全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于星载SAR数据的台风参数估计及风场构建

, PP. 355-366

Keywords: 降雨订正,台风参数估计,风场构建,星载SAR数据

Full-Text   Cite this paper   Add to My Lib

Abstract:

?传统的星载SAR数据海面风场反演方法是利用海面风场与雷达后向散射系数之间的经验关系即CMOD5模式函数求解海面风场.但在台风条件下,由于降雨对雷达信号的影响及高风速条件下CMOD5模式函数的停滞效应,海面风场的反演精度迅速下降.针对降雨对雷达信号的影响,本文基于星载SAR卫星平台未搭载降雨测量载荷的特点,将多时次的静止气象卫星红外云图用于推导台风云系的运动矢量,并由该运动矢量及非同步观测降雨数据估算星载SAR数据过境时的降雨强度.最后,利用订正模型和降雨强度数据进行降雨订正.针对高风速条件下CMOD5模式函数的停滞效应,本文基于台风的SAR图像特征和改进的HOLLAND台风模型,提出了台风参数估计及风场构建方案.首先,利用基于小波分析的风向提取算法提取台风风场的海面风向信息,并通过地球物理模式函数和风向信息反演海面风速.然后,根据台风眼的SAR图像特征计算台风中心位置和最大风速半径,并将其代入改进的HOLLAND台风模型.最后,利用中低风速数据通过最小二乘法拟合台风中心气压和最大风速,并将台风风向、中心位置、最大风速半径、中心气压和最大风速等参量代入改进的HOLLAND模型构建台风海面风场.为了验证方案的精度,选择台风“艾利”、“卡努”和“奥菲利娅”的星载SAR数据进行试验,并利用美国联合台风预警中心和飓风研究中心的最佳路径数据和风场数据进行精度检验.结果表明,本文利用星载SAR数据估算的台风中心位置、中心气压、最大风速与最佳路径数据基本一致,构建的海面风场精度较高,其中,海面风速的均方差为1.4ms-1,风向的均方差为2.1°,为台风监测提供了新的技术途径.

