Tropical Cyclone Center Determination Algorithm by Texture and Gradient of Infrared Satellite Image

A novel algorithm for tropical cyclone (TC) center determination is presented by using texture and gradient of infrared satellite image from geostationary satellite. Except those latter disappearing TC satellite images that are little valuable to a TC center determination, generally other periods of TC, all have an inner core. And the centers are generally determined in the inner core. Based on this, an efficient TC center determination algorithm is designed. First, the inner core of a TC is obtained. Then, according to the texture and gradient information of the inner core, the center location of the TC is determined. The effectiveness of the proposed TC center determination algorithm is verified by using Chinese FY-2C stationary infrared satellite image. And the location result is compared with that of the “tropical cyclone yearbook,” which was compiled by Shanghai Typhoon Institute of China Meteorological Administration. Experimental results show that the proposed algorithm can provide a new technique that can automatically determine the center location for a TC based on infrared satellite image

The Use of a Spiral Band Model to Estimate Tropical Cyclone Intensity

Spiral cloud-rain bands (SCRBs) are some of the most distinguishing features inherent in satellite and radar images of tropical cyclones (TC). The subject of the proposed research is the finding of a physically substantiated method for estimation of the TC’s intensity using SCRBs’ configuration parameters. To connect a rainband pattern to a physical process that conditions the spiraling feature of a rainband, it is assumed that the rainband’s configuration near the core of a TC is governed primarily by a streamline. In turn, based on the distribution of primarily forces in a TC, an analytical expression as a combination of hyperbolic and logarithmic spirals (HLS) for the description of TC spiral streamline (rainband) is retrieved. Parameters of the HLS are determined by the physical parameters of a TC, particularly, by the maximal wind speed (MWS). To apply this theoretical finding to practical estimation of the TC’s intensity, several approximation techniques are developed to “convert” rainband configuration to the estimation of the MWS. The developed techniques have been tested by exploring satellite infrared imageries and airborne and coastal radar data, and the outcomes were compared with in situ measurements of wind speeds and the best track data of tropical cyclones

Evaluation and Predictability of Observation-based Surface Wind Asymmetric Structure in Tropical Cyclones

Surface wind speeds are an important and revealing component of the structure of tropical cyclones (TCs). To understand the asymmetric structure of surface winds in TCs associated with differences in formation region, environmental wind shear, storm forward motion, and TC strength and intensification, a twelve year database of satellite scatterometer data are utilized to produce composite total wind speed and Fourier-derived, low wavenumber analyses. A quantified asymmetry is determined as a function of TC intensity and reveals the tropical storms are influenced by wind shear at all TC-centric radii but only for areas away from the radius of maximum wind in hurricanes. Additionally, an increase of absolute angular momentum flux has a preference for the downshear-right quadrant, and the low wavenumber maximum develops downwind of this momentum transport. Further evaluation of the asymmetric structure with respect to wind shear’s relation to motion and impacts during TC intensity change are also considered. A composite rapid intensification event is produced and compared to overlapping satellite rain estimates. Results indicate that the TC becomes more symmetric during intensification and the phase of the maximum asymmetry rotates from a downshear-left direction to upshear-left direction after the intensification slows. The rain or convective maximum is generally located upwind of the surface wind maximum at the early stages of intensification and is coincident with the region of large angular momentum transport, which supports the idea that the surface wind asymmetry is likely a consequence of convective or other processes. Using data from a regional TC model, it is also determined that the scatterometer data are useful for model verification of tropical storms and non-major hurricanes and performs similar to or better than the standard tool at forecast lead times up to 60 hours. Preliminary comparisons of model-derived surface wind asymmetry relative to rain generally confirm the observational results

Electromagnetic Radiation

The application of electromagnetic radiation in modern life is one of the most developing technologies. In this timely book, the authors comprehensively treat two integrated aspects of electromagnetic radiation, theory and application. It covers a wide scope of practical topics, including medical treatment, telecommunication systems, and radiation effects. The book sections have clear presentation, some state of the art examples, which makes this book an indispensable reference book for electromagnetic radiation applications

