Detection of Bottom Features on Seasat Synthetic Aperture Radar Imagery
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Part II-1 Water Wave Mechanics
Chapter 1 EM 1110-2-1100 WATER WAVE MECHANICS (Part II) 1 August 2008 (Change 2) Table of Contents Page II-1-1. Introduction ............................................................II-1-1 II-1-2. Regular Waves .........................................................II-1-3 a. Introduction ...........................................................II-1-3 b. Definition of wave parameters .............................................II-1-4 c. Linear wave theory ......................................................II-1-5 (1) Introduction .......................................................II-1-5 (2) Wave celerity, length, and period.......................................II-1-6 (3) The sinusoidal wave profile...........................................II-1-9 (4) Some useful functions ...............................................II-1-9 (5) Local fluid velocities and accelerations .................................II-1-12 (6) Water particle displacements .........................................II-1-13 (7) Subsurface pressure ................................................II-1-21 (8) Group velocity ....................................................II-1-22 (9) Wave energy and power.............................................II-1-26 (10)Summary of linear wave theory.......................................II-1-29 d. Nonlinear wave theories .................................................II-1-30 (1) Introduction ......................................................II-1-30 (2) Stokes finite-amplitude wave theory ...................................II-1-32 -
Title Relation Between Wave Characteristics of Cnoidal Wave
Relation between Wave Characteristics of Cnoidal Wave Title Theory Derived by Laitone and by Chappelear Author(s) YAMAGUCHI, Masataka; TSUCHIYA, Yoshito Bulletin of the Disaster Prevention Research Institute (1974), Citation 24(3): 217-231 Issue Date 1974-09 URL http://hdl.handle.net/2433/124843 Right Type Departmental Bulletin Paper Textversion publisher Kyoto University Bull. Disas. Prey. Res. Inst., Kyoto Univ., Vol. 24, Part 3, No. 225,September, 1974 217 Relation between Wave Characteristics of Cnoidal Wave Theory Derived by Laitone and by Chappelear By Masataka YAMAGUCHIand Yoshito TSUCHIYA (Manuscriptreceived October5, 1974) Abstract This paper presents the relation between wave characteristicsof the secondorder approxi- mate solutionof the cnoidal wave theory derived by Laitone and by Chappelear. If the expansionparameters Lo and L3in the Chappeleartheory are expanded in a series of the ratio of wave height to water depth and the expressionsfor wave characteristics of the secondorder approximatesolution of the cnoidalwave theory by Chappelearare rewritten in a series form to the second order of the ratio, the expressions for wave characteristics of the cnoidalwave theory derived by Chappelearagree exactly with the ones by Laitone, whichare convertedfrom the depth below the wave trough to the mean water depth. The limitingarea betweenthese theories for practical applicationis proposed,based on numerical comparison. In addition, somewave characteristicssuch as wave energy, energy flux in the cnoidal waves and so on are calculated. 1. Introduction In recent years, the various higher order solutions of finite amplitude waves based on the perturbation method have been extended with the progress of wave theories. For example, systematic deviations of the cnoidal wave theory, which is a nonlinear shallow water wave theory, have been made by Kellern, Laitone2), and Chappelears> respectively. -
Appendix C: Insar
