Cyclones, Hurricanes, Typhoons, Radar, Cloud analysis

Chapter Contents (Back)
Cyclone. Hurricane. Typhoon.
See also Weather Radar Applications, Meteorological Radar, Weather Analysis.
See also Wind Sensing, Wind Speed, Wind from Sensors.

Lee, R.S.T., Liu, J.N.K.,
An Automatic Satellite Interpretation of Tropical Cyclone Patterns Using Elastic Graph Dynamic Link Model,
PRAI(13), No. 8, December 1999, pp. 1251. 0005

Zhou, L.[Lin], Kambhamettu, C.[Chandra], Goldgof, D.B.[Dmitry B.], Palaniappan, K., Hasler, A.F.,
Tracking Nonrigid Motion and Structure from 2D Satellite Cloud Images without Correspondences,
PAMI(23), No. 11, November 2001, pp. 1330-1336.
Integrate local analysis with global fluid motion constraints. BibRef

Zhou, L.[Lin], Kambhamettu, C.[Chandra],
Hierarchical Structure and Nonrigid Motion Recovery from 2D Monocular Views,
CVPR00(II: 752-759).

Zhou, L.[Lin], Kambhamettu, C.[Chandra], Goldgof, D.B.[Dmitry B.],
Fluid Structure and Motion Analysis from Multi-spectrum 2D Cloud Image Sequences,
CVPR00(II: 744-751).
Extracting Nonrigid Motion and 3D Structure of Hurricanes from Satellite Image Sequences without Correspondences,
CVPR99(II: 280-285).
See also coarse-to-fine deformable contour optimization framework, A. Weather BibRef

Balasubramanian, R., Goldgof, D.B., Kambhamettu, C.,
Tracking of nonrigid motion and 3D structure from 2D image sequences without correspondences,
ICIP98(I: 933-937).

Kambhamettu, C., Palaniappan, K., Hasler, A.F.,
Coupled, Multi-Resolution Stereo and Motion Analysis,
IEEE DOI NASA/Goddard Space Flight Center. Applied to satellite weather images. BibRef 9500

Lee, R.S.T., Liu, J.N.K.,
An elastic contour matching model for tropical cyclone pattern recognition,
SMC-B(31), No. 3, June 2001, pp. 413-417.
IEEE Top Reference. 0108

Tuttle, J., and Gall, R.,
A single-radar technique for estimating the winds in tropical cyclones,
Meteorological(80), No. 4, 1999, pp. 653-668. BibRef 9900

Majumdar, K.K.,
A mathematical model of the nascent cyclone,
GeoRS(41), No. 5, May 2003, pp. 1118-1122.
IEEE Abstract. 0307

Yueh, S.H., Stiles, B.W., Liu, W.T.,
Quikscat wind retrievals for tropical cyclones,
GeoRS(41), No. 11, November 2003, pp. 2616-2628.
IEEE Abstract. 0311

Wong, K.Y.[Ka Yan], Yip, C.L.[Chi Lap],
Identifying centers of circulating and spiraling vector field patterns and its applications,
PR(42), No. 7, July 2009, pp. 1371-1387.
Elsevier DOI 0903
A Fast and Noise-Tolerant Method for Positioning Centers of Spiraling and Circulating Vector Fields,
ACCV07(II: 764-773).
Springer DOI 0711
Earlier: A2, A1:
Identifying centers of circulating and spiraling flow patterns,
ICPR06(I: 769-772).
Vector field; Center identification; Rotation center detection; Tropical cyclone eye fix; Circulating and spiraling vector field center. Center of region of high magnitude of vorticity. BibRef

Wong, K.Y.[Ka Yan], Yip, C.L.[Chi Lap], Li, P.W.[Ping Wah],
Identifying Weather Systems from Numerical Weather Prediction Data,
ICPR06(IV: 841-844).

Wong, K.Y.[Ka Yan], Yip, C.L.[Chi Lap], Li, P.W.[Ping Wah],
Automatic tropical cyclone eye fix using genetic algorithm,
ExSysApp(34), No. 1, 2008, pp. 643-656.
Elsevier DOI BibRef 0800

Wong, K.Y.[Ka Yan], Yip, C.L.[Chi Lap], Li, P.W.[Ping Wah], Tsang, W.W.[Wai Wan],
Automatic template matching method for tropical cyclone eye fix,
ICPR04(III: 650-653).

Reppucci, A., Lehner, S., Schulz-Stellenfleth, J., Brusch, S.,
Tropical Cyclone Intensity Estimated From Wide-Swath SAR Images,
GeoRS(48), No. 4, April 2010, pp. 1639-1649.