An Intensity and Size Phase Space for Tropical Cyclone Structure and Evolution

Intensity and size are important to characterize a tropical cyclone (TC), but there are a wide variety of ways that both metrics are defined. TC intensity can refer to either a maximum sustained wind speed at some height level or central surface pressure minimum, and TC size may refer to the radius of maximum wind, the radius of gale force wind, or be based on other criteria. While different definitions of TC intensity and size have useful applications, there are varying amounts of redundant information and covariations between some size and intensity variables that make investigating physical relationships more challenging. In this study, we use aircraft observations and Best Track information to calculate an empirical orthogonal function analysis that yields new, orthogonal metrics of TC intensity and size. The new, linearly independent metrics reduce a seven-dimensional space of co-varying parameters into a simplified, two-dimensional phase space in which key TC structural changes can be visualized and historically contextualized. Additionally, our analysis introduces a new parameter that is a simplified measure of the wind decay outside the radius of maximum tangential velocity. We show that this decay parameter is nearly orthogonal to the new intensity and size metrics and is useful for identifying TC maturity. We demonstrate the utility of the new phase space by first comparing the structural evolution of the large Hurricane Rita (2005) and small Hurricane Charley (2004) using observations, as well as comparing two modeling simulations of Hurricane Rita with different initial conditions in the phase space.publishedVersio

Tropical Cyclone Intensity Estimation Using Multi-Dimensional Convolutional Neural Networks from Geostationary Satellite Data

For a long time, researchers have tried to find a way to analyze tropical cyclone (TC) intensity in real-time. Since there is no standardized method for estimating TC intensity and the most widely used method is a manual algorithm using satellite-based cloud images, there is a bias that varies depending on the TC center and shape. In this study, we adopted convolutional neural networks (CNNs) which are part of a state-of-art approach that analyzes image patterns to estimate TC intensity by mimicking human cloud pattern recognition. Both two dimensional-CNN (2D-CNN) and three-dimensional-CNN (3D-CNN) were used to analyze the relationship between multi-spectral geostationary satellite images and TC intensity. Our best-optimized model produced a root mean squared error (RMSE) of 8.32 kts, resulting in better performance (~35%) than the existing model using the CNN-based approach with a single channel image. Moreover, we analyzed the characteristics of multi-spectral satellite-based TC images according to intensity using a heat map, which is one of the visualization means of CNNs. It shows that the stronger the intensity of the TC, the greater the influence of the TC center in the lower atmosphere. This is consistent with the results from the existing TC initialization method with numerical simulations based on dynamical TC models. Our study suggests the possibility that a deep learning approach can be used to interpret the behavior characteristics of TCs

Remote Sensing of Tropical Cyclones: Applications from Microwave Radiometry and Global Navigation Satellite System Reflectometry

Tropical cyclones (TCs) are important to observe, especially over the course of their lifetimes, most of which is spent over the ocean. Very few in situ observations are available. Remote sensing has afforded researchers and forecasters the ability to observe and understand TCs better. Every remote sensing platform used to observe TCs has benefits and disadvantages. Some remote sensing instruments are more sensitive to clouds, precipitation, and other atmospheric constituents. Some remote sensing instruments are insensitive to the atmosphere, which allows for unobstructed observations of the ocean surface. Observations of the ocean surface, either of surface roughness or emission can be used to estimate ocean surface wind speed. Estimates of surface wind speed can help determine the intensity, structure, and destructive potential of TCs. While there are many methods by which TCs are observed, this thesis focuses on two main types of remote sensing techniques: passive microwave radiometry and Global Navigation Satellite System reflectometry (GNSS-R). First, we develop and apply a rain rate and ocean surface wind speed retrieval algorithm for the Hurricane Imaging Radiometer (HIRAD). HIRAD, an airborne passive microwave radiometer, operates at C-band frequencies, and is sensitive to rain absorption and emission, as well as ocean surface emission. Motivated by the unique observing geometry and high gradient rain scenes that HIRAD typically observes, a more robust rain rate and wind speed retrieval algorithm is developed. HIRAD’s observing geometry must be accounted for in the forward model and retrieval algorithm, if high rain gradients are to be estimated from HIRAD’s observations, with the ultimate goal of improving surface wind speed estimation. Lastly, TC science data products are developed for the Cyclone Global Navigation Satellite System (CYGNSS). The CYGNSS constellation employs GNSS-R techniques to estimate ocean surface wind speed in all precipitating conditions. From inputs of CYGNSS level-2 wind speed observations and the storm center location, a variety of products are created: integrated kinetic energy, wind radii, radius of maximum wind speed, and maximum wind speed. These products provide wind structure and intensity information—valuable for situational awareness and science applications.PHDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137109/1/marygm_1.pd

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography