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Über dieses Buch

This book discusses in detail the science and morphology of powerful hurricane detection systems. It broadly addresses new approaches to monitoring hazards using freely available images from the European Space Agency’s (ESA’s) Sentinel-1 SAR satellite and benchmarks a new interdisciplinary field at the interface between oceanography, meteorology and remote sensing. Following the launch of the first European Space Agency (ESA) operational synthetic aperture radar satellite, Sentinel-1, in 2014, synthetic aperture radar (SAR) data has been freely available on the Internet hub in real-time. This advance allows weather forecasters to view hurricanes in fine detail for the first time. As a result, the number of synthetic aperture radar research scientists working in this field is set to grow exponentially in the next decade; the book is a valuable resource for this large and budding audience.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Hurricane Precipitation Observed by SAR

Abstract
The SAR-observed backscatter from the ocean’s surface is related to the surface wave spectrum, which is in turn related to the near-surface vector wind. This enables retrieval of near-surface winds from SAR images. Rain impacting the surface affects the wind-driven surface wave spectrum and roughens the surface. Rain can be observed in SAR images due to the effects the rain has on the surface and scattering and attenuation of the radar signal by the falling rain. With its high resolution SAR is a useful sensor for studying rain. This Chapter focuses on SAR observation of rain in ocean images. The effect of rain on the SAR backscatter image is modeled. Using a case study of RADARSAT ScanSAR SWA images of Hurricane Katrina, rain effects are analyzed for three different incidence angle ranges using collocated ground-based Doppler weather radar (NEXRAD) rain measurements. The rain-induced backscatter observed by the ScanSAR is consistent with C-band scatterometer-derived wind/rain scattering models when the polarization difference between the sensors are considered. New insights into the temporal behavior of rain effects on the small-scale surface wave spectrum derived from the ScanSAR images are presented.
D. G. Long, C. Nie

Chapter 2. Tropical Cyclone Multiscale Wind Features from Spaceborne Synthetic Aperture Radar

Abstract
This study presents multi-scale wind features observed in space-borne synthetic aperture radar (SAR) images in tropical cyclones. Examples of eyewall mesovotices, spiral rainbands, fine-scale-band features, arc clouds, and boundary layer rolls are documented. Although these wind features are strongly tied to tropical cyclone dynamics and intensity based on previous numerical studies, they are not well-observed due to high rainfall and cloudiness that limits remote sensing instrument and severe environment for in-situ observations to survive. Since SAR images view the actual ocean surface responses to the storm-forced winds, they provide clear evidence for the presence of these wind features below clouds and their interaction with the sea surface. Analyses of the characteristics of boundary layer rolls based on SAR images show good agreement with in-situ aircraft observations, suggesting that a SAR image has a great potential to be utilized to study tropical cyclone low-level structure.
Jun A. Zhang, Xiaofeng Li

Chapter 3. Observations of Typhoon Eye on Ocean Surface Using SAR and Other Satellite Sensors

Abstract
In this study, typhoon eyes have been delineated using wavelet analysis from the synthetic aperture radar (SAR) images of ocean surface roughness and from the warmer area at the cloud top in the infrared (IR) images, respectively. RADARSAT and ENVISAT SAR imagery, and multi-functional transport satellite (MTSAT) and Feng Yun (FY)-2 Chinese meteorological satellite IR imagery were used to examine the typhoons in the western North Pacific from 2005 to 2011. Nine cases of various typhoons in different years, locations, and conditions have been used to compare the typhoon eyes by SAR (on the ocean surface) with IR (at the cloud-top level) images. Furthermore, the best track data getting from the Joint Typhoon Warning Center (JTWC), Chinese Meteorological Administration (CMA), and the Japan Meteorological Agency (JMA) are checked for the calibration and validation along with the Moderate Resolution Imaging Spectroradiometer (MODIS) image. Because of the vertical wind shear, which acts as an upright tilt, the location of the typhoon eye on the ocean surface differs from that at the top of the clouds. Consequently, the large horizontal distance between typhoon eyes on the ocean surface and on the cloud top implies that the associated vertical wind shear profile is considerably more complex than generally expected. The upright tilt structure may be caused by the ocean’s feedback or the effect of island obstruction. This result demonstrates that SAR can be a useful tool for typhoon monitoring study over the ocean surface.
Antony K. Liu, Yu-Hsin Cheng, Jingsong Yang

