also included. The REMSS SST analysis however does not use any \u003cem\u003ein situ\u003c/em\u003e observations (Remote Sensing Systems \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThe track and intensity of TC \u0026ldquo;Asani\u0026rdquo; from IBTrACS data was overlaid on the minimum ERA5 mean sea level pressure (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea). Three boxes (2\u0026deg; \u0026times; 2\u0026deg;) were identified corresponding to the genesis, maximum intensity, and landfall regions of the cyclone. All subsequent analysis were carried out based on these selected areas. We then attempted to identify suitable proxy measures for each of the four primary air-sea interaction mechanisms driving the ocean response: wind-stirred mixing, buoyancy flux driven mixing, open ocean upwelling and coastal upwelling.\u003c/p\u003e\n\u003cp\u003eThe Monin-Obhukov similarity theory (Monin and Obhukov 1954) describes the comparison of the dynamic significance of buoyancy flux to wind-stirring in terms of their contribution to the turbulent kinetic energy (TKE) within the ocean boundary layer through the Monin-Obhukov length scale (L) (Zheng 2021), as:\u003c/p\u003e\n\u003cdiv class=\"Equation\" id=\"Equ1\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e$$L= \\frac{{u}_{*}^{3}}{\\kappa {B}_{0}}$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003ewhere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{*}\\)\u003c/span\u003e\u003c/span\u003e is the friction velocity, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({B}_{0}\\)\u003c/span\u003e\u003c/span\u003e is the surface buoyancy flux and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\kappa =0.4\\)\u003c/span\u003e\u003c/span\u003e is the Von Karman constant. The magnitude of L is an estimate of the depth at which buoyancy flux dominates over wind-stirring in TKE production. Based on this, we selected \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{*}^{3}\\)\u003c/span\u003e\u003c/span\u003e (which is proportional to the cube of surface wind speed) to be the proxy for wind-stirred production of TKE where,\u003c/p\u003e\n\u003cdiv class=\"Equation\" id=\"Equ2\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e$${u}_{*}=\\sqrt{{\\tau }_{0}/{\\rho }_{a}}$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\({\\tau }_{0}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e being the surface windstress and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\rho }_{a}\\)\u003c/span\u003e\u003c/span\u003e being the surface air density. Different formulations of wind energy transfer at the surface use a similar dependence on the cube of surface wind speed; the total power dissipation is formulated by Emmanuel (2005) as a spatio-temporal integral involving the cube of surface wind speed. Niiler (\u003cspan class=\"CitationRef\"\u003e1977\u003c/span\u003e) similarly quantified the wind-stirred TKE production within the ocean mixed layer as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{*}^{3}\\)\u003c/span\u003e\u003c/span\u003e in the 1 dimensional bulk mixed layer theory.\u003c/p\u003e\n\u003cp\u003eThe surface buoyancy flux (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({B}_{0}\\)\u003c/span\u003e\u003c/span\u003e) was considered to be the proxy for buoyant TKE production. As the density of seawater depends on temperature and salinity, both air-sea heat and moisture fluxes could alter the surface water density making the water column more or less buoyant. Following Cronin (\u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e), the buoyancy flux (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({B}_{0}\\)\u003c/span\u003e\u003c/span\u003e) could be expressed in terms of the net surface heat flux (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Q}_{0}\\)\u003c/span\u003e\u003c/span\u003e), rate of evaporation (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(E\\)\u003c/span\u003e\u003c/span\u003e) and precipitation (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(P\\)\u003c/span\u003e\u003c/span\u003e) as:\u003c/p\u003e\n\u003cdiv class=\"Equation\" id=\"Equ3\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e$${B}_{0}=-\\frac{g\\alpha }{\\rho {c}_{p}}{Q}_{0}+g\\beta {S}_{0}(E-P)$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003ewhere, g is the acceleration due to gravity, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({S}_{0}\\)\u003c/span\u003e\u003c/span\u003e is the surface salinity, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\rho\\)\u003c/span\u003e\u003c/span\u003e is the density of sea water, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({c}_{p}\\)\u003c/span\u003e\u003c/span\u003e is its specific heat, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\alpha\\)\u003c/span\u003e\u003c/span\u003e (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\alpha = -\\frac{1}{\\rho } \\frac{\\partial \\rho }{\\partial T}\\)\u003c/span\u003e\u003c/span\u003e) is the thermal expansion coefficient, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta\\)\u003c/span\u003e\u003c/span\u003e (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta = \\frac{1}{\\rho }\\frac{\\partial \\rho }{\\partial S}\\)\u003c/span\u003e\u003c/span\u003e) is the haline contraction coefficient. A positive buoyancy flux due to heat loss or excess evaporation makes the surface waters less buoyant (more dense), decreases convective stability of the water column with the resultant overturning leading to the entrainment of deeper waters to the surface.\u003c/p\u003e\n\u003cp\u003eThe open ocean upwelling process is quantified in terms of the Ekman pumping velocity (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({w}_{E}\\)\u003c/span\u003e\u003c/span\u003e) which is the vertical velocity produced at the base of the Ekman layer due to the divergence of surface currents resulting from a positive windstress curl at the surface. The Ekman pumping velocity is expressed as:\u003c/p\u003e\n\u003cdiv class=\"Equation\" id=\"Equ4\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e$${w}_{E}=\\frac{\\overrightarrow{{\\nabla }_{z}} \\times \\overrightarrow{{\\tau }_{0}}}{\\rho f}$$\u003c/div\u003e\n \u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003ewhere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\tau }_{0}\\)\u003c/span\u003e\u003c/span\u003e is the surface windstress, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\rho\\)\u003c/span\u003e\u003c/span\u003e is the density of water, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(f\\)\u003c/span\u003e\u003c/span\u003e is the Coriolis parameter (Smith 1968). In the vicinity of the coast, the alongshore windstress (AWS) could generate a divergence of surface currents along the coast, resulting in coastal upwelling (Smith 1968). This process is quantified in terms of the Ekman transport (M) which represents the horizontal flow of coastal waters in the cross-shore direction (Smith 1968; Varela et. al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Jayaram and Kumar \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), given by:\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Taba\"\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(M= \\frac{{\\tau }_{l}}{\\rho f}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e(5)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewhere,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\tau }_{l}= {\\rho }_{a}{c}_{d}{v}_{l}\\sqrt{{u}^{2}+{v}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewhere,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({v}_{l}= \\pm (u\\text{cos}\\left(\\theta -\\frac{\\pi }{2}\\right)+v sin \\left(\\theta -\\frac{\\pi }{2}\\right))\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ewhere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({c}_{d}\\)\u003c/span\u003e\u003c/span\u003e is the drag coefficient, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\tau }_{l}\\)\u003c/span\u003e\u003c/span\u003e is the alongshore windstress, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({v}_{l}\\)\u003c/span\u003e\u003c/span\u003e is the alongshore wind speed, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(u\\)\u003c/span\u003e\u003c/span\u003e is the zonal wind speed, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(v\\)\u003c/span\u003e\u003c/span\u003e is the meridional wind speed, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\theta\\)\u003c/span\u003e\u003c/span\u003e is the coastal angle, which is the angle subtended by the seaward normal to the coastline. The sign of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({v}_{l}\\)\u003c/span\u003e\u003c/span\u003e is negative (positive) in the northern (southern) hemisphere.