References

[1]  Ulaby F T, Moore R K, Fung A K. 1982. Microwave Remote Sensing: Active and Passive, vol. II. Reading, MA: Artech House
[2]  王炯琦, 周海银, 吴翊. 2007. 基于最优估计的数据融合理论. 应用数学, 20: 392-399
[3]  张庆红, 韦青, 陈联寿. 2010. 登陆中国大陆台风影响力研究. 中国科学: 地球科学, 40: 941-946
[4]  周旋, 杨晓峰, 李紫薇, 等. 2012. 降雨对C波段散射计测风的影响及其校正. 物理学报, 61: 149202
[5]  Alpers W, Brummer B. 2012. Atmospheric boundary layer rolls observed by the synthetic aperture radar aboard the ERS-1 SAR satellite. J Geophys Res, 99: 12613-12621
[6]  Battan L J. 1973. Radar Observation of the Atmosphere. Chicago: University Chicago Press
[7]  Depperman R C. 1947. Notes on the origin and structures of Philippine typhoons. Bull Amer Meteor Soc, 28: 399-404
[8]  Donelan M A, Haus B K, Reul N, et al. 2004. On the limiting aerodynamic roughness of the ocean in very strong winds. Geophys Res Lett, 31: L18306
[9]  Du Y, Vachon P W, Wolfe J. 2002. Wind direction estimation from SAR images of the ocean using wavelet analysis. Can J Remote Sens, 28: 498-509
[10]  Du Y, Vachon P W. 2003. Characterization of hurricane eyes in RADARSAT-1 images with wavelet analysis. Can J Remote Sens, 29: 491-498
[11]  Fernandez D E, Carswell J R, Frasier S, et al. 2006. Dual-polarized C-and Ku-band ocean backscatter response to hurricane-force winds. J Geophy Res, 111: C08013
[12]  Fore A, Haddad Z S, Krishnamurti T N, et al. 2010. Improving scatterometry retrievals of wind in hurricanes using non-simultaneous passive microwave estimates of precipitation and a split-step advection/convection model. Pure Appl Geophys, 169: 415-424
[13]  Hersbach H, Stoffelen A, Haan S D. 2007. An improved C-band scatterometer ocean geophysical model function: CMOD5. J Geophys Res, 112: C03006
[14]  Holland G J. 1980. An analytical model of the wind and pressure profiles in hurricanes. Mon Weather Rev, 108: 1212-1218
[15]  Horstmann J, Koch W, Lehner S, et al. 2000. Wind retrieval over the ocean using synthetic aperture radar with C-band HH polarization. IEEE Trans Geosci Remote Sensing, 38: 2122-2131
[16]  Horstmann J, Koch W, Lehner S, et al. 2002. Ocean winds from RADARSAT-1 ScanSAR. Can J Remote Sens, 28: 524-533
[17]  Horstmann J. Wackerman C, Forster R, et al. 2012. Estimating winds from synthetic aperture radar in typhoon conditions. In: IEEE Geoscience and Remote Sensing Society. Munich. 3
[18]  Katsaros K B, Vachon P W, Liu W T, et al. 2002. Microwave remote sensing of tropical cyclones from space. J Oceanogr, 58: 137-157
[19]  Nie C L, Long D G. 2008. A C-band scatterometer simultaneous wind/rain retrieval method. IEEE Trans Geosci Remote Sensing, 46: 3618-3631
[20]  Nie C L, Long D G. 2007. A C-band wind/rain backscatter model. IEEE Trans Geosci Remote Sensing, 45: 621-631
[21]  Pichel W G, Li X F, Monaldo F, et al. 2007. ENVISAT ASAR applications demonstrations: Alaska SAR demonstration and Gulf of Mexico hurricane studies. In: Proceedings of Envisat Symposium. Montreux. 23-27
[22]  Powell M D, Vickery P J, Reinhold T A, et al. 2003. Reduced drag coefficient for high wind speeds in tropical cyclones. Nature, 422: 279-283
[23]  Reppucci A, Lehner S, Schulz-Stellenfleth J, et al. 2008. Extreme wind conditions observed by satellite synthetic aperture radar in the North West Pacific. Int J Remote Sens, 29: 6129-6144
[24]  Reppucci A, Lehner S, Schulz-Stellenfleth J, et al. 2010. Tropical cyclone intensity estimated from wide-swath sar images. IEEE Trans Geosci Remote Sensing, 48: 1639-1649
[25]  Schloemer R W. 1954. Analysis and synthesis of hurricane wind patterns over Lake Okeechobee. NOAA Hydromet Rep, 31: 49
[26]  Srivastava S K, Cote S, Le Dantec P, et al. 2007. RADARSAT-1 calibration and image quality evolution to the extended mission. Adv Space Res, 39: 7-12
[27]  Thompson D R, Elfouhaily T M, Chapron B. 1998. Polarization ratio for microwave backscattering from the ocean surface at low to moderate incidence angles. Geosci Remote Sensing Symp Proc, 3: 1671-1673
[28]  Unal C M H, Snooji P, Swart P J F. 1991. The ploarization-dependent relation between radar backscatter from the ocean surface and surface wind vector at frequencies between 1 and 18 GHz. IEEE Trans Geosci Remote Sensing, 29: 621-626
[29]  Valenzuela G R. 1971. Theories for interaction of electromagnetic and oceanic waves--A review. Bound-Layer Meteor, 13: 61-85
[30]  Willoughby H E, Rahn M E. 2004. Parametric representation of the primary hurricane vortex. part I: Observations and evaluation of the Holland (1980) model. Mon Weather Rev, 132: 3033-3045
[31]  Xie L, Bao S W, Pietrafesa L J, et al. 2006. A real-time hurricane surface wind forecasting model: Formulation and verification. Mon Weather Rev, 134: 1355-1370
[32]  Young I R. 1993. An estimate of the Geosat altimeter wind speed algorithm at high wind speeds. J Geophy Res, 98: 20275-20285

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133