Tropical hurricanes are among the most devastating hazards on Earth.Knowledge about its intense inner-core structure and dynamics will improve hurricane forecasts and advisories.The precise morphological parameters ex...Tropical hurricanes are among the most devastating hazards on Earth.Knowledge about its intense inner-core structure and dynamics will improve hurricane forecasts and advisories.The precise morphological parameters extracted from high-resolution spaceborne Synthetic Aperture Radar(SAR)images,can play an essential role in further exploring and monitoring hurricane dynamics,especially when hurricanes undergo amplification,shearing,eyewall replacements and so forth.Moreover,these parameters can help to build guidelines for wind calibration of the more abundant,but lower resolution scatterometer wind data,thus better linking scatterometer wind fields to hurricane categories.In this paper,we develop a new method for automatically extracting the hurricane eyes from C-band SAR data by constructing Gray Level-Gradient Co-occurrence Matrices(GLGCMs).The hurricane eyewall is determined with a two-dimensional vector,generated by maximizing the class entropy of the hurricane eye region in GLGCM.The results indicate that when the hurricane is weak,or the eyewall is not closed,the hurricane eye extracted with this automatic method still agrees with what is observed visually,and it preserves the texture characteristics of the original image.As compared to Du’s wavelet analysis method and other morphological analysis methods,the approach developed here has reduced artefacts due to factors like hurricane size and has lower programming complexity.In summary,the proposed method provides a new and elegant choice for hurricane eye morphology extraction.展开更多
This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Orga...This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Organization(WMO)report prepared for the 10th International Workshop on Tropical Cyclones(IWTC),held in Bali in December 2022,and its objective is to present updates in TC research and operation every four years.Here we focus on updates regarding the most recent space-based TC observations,and we cover new methodologies and techniques using polar orbiting sensors,such as C-band synthetic aperture radars(SARs),L-band and combined C/X-band radiometers,scatterometers,and microwave imagers/sounders.We additionally address progress made with the new generation of geostationary and small satellites,and discuss future sensors planned to be launched in the next years.We then briefly describe some examples on how the newest sensors are used in operations and data assimilation for TC forecasting and research,and conclude the article with a discussion on the remaining challenges of TC space-based observations and possible ways to address them in the near future.展开更多
基金supported by the National Key Research and Development Program of China(No.2018YFC1406206)supported by the National Natural Science Foundation of China(Grant No.61802424).Ad Stoffelen is supported by the EUMETSAT OSI SAF.
文摘Tropical hurricanes are among the most devastating hazards on Earth.Knowledge about its intense inner-core structure and dynamics will improve hurricane forecasts and advisories.The precise morphological parameters extracted from high-resolution spaceborne Synthetic Aperture Radar(SAR)images,can play an essential role in further exploring and monitoring hurricane dynamics,especially when hurricanes undergo amplification,shearing,eyewall replacements and so forth.Moreover,these parameters can help to build guidelines for wind calibration of the more abundant,but lower resolution scatterometer wind data,thus better linking scatterometer wind fields to hurricane categories.In this paper,we develop a new method for automatically extracting the hurricane eyes from C-band SAR data by constructing Gray Level-Gradient Co-occurrence Matrices(GLGCMs).The hurricane eyewall is determined with a two-dimensional vector,generated by maximizing the class entropy of the hurricane eye region in GLGCM.The results indicate that when the hurricane is weak,or the eyewall is not closed,the hurricane eye extracted with this automatic method still agrees with what is observed visually,and it preserves the texture characteristics of the original image.As compared to Du’s wavelet analysis method and other morphological analysis methods,the approach developed here has reduced artefacts due to factors like hurricane size and has lower programming complexity.In summary,the proposed method provides a new and elegant choice for hurricane eye morphology extraction.
基金support of NASA Ocean Vector Wind Science Team contract 80HQTR19C0003.
文摘This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Organization(WMO)report prepared for the 10th International Workshop on Tropical Cyclones(IWTC),held in Bali in December 2022,and its objective is to present updates in TC research and operation every four years.Here we focus on updates regarding the most recent space-based TC observations,and we cover new methodologies and techniques using polar orbiting sensors,such as C-band synthetic aperture radars(SARs),L-band and combined C/X-band radiometers,scatterometers,and microwave imagers/sounders.We additionally address progress made with the new generation of geostationary and small satellites,and discuss future sensors planned to be launched in the next years.We then briefly describe some examples on how the newest sensors are used in operations and data assimilation for TC forecasting and research,and conclude the article with a discussion on the remaining challenges of TC space-based observations and possible ways to address them in the near future.