Chapter 4. Tropical Cyclone Wind Field Reconstruction from SAR and Analytical Model

Abstract
Sea surface wind field retrieval from Synthetic Aperture Radar (SAR) imagery is based on geophysical model functions (GMFs), which describe the relationship between the near surface winds and the normalized radar backscatter cross section. However, existing GMFs will saturate under tropical cyclone conditions, and cause huge wind retrieval errors. This study develops an approach to estimate tropical cyclone parameters and wind fields based on an improved Holland model and the SAR images. To evaluate its accuracy, three case studies of Typhoon Aere, Typhoon Khanun and Hurricane Ophelia are presented. Estimated results are validated by the best track data of the Joint Typhoon Warning Center (JTWC) and reanalyzed H*wind fields from the Hurricane Research Division (HRD). These results indicate that the tropical cyclone center, maximum wind speed and central pressure are generally consistent with the best track data, and wind fields agree well with reanalyzed data.
Xiaofeng Yang, Xuan Zhou, Xiaofeng Li, Ziwei Li

Chapter 5. High Wind Speed Retrieval from Multi-polarization SAR

Abstract
Synthetic aperture radar (SAR) has capability to observe tropical cyclones (TCs) with high-resolution and large coverage under all weather conditions. The intensity parameters and two-dimensional fine structure characteristics for TCs can be derived from SAR observations. In this chapter, we make an overview of high wind retrieval from C-band multi-polarization SAR. Co- and cross-polarized geophysical model functions (GMFs) for high wind speed derivation are summarized. The validation results are presented using various GMFs and data sources. The intense effect of rainfall on SAR high winds retrieval is emphasized. We summarize potential challenges and provide possible solutions for high wind retrieval in the future.
Biao Zhang, William Perrie

Chapter 6. Observation of Sea Surface Wind and Wave in X-Band TerraSAR-X and TanDEM-X Over Hurricane Sandy

Abstract
Several TerraSAR-X and TanDEM-X ScanSAR images are acquired in October, 2012 to track the Hurricane Sandy. Three of the images are acquired in the open sea, which are presented in this chapter to demonstrate observations of sea surface wind and wave extracted from X-band ScanSAR image with high spatial resolution of 17 m in the hurricane. In the case of the TerraSAR-X image acquired on October 26, 2012, we analyze the peak wave direction and length of swell generated by Hurricane Sandy, as well as interaction of swell with the Abaco Island, Bahamas. In the other two cases, sea surface wind field derived from the TerraSAR-X and TanDEM-X acquired on October 27 and 28 are presented. The sea surface wind speed retrieved by the X-band Geophysical Model Function (GMF) XMOD2 using wind direction derived from SAR images and the NOAA Hurricane Research Division (HRD) wind analyses are both presented for comparisons. We also compare the retrieved sea surface wind speed with Stepped Frequency Microwave Radiometer (SFMR) to quantify effect of rainfall on X-band SAR images.
XiaoMing Li, Susanne Lehner

Chapter 7. Extracting Hurricane Eye Morphology from Spaceborne SAR Images Using Morphological Analysis

Abstract
Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. The subsequent reconstructed of the hurricane eyes thereby proves the morphology-based analyses results in a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.
Isabella K. Lee, Ali Shamsoddini, Xiaofeng Li, John C. Trinder, Zeyu Li

Chapter 8. Tropical Cyclone Center Location in SAR Images Based on Feature Learning and Visual Saliency