Dirty Little Secrets about InSAR [EarthScope 2009] C-band interferograms are decorrelated over most of the SAF and Cascadia except urban areas. Envisat is almost out of fuel and the C-band replacement is a few years away. L-band ALOS has almost no data on descending tracks. L-band ALOS has ionospheric phase variations are +/- 10 cm on some interferograms. L-band ALOS has poor orbit control (but excellent orbit occuracy). Less than 2% of the 17 Tbytes of GeoEarthScope data has been downloaded. DESDYNI the US InSAR mission will launch in 2019 (40 years after Seasat). Open source InSAR software is not of “geodetic” quality. Dirty Little Secrets about InSAR [Today] C-band interferograms are decorrelated over most of the SAF and Cascadia except urban areas. Sentinel-1A and B are both functioning. They operate in TOPS mode which is a nightmare! < 10 cm accuracy orbits are essential. L-band ALOS-1 has almost no data on descending tracks. L-band ALOS-/2 has ionospheric phase variations are +/- 100 cm on some interferograms. L-band ALOS has poor orbit control (but excellent orbit occuracy). ALOS-2 data ree morerestricted than ALOS-1 NISAR the US InSAR mission will launch in 2021 (43 years after Seasat). NISAR is only a 3-year mission! Open source InSAR software is getting better but contains some ugly code. Need a programmer to remove the deadwood and streamline the installation and testing. X-band 3 cm TerraSAR COSMO-SkyMed interferogram using data from 19 February 2009 and 9 April 2009. Perpendicular baseline is 480 m, and the satellite’s right-looking angle is 37 degrees. -
NASA's Earth Science Data Systems Program
NASA's Earth Science Data Systems Program Program Executive for Earth Science Data Systems Earth Science Division (DK) Science Mission Directorate, NASA Headquarters February 16, 2016 5/25/2016 1 NASA Strategic Plan 2014 • Objective 2.2: Advance knowledge of Earth as a system to meet the challenges of environmental change, and to improve life on our planet. – How is the global Earth system changing? What causes these changes in the Earth system? How will Earth’s systems change in the future? How can Earth system science provide societal benefits? – NASA’s Earth science programs shape an interdisciplinary view of Earth, exploring the interaction among the atmosphere, oceans, ice sheets, land surface interior, and life itself, which enables scientists to measure global climate changes and to inform decisions by Government, organizations, and people in the United States and around the world. We make the data collected and results generated by our missions accessible to other agencies and organizations to improve the products and services they provide… 5/25/2016 2 Major Components of the Earth Science Data Systems Program • Earth Observing System Data and Information System (EOSDIS) – Core systems for processing, ingesting and archiving data for the Earth Science Division • Competitively Selected Programs – Making Earth System Data Records for Use in Research Environments (MEaSUREs) – Advancing Collaborative Connections for Earth System Science (ACCESS) • International and Interagency Coordination and Development – CEOS Working Group on Information -
The Space-Based Global Observing System in 2010 (GOS-2010)
WMO Space Programme SP-7 The Space-based Global Observing For more information, please contact: System in 2010 (GOS-2010) World Meteorological Organization 7 bis, avenue de la Paix – P.O. Box 2300 – CH 1211 Geneva 2 – Switzerland www.wmo.int WMO Space Programme Office Tel.: +41 (0) 22 730 85 19 – Fax: +41 (0) 22 730 84 74 E-mail: [email protected] Website: www.wmo.int/pages/prog/sat/ WMO-TD No. 1513 WMO Space Programme SP-7 The Space-based Global Observing System in 2010 (GOS-2010) WMO/TD-No. 1513 2010 © World Meteorological Organization, 2010 The right of publication in print, electronic and any other form and in any language is reserved by WMO. Short extracts from WMO publications may be reproduced without authorization, provided that the complete source is clearly indicated. Editorial correspondence and requests to publish, reproduce or translate these publication in part or in whole should be addressed to: Chairperson, Publications Board World Meteorological Organization (WMO) 7 bis, avenue de la Paix Tel.: +41 (0)22 730 84 03 P.O. Box No. 2300 Fax: +41 (0)22 730 80 40 CH-1211 Geneva 2, Switzerland E-mail: [email protected] FOREWORD The launching of the world's first artificial satellite on 4 October 1957 ushered a new era of unprecedented scientific and technological achievements. And it was indeed a fortunate coincidence that the ninth session of the WMO Executive Committee – known today as the WMO Executive Council (EC) – was in progress precisely at this moment, for the EC members were very quick to realize that satellite technology held the promise to expand the volume of meteorological data and to fill the notable gaps where land-based observations were not readily available. -
