Estimating Tropical Cyclone Intensity by Satellite Imagery Utilizing Convolutional Neural Networks

AbstractAccurately estimating tropical cyclone (TC) intensity is one of the most critical steps in TC forecasting and disaster warning/management. For over 40 years, the Dvorak technique (and sever...

[1]  C. M. Kishtawal,et al.  Estimating impacts of North Atlantic tropical cyclones using an index of damage potential , 2018, Climatic Change.

[2]  Nitish Srivastava,et al.  Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..

[3]  V. F. Dvorak Tropical Cyclone Intensity Analysis and Forecasting from Satellite Imagery , 1975 .

[4]  Christopher A. Davis,et al.  Diagnosing Forecast Errors in Tropical Cyclone Motion , 2013 .

[5]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[6]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[7]  Anand K. Inamdar,et al.  Intercomparison of Independent Calibration Techniques Applied to the Visible Channel of the ISCCP B1 Data , 2015 .

[8]  Sander Dieleman,et al.  Rotation-invariant convolutional neural networks for galaxy morphology prediction , 2015, ArXiv.

[9]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[10]  James L. Franklin,et al.  THE JOINT HURRICANE TEST BED Its First Decade of Tropical Cyclone Research-To-Operations Activities Reviewed , 2012 .

[11]  Yoshua. Bengio,et al.  Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..

[12]  Jin-Fang Qian,et al.  Tropical Cyclone Intensity Estimation Using RVM and DADI Based on Infrared Brightness Temperature , 2016 .

[13]  R. Murnane,et al.  A globally consistent reanalysis of hurricane variability and trends , 2007 .

[14]  Simon Haykin,et al.  GradientBased Learning Applied to Document Recognition , 2001 .

[15]  Christopher S. Velden,et al.  Tropical Cyclone Convection and Intensity Analysis Using Differenced Infrared and Water Vapor Imagery , 2009 .

[16]  Abdollah Homaifar,et al.  Objective Tropical Cyclone Intensity Estimation Using Analogs of Spatial Features in Satellite Data , 2013 .

[17]  Geoffrey E. Hinton,et al.  Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.

[18]  Hsuan-Tien Lin,et al.  Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression , 2018, KDD.

[19]  D. Herndon,et al.  An Update on Tropical Cyclone Intensity Estimation from Satellite Microwave Sounders , 2014 .

[20]  Bradford S. Barrett,et al.  Relationships between Tropical Cyclone Intensity and Eyewall Structure as Determined by Radial Profiles of Inner-Core Infrared Brightness Temperature , 2014 .

[21]  Roy W. Spencer,et al.  Atlantic Tropical Cyclone Monitoring with AMSU-A: Estimation of Maximum Sustained Wind Speeds , 2001 .

[22]  Jonathan H. Jiang,et al.  Dependence of US hurricane economic loss on maximum wind speed and storm size , 2014, 1403.5581.

[23]  Chian-Yi Liu,et al.  A satellite-derived typhoon intensity index using a deviation angle technique , 2015 .

[24]  Yuan Yu,et al.  TensorFlow: A system for large-scale machine learning , 2016, OSDI.

[25]  T. Nakazawa,et al.  Intercomparison of Dvorak Parameters in the Tropical Cyclone Datasets over the Western North Pacific , 2009 .

[26]  Chaofang Zhao,et al.  A Multiple Linear Regression Model for Tropical Cyclone Intensity Estimation from Satellite Infrared Images , 2016 .

[27]  D. Herndon,et al.  The CIMSS SATellite CONsensus (SATCON) tropical cyclone intensity algorithm , 2010 .

[28]  Jun A. Zhang,et al.  Evaluating Environmental Impacts on Tropical Cyclone Rapid Intensification Predictability Utilizing Statistical Models , 2015 .

[29]  Edward J. Zipser,et al.  Relationships between Tropical Cyclone Intensity and Satellite-Based Indicators of Inner Core Convection: 85-GHz Ice-Scattering Signature and Lightning , 1999 .

[30]  Mark A. Bourassa,et al.  Globally Gridded Satellite Observations for Climate Studies , 2011 .

[31]  Rahul Ramachandran,et al.  Tropical Cyclone Intensity Estimation Using Deep Convolutional Neural Networks , 2018 .

[32]  Timothy L. Olander,et al.  The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years , 2006 .

[33]  Charles R. Sampson,et al.  Is Tropical Cyclone Intensity Guidance Improving , 2014 .

[34]  Christopher S. Velden,et al.  Development of an Objective Scheme to Estimate Tropical Cyclone Intensity from Digital Geostationary Satellite Infrared Imagery , 1998 .

[35]  Mark DeMaria,et al.  A Statistical Hurricane Intensity Prediction Scheme (SHIPS) for the Atlantic Basin , 1994 .

[36]  Timothy L. Olander,et al.  The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery , 2007 .

[37]  John A. Knaff,et al.  Evaluation of Advanced Microwave Sounding Unit Tropical-Cyclone Intensity and Size Estimation Algorithms , 2004 .

[38]  J. Scott Tyo,et al.  Tropical Cyclone Intensity Estimation in the North Atlantic Basin Using an Improved Deviation Angle Variance Technique , 2012 .

[39]  Yoshua Bengio,et al.  Deep Sparse Rectifier Neural Networks , 2011, AISTATS.

[40]  J. Scott Tyo,et al.  Satellite-Derived Tropical Cyclone Intensity in the North Pacific Ocean Using the Deviation-Angle Variance Technique , 2014 .

[41]  Lakshmi Kantha,et al.  Tropical Cyclone Destructive Potential by Integrated Kinetic Energy , 2008 .

[42]  V. F. Dvorak Tropical cyclone intensity analysis using satellite data , 1984 .

[43]  Donald T. Resio,et al.  The Influence of Storm Size on Hurricane Surge , 2008 .

[44]  E. Newnham,et al.  The Tropical Cyclone , 1926, Nature.

[45]  Ying-Hwa Kuo,et al.  Effects of Low-Level Flow Orientation and Vertical Shear on the Structure and Intensity of Tropical Cyclones , 2018, Monthly Weather Review.

[46]  Thomas A. Jones,et al.  Passive-Microwave-Enhanced Statistical Hurricane Intensity Prediction Scheme , 2006 .

[47]  Charles R. Sampson,et al.  An Operational Statistical Typhoon Intensity Prediction Scheme for the Western North Pacific , 2005 .

[48]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).