Wei, K.[Kun], Jing, Z.L.[Zhong-Liang], Li, Y.X.[Yuan-Xiang], Liu, S.L.[Su-Liang],
Spiral band model for locating Tropical Cyclone centers,
PRL(32), No. 6, 15 April 2011, pp. 761-770.
Elsevier DOI 1103
Tropical Cyclone; Center locating; Spiral band model; Particle swarm optimization BibRef

Kamal, M., Yang, R., Qu, J.,
Multivariate Analysis of MODerate Resolution Imaging Spectroradiometer (MODIS) Aerosol Retrievals and the Statistical Hurricane Intensity Prediction Scheme (SHIPS) Parameters for Atlantic Hurricanes,
RS(4), No. 9, September 2012, pp. 2846-2865.
DOI Link 1210

Pan, Y.F.[Yu-Fang], Liu, A.K.[Antony K.], He, S.Y.[Shuang-Yan], Yang, J.S.[Jing-Song], He, M.X.[Ming-Xia],
Comparison of Typhoon Locations over Ocean Surface Observed by Various Satellite Sensors,
RS(5), No. 7, 2013, pp. 3172-3189.
DOI Link 1308

Kumar, P., Kumar, K.P.H.[K.P. Harish], Pal, P.K.,
Impact of Oceansat-2 Scatterometer Winds and TMI Observations on Phet Cyclone Simulation,
GeoRS(51), No. 6, 2013, pp. 3774-3779.
storms; weather forecasting; cyclone track; Wind speed; Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) BibRef

Yang, S.[Song], Hawkins, J.[Jeffrey], Richardson, K.[Kim],
The Improved NRL Tropical Cyclone Monitoring System with a Unified Microwave Brightness Temperature Calibration Scheme,
RS(6), No. 5, 2014, pp. 4563-4581.
DOI Link 1407

Wang, Y.[Yu], Fu, Y.F.[Yun-Fei], Fang, X.[Xiang], Zhang, Y.[Ying],
Estimating Ice Water Path in Tropical Cyclones With Multispectral Microwave Data From the FY-3B Satellite,
GeoRS(52), No. 9, Sept 2014, pp. 5548-5557.
geophysical signal processing BibRef

Liu, J.C.[Ji-Chyun], Liou, Y.A.[Yuei-An], Wu, M.X.[Meng-Xi], Lee, Y.J.[Yueh-Jyun], Cheng, C.H.[Chi-Han], Kuei, C.P.[Ching-Pin], Hong, R.M.[Rong-Moo],
Analysis of Interactions Among Two Tropical Depressions and Typhoons Tembin and Bolaven (2012) in Pacific Ocean by Using Satellite Cloud Images,
GeoRS(53), No. 3, March 2015, pp. 1394-1402.
clouds BibRef

Ruf, C.[Chris], Shafer, A.[Allison],
A new generation of hurricane-observing satellites,
SPIE(Newsroom), December 30, 2015
DOI Link 1602
A new NASA satellite mission will improve hurricane forecasting by making frequent measurements of ocean surface winds. BibRef

Zheng, G., Yang, J., Liu, A.K., Li, X., Pichel, W.G., He, S.,
Comparison of Typhoon Centers From SAR and IR Images and Those From Best Track Data Sets,
GeoRS(54), No. 2, February 2016, pp. 1000-1012.
Clouds BibRef

Bhowmick, S.A., Basu, S., Sharma, R., Kumar, R.,
Impact of Assimilating SARAL/AltiKa SWH in SWAN Model During Indian Ocean Tropical Cyclone Phailin,
GeoRS(54), No. 3, March 2016, pp. 1812-1817.
Cyclones BibRef

Kang, K.M., Kim, D.J., Kim, S.H., Moon, W.M.,
Doppler Velocity Characteristics During Tropical Cyclones Observed Using ScanSAR Raw Data,
GeoRS(54), No. 4, April 2016, pp. 2343-2355.
Doppler shift BibRef

Routray, A., Mohanty, U.C., Osuri, K.K., Kar, S.C., Niyogi, D.,
Impact of Satellite Radiance Data on Simulations of Bay of Bengal Tropical Cyclones Using the WRF-3DVAR Modeling System,
GeoRS(54), No. 4, April 2016, pp. 2285-2303.
Data assimilation BibRef

Xu, Q., Li, X., Bao, S., Pietrafesa, L.J.,
SAR Observation and Numerical Simulation of Mountain Lee Waves Near Kuril Islands Forced by an Extratropical Cyclone,
GeoRS(54), No. 12, December 2016, pp. 7157-7165.
gravity waves BibRef

Lee, Y.S., Liou, Y.A., Liu, J.C., Chiang, C.T., Yeh, K.D.,
Formation of Winter Supertyphoons Haiyan (2013) and Hagupit (2014) Through Interactions With Cold Fronts as Observed by Multifunctional Transport Satellite,
GeoRS(55), No. 7, July 2017, pp. 3800-3809.
Clouds, Hurricanes, Ocean temperature, Satellites, Tropical cyclones, Wind speed, Cold fronts, satellite imagery, supertyphoons BibRef