\u003c/p\u003e\n\u003cp\u003eThree 2\u0026deg;\u0026times; 2\u0026deg; boxes (as in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) were selected along the track of the cyclone covering three different stages. The ERA5 SST and the first three proxy parameters, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({u}_{*}^{3}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({B}_{0}\\)\u003c/span\u003e\u003c/span\u003e, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({w}_{E}\\)\u003c/span\u003e\u003c/span\u003e were computed within each box over the period from 0000 UTC of 3rd May, 2022 to 2300 UTC on 15th May, 2022. The first box extended between 9 \u0026deg;N \u0026ndash; 11 \u0026deg;N and 89.35 \u0026deg;E \u0026ndash; 91.35 \u0026deg;E and covered the location of genesis and the earlier part of the intensification of the cyclone. The second box which spanned the location just prior to the cyclone reaching its maximum intensity extended between 12 \u0026deg;N \u0026ndash; 14 \u0026deg;N and 86 \u0026deg;E \u0026ndash; 88 \u0026deg;E. The third box extends between 14 \u0026deg;N \u0026ndash; 16 \u0026deg;N and 80.5 \u0026deg;E \u0026ndash; 82.5 \u0026deg;E and stretched over the final part of the TC trajectory where it started weakening and finally made landfall. In addition to the above three, the Ekman transport (M) associated with coastal upwelling was also computed for the third box which spanned the coastal region. For this, five coastal points that lay within this box area were selected and the coastal angle was computed at each of those points. The zonal and meridional wind speed were sampled at each of these five points for every time-step using a Cressman window (Cressman \u003cspan class=\"CitationRef\"\u003e1959\u003c/span\u003e) of 50 km radius, and the mean Ekman transport (M) over the five points were obtained. Further, ERA5 SST was also inter-compared with OSTIA SST and REMSS SST over each of these boxes to ascertain the performance of the SST products.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cp\u003eThe Monin-Obukhov length (L) computed over each of the three areas is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The greatest variation of L is observed in the intensification area of the cyclone with minimum values less than 10\u003csup\u003e3\u003c/sup\u003e m observed in the period immediately prior to its genesis. During the period of influence of the cyclone, the value of L ranges between 10\u003csup\u003e4\u003c/sup\u003e \u0026ndash; 10\u003csup\u003e9\u003c/sup\u003e m in all three areas. This implies that shear-driven TKE production dominates over buoyant TKE production within the depth of the surface mixed layer. The subsequent analysis therefore focuses on wind-stirred TKE production and upwelling as the key mechanisms regulating the oceanic response to the cyclone.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe computed values of all the mixing parameters were plotted for the entire duration of the cyclone over the three 2\u0026deg; \u0026times; 2\u0026deg; boxes and presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e along with the corresponding SST values (from the ERA5, OISST and REMSS SST data sets). The largest SST drop was observed for the second box corresponding to the region just before TC \u0026ldquo;Asani\u0026rdquo; reached its maximum intensity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb), while the lowest SST drop was surprisingly observed for the landfall area of the cyclone (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe eye of the cyclone passed over the box labelled genesis area between 0600 to 2100 hours UTC of 7th May 2022, the first 15 hours after its genesis. During this time, it gradually intensified from a sustained wind speed of 39 kt to 55 kt (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The TS of the cyclone was moderate, varying between 8\u0026ndash;10 kt. The mixing parameter remained low in this region throughout the observed period (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), reaching a maximum value of about 0.2 m\u003csup\u003e3\u003c/sup\u003e/s\u003csup\u003e3\u003c/sup\u003e between 1900 hours UTC of 7th May to 0000 hours UTC of 8th May 2022. A moderately low Ekman pumping value of less than 0.5 m/s was observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea) with a peak around 1800 hours UTC of 7th May. The ERA5 SST dropped by 0.22\u0026deg;C from 6th to 7th and by 0.862\u0026deg;C from 7th to 8th May 2022 (total of 1.08\u0026deg;C over two days).