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Observing and Studying Extreme Low Pressure Events with Altimetry

Loren Carrère, Françoise Mertz, Joel Dorandeu, Yves Quilfen, Jerome Patoux
2009 Sensors  
Specific altimeter treatments have been developed for tropical cyclones and applied to obtain a relevant along-track sea surface height (SSH) signal: the case of tropical cyclone Isabel is presented here  ...  More accurate strong altimeter wind speeds are computed thanks to the Young algorithm.  ...  : buoy data include the NDBC network, data available via Météo-France, and the TAO array; -the ECMWF pressure analyses at 0.5 degree-6 hour resolution; -the QuikSCAT scatterometer wind measurements; QuikSCAT  ... 
doi:10.3390/s90301306 pmid:22573955 pmcid:PMC3345817 fatcat:hrmoauqlu5d2nid6htuxvuxpaq

Storm Eye Identification Using Fuzzy Inference System

Kulwarun Warunsin, Orachat Chitsobhuk
2016 International Journal of Innovative Computing, Information and Control  
The ocean wind vectors are provided by the NASA QuikSCAT satellite to predict the significance of tropical cyclogenesis. This database is slightly noisy, incomplete and indirect.  ...  However, the cloud shape may be ambiguous, which can introduce a long search time. As a result, utilizing combined information from both resources can lead to a reduction in resource deficiency.  ...  Fully automatic cyclone identification was approached using the Support Vector Machines (SVM) technique on QuikSCAT wind data [4] , while the same objective cyclone identification based on the Fuzzy-C  ... 
doi:10.24507/ijicic.12.04.1333 fatcat:rt4lu2g5mbdudhnlomc5izsmdy

Estimates of tropical cyclone geometry parameters based on best-track data

Kees Nederhoff, Alessio Giardino, Maarten van Ormondt, Deepak Vatvani
2019 Natural Hazards and Earth System Sciences  
Parametric wind profiles are commonly applied in a number of engineering applications for the generation of tropical cyclone (TC) wind and pressure fields.  ...  Outer wind speeds can be reproduced well by the commonly used Holland wind profile when calibrated using information either from best-track data or from the proposed relationships.  ...  Final thanks are due to Stuart Pearson for proofreading a previous version of the article and providing valuable comments, which have led to an improved paper. Financial support.  ... 
doi:10.5194/nhess-19-2359-2019 fatcat:mjo4qakj3fhz3m5nvztshdb5fq

QSCAT-R: The QuikSCAT Tropical Cyclone Radial Structure Dataset QSCAT-R: The QuikSCAT Tropical Cyclone Radial Structure Dataset Wind radii and radial profiles of wind and rain for Tropical Cyclones globally

Daniel Chavas, Jonathan Vigh, Daniel Chavas, Jonathan Vigh, Daniel Chavas, Daniel Chavas, Jonathan Vigh
2014 unpublished
The Technical Notes series provides an outlet for a variety of NCAR Manuscripts that contribute in specialized ways to the body of scientific knowledge but that are not yet at a point of a formal journal  ...  cyclone wind field products used as the basis for this dataset, as well as for their assistance in navigating data access and understanding the origins and limitations of the data.  ...  Acknowledgements" The authors gratefully thank Bryan Stiles and Svetla Hristova-Veleva of the NASA Jet Propulsion Laboratory (JPL) for all of their hard work in creating the 2-D QuikSCAT-based tropical  ... 
fatcat:q6vmshovkza5fhz6m3eaao63di

Challenges to Satellite Sensors of Ocean Winds: Addressing Precipitation Effects

D. E. Weissman, B. W. Stiles, S. M. Hristova-Veleva, D. G. Long, D. K. Smith, K. A. Hilburn, W. L. Jones
2012 Journal of Atmospheric and Oceanic Technology  
When Quick Scatterometer (QuikSCAT) was launched in 1999, it ushered in a new era of dual-polarized, pencil-beam, higher-resolution scatterometers for measuring the global ocean surface winds from space  ...  A constant limitation on the full utilization of scatterometer-derived winds is the presence of isolated rain events, which affect about 7% of the observations.  ...  The QuikSCAT data were provided by the NASA Jet Propulsion Laboratory PO.DAAC.  ... 
doi:10.1175/jtech-d-11-00054.1 fatcat:lxbdzy6i3zd7fdpytg646gvrye

Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling

Mark A. Bourassa, Thomas Meissner, Ivana Cerovecki, Paul S. Chang, Xiaolong Dong, Giovanna De Chiara, Craig Donlon, Dmitry S. Dukhovskoy, Jocelyn Elya, Alexander Fore, Melanie R. Fewings, Ralph C. Foster (+22 others)
2019 Frontiers in Marine Science  
The observational needs for a wide range of wind and stress applications are provided. These needs strongly support a short list of desired capabilities of future missions and constellations.  ...  Strengths and weakness of remotely sensed winds are discussed, along with the current capabilities for remotely sensing winds and stress. Future missions are briefly mentioned.  ...  Shen et al. (2012) developed a technique to extract the wind speed from the strength of the 1st order returns using neural networks that has the advantage of longer-range observation, but the range of  ... 
doi:10.3389/fmars.2019.00443 fatcat:mbket5dcjvaibhd2j5ngkyvvri

A comparative assessment of monthly mean wind speed products over the global ocean

Elizabeth C. Kent, Susanne Fangohr, David I. Berry
2012 International Journal of Climatology  
Twelve different monthly mean wind speed datasets are compared for the period from 1987 to 2009.  ...  The in situ and reanalysis datasets present stability-dependent, earth-relative, wind speeds adjusted to a reference level of 10 m.  ...  QuikSCAT data (QS_RSS4) are produced by Remote Sensing Systems (http://www.remss. com) and sponsored by the NASA Ocean Vector Winds Science Team.  ... 
doi:10.1002/joc.3606 fatcat:64jkmnd6ejhqziexxjqz2g6b6u