Duan, B.H.[Bo-Heng], Zhang, W.M.[Wei-Min], Yang, X.F.[Xiao-Feng], Dai, H.J.[Hai-Jin], Yu, Y.[Yi],
Assimilation of Typhoon Wind Field Retrieved from Scatterometer and SAR Based on the Huber Norm Quality Control,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711

Zhang, G.[Guosheng], Perrie, W.[William],
Dual-Polarized Backscatter Features of Surface Currents in the Open Ocean during Typhoon Lan (2017),
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806

Jin, S., Wang, S., Li, X., Jiao, L., Zhang, J.A., Shen, D.,
A Salient Region Detection and Pattern Matching-Based Algorithm for Center Detection of a Partially Covered Tropical Cyclone in a SAR Image,
GeoRS(55), No. 1, January 2017, pp. 280-291.
clouds BibRef

Lu, X.Q.[Xiao-Qin], Yu, H.[Hui], Yang, X.M.[Xiao-Ming], Li, X.F.[Xiao-Feng],
Estimating Tropical Cyclone Size in the Northwestern Pacific from Geostationary Satellite Infrared Images,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708

Gopalakrishnan, D., Chandrasekar, A.,
On the Improved Predictive Skill of WRF Model With Regional 4DVar Initialization: A Study With North Indian Ocean Tropical Cyclones,
GeoRS(56), No. 6, June 2018, pp. 3350-3357.
Cyclones, Humidity, Numerical models, Ocean temperature, Predictive models, Satellites, 4-D variational (4DVar), weather research and forecasting (WRF) model BibRef

Gopalakrishnan, D., Chandrasekar, A.,
Improved 4-DVar Simulation of Indian Ocean Tropical Cyclones Using a Regional Model,
GeoRS(56), No. 9, September 2018, pp. 5107-5114.
Predictive models, Sea surface, Analytical models, Tropical cyclones, Computational modeling, weather research and forecasting (WRF) model BibRef

Pradhan, R., Aygun, R.S., Maskey, M., Ramachandran, R., Cecil, D.J.,
Tropical Cyclone Intensity Estimation Using a Deep Convolutional Neural Network,
IP(27), No. 2, February 2018, pp. 692-702.
Computer architecture, Estimation, Feature extraction, Hurricanes, Neural networks, Tropical cyclones, Deep learning, tropical cyclone category and intensity estimation BibRef

Liou, Y.A., Liu, J.C., Liu, C.P., Liu, C.C.,
Season-Dependent Distributions and Profiles of Seven Super-Typhoons (2014) in the Northwestern Pacific Ocean From Satellite Cloud Images,
GeoRS(56), No. 5, May 2018, pp. 2949-2957.
Clouds, Meteorology, Ocean temperature, Satellites, Sea surface, Tropical cyclones, Turning, Cold fronts and southwest airflows, super-typhoons BibRef

Zhang, G.S.[Guo-Sheng], Perrie, W.[William],
Symmetric Double-Eye Structure in Hurricane Bertha (2008) Imaged by SAR,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809

van Beusekom, A.E.[Ashley E.], Álvarez-Berríos, N.L.[Nora L.], Gould, W.A.[William A.], Quiñones, M.[Maya], González, G.[Grizelle],
Hurricane Maria in the U.S. Caribbean: Disturbance Forces, Variation of Effects, and Implications for Future Storms,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Jin, S., Li, X., Yang, X., Zhang, J.A., Shen, D.,
Identification of Tropical Cyclone Centers in SAR Imagery Based on Template Matching and Particle Swarm Optimization Algorithms,
GeoRS(57), No. 1, January 2019, pp. 598-608.
Synthetic aperture radar, Rain, Spirals, Pattern matching, Wind speed, Monitoring, Satellites, Filtering, pattern matching, synthetic aperture radar (SAR) BibRef

Krien, Y.[Yann], Arnaud, G.[Gaël], Cécé, R.[Raphaël], Ruf, C.[Chris], Belmadani, A.[Ali], Khan, J.[Jamal], Bernard, D.[Didier], Islam, A.K.M.S., Durand, F.[Fabien], Testut, L.[Laurent], Palany, P.[Philippe], Zahibo, N.[Narcisse],
Can We Improve Parametric Cyclonic Wind Fields Using Recent Satellite Remote Sensing Data?,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901

Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y., Li, Y.,
Tropical Cyclone Center Automatic Determination Model Based on HY-2 and QuikSCAT Wind Vector Products,
GeoRS(57), No. 2, February 2019, pp. 709-721.
Radar measurements, Wind speed, Tropical cyclones, Oceans, Spaceborne radar, Satellite broadcasting, Center determination, tropical cyclone (TC) BibRef

