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Remote Sensing of Winds and Windstress for Ocean State Forecasting...
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Remote Sensing of Winds and Windstress for Ocean State Forecasting and Modelling

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (30 August 2022) | Viewed by 12093

Special Issue Editors

Dr. Meer Mohammed Ali

E-Mail Website
Guest Editor
Florida State University, Tallahassee, United States
Interests: ocean–atmosphere interaction; air–sea interaction
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mark Bourassa

E-Mail Website
Co-Guest Editor
Department of Earth, Ocean and Atmospheric Science, Florida State University, EOAS Building 1011 Academic Way, Tallahassee, FL 32306, USA
Interests: remote sensing of the surface and boundary layer; boundary layers (ocean and atmosphere); air–sea interaction; the observing system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The two main sources of ocean energy are the incoming solar radiation and the winds. Wind stress, driving the ocean currents, is the most important force, particularly in the tropical and subtropical oceans. The availability of stress helps to improve the estimates of surface scalar fluxes (for example, sensible and latent heats, evaporation, and gas fluxes). Using stress directly avoids the uncertainty of how the sea state modifies stress determined from winds. Stress is also required in estimating the white cap fraction that affects the remote sensing of the ocean through an ocean color monitor. Furthermore, it also helps in evaluating the magnitude of wind-forced currents, upper ocean transport, and the wind roughness contribution to the surface signal for remotely sensed surface salinity. Stress can be described in terms of surface roughness relating to either scatterometer or altimeter observations, or in conventional monitoring, where it can be described in terms of near surface vertical wind shear modified by atmospheric stability.

Since in situ measurements of winds/windstress have spatial and temporal limitations, remote sensing techniques have been developed since the launch of Seasat in 1978. While scatterometers provide vector winds, altimeters can give only scalar winds. Estimating windstress at the ocean surface from winds at 10 m height assumes a neutrally stable atmosphere, which is not always the case. Hence, methodologies have also been developed to infer this parameter at the ocean surface directly from scatterometers and altimeters.

In this Special Issue, we solicit articles on estimating winds and/or windstress from remote platforms, their retrievals, and the advantage of using them in various fields of ocean and atmosphere, including modeling.

Dr. Meer Mohammed Ali
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • winds
  • windstress
  • remote sensing
  • scatterometers
  • altimeters
  • ocean modeling
  • atmospheric stability
  • ocean currents

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Published Papers (5 papers)