A Comparison of Atmospheric Reanalysis Surface Products over the Ocean and Implications for Uncertainties in Air–Sea Boundary Forcing

Ayan H. Chaudhuri, Rui M. Ponte, Gael Forget, Patrick Heimbach
2013 Journal of Climate  
errors, particularly in the tropics.  ...  Adjusted atmospheric fields from the Estimating the Circulation and Climate of the Ocean (ECCO) optimizations are also in agreement with other reanalysis products.  ...  The precipitation values are derived from a neural network-based precipitation algorithm that takes SSM/I data as input (Andersson et al. 2010) .  ... 
doi:10.1175/jcli-d-12-00090.1 fatcat:xgrclkknf5bqfkd43tgcrb67zy

A Novel Tropical Cyclone Size Estimation Model Based on a Convolutional Neural Network Using Geostationary Satellite Imagery

You-Hyun Baek, Il-Ju Moon, Jung-Ho Im, Ju-Hyun Lee
2022 Remote Sensing  
A novel tropical cyclone (TC) size estimation model (TC-SEM) in the western North Pacific was developed based on a convolutional neural network (CNN) using geostationary satellite infrared (IR) images.  ...  The proposed TC-SEM was tested using three CNN schemes: a single-task regression model that separately estimated the radius of maximum wind (RMW) and the radius of 34 kt wind (R34) of the TC, a multi-task  ...  Data Convolutional Neural Network (CNN) A CNN is a hierarchical neural network system that can extract and analyze feature vectors from complex multidimensional data [32] .  ... 
doi:10.3390/rs14020426 fatcat:qvqi6hzdv5fk3kk26ngizlob7y

Confidence and sensitivity study of the OAFlux multisensor synthesis of the global ocean surface vector wind from 1987 onward

Lisan Yu, Xiangze Jin
2014 Journal of Geophysical Research - Oceans  
It is worth noting, however, a new QuikSCAT product was recently developed by Fore et al. [2014], in which a neural network approach was implemented to correct rain contaminated wind speeds  ...  The time series was synthesized from multiple satellite sensors using a variational approach to find a L.  ... 
doi:10.1002/2014jc010194 fatcat:qx5zqelrfjdknhcimr23irefxq

A More Accurate Field-to-Field Method towards the Wind Retrieval of HY-2B Scatterometer

Xinjie Shi, Boheng Duan, Kaijun Ren
2021 Remote Sensing  
In this paper, we present a method for retrieving sea surface wind field (SSWF) from HaiYang-2B (HY-2B) scatterometer data.  ...  the neural network model, and then synchronously obtain the wind field within the range.  ...  Acknowledgments: MetOp-A and MetOp-B data were obtained from https://data.eumetsat.int/ (accessed on 20 May 2021).  ... 
doi:10.3390/rs13122419 fatcat:grisbrhyije73pq3jgjo7y272a

High Wind Geophysical Model Function Modeling for the HY-2A Scatterometer Using Neural Network

Xuetong Xie, Jing Wang, Mingsen Lin
2022 Remote Sensing  
To enhance the wind retrieval precision of the HY-2A scatterometer under high wind conditions, a new GMF for high wind (HW-GMF) is established by using the neural network method based on the backscattering  ...  Under low to medium wind speeds and no rainfall, the retrieved vector wind from a scatterometer is accurate and reliable.  ...  As a consequence, the maximum sustained wind speed represents the highest average wind speed in one minute near the eye of a tropical cyclone [41, 42] .  ... 
doi:10.3390/rs14102335 fatcat:747ydj4jkje7fdclf6jgzr4nqa

New possibilities for geophysical parameter retrievals opened by GCOM-W1 AMSR2

Elizaveta Zabolotskikh, Leonid Mitnik, Nicolas Reul, Bertrand Chapron
2014 2014 13th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad)  
A new approach to retrieve sea surface wind speed (SWS) in tropical cyclones (TCs) from the Advanced Microwave Scanning Radiometer 2 (AMSR2) data is presented.  ...  Despite few particular cases, most SWS fields are in a very good agreement with TC center data on maximum wind speeds, radii of storm, and hurricane winds.  ...  Both algorithms use simulated microwave radiances and Neural Networks (NNs) approach to create inversion operators for the algorithm derivation.  ... 
doi:10.1109/microrad.2014.6878931 fatcat:vctybm433nh5lcbq6k6bwzvpa4

New Possibilities for Geophysical Parameter Retrievals Opened by GCOM-W1 AMSR2

Elizaveta V. Zabolotskikh, Leonid M. Mitnik, Nicolas Reul, Bertrand Chapron
2015 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
A new approach to retrieve sea surface wind speed (SWS) in tropical cyclones (TCs) from the Advanced Microwave Scanning Radiometer 2 (AMSR2) data is presented.  ...  Despite few particular cases, most SWS fields are in a very good agreement with TC center data on maximum wind speeds, radii of storm, and hurricane winds.  ...  Both algorithms use simulated microwave radiances and Neural Networks (NNs) approach to create inversion operators for the algorithm derivation.  ... 
doi:10.1109/jstars.2015.2416514 fatcat:n4vuutufb5gyxiceuh32ebe6v4

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Tropical Cyclone Center  ...  ., +, TGRS Feb. 2019 655-666 Tropical Cyclone Center Automatic Determination Model Based on HY-2 and QuikSCAT Wind Vector Products.  ...  Titchenko, Y., +, TGRS Feb. 2019 936-943 Tropical Cyclone Center Automatic Determination Model Based on HY-2 and QuikSCAT Wind Vector Products.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
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