\u003c/p\u003e \u003cp\u003eThe second box covered the track of Cyclone \u0026ldquo;Asani\u0026rdquo;, where it reached its maximum intensity (64 kts) from 1200 to 1800 hours UTC (1730 to 2330 IST) of 8th May before weakening down to 54 kts. The cyclone began intensification again upon its center leaving this area. Interestingly, the cyclone slowed down at this point allowing enhanced LHF which again caused intensification (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The cyclone had a high TS of 9\u0026ndash;12 kt while traversing this area. The proxy parameters for the different air-sea interaction processes show an interesting variation over this area: Ekman pumping velocity and wind-stirring based mixing parameter peaked in quick succession (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The Ekman pumping velocity began to rise in this area from 2200 hours UTC of 7th May, reaching a maximum value of over 1.7\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e m/s at 1600 hours UTC of 8th May (during the period of maximum intensity), before dropping again to about \u0026minus;\u0026thinsp;0.18\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e m/s on 0700 hours UTC of 9th May 2022. The mixing parameter rose sharply from 1800 hours UTC of 7th May reaching a maximum of 0.84 m\u003csup\u003e3\u003c/sup\u003e/s\u003csup\u003e3\u003c/sup\u003e between 2300 hours UTC on 8th May (5 hours after the maximum intensity period) and 0000 hours UTC of the following day. The mixing parameter also showed a second weaker peak of 0.82 m\u003csup\u003e3\u003c/sup\u003e/s\u003csup\u003e3\u003c/sup\u003e on 0700 hours UTC of 9th May and subsequently dropped below 0.1 m\u003csup\u003e3\u003c/sup\u003e/s\u003csup\u003e3\u003c/sup\u003e by 0200 hours UTC of 10th May. The ERA5 SST in this area dropped continuously from 7th to 12th May, with the sharpest falls of 0.74\u0026deg;C, 0.54\u0026deg;C, and 0.86\u0026deg;C observed on the 8th, 9th, and 10th of May, respectively. A total SST cooling of 2.14\u0026deg;C was observed in ERA5 SST in this area over the 3-day period.\u003c/p\u003e \u003cp\u003eThe final box, labelled landfall area, covered the final part of the cyclone from 0600 hours UTC of 10th May till landfall on 11th May and its subsequent weakening. While the cyclone entered this area with a TS of 11 kts, it dropped sharply varying between 1\u0026ndash;6 kt for the remaining period. This remarkably slow TS resulted in the cyclone spending an unusually high amount of time in the near vicinity of the coast. The intensity of the cyclone also dropped during this period from 64 kt to 35 kt just prior to landfall (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec illustrates the Ekman pumping velocity to remain very low (magnitude\u0026thinsp;\u0026lt;\u0026thinsp;0.15 \u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e m/s) here throughout the influence of the cyclone, reaching a value of around \u0026minus;\u0026thinsp;0.14 \u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e m/s on 0700 hours UTC of 9th May (prior to the entry of the eye of the cyclone into the region), and increasing to 0.11 \u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e m/s at 1800 hours UTC on the following day. The mixing parameter rose sharply from 1800 hours UTC of 9th May, reaching a maximum value of 1.16 m\u003csup\u003e3\u003c/sup\u003e/s\u003csup\u003e3\u003c/sup\u003e on 1500 hours UTC (2030 IST) of 10th May 2022, and then decreasing below 0.1 m\u003csup\u003e3\u003c/sup\u003e/s\u003csup\u003e3\u003c/sup\u003e by 1800 hours UTC the following day (6 hours after landfall). The mean Ekman mass transport (resulting from costal upwelling) also began to decrease from 1000 hours UTC of 9th May 2022 before attaining the maximum onshore Ekman transport of 4.28 m\u003csup\u003e2\u003c/sup\u003e/s on 1900 hours UTC of 10th May (17 hours before landfall). It increased subsequently to a weakly positive value of 1.05 m\u003csup\u003e2\u003c/sup\u003e/s on 1900 hours UTC of 11th May (7 hours after landfall) and dropped close to zero thereafter. Surprisingly, in spite of observed higher values of wind-stirred mixing parameter and buoyancy flux, the ERA5 SST in this region remained fairly constant and in fact rose by about 0.1\u0026deg;C between the 10th and 11th of May 2022, and a dropped hardly about 0.4\u0026deg;C between the 11th and 12th of May 2022. A comparison of the spatial extent of lowest surface pressure and SST cooling (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) also illustrates comparatively lower cooling in the low surface pressure area towards the coast in spite of the availability of adequate depth for mixing to occur.