Abstract
Synthetic aperture radar (SAR), with its high spatial resolution, large area coverage, day/night imaging capability, and penetrating cloud capability, has been used as an important tool for tropical cyclone monitoring. The accuracy of locating tropical cyclone centers has a large impact on the accuracy of tropical cyclone track prediction. This study focuses on the center location of tropical cyclones in the SAR images. Based on the analysis of the characteristics of the tropical cyclone SAR images, combined with the theory and methods of SAR image segmentation and computer vision, center location methods for both the tropical cyclones with eyes in the SAR images and the tropical cyclones without eyes in the SAR images are presented in this chapter. The main work is as follows: 1, For a tropical cyclone with its eye in the SAR image, The eye area in image appears as black or dark grey area for there being no rain and little wind in the eye area. But the gray level contrast is not always obvious. There may be no complete and clear eye when a tropical cyclone is in the development period or the recession period. The eye area in the tropical cyclone SAR image may appears as light grey area at these periods. So it is necessary to enhance the gray level contrast before image segmentation. Besides, denoising the speckle noise is also necessary for the SAR image processing. A tropical cyclone eye extraction method based on non-local means method and labeled watershed algorithm is given. PPB filter is used to denoise the speckle noise. Then the top-hat transform is used to enhance the contrast. At last the tropical cyclone eye is extracted labeled watershed algorithm. The eye area extracted with this method is computed to compare with the eye area extracted manually. The comparison indicates the accuracy of the extraction accuracy. 2, Generally speaking, the center of the tropical cyclone without its eye is located with template matching method for a single image. The spiral cloud band of the tropical cyclone without its eye is the information can be fully used in the tropical cyclone SAR image. Take the advantage of simple background with little texture information, a center location method of the tropical cyclone without its eye in the SAR image based on feature learning and visual saliency detection is proposed. Spiral cloud bands appear as light and dark spiral structure in the tropical cyclone SAR image, containing rich directional information. Therefore salient region map taking advantage of the gray contrast feature and orientation feature is built. The salient region map makes the spiral cloud bands outstanding and the irrelevant clouds excluded. Then the morphology method is used to extract the spiral bands in the salient region map, the skeleton lines of spiral cloud bands is extracted. At last the tropical cyclone center is estimated with the inflow angle model and the particle swarm optimization algorithm. And the estimation results are compared with the Best Track Data, confirming the validity of the algorithm.
Shaohui Jin, Shuang Wang, Xiaofeng Li, Licheng Jiao, Jun A. Zhang

Chapter 9. Observing Typhoons from Satellite-Derived Images

Abstract
This chapter compares the typhoon centers from the tropical cyclone best track (BT) datasets of three meteorological agencies and those from synthetic aperture radar (SAR) and infrared (IR) images. First, we carried out algorithm comparison, using two newly developed and one existing wavelet-based algorithms, which were used to extract typhoon eyes in six SAR images and two IR images. These case studies showed that the extracted eyes by the three algorithms are consistent with each other. The differences among them are relatively small. However, there is a systematic difference between these extracted centers and the typhoon centers from the three BT datasets, which are interpolated to the imaging times first. We then compared the typhoon centers determined from 25 SAR and 43 IR images with those from the three BT datasets to investigate the performance of the latter at the sea surface and at the cloud top, respectively. We found the typhoon centers from the three BT datasets are generally closer to the locations extracted from the SAR images showing sea surface imprints of the typhoons than those from the IR images showing cloud top structures of the typhoons. We also evaluate the effect caused by rain to the SAR wind field retrieval. By using RADARSAT-2 data, National Centers for Environmental Prediction (NCEP) reanalysis data and Tropical Rainfall Measuring Mission satellite (TRMM) precipitation radar rainfall data, rain-induced attenuation, raindrop volumetric scattering are calculated and the perturbation of the water surface is simulated by rainfall and incident angle. The performance of this model is further proved by one typhoon case.
Gang Zheng, Jingsong Yang, Antony K. Liu, Xiaofeng Li, William G. Pichel, Shuangyan He, Shui Yu

Chapter 10. Coupled Nature of Hurricane Wind and Wave Properties for Ocean Remote Sensing of Hurricane Wind Speed