Sun, W.J.[Wen-Jin], Dong, C.M.[Chang-Ming], Tan, W.[Wei], He, Y.J.[Yi-Jun],
Statistical Characteristics of Cyclonic Warm-Core Eddies and Anticyclonic Cold-Core Eddies in the North Pacific Based on Remote Sensing Data,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902

Xiang, K.S.[Kun-Sheng], Yang, X.F.[Xiao-Feng], Zhang, M.[Miao], Li, Z.[Ziwei], Kong, F.P.[Fan-Ping],
Objective Estimation of Tropical Cyclone Intensity from Active and Passive Microwave Remote Sensing Observations in the Northwestern Pacific Ocean,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903

Ma, C.Y.[Chun-Yong], Li, S.Q.[Si-Qing], Wang, A.N.[An-Ni], Yang, J.[Jie], Chen, G.[Ge],
Altimeter Observation-Based Eddy Nowcasting Using an Improved Conv-LSTM Network,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904

Ning, J.[Jue], Xu, Q.[Qing], Zhang, H.[Han], Wang, T.[Tao], Fan, K.[Kaiguo],
Impact of Cyclonic Ocean Eddies on Upper Ocean Thermodynamic Response to Typhoon Soudelor,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905

He, J.Y.[Jie-Ying], Chen, H.[Haonan],
Atmospheric Retrievals and Assessment for Microwave Observations from Chinese FY-3C Satellite during Hurricane Matthew,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905

Cai, J., Zhang, Y., Doviak, R.J., Shrestha, Y., Chan, P.W.,
Diagnosis and Classification of Typhoon-Associated Low-Altitude Turbulence Using HKO-TDWR Radar Observations and Machine Learning,
GeoRS(57), No. 6, June 2019, pp. 3633-3648.
Training, Radar measurements, Data integrity, Doppler radar, Signal to noise ratio, Training data, Aviation safety, weather radar BibRef

Kim, M.[Minsang], Park, M.S.[Myung-Sook], Im, J.[Jungho], Park, S.[Seonyoung], Lee, M.I.[Myong-In],
Machine Learning Approaches for Detecting Tropical Cyclone Formation Using Satellite Data,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906

Liu, J., Zheng, G., Yang, J., Wang, J.,
Top Cloud Motion Field of Typhoon Megi-2016 Revealed by GF-4 Images,
GeoRS(57), No. 7, July 2019, pp. 4427-4444.
Tropical cyclones, Clouds, Imaging, Spatial resolution, Wind, Sea surface, Cloud computing, Gaofen-4 (GF-4) satellite, tropical cyclones (TCs) BibRef

Zheng, Y.M.[Yuan-Mao], Shao, G.F.[Guo-Fan], Tang, L.[Lina], He, Y.R.[Yuan-Rong], Wang, X.R.[Xiao-Rong], Wang, Y.[Yening], Wang, H.W.[Hao-Wei],
Rapid Assessment of a Typhoon Disaster Based on NPP-VIIRS DNB Daily Data: The Case of an Urban Agglomeration along Western Taiwan Straits, China,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908

Chen, R.[Rui], Wang, X.[Xiang], Zhang, W.M.[Wei-Min], Zhu, X.Y.[Xiao-Yu], Li, A.P.[Ai-Ping], Yang, C.[Chao],
A hybrid CNN-LSTM model for typhoon formation forecasting,
GeoInfo(23), No. 3, July 2019, pp. 375-396.
WWW Link. 1908

Liou, Y.A.[Yuei-An], Liu, J.C.[Ji-Chyun], Liu, C.C.[Chung-Chih], Chen, C.H.[Chun-Hsu], Nguyen, K.A.[Kim-Anh], Terry, J.P.[James P.],
Consecutive Dual-Vortex Interactions between Quadruple Typhoons Noru, Kulap, Nesat and Haitang during the 2017 North Pacific Typhoon Season,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909

Stettner, D.[David], Velden, C.[Christopher], Rabin, R.[Robert], Wanzong, S.[Steve], Daniels, J.[Jaime], Bresky, W.[Wayne],
Development of Enhanced Vortex-Scale Atmospheric Motion Vectors for Hurricane Applications,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909

Haakman, K.[Koen], Sayol, J.M.[Juan-Manuel], van der Boog, C.G.[Carine G.], Katsman, C.A.[Caroline A.],
Statistical Characterization of the Observed Cold Wake Induced by North Atlantic Hurricanes,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910

Ning, J.[Jue], Xu, Q.[Qing], Feng, T.[Tao], Zhang, H.[Han], Wang, T.[Tao],
Upper Ocean Response to Two Sequential Tropical Cyclones over the Northwestern Pacific Ocean,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910