\u003c/p\u003e \u003cp\u003eAn intercomparison between the three SST products was carried out for the three selected grids to analyse the probable differences in the response of the three different data products as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The three SST datasets were found to compare fairly well with each other with the best agreement between the ERA5 and OSTIA SST (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The REMSS SST dropped more sharply than the other two SSTs over the period of influence of the cyclone, especially in the intensification and landfall stages (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb \u0026amp; c). Further, the REMSS SST values over the intensification box underestimated ERA5 SST by 0.21\u0026deg;C, 0.30\u0026deg;C, 1.05\u0026deg;C, and 0.57\u0026deg;C on 7th, 8th, 9th, and 10th May 2022, respectively. However, the total SST cooling observed in the REMSS SST data over the three-day period from 8th to 10th May was overestimated as 2.51\u0026deg;C as compared to 2.14\u0026deg;C for the ERA5 SST. The REMSS SST values observed over the landfall area were also relatively cooler than the other two SST products although the magnitude of the difference was less (\u0026lt;\u0026thinsp;0.5\u0026deg;C) than the values over intensification grid. Compared to the ERA5 dataset which illustrated a\u0026thinsp;~\u0026thinsp;0.1\u0026deg;C rise of SST on 11th May 2022, REMSS SST showed a drop of ~\u0026thinsp;0.4\u0026deg;C. The largest difference (of 0.65\u0026deg;C) between the two datasets was observed on 11th May 2022. A total cooling of 0.65\u0026deg;C was observed over 9\u0026ndash;13th May 2022 in ERA5 SST while the corresponding cooling observed in the REMSS SST was 0.86\u0026deg;C. Irrespective of these differences, the SST cooling in the landfall area was observed to be significantly less than that observed over the intensification area in both the data sets (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), even though the cyclone entered both the grids with a comparable intensity. The TC however spent a significantly longer duration within the landfall area due to a sharp decrease in its TS. The total SST cooling during this period of influence of the cyclone in the landfall area was ~\u0026thinsp;30% of that observed in the intensification area in all three SST datasets. The difference between the ERA5 SST and OSTIA SST are typically between 0.01\u0026ndash;0.02\u0026deg;C in the open ocean (genesis and intensification area). The corresponding difference in the landfall area (near the coast) can be slightly higher (0.04\u0026ndash;0.06\u0026deg;C) with a maximum difference of 0.065\u0026deg;C observed on 12th May.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"5. Discussions","content":"\u003cp\u003eThe upper-ocean temperature responds to the TC wind forcing in multiple ways; the wind-driven vertical mixing and upwelling play a dominant role especially at higher wind speeds (Jullien et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). For weaker winds, e.g. during cyclogenesis, surface heat fluxes (especially LHF) can play a more significant role (Vincent et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Chowdhury et al. 2020). Wind-stirring (measured in terms of the proxy mixing parameter) associated with cyclones can indirectly cool waters close to the ocean surface by inducing velocity shear, which leads to the deepening of the mixed layer through the entrainment (turbulent mass flux) of deeper colder waters into the surface-adjacent layer (Subrahmanyam et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Byju and Kumar 2011). Along with these entrainment processes, Ekman pumping (quantified in terms of the proxy quantity Ekaman pumping velocity) resulting from the positive wind stress curl (and resultant surface current divergence) can upwell deeper waters into the surface layer (Vinayachandra and Mathew 2003; Byju and Kumar 2011; Suzuki et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) resulting in surface cooling. In addition to the aforementioned process, coastal upwelling driven by alongshore windstress (associated with the divergence of surface currents along the coast, and measured in terms of the proxy offshore Ekman transport) can also have a similar effect near the coast (Smitha et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The contribution of these forcing mechanisms largely depend on the TS of the cyclone and the underlying oceanographic conditions (Yablonsky and Ginnis 2009). Slow moving cyclones (TS\u0026thinsp;\u0026lt;\u0026thinsp;7.56 kt) have more time to interact with the ocean and therefore cause greater cooling (Mandal et al. 2018; Singh and Roxy \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) than faster moving ones (TS\u0026thinsp;\u0026gt;\u0026thinsp;13.5 kt). Cyclone Asani initially illustrated a moderate TS (TS between 7.56\u0026ndash;13.50 kt) but decelerated to a slow TS (TS\u0026thinsp;\u0026lt;\u0026thinsp;7.56 kt) roughly 27 hours prior to landfall, thereby allowing an extended period of interaction with the coast.