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15 pages, 10277 KiB  
Article
Generation of Non-Linear Technique Based 6 Hourly Wind Reanalysis Products Using SCATSAT-1 and Numerical Weather Prediction Model Outputs
by Suchandra Aich Bhowmick, Maneesha Gupta, Abhisek Chakraborty, Neeraj Agarwal, Rashmi Sharma and Meer Mohammed Ali
Remote Sens. 2023, 15(4), 1040; https://doi.org/10.3390/rs15041040 - 14 Feb 2023
Cited by 2 | Viewed by 1397
Abstract
We combined observations of ocean surface winds from Indian SCATterometer SATellite-1 (SCATSAT-1) with a background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium-Range Weather Forecast (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive [...] Read more.
We combined observations of ocean surface winds from Indian SCATterometer SATellite-1 (SCATSAT-1) with a background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium-Range Weather Forecast (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. We are following the concept from the modern particle filter technique, which does not represent the model probability density function (PDF) as Gaussian. We generated the 6-hourly hybrid winds for 2018 and validated them using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform (CCMP) dataset and global buoy data from National Data Buoy Centre (NDBC). The results suggest the potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and bias along the swath. The study shows that the generated hybrid winds are of prime quality compared with the already existing daily products available from Indian Space Research Organization (ISRO). Full article
(This article belongs to the Special Issue Remote Sensing of Winds and Windstress for Ocean State Forecasting and Modelling)
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23 pages, 7838 KiB  
Article
Coastal Upwelling in the Western Bay of Bengal: Role of Local and Remote Windstress
by Sthitapragya Ray, Debadatta Swain, Meer M. Ali and Mark A. Bourassa
Remote Sens. 2022, 14(19), 4703; https://doi.org/10.3390/rs14194703 - 21 Sep 2022
Cited by 6 | Viewed by 2782
Abstract
Monsoon winds drive upwelling along the eastern coast of India. This study examined the role of coastally trapped Kelvin waves in modulating the seasonal variability of local alongshore windstress (AWS)-driven coastal upwelling along the western Bay of Bengal. The winds generated AWS resulting [...] Read more.
Monsoon winds drive upwelling along the eastern coast of India. This study examined the role of coastally trapped Kelvin waves in modulating the seasonal variability of local alongshore windstress (AWS)-driven coastal upwelling along the western Bay of Bengal. The winds generated AWS resulting in a positive cross-shore Ekman transport (ET) from March to the end of September, which forced coastal upwelling along the eastern coast of India. However, coastally trapped Kelvin waves could also modulate this process by raising or lowering the thermocline. Remotely sensed windstress, sea surface temperature (SST), and sea surface height anomaly (SSHA) were used to compute the AWS (the wind-based proxy upwelling index) and an SST-based proxy upwelling index (UISST). A new parametric method of the estimation of coastal angles was developed to estimate the AWS and ET. Coastal upwelling and the Kelvin waves were identified based on the climatology of SSHA, AWS, and UISST, in addition to a complex principal component (CEOF) analysis of the SSHA. The UISST and AWS were found to be closely correlated along the southern section of the east coast of India (between Kavali and Point Calimere), where the coastal upwelling was largely local AWS-driven. However, along the northern section of the coast (between Kashinagara and Kakinada), coastal upwelling was triggered by the first upwelling Kelvin wave, sustained by the local AWS, and then terminated by the first downwelling Kelvin wave. This analysis illustrated that remote equatorial windstress caused coastal upwelling along the northern part of the Indian east coast, while it was primarily locally driven in the southern coast. The findings are helpful in better understanding the mechanisms modulating coastal upwelling along the western Bay of Bengal. These would provide useful insights into the primary productivity and the air–sea interactions in the region. Full article
(This article belongs to the Special Issue Remote Sensing of Winds and Windstress for Ocean State Forecasting and Modelling)
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13 pages, 4991 KiB  
Article
Impact of Ocean Currents on Wind Stress in the Tropical Indian Ocean
by Neethu Chacko, Meer M. Ali and Mark A. Bourassa
Remote Sens. 2022, 14(7), 1547; https://doi.org/10.3390/rs14071547 - 23 Mar 2022
Cited by 5 | Viewed by 2669
Abstract
This study examines the effect of surface currents on the bulk algorithm calculation ofwind stress estimated using the scatterometer data during 2007–2020 in the Indian Ocean. In the study region as a whole, the wind stress decreased by 5.4% by including currents in [...] Read more.