Zhang, H.[Han], Liu, X.H.[Xiao-Hui], Wu, R.[Renhao], Liu, F.[Fu], Yu, L.[Linghui], Shang, X.D.[Xiao-Dong], Qi, Y.F.[Yong-Feng], Wang, Y.[Yuan], Song, X.[Xunshu], Xie, X.H.[Xiao-Hui], Yang, C.H.[Cheng-Hao], Tian, D.[Di], Zhang, W.[Wenyan],
Ocean Response to Successive Typhoons Sarika and Haima (2016) Based on Data Acquired via Multiple Satellites and Moored Array,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910

Cheng, Y.C.[Yeuan-Chang], Yang, C.J.[Ci-Jian], Lin, J.C.[Jiun-Chuan],
Application for Terrestrial LiDAR on Mudstone Erosion Caused by Typhoons,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910

Alasgah, A.[Abdusalam], Jacob, M.[Maria], Jones, L.[Linwood], Schneider, L.[Larry],
Validation of the Hurricane Imaging Radiometer Forward Radiative Transfer Model for a Convective Rain Event,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911

Sun, Z.[Ziyao], Zhang, B.[Biao], Zhang, J.A.[Jun A.], Perrie, W.[William],
Examination of Surface Wind Asymmetry in Tropical Cyclones over the Northwest Pacific Ocean Using SMAP Observations,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911

Zheng, G., Liu, J., Yang, J., Li, X.,
Automatically Locate Tropical Cyclone Centers Using Top Cloud Motion Data Derived From Geostationary Satellite Images,
GeoRS(57), No. 12, December 2019, pp. 10175-10190.
Tropical cyclones, Spirals, Satellites, Sensors, Cloud computing, Spatial resolution, Clouds, Geostationary satellite, typhoon eye BibRef

Yu, P.[Peng], Johannessen, J.A.[Johnny A.], Yan, X.H.[Xiao-Hai], Geng, X.[Xupu], Zhong, X.J.[Xiao-Jing], Zhu, L.[Lin],
A Study of the Intensity of Tropical Cyclone Idai Using Dual-Polarization Sentinel-1 Data,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912

Li, J.[Jian], Hou, Y.J.[Yi-Jun], Mo, D.X.[Dong-Xue], Liu, Q.R.[Qing-Rong], Zhang, Y.Z.[Yuan-Zhi],
Influence of Tropical Cyclone Intensity and Size on Storm Surge in the Northern East China Sea,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912

Wang, J.[Jie], Xu, Y.[Youpeng], Yang, L.[Long], Wang, Q.A.[Qi-Ang], Yuan, J.[Jia], Wang, Y.[Yuefeng],
Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001

Qian, B.[Bo], Jiang, H.Y.[Hai-Yan], Weng, F.Z.[Fu-Zhong], Wu, Y.[Ying],
Climatology of Passive Microwave Brightness Temperatures in Tropical Cyclones and their Relations to Storm Intensities as Seen by FY-3B/MWRI,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001

Lee, J.[Juhyun], Im, J.[Jungho], Cha, D.H.[Dong-Hyun], Park, H.[Haemi], Sim, S.[Seongmun],
Tropical Cyclone Intensity Estimation Using Multi-Dimensional Convolutional Neural Networks from Geostationary Satellite Data,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001

Baek, Y.H.[You-Hyun], Moon, I.J.[Il-Ju], Im, J.[Jungho], Lee, J.[Juhyun],
A Novel Tropical Cyclone Size Estimation Model Based on a Convolutional Neural Network Using Geostationary Satellite Imagery,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201

Zhang, R., Liu, Q., Hang, R.,
Tropical Cyclone Intensity Estimation Using Two-Branch Convolutional Neural Network From Infrared and Water Vapor Images,
GeoRS(58), No. 1, January 2020, pp. 586-597.
Tropical cyclones, Satellites, Data models, Estimation, Microwave imaging, Clouds, Feature extraction, Rainfall intensity, two-branch convolutional neural network (CNN) BibRef

Lasota, E., Rohm, W., Guerova, G., Liu, C.,
A Comparison Between Ray-Traced GFS/WRF/ERA and GNSS Slant Path Delays in Tropical Cyclone Meranti,
GeoRS(58), No. 1, January 2020, pp. 421-435.
Global navigation satellite system, Delays, Atmospheric modeling, Meteorology, Predictive models, Global Positioning System, weather research and forecasting (WRF) BibRef

Fan, S., Zhang, B., Mouche, A.A., Perrie, W., Zhang, J.A., Zhang, G.,
Estimation of Wind Direction in Tropical Cyclones Using C-Band Dual-Polarization Synthetic Aperture Radar,
GeoRS(58), No. 2, February 2020, pp. 1450-1462.
Synthetic aperture radar, Radar polarimetry, Wind speed, Atmospheric modeling, Spaceborne radar, Radar measurements, wind direction BibRef