\u003c/p\u003e \u003cp\u003eCyclone \u0026ldquo;Asani\u0026rdquo; induced SST cooling presented some interesting facts as emerged from the present study. On analyzing the four mechanisms which are key during a TC event and also generally responsible for the cyclone feedback with the ocean, contributions of each factor to SST cooling in the genesis area was found to be fairly straightforward. The first box covered the phase of initial intensification of the cyclone immediately following its genesis. Both, mixing parameter and the Ekman pumping velocity were relatively low in this area throughout the cyclone period. The region of high mixing parameter values remained diffused through most of the passage of the center of the cyclone through this box. By 2100 hours UTC of 7th May, mixing parameter values exceeding 0.3 are observed over a well-defined ring around the cyclone center with particularly high values observed behind the eye. Similar to the mixing parameter, the Ekman pumping is also initially observed as a diffused region of low positive pumping velocity values. With the intensification of the cyclone, as the center of the cyclone neared the north-western edge of the genesis area, high Ekman pumping velocities behind the eye of the cyclone (with magnitudes reaching 2.6 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e m/s) contributed to the peak of Ekamn pumping velocity observed at 1700 hours UTC of 7th May. However, in spite of the comparatively lower values of Ekamn pumping and mixing parameter observed here, a considerable SST cooling of 0.86\u0026deg;C is observed on the 7th of May 2022, corresponding to the date of maximum mixing parameter and Ekman pumping velocity values.\u003c/p\u003e \u003cp\u003eThe second area was selected to span a part of the cyclone where it displayed a strong intensity (64 kt) and moderately high TS, although both reduced partially as the center of the cyclone moved towards the north-west. The storm \u0026lsquo;Asani\u0026rsquo; was categorized as a Severe Cyclonic Storm (maximum sustained wind speed between 48 to 63 kt) by IMD based on 3-min averaging of winds. However, the present analysis relied on 1-min sustained wind speeds available from IBTrACS. Since, 1-min averaging of winds overestimates the intensity when compared to a 3-min averaging; the IBTrACS sustained wind speeds are not expected to be comparable with IMD estimated winds. The cyclone intensity rose again upon leaving this area. The Ekman pumping velocity, and mixing parameter peaked in quick succession; the Ekman pumping at 1600 hours UTC, and the mixing parameter at 2300 hours UTC of 8th May 2022. The region of maximum Ekman pumping velocity was concentrated around the center of the cyclone with a large cross-track spread. Therefore, its peak coincided with the center traversing the box. The mixing parameter value also increased as the storm moved through the box while slowing down in TS. However, unlike the buoyancy flux, the mixing parameter value was the strongest behind the eye, on either side of the cyclone center. Consequently, the mixing peak appeared later as it corresponded with the entry of the high mixing region behind the eye into the box. The increase in heat flux parameters as the center exited the box and slowed down might have contributed to the strengthening of the cyclone at this stage. The strongest cooling was observed between 7th and 8th (\u0026gt;\u0026thinsp;1.5\u0026deg;C/day around the storm center), followed by that between 9th and 10th May 2022 (\u0026gt;\u0026thinsp;1.0\u0026deg;C/day). These periods also corresponded to a low TS of the cyclone. The cooling between 8th and 9th May was weak (\u0026lt;\u0026thinsp;0.5\u0026deg;C/day) and largely restricted to the rear and right of the cyclone track.\u003c/p\u003e \u003cp\u003eTC \u0026ldquo;Asani\u0026rdquo; moved into the third region selected for analysis during its final phase of weaking and subsequent landfall as a deep depression. Therefore, the observations from this area allowed us to analyze the interaction of the cyclone with the coastal ocean, the primary focus of this analysis. The intensity and TS of the cyclone dropped steadily just as it entered this area. During this time, the spread of high mixing parameter values decreased considerably due to the weakening of the cyclone. This was also the time when the area of high mixing parameter values (around the center of the cyclone) entered the box. The peak values of this parameters within the box occurred at 1500 hours UTC of 10th May 2022, respectively. The peak value of mixing parameter was greater in this box compared to the previous one. Moderate to high values of both this parameter persisted in the region from 0600 hours UTC of 10th May till 1200 hours UTC on 11th May, 2022. However, the most significant observation in this region was the incredibly low SST cooling induced by cyclone \u0026ldquo;Asani\u0026rdquo;. On the day of peak mixing parameters, a minor warming of coastal SST (~\u0026thinsp;0.1\u0026deg;C) was observed between 10th and 11th May (in the ERA5 SST data). The anticlockwise winds associated with the leading (ahead/east of eye) edge of the cyclone provided downwelling-favourable along-shore windstress (\u0026minus;\u0026thinsp;4.3 m\u003csup\u003e2\u003c/sup\u003e/s), and onshore Ekman transport. This downwelling favouring forcing could have easily counteracted the shear driven entrainment, thereby leading to a limited cooling or net warming. Eventually, as the cyclone center made landfall and the cyclone moved inland, the coast came under the influence of the trailing (west of/behind eye) edge of the cyclone which provided a moderately positive (offshore) Ekman transport (+\u0026thinsp;1.0 m\u003csup\u003e2\u003c/sup\u003e/s) accompanied by a coastal SST cooling of 0.39\u0026deg;C. As cyclone \u0026ldquo;Asani\u0026rdquo; hovered around the coast (TS between 1\u0026ndash;6 kt) both before and after landfall, a significant amount of weakening occurred between the interaction of the leading edge with the coast and the interaction of the trailing edge. Consequently, the upwelling-favouring forcing was significantly weaker than the downwelling favouring one. As entrainment caused cooling simultaneously with both of these processes, the SST response to the downwelling-favourable alongshore windstress was less than the response to upwelling-favouring alongshore wind stress.\u003c/p\u003e \u003cp\u003eSimilar observations of limited coastal SST cooling (resulting from the absence of upwelling-favouring winds) due to the partial interaction of a cyclone with a coast was also observed by Scorsati (2020) for cyclone \u0026ldquo;Dorian\u0026rdquo; along the western part of Nova Scotia. Wang and Zhang (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) had also observed two instances of decline in biological activity (typically associated with downwelling, or reduced upwelling) resulting from onshore Ekman transport (driven by a negative alongshore windstress) during the interaction of typhoon \u0026ldquo;Linfa\u0026rdquo; with the coast of China. Gramer et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) used a coupled TC model (HWRF-B) and in situ ocean observations to show the development of coastal downwelling when 3 TCs approached land in 2020, illustrating the increase in air-sea enthalpy influencing the intensification of TCs. These past analyses (in addition to the present one) highlight an important mechanism by which TCs could limit the coastal temperature decline through partial interaction with a coastline (as a consequence of low TS or even the orientation of the track with respect to the coast). The present analysis establishes that coastal downwelling mediated restriction of SST cooling significantly influenced the intensity of TC Asani around the time of landfall. It is also highly possible that this restricted coastal cooling would in turn restrict the weakening of the cyclone just prior to its landfall.\u003c/p\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003eOcean mixing driven by wind-stirring and buoyancy flux as well as open-ocean and coastal upwelling were all found to have significant variations through the course of cyclone \u0026ldquo;Asani\u0026rdquo;. As the intensity (wind speed) was not sufficiently strong just after genesis, buoyancy flux driven mixing appeared to play an important role in driving SST cooling during this phase. With the intensification of the cyclone, windstress curl increased near the center of the cyclone and the mixing parameter (wind-stirred) values increased behind the eye of the cyclone. This played an important role in extending the period of SST cooling as well as its intensity. The unique feature of Cyclone \u0026ldquo;Asani\u0026rdquo; was its extended interaction with the coast as result of its low TS during this phase. Around the time of landfall, in addition to the mechanisms already discussed, coastal downwelling-favouring alongshore windstress was found to play a pivotal role in restricting SST cooling. The leading part of the cyclone (north-west of the eye/ ahead of the eye) generated a coastal downwelling favourable forcing that was counteracted but only in part by