Improved Quality Control for Quikscat Near Real-Time Data
JP4.6 Improved Quality Control for QuikSCAT Near Real-time Data S. Mark Leidner, Ross N. Hoffman, and Mark C. Cerniglia Atmospheric and Environmental Research Inc., Lexington, Massachusetts Abstract errors. We will illustrate the types of errors that occur due to rain contamination and ambiguity removal. SeaWinds on QuikSCAT, launched in June 1999, We will also give examples of how the quality of the provides a new source of surface wind information retrieved winds varies across the satellite track, and over the world’s oceans. This new window on global varies with wind speed. surface vector winds has been a great aid to real- SeaWinds is an active, Ku-band microwave radar time operational users, especially in remote areas operating near ¢¤£¦¥¨§ © and is sensitive to centimeter- of the world. As with in situ observations, the qual- scale or capillary waves on the ocean surface. ity of remotely-sensed geophysical data is closely These waves are usually in equilibrium with the wind. tied to the characteristics of the instrument. But Each radar backscatter observation samples a patch remotely-sensed scatterometer winds also have a of ocean about . The vector wind is re- whole range of additional quality control concerns trieved by combining several backscatter observa- different from those of in situ observation systems. tions made from multiple viewing geometries as the The retrieval of geophysical information from the raw scatterometer passes overhead. The resolution of satellite measurements introduces uncertainties but the retrieved winds is . also produces diagnostics about the reliability of the Backscatter from capillary waves on the ocean retrieved quantities. -
Watching the Winds Where Sea Meets Sky 14 August 2014, by Rosalie Murphy
Watching the winds where sea meets sky 14 August 2014, by Rosalie Murphy the speed and direction of wind at the ocean's surface. "Before scatterometers, we could only measure ocean winds on ships, and sampling from ships is very limited," said Timothy Liu of NASA's Jet Propulsion Laboratory in Pasadena, California, who led the science team for NASA's QuikScat mission. Scatterometry began to emerge during World War II, when scientists realized wind disturbing the ocean's surface caused noise in their radar signals. NASA included an experimental scatterometer in its The SeaWinds scatterometer on NASA's QuikScat first space station in 1973 and again when it satellite stares into the eye of 1999's Hurricane Floyd as launched its SeaSat satellite in 1978. During its it hits the U.S. coast. The arrows indicate wind direction, three-month life, SeaSat's scatterometer provided while the colors represent wind speed, with orange and scientists with more individual wind observations yellow being the fastest. Credit: NASA/JPL-Caltech than ships had collected in the previous century. The ocean covers 71 percent of Earth's surface and affects weather over the entire globe. Hurricanes and storms that begin far out over the ocean affect people on land and interfere with shipping at sea. And the ocean stores carbon and heat, which are transported from the ocean to the air and back, allowing for photosynthesis and affecting Earth's climate. To understand all these processes, scientists need information about winds A JPL team then designed a mission called near the ocean's surface. -
Spectral Analysis
Ocean Environment Sep. 2014 Kwang Hyo Jung, Ph.D Assistant Professor Dept. of Naval Architecture & Ocean Engineering Pusan National University Introduction Project Phase and Functions Appraise Screen new development development Identify Commence basic Complete detail development options options & define Design & define design & opportunity & Data acquisition base case equipment & material place order LLE Final Investment Field Feasibility Decision Const. and Development Pre-FEED FEED Detail Eng. Procurement Study Installation Planning (3 - 5 M) (6 - 8 M) (33 - 36 M) 1st Production 45/40 Tendering for FEED Tendering for EPCI Single Source 30/25 (4 - 6 M) (11 - 15 M) Design Competition 20/15 15/10 0 - 