He, Q.[Qimin], Zhang, K.[Kefei], Wu, S.[Suqin], Zhao, Q.Z.[Qing-Zhi], Wang, X.M.[Xiao-Ming], Shen, Z.[Zhen], Li, L.J.[Long-Jiang], Wan, M.F.[Mou-Feng], Liu, X.Y.[Xiao-Yang],
Real-Time GNSS-Derived PWV for Typhoon Characterizations: A Case Study for Super Typhoon Mangkhut in Hong Kong,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link 2001

Zhao, L.L.[Li-Ling], Chen, Y.F.[Yi-Fei], Sheng, V.S.[Victor S.],
A real-time typhoon eye detection method based on deep learning for meteorological information forensics,
RealTimeIP(17), No. 1, February 2020, pp. 95-102.
WWW Link. 2002

Hu, L., Ritchie, E.A., Tyo, J.S.,
Influence of Satellite Observation Angle to Tropical Cyclone Intensity Estimation Using the Deviation Angle Variance Technique,
GeoRS(58), No. 5, May 2020, pp. 3703-3710.
Deviation angle variance (DAV), satellite observation angle, tropical cyclone (TC) intensity estimation BibRef

Tymochko, S.[Sarah], Munch, E.[Elizabeth], Dunion, J.[Jason], Corbosiero, K.[Kristen], Torn, R.[Ryan],
Using persistent homology to quantify a diurnal cycle in hurricanes,
PRL(133), 2020, pp. 137-143.
Elsevier DOI 2005
Topological Data Analysis, Atmospheric science, Diurnal cycle, Image processing BibRef

Sapp, J.W., Mouche, A.A., Jelenak, Z., Chang, P.S., Frasier, S.J.,
Comparison of the Sentinel-1B Synthetic Aperture Radar With Airborne Microwave Sensors in an Extra-Tropical Cyclone,
GeoRS(58), No. 7, July 2020, pp. 4721-4729.
Satellites, Aircraft, Spaceborne radar, Synthetic aperture radar, Sea measurements, Wind speed, C-band, cross polarization, scatterometry BibRef

Wang, H.M.[Hui-Meng], Du, Y.Y.[Yun-Yan], Yi, J.W.[Jia-Wei], Wang, N.[Nan], Liang, F.Y.[Fu-Yuan],
Mining Evolution Patterns from Complex Trajectory Structures: A Case Study of Mesoscale Eddies in the South China Sea,
IJGI(9), No. 7, 2020, pp. xx-yy.
DOI Link 2007

Roman-Stork, H.L.[Heather L.], Subrahmanyam, B.[Bulusu],
The Impact of the Madden-Julian Oscillation on Cyclone Amphan (2020) and Southwest Monsoon Onset,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009

Nadimpalli, R., Srivastava, A., Prasad, V.S., Osuri, K.K., Das, A.K., Mohanty, U.C., Niyogi, D.,
Impact of INSAT-3D/3DR Radiance Data Assimilation in Predicting Tropical Cyclone Titli Over the Bay of Bengal,
GeoRS(58), No. 10, October 2020, pp. 6945-6957.
Predictive models, Data models, Clouds, Atmospheric modeling, Weather forecasting, Earth, 3-D variational (3DVAR), radiance data assimilation (DA) BibRef

Xie, M.[Ming], Li, Y.[Ying], Cao, K.[Kai],
Global Cyclone and Anticyclone Detection Model Based on Remotely Sensed Wind Field and Deep Learning,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010

Wang, S.W.[Shi-Wei], Shi, S.Z.[Shu-Zhu], Ni, B.B.[Bin-Bin],
Joint Use of Spaceborne Microwave Sensor Data and CYGNSS Data to Observe Tropical Cyclones,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010

Yang, S.[Song], Bankert, R.[Richard], Cossuth, J.[Joshua],
Tropical Cyclone Climatology from Satellite Passive Microwave Measurements,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011

Freeshah, M.[Mohamed], Zhang, X.H.[Xiao-Hong], Sentürk, E.[Erman], Adil, M.A.[Muhammad Arqim], Mousa, B.G., Tariq, A.[Aqil], Ren, X.D.[Xiao-Dong], Refaat, M.[Mervat],
Analysis of Atmospheric and Ionospheric Variations Due to Impacts of Super Typhoon Mangkhut (1822) in the Northwest Pacific Ocean,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103