shear-driven mixing and entrainment arising from wind-stirring. However, this limited the coastal SST cooling while the coasts were under the influence of the leading edge of the cyclone. On the other hand, the trailing edge of the cyclone (south-east of eye/ behind eye) could provide coastal upwelling-favourable forcing leading to significant weakening of cyclone \u0026ldquo;Asani\u0026rdquo; by this time due to its remarkably low TS prior to and after landfall. Thus, despite demonstrating the highest values of wind-stirred mixing parameter, the landfall region showed the lowest cooling compared to the genesis and intensification regions of the ocean for TC \u0026ldquo;Asani\u0026rdquo;. This phenomenon of restricted cooling of coastal SST (due to coastal downwelling), resulting from the partial interaction of the cyclone with the coast could be a significant mechanism influencing the intensity of slow moving cyclones close to the coast and needs to be investigated for other such TCs in the global oceans as well.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors acknowledge Indian Institute of Technology Bhubaneswar for providing necessary support for carrying out the present work. SSM acknowledges the Council of Scientific \u0026amp; Industrial Research (CSIR), Govt. of India for the Junior Research Fellowship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for carrying out this work\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor's contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSR, SSM and DS have conceptualized the work; SR and SSM has carried out the analysis. SR, SSM and DS have written the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eByju P, Prasanna Kumar S (2011) Physical and biological response of the Arabian Sea to tropical cyclone Phyan and its implications. 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J Phys Ocean 51(3), 911\u0026ndash;930. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1175/JPO-D-20-0201.1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cyclone Asani, Coastal upwelling, Ekman transport, Downwelling, Translational speed","lastPublishedDoi":"10.21203/rs.3.rs-2001209/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2001209/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe severe cyclonic storm “Asani” formed in the southeastern Bay of Bengal on 6\u003csup\u003eth\u003c/sup\u003e May 2022 and made landfall on the evening of 11\u003csup\u003eth\u003c/sup\u003e May 2022 in Andhra Pradesh, India. The unique characteristic of this cyclone was its low TS from roughly 27 hours prior to its landfall resulting in a remarkably prolonged interaction with the coastal ocean. In this analysis, we examined the sea surface temperature (SST) response to the cyclone at three locations along its track and analyzed the temporal variation of the observed cyclone-driven SST cooling. Four different ocean processes (wind-stirred and buoyancy flux-driven mixing, windstress-curl and alongshore windstress driven upwelling) could be identified by the corresponding proxies as the drivers of this cooling. A SST cooling of 1.08 °C was observed over a two-day period around the genesis area. Ekman pumping and wind-stirred mixing illustrated high values over the maximum intensity region during the passage of the cyclone, resulting in a SST drop by 2.14 °C. The landfall area had a significantly longer duration of interaction with the cyclone, as its TS reduced from moderate to slow, exhibiting wind-stirred mixing values comparable to the other two regions. However, the SST drop was the lowest at ~0.65 °C. Coastal downwelling-favourable windstress associated with the leading edge of the cyclone was responsible for limiting the cooling that could have otherwise resulted from mixing and entrainment. This unique modification of cyclone-ocean interaction through coastal upwelling possibly delayed the dissipation of cyclone “Asani”.\u003c/p\u003e","manuscriptTitle":"Ocean response to Tropical Cyclone “Asani”: Surface cooling restricted by Coastal Downwelling","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-09-01 19:30:41","doi":"10.21203/rs.3.rs-2001209/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f832f8e-26f3-4dc5-9a0d-47831588f860","owner":[],"postedDate":"September 1st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-12-07T15:44:31+00:00","versionOfRecord":[],"versionCreatedAt":"2022-09-01 19:30:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2001209","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2001209","identity":"rs-2001209","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}