10/- 5 - 15/-10 - 25/-15 Cost Estimate Accuracy (%) EstimateAccuracy Cost - 40/- 25 Equipment Bills of Material & Concept options Process systems & Material Purchase order & Process blocks defined Definition information Ocean Water Properties Density, Viscosity, Salinity and Temperature Temperature • The largest thermocline occurs near the water surface. • The temperature of water is the highest at the surface and decays down to nearly constant value just above 0 at a depth below 1000 m. • This decay is much faster in the colder polar region compared to the tropical region and varies between the winter and summer seasons. Salinity • The variation of salinity is less profound, except near the coastal region. • The river run-off introduces enough fresh water in circulation near the coast producing a variable horizontal as well as vertical salinity. • In the open sea. the salinity is less variable having an average value of about 35 ‰ (permille, parts per thousand). Viscosity • The dynamic viscosity may be obtained by multiplying the viscosity with mass density. -
Variational of Surface Gravity Waves Over Bathymetry BOUSSINESQ
Gert Klopman Variational BOUSSINESQ modelling of surface gravity waves over bathymetry VARIATIONAL BOUSSINESQ MODELLING OF SURFACE GRAVITY WAVES OVER BATHYMETRY Gert Klopman The research presented in this thesis has been performed within the group of Applied Analysis and Mathematical Physics (AAMP), Department of Applied Mathematics, Uni- versity of Twente, PO Box 217, 7500 AE Enschede, The Netherlands. Copyright c 2010 by Gert Klopman, Zwolle, The Netherlands. Cover design by Esther Ris, www.e-riswerk.nl Printed by W¨ohrmann Print Service, Zutphen, The Netherlands. ISBN 978-90-365-3037-8 DOI 10.3990/1.9789036530378 VARIATIONAL BOUSSINESQ MODELLING OF SURFACE GRAVITY WAVES OVER BATHYMETRY PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit Twente, op gezag van de rector magnificus, prof. dr. H. Brinksma, volgens besluit van het College voor Promoties in het openbaar te verdedigen op donderdag 27 mei 2010 om 13.15 uur door Gerrit Klopman geboren op 25 februari 1957 te Winschoten Dit proefschrift is goedgekeurd door de promotor prof. dr. ir. E.W.C. van Groesen Aan mijn moeder Contents Samenvatting vii Summary ix Acknowledgements x 1 Introduction 1 1.1 General .................................. 1 1.2 Variational principles for water waves . ... 4 1.3 Presentcontributions........................... 6 1.3.1 Motivation ............................ 6 1.3.2 Variational Boussinesq-type model for one shape function .. 7 1.3.3 Dispersionrelationforlinearwaves . 10 1.3.4 Linearwaveshoaling. 11 1.3.5 Linearwavereflectionbybathymetry . 12 1.3.6 Numerical modelling and verification . 14 1.4 Context .................................. 16 1.4.1 Exactlinearfrequencydispersion . 17 1.4.2 Frequency dispersion approximations . 18 1.5 Outline ................................. -
Seasat—A 25-Year Legacy of Success
Remote Sensing of Environment 94 (2005) 384–404 www.elsevier.com/locate/rse Seasat—A 25-year legacy of success Diane L. Evansa,*, Werner Alpersb, Anny Cazenavec, Charles Elachia, Tom Farra, David Glackind, Benjamin Holta, Linwood Jonese, W. Timothy Liua, Walt McCandlessf, Yves Menardg, Richard Mooreh, Eni Njokua aJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, United States bUniversitaet Hamburg, Institut fuer Meereskunde, D-22529 Hamburg, Germany cLaboratoire d´Etudes en Geophysique et Oceanographie Spatiales, Centre National d´Etudes Spatiales, Toulouse 31401, France dThe Aerospace Corporation, Los Angeles, CA 90009, United States eCentral Florida Remote Sensing Laboratory, University of Central Florida, Orlando, FL 32816, United States fUser Systems Enterprises, Denver, CO 80220, United States gCentre National d´Etudes Spatiales, Toulouse 31401, France hThe University of Kansas, Lawrence, KS 66047-1840, United States Received 10 June 2004; received in revised form 13 September 2004; accepted 16 September 2004 Abstract Thousands of scientific publications and dozens of textbooks include data from instruments derived from NASA’s Seasat. The Seasat mission was launched on June 26, 1978, on an Atlas-Agena rocket from Vandenberg Air Force Base. It was the first Earth-orbiting satellite to carry four complementary microwave experiments—the Radar Altimeter (ALT) to measure ocean surface topography by measuring spacecraft altitude above the ocean surface; the Seasat-A Satellite Scatterometer (SASS), to measure wind speed and direction over the ocean; the Scanning Multichannel Microwave Radiometer (SMMR) to measure surface wind speed, ocean surface temperature, atmospheric water vapor content, rain rate, and ice coverage; and the Synthetic Aperture Radar (SAR), to image the ocean surface, polar ice caps, and coastal regions. -