Abstract
Wind measurement using microwave radar suffers decreased or loss of sensitivity of the return signal in high winds. The 2D wavenumber spectra collected by airborne scanning radar altimeter in hurricane hunter missions are used to investigate the fetch- and duration-limited nature of wave growth inside hurricanes. Despite the much more complex wind forcing conditions, the dimensionless growth curves obtained with the wind wave triplets (reference wind velocity, significant wave height and dominant wave period) inside hurricanes except near the eye region are comparable to the reference similarity counterparts constructed with the wind wave triplets collected in field experiments conducted under ideal quasi-steady fetch-limited conditions. Making use of this property, the hurricane wind speed is retrievable from the dominant wave parameter (significant wave height or dominant wave period) using the fetch- or duration-limited wave growth functions. An algorithm based on such consideration is developed and applied to two hurricanes of different strengths (category 2 and 4). The retrieved wind speeds are in good agreement with the reference wind speeds from hurricane hunter measurements, and there is no indication of saturation problem in the wind retrieval using the dominant wave parameters.
Paul A. Hwang, Xiaofeng Li, Biao Zhang

Chapter 11. Hurricane Winds Retrieval from C Band Co-pol SAR

Abstract
Since the beginning of modern radar technology, the co-polarization (co-pol) mode has been predominantly used for marine navigation, target detection, ocean and atmospheric monitoring etc. In remote sensing of ocean surface winds, co-pol is operationally used in satellite scatterometer missions and some of SAR winds demonstration projects. Compared to cross-polarization modes, co-pol radar measurements have much stronger backscattered intensity and signal to noise ratio; thus, cross-pol measurements could sense atmospheric and oceanic processes which could affect small scale waves on the ocean surface. Co-pol measurements also have stronger sensitivity to wind direction than cross-pol, which made it suitable for monitoring ocean surface wind direction as well as wind speed. However, due to the different radar configuration of cross-pol SAR and the complicated dynamical processes that develop under hurricane conditions, wind monitoring under hurricane forces has formidable challenges. These include the demands for wind direction a priori, saturation of radar backscattered signals, speed ambiguity with decreased radar NRCS response under high wind speeds in low incidence angles. This chapter will summarize some recent progress in these fields. The demands for combining the advantages of both co-pol and cross-pol measurements and appropriate data assimilation methodology to ingest SAR winds into marine and hurricane numerical weather forecasting will also be discussed.
Hui Shen, Will Perrie, Yijun He

Chapter 12. Sea-Level Pressure Retrieval from SAR Images of Tropical Cyclones

Abstract
Validation and calibration of wind vector retrievals from synthetic aperture radar images of tropical cyclones remains a serious challenge. The basic wind vector measurements in tropical cyclones come from the approximately ten to twenty drop sonde profiles that are obtained during reconnaissance flights. In the highly turbulent tropical cyclone boundary layer, any given drop sonde profile represents a single realization of the virtual ensemble that must be averaged to estimate a mean surface wind vector. This is the quantity of interest because geophysical model functions are calibrated in terms of mean surface wind speeds. Even if a mean surface wind vector can be estimated from a single sonde profile, it can only be compared to the nearest wind retrieval. Furthermore, in the high wind regime geophysical model functions can be extremely sensitive to small errors in either backscatter measurements or assumed wind direction. Drop sondes do provide very accurate atmospheric pressure data, which has the beneficial property of being a scalar mean flow quantity. A method for calculating surface pressure fields from synthetic aperture radar images of tropical cyclones is presented. These fields are very accurate, with an RMS error of about 3 mb. Importantly, the surface pressure field represents an integral of the full wind vector field. Hence, comparing the pair-wise (between drop sonde splash locations) aircraft- and satellite-derived pressure differences provides a means by which the overall quality of the wind vector retrievals can be assessed. Finally, wind vector fields derived from the surface pressure fields can provide significantly improved estimates in regions of the image where objective quality flags reject the raw winds.
Ralph Foster

Chapter 13. Electromagnetic Scattering of Rainfall and Tropical Cyclones over Ocean