Wang, Y.B.[Yuan-Bing], He, J.Y.[Jie-Ying], Chen, Y.D.[Yao-Deng], Min, J.Z.[Jin-Zhong],
The Potential Impact of Assimilating Synthetic Microwave Radiances Onboard a Future Geostationary Satellite on the Prediction of Typhoon Lekima Using the WRF Model,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103

Chen, Z., Yu, X.,
A Novel Tensor Network for Tropical Cyclone Intensity Estimation,
GeoRS(59), No. 4, April 2021, pp. 3226-3243.
Estimation, Tensile stress, Wind speed, Cyclones, Satellites, Task analysis, Artificial neural networks, tucker decomposition (TD) BibRef

Priftis, G.[Georgios], Lang, T.J.[Timothy J.], Garg, P.[Piyush], Nesbitt, S.W.[Stephen W.], Lindsley, R.D.[Richard D.], Chronis, T.[Themistoklis],
Evaluating the Detection of Mesoscale Outflow Boundaries Using Scatterometer Winds at Different Spatial Resolutions,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104

Ravindra, V.[Vinay], Nag, S.[Sreeja], Li, A.[Alan],
Ensemble-Guided Tropical Cyclone Track Forecasting for Optimal Satellite Remote Sensing,
GeoRS(59), No. 5, May 2021, pp. 3607-3622.
Satellites, Predictive models, Satellite broadcasting, Forecasting, Data models, Numerical models, Prediction algorithms, Forecasting, tropical cyclones (TCs) BibRef

Meissner, T.[Thomas], Ricciardulli, L.[Lucrezia], Manaster, A.[Andrew],
Tropical Cyclone Wind Speeds from WindSat, AMSR and SMAP: Algorithm Development and Testing,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105

Eley, E.N.[Emily N.], Subrahmanyam, B.[Bulusu], Trott, C.B.[Corinne B.],
Ocean-Atmosphere Interactions during Hurricanes Marco and Laura (2020),
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105

Manaster, A.[Andrew], Ricciardulli, L.[Lucrezia], Meissner, T.[Thomas],
Tropical Cyclone Winds from WindSat, AMSR2, and SMAP: Comparison with the HWRF Model,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106

Hu, Y.[Yanyang], Zou, X.L.[Xiao-Lei],
Tropical Cyclone Center Positioning Using Single Channel Microwave Satellite Observations of Brightness Temperature,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107

Li, J.G.[Jia-Gen], Yang, Y.J.[Yuan-Jian], Wang, G.H.[Gui-Hua], Cheng, H.[Hao], Sun, L.[Liang],
Enhanced Oceanic Environmental Responses and Feedbacks to Super Typhoon Nida (2009) during the Sudden-Turning Stage,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107

Sun, Z.Y.[Zi-Yao], Zhang, B.[Biao], Tang, J.[Jie],
Estimating the Key Parameter of a Tropical Cyclone Wind Field Model over the Northwest Pacific Ocean: A Comparison between Neural Networks and Statistical Models,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107

Niu, Z.Y.[Ze-Yi], Zou, X.L.[Xiao-Lei], Huang, W.[Wei],
Typhoon Warm-Core Structures Derived from FY-3D MWTS-2 Observations,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109

Li, Y.[Yang], Liu, Y.[Yubao], Chen, Y.[Yun], Chen, B.[Baojun], Zhang, X.[Xin], Wang, W.S.[Wei-Sheng], Shu, Z.Z.[Zhuo-Zhi], Huo, Z.Y.[Zhao-Yang],
Characteristics of Deep Convective Systems and Initiation during Warm Seasons over China and Its Vicinity,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112

Xu, D.M.[Dong-Mei], Zhang, X.[Xuewei], Li, H.[Hong], Wu, H.Y.[Hai-Ying], Shen, F.F.[Fei-Fei], Shu, A.[Aiqing], Wang, Y.[Yi], Zhuang, X.[Xiaoran],
Evaluation of the Simulation of Typhoon Lekima (2019) Based on Different Physical Parameterization Schemes and FY-3D Satellite's MWHS-2 Data Assimilation,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112

Ricciardulli, L.[Lucrezia], Mears, C.[Carl], Manaster, A.[Andrew], Meissner, T.[Thomas],
Assessment of CYGNSS Wind Speed Retrievals in Tropical Cyclones,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112

Prat, A.C.[Albert Comellas], Federico, S.[Stefano], Torcasio, R.C.[Rosa Claudia], d'Adderio, L.P.[Leo Pio], Dietrich, S.[Stefano], Panegrossi, G.[Giulia],
Evaluation of the Sensitivity of Medicane Ianos to Model Microphysics and Initial Conditions Using Satellite Measurements,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
Tropical-like cyclone. BibRef

Shi, M.J.[Min-Jing], He, P.F.[Peng-Fei], Shi, Y.[Yuli],
Detecting Extratropical Cyclones of the Northern Hemisphere with Single Shot Detector,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201