This study examines the effect of surface currents on the bulk algorithm calculation ofwind stress estimated using the scatterometer data during 2007–2020 in the Indian Ocean. In the study region as a whole, the wind stress decreased by 5.4% by including currents in the wind stress equation. The most significant reduction in the wind stress is found along the most energetic regions with strong currents such as Somali Current, Equatorial Jets, and Agulhas retroflection. The highest reduction of 11.5% is observed along the equator where the Equatorial Jets prevail. A sensitivity analysis has been carried out for the study region and for different seasons to assess the relative impact of winds and currents in the estimation of wind stress by changing the winds while keeping the currents constants and vice versa. The inclusion of currents decreased the wind stress (consistent with scatterometer winds) and this decrease is prominent when the currents are stronger. This study showed that the equatorial Indian Ocean is the most sensitive region where the current can impact wind stress estimation. The results showed that uncertainties in the wind stress estimations are quite large at regional levels and hence better representation of wind stress incorporating ocean currents should be considered in the ocean/climatic models for accurate air-sea interaction studies that are not based on remotely sensed winds. Full article
(This article belongs to the Special Issue Remote Sensing of Winds and Windstress for Ocean State Forecasting and Modelling)
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18 pages, 5897 KiB  
Article
Ocean–Atmosphere Interactions during Hurricanes Marco and Laura (2020)
by Emily N. Eley, Bulusu Subrahmanyam and Corinne B. Trott
Remote Sens. 2021, 13(10), 1932; https://doi.org/10.3390/rs13101932 - 15 May 2021
Cited by 7 | Viewed by 2569
Abstract
During August of the 2020 Atlantic Hurricane Season, the Gulf of Mexico (GoM) was affected by two subsequent storms, Hurricanes Marco and Laura. Hurricane Marco entered the GoM first (22 August) and was briefly promoted to a Category 1 storm. Hurricane Laura followed [...] Read more.
During August of the 2020 Atlantic Hurricane Season, the Gulf of Mexico (GoM) was affected by two subsequent storms, Hurricanes Marco and Laura. Hurricane Marco entered the GoM first (22 August) and was briefly promoted to a Category 1 storm. Hurricane Laura followed Marco closely (25 August) and attained Category 4 status after a period of rapid intensification. Typically, hurricanes do not form this close together; this study aims to explain the existence of both hurricanes through the analysis of air-sea fluxes, local thermodynamics, and upper-level circulation. The GoM and its quality of warm, high ocean heat content waters proved to be a resilient and powerful reservoir of heat and moisture fuel for both hurricanes; however, an area of lower ocean heat content due to circulation dynamics was crucial in the evolution of both Marco and Laura. An analysis of wind shear further explained the evolution of both hurricanes. Furthermore, a suite of satellite observations and ocean model outputs were used to evaluate the biophysical modulations in the GoM. The cold core eddy (CCE) and Mississippi River surface plume had the greatest biophysical oceanic responses; the oceanic modulations were initialized by Marco and extended temporally and spatially by Laura. Reduced sea surface temperatures (SST), changes in sea surface salinity (SSS), and changes in Chlorophyll-a (Chl-a) concentrations are related to translation speeds, and respective contributions of hurricane winds and precipitation are evaluated in this work. Full article
(This article belongs to the Special Issue Remote Sensing of Winds and Windstress for Ocean State Forecasting and Modelling)
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14 pages, 6343 KiB  
Technical Note
Analysis of the 10–20-Day Intraseasonal Oscillation in the Indian Ocean Using Surface Winds
by Heather L. Roman-Stork and Mark A. Bourassa
Remote Sens. 2022, 14(14), 3419; https://doi.org/10.3390/rs14143419 - 16 Jul 2022
Viewed by 1313
Abstract
The 10–20-day mode of surface wind is examined in the Indian Ocean, with special reference to the Arabian Sea, Bay of Bengal, equatorial, southern, and southeastern Indian Ocean during a strong (1994), weak (2002), and normal (1995) southwest monsoon season. Results indicate the [...] Read more.
The 10–20-day mode of surface wind is examined in the Indian Ocean, with special reference to the Arabian Sea, Bay of Bengal, equatorial, southern, and southeastern Indian Ocean during a strong (1994), weak (2002), and normal (1995) southwest monsoon season. Results indicate the 10–20-day mode of surface winds in the Bay of Bengal, southern Indian Ocean, and southeastern Indian Ocean is more energetic than in other regions. The strongest 10–20-day signal is found to be in the southeastern Indian Ocean, where 45% of surface wind variability can be explained by this mode during a strong monsoon year. Composite analysis based on a time series in this region revealed a positive surface wind anomaly that appears at 60°E, centered on 15°S, and propagates zonally eastward to 90°E before reflecting back to propagate westward and then disperse off the coast of Madagascar. It is proposed that this oscillating positive wind anomaly is a feature of the southernmost cell of the 10–20-day convective double-cell structure that has extended farther south into the southern Indian Ocean and that this mode connects the northern and southern Indian Ocean through surface winds and atmospheric convection through the motion of the linked double-cell structure. Full article
(This article belongs to the Special Issue Remote Sensing of Winds and Windstress for Ocean State Forecasting and Modelling)
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