Abstract
This chapter introduces a physics-based radiative transfer model to capture the scattering behavior of rainfall over a rough sea surface. Raindrops are modeled as Rayleigh scattering nonspherical particles, while the rain-induced rough surface is described by the Log-Gaussian ring-wave spectrum. The model is validated against both empirical models and measurements. A case study of collocated Envisat ASAR data and NEXRAD rain data is presented. To showcase the capability of the developed scattering model in studying cyclones, we use regional WRF weather model to simulate the Hurricane Hermine occurred in North America at September 2016. Finally, numerical analyses suggest that rain-related scattering becomes significant as compared to wind-related scattering when the frequency is above C-band, while the raindrop volumetric scattering becomes significant above X-band.
Feng Xu, Xiaofeng Li

Chapter 14. Synthetic Aperture Radar Observations of Extreme Hurricane Wind and Rain

Abstract
Over the last decades, data from spaceborne Synthetic Aperture Radar (SAR) have been used in hurricane research. However, some issues remain: (1) many SAR images capture incomplete hurricane core structures; (2) the radar signal is attenuated by the heavy precipitation associated with hurricane; (3) wind directions retrievals are not available from the cross-polarized SAR measurements. When wind is at hurricane strength, the wind speed retrievals from co-polarized SAR may have errors because the backscatter signal may experience saturation and become double-valued. By comparison, wind direction retrievals from cross-polarization SAR are not possible until now. In this study, we develop a two-dimensional model, the Symmetric Hurricane Estimates for Wind (SHEW) model based on the mean wind profile in all radial directions, and combine it with the modified inflow angle model to detect hurricane morphology and estimate the wind vector field imaged by cross-polarization SAR. By fitting SHEW to the SAR derived hurricane wind speed, we find the initial closest elliptical-symmetrical wind speed field, hurricane center location, major and minor axes, the azimuthal (orientation) angle relative to the reference ellipse, and maximum wind speed. This set of hurricane morphology parameters, along with the speed of hurricane motion, are input to the inflow angle model modified with an ellipse-shaped eye, to derive the hurricane wind direction. A one-half modified Rankine vortex (OHMRV) model is proposed to describe the hurricane wind profile, particularly for those wind profiles with a wind speed maximum and an inflection point possibly associated with the degeneration of the inner wind maximum in the hurricane reintensification phase. The proposed method works well in area with significant radar attenuation by precipitation. Moreover, five possible mechanisms for the rain effects on the spaceborne C-band SAR observations are investigated: (1) attenuation and (2) volume backscattering for the microwave transfer in atmosphere; as well as (3) diffraction on the sharp edges of rain products, and (4) rain-induced damping to the wind waves and (5) rain-generated ring waves on the ocean surface.
Guosheng Zhang, Xiaofeng Li, William Perrie

Chapter 15. Detecting the Effects of Hurricanes on Oil Infrastructure (Damage and Oil Spills) Using Synthetic Aperture Radar (SAR) Imagery

Abstract
In addition to their effects on coastal areas (flooding, erosion, property damage), tropical cyclones (tropical depressions, tropical storms and hurricanes) in the Gulf of Mexico can significantly impact offshore oil and gas infrastructure (platforms, rigs, pipelines).
Christopher R. Jackson, Oscar Garcia-Pineda

Chapter 16. Tropical Cyclone Eye Morphology and Extratropical-Cyclone-Forced Mountain Lee Waves on SAR Imagery

Abstract
This chapter introduces an objective method for determining the center of the tropical cyclone (TC) from spaceborne synthetic aperture radar (SAR) data based on the structures of the well-defined TC eyes in the SAR images. A series of Radarsat-1 SAR images are used, which capture the TCs over the world ocean basins during the years from 2001 to 2007. Also, a case study of the atmospheric gravity waves over the Kuril Islands observed in a Sentinel-1A SAR image during the passage of an extratropical cyclone will be presented together with the use of the state-of-the-art atmospheric numerical model. The objective is to obtain a more complete understanding of the generation mechanism and the dynamics governing the gravity waves.
Qing Xu, Xiaofeng Li, Shaowu Bao, Guosheng Zhang
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