Chen, L.[Liren], Zhuge, X.Y.[Xiao-Yong], Tang, X.D.[Xiao-Dong], Song, J.J.[Jin-Jie], Wang, Y.[Yuan],
A New Type of Red-Green-Blue Composite and Its Application in Tropical Cyclone Center Positioning,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202

Wang, T.[Tongyu], Chen, F.[Fajin], Zhang, S.[Shuwen], Pan, J.Y.[Jia-Yi], Devlin, A.T.[Adam T.], Ning, H.[Hao], Zeng, W.Q.[Wei-Qiang],
Physical and Biochemical Responses to Sequential Tropical Cyclones in the Arabian Sea,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202

Liu, S.[Siqi], Lin, W.M.[Wen-Ming], Portabella, M.[Marcos], Wang, Z.X.[Zhi-Xiong],
Characterization of Tropical Cyclone Intensity Using the HY-2B Scatterometer Wind Data,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202

Tan, J.[Jinkai], Yang, Q.[Qidong], Hu, J.J.[Jun-Jun], Huang, Q.[Qiqiao], Chen, S.[Sheng],
Tropical Cyclone Intensity Estimation Using Himawari-8 Satellite Cloud Products and Deep Learning,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202

Hu, H.[Hao], Weng, F.Z.[Fu-Zhong],
Influences of 1DVAR Background Covariances and Observation Operators on Retrieving Tropical Cyclone Thermal Structures,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203

Xu, G.[Guangning], Lin, K.[Kenghong], Li, X.[Xutao], Ye, Y.M.[Yun-Ming],
SAF-Net: A spatio-temporal deep learning method for typhoon intensity prediction,
PRL(155), 2022, pp. 121-127.
Elsevier DOI 2203
Typhoon intensity, Spatio-temporal, Wind speed, Wide and Deep, Deep learning, Machine learning BibRef

Pu, J.C.[Jing-Chen], Zou, X.L.[Xiao-Lei],
Characteristic Scales of Tropical Convection Based on the Japanese Advanced Himawari-8 Imager Observations,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205

Dong, H.[Huijie], Zou, X.L.[Xiao-Lei],
Mitigation of Significant Data Noise in F17 SSMIS Observations since October 2017,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
Special Sensor Microwave Imager Sounder. BibRef

Hua, H.[Han], Zhang, B.[Biao], Zhang, G.S.[Guo-Sheng], Perrie, W.[William], Chen, C.L.[Chang-Lin], Li, Y.B.[Yuan-Ben],
Aircraft and Satellite Observations of Vortex Evolution and Surface Wind Asymmetry of Concentric Eyewalls in Hurricane Irma,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205

Yurovskaya, M.[Maria], Kudryavtsev, V.[Vladimir], Mironov, A.[Alexey], Mouche, A.[Alexis], Collard, F.[Fabrice], Chapron, B.[Bertrand],
Surface Wave Developments under Tropical Cyclone Goni (2020): Multi-Satellite Observations and Parametric Model Comparisons,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205

Lu, X.[Xu], Davis, B.[Benjamin], Wang, X.[Xuguang],
Improving the Assimilation of Enhanced Atmospheric Motion Vectors for Hurricane Intensity Predictions with HWRF,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205

Zhang, Y.[Yun], Wu, Z.[Zuhang], Zhang, L.F.[Li-Feng], Zheng, H.[Hepeng],
A Comparison of Spectral Bin Microphysics versus Bulk Parameterization in Forecasting Typhoon In-Fa (2021) before, during, and after Its Landfall,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205

Huang, C.[Cheng], Chan, S.X.[Si-Xian], Bai, C.[Cong], Ding, W.L.[Wei-Long], Zhang, J.L.[Jing-Lin],
Tropical Cyclones Tracking Based on Satellite Cloud Images: Database and Comprehensive Study,
Springer DOI 2106

Xu, Y., Yang, H., Cheng, M., Li, S.,
Cyclone Intensity Estimate with Context-Aware Cyclegan,
context-aware CycleGAN, cyclone intensity estimation, feature generation BibRef

Kim, S., Kim, H., Lee, J., Yoon, S., Kahou, S.E., Kashinath, K., Prabhat, M.,
Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events,
climatology, convolutional neural nets, data analysis, geophysics computing, learning (artificial intelligence), Videos BibRef

Combinido, J.S., Mendoza, J.R., Aborot, J.,
A Convolutional Neural Network Approach for Estimating Tropical Cyclone Intensity Using Satellite-based Infrared Images,
Feature extraction, Training, Satellites, Estimation, Clouds, Task analysis, Organizations BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Target Tracking Techniques, Performance Evaluation, Comparison, Benchmarks, Datasets, Survey .

Last update:May 21, 2022 at 16:37:58