Aqua Summary (As of May 31, 2019) • Spacecraft Bus – Nominal Operations (Excellent Health) ‒ All Components Remain on Primary Hardware
Aqua Summary (as of May 31, 2019) • Spacecraft Bus – Nominal Operations (Excellent Health) ‒ All components remain on primary hardware. ‒ 18 of 132 Solar Array Strings appear to have failed. See slide 2. Similar failures have occurred on Aura. ‒ Significant power generation margin remains. • MODIS – Nominal Operations (Excellent Health) ‒ All voltages, currents, and temperatures are as expected. ‒ All components remain on primary hardware except 10W Lamps used for calibration. • AIRS – Nominal Operations (<10% of Channels degraded) – (Excellent Health) ‒ All voltages, currents, and temperatures are as expected. ‒ ~200 of 2378 channels are degraded due to radiation, however they are still useful. ‒ Cooler-A Telemetry, frozen since a 3/28/2014 Anomaly, was restored during recovery activities performed on 9/27/2016. • AMSU-A – Nominal Operations for 9 of 15 Channels (Fair Health) ‒ All voltages, currents, and temperatures are as expected. ‒ 3 of 15 channels have been removed from Level 2 processing. 2 channels (#1 & #2) are unavailable. ‒ AMSU-A2 Anomaly on 9/24/2016 caused loss of Channels 1 and 2. The initial recovery attempts were unsuccessful. The instrument manufacturer recommends not switching to the A-side to attempt to recover AMSU-A2. ‒ AMSU-A1 Anomaly on 6/21/2018 caused unexplained shift in Channel 14. Channel 14 data have now been removed from processing, and the anomaly is considered closed. • CERES-AFT (FM-3) – Nominal Operations (Excellent Health) ‒ All voltages, currents, and temperatures are as expected. ‒ Cross-Track and Biaxial Modes are fully functioning. ‒ All channels remain operational. • CERES-FORE (FM-4) – Nominal Operations (Good Health) ‒ All voltages, currents, and temperatures are as expected. -
SMEX05 Quikscat/Seawinds Backscatter Data: Iowa
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited. SMEX05 QuikSCAT/SeaWinds Backscatter Data: Iowa Summary This data set includes radar backscatter data collected over the Soil Moisture Experiment 2005 (SMEX05) area of Iowa, USA from 01 May 2005 through 31 July 2005. The SeaWinds scatterometer on the NASA Quick Scatterometer (QuikSCAT) satellite collected backscatter data. The total volume of this data set is approximately 18 megabytes. Data are provided in gzip compressed Brigham Young University - Microwave Earth Remote Sensing (BYU-MERS) Scatterometer Image Reconstruction (SIR) images and Graphics Interchange Format (GIF) images, and are available via FTP. The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a mission instrument launched aboard NASA's Aqua satellite on 04 May 2002. AMSR-E validation studies linked to SMEX are designed to evaluate the accuracy of AMSR-E soil moisture data. Specific validation objectives include: assessing and refining soil moisture algorithm performance; verifying soil moisture estimation accuracy; investigating the effects of vegetation, surface temperature, topography, and soil texture on soil moisture accuracy; and determining the regions that are useful for AMSR-E soil moisture measurements. Citing These Data: Long, David G. 2010. SMEX05 QuikSCAT/SeaWinds Backscatter Data: Iowa. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice Data Center. Overview Table Category Description gzip compressed SIR Data format GIF Spatial coverage 41.5º to 42.5º N, 93º to 95º W Temporal coverage 01 May 2005 to 31 July 2005 queh-a-NAm05-121-124.sir.SME.gz File naming convention queh-a-NAm05-121-124.sir.SM.gif .gz files range in size from 7 to 32 KB File size .gif files range in size from 3 KB to 14 KB Procedures for obtaining data Data are available via FTP.