Information on the NASA Research and Development Satellites
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New Millennium Program
NASA Facts National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, CA 91109 New Millennium Program NASA's New Millennium program, a series of discerning trends, examining planetary climates and missions to test cutting-edge technologies never atmospheres, or landing to study such surface phe- before flown, will pave the way for a 21st century nomena as seismic and meteorological activity. Other fleet of affordable, frequently launched spacecraft sets of spacecraft could form a constellation uniquely perhaps 10 to suited to study 15 per year solar systems with highly beyond our own. focused sci- These goals ence objec- require significant tives. changes in almost New all aspects of Millennium spacecraft design will develop and deployment. and validate New Millennium the essential experimental tech- technologies nology flights will and capabilities validate key tech- required for nologies required these new to move toward. types of mis- Testing these sions. The pro- technologies in gram is flight will speed designed to ini- up their infusion tiate a revolu- New Millenniums Deep Space 1 will test ion propulsion and other technologies into the market- tionary new when the spacecraft flies by an asteroid and later possibly a comet (above). place. Some of way of explor- the space instru- ing Earth, the solar system and astrophysical events in ments of tomorrow may become as small and light- and far beyond the Milky Way galaxy. These new weight as a pocket wallet. missions will ensure NASA's technological readiness Drawing on diverse sectors of the country's sci- for post-2000 space and Earth science missions. -
Estimating Gale to Hurricane Force Winds Using the Satellite Altimeter
VOLUME 28 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY APRIL 2011 Estimating Gale to Hurricane Force Winds Using the Satellite Altimeter YVES QUILFEN Space Oceanography Laboratory, IFREMER, Plouzane´, France DOUG VANDEMARK Ocean Process Analysis Laboratory, University of New Hampshire, Durham, New Hampshire BERTRAND CHAPRON Space Oceanography Laboratory, IFREMER, Plouzane´, France HUI FENG Ocean Process Analysis Laboratory, University of New Hampshire, Durham, New Hampshire JOE SIENKIEWICZ Ocean Prediction Center, NCEP/NOAA, Camp Springs, Maryland (Manuscript received 21 September 2010, in final form 29 November 2010) ABSTRACT A new model is provided for estimating maritime near-surface wind speeds (U10) from satellite altimeter backscatter data during high wind conditions. The model is built using coincident satellite scatterometer and altimeter observations obtained from QuikSCAT and Jason satellite orbit crossovers in 2008 and 2009. The new wind measurements are linear with inverse radar backscatter levels, a result close to the earlier altimeter high wind speed model of Young (1993). By design, the model only applies for wind speeds above 18 m s21. Above this level, standard altimeter wind speed algorithms are not reliable and typically underestimate the true value. Simple rules for applying the new model to the present-day suite of satellite altimeters (Jason-1, Jason-2, and Envisat RA-2) are provided, with a key objective being provision of enhanced data for near-real- time forecast and warning applications surrounding gale to hurricane force wind events. Model limitations and strengths are discussed and highlight the valuable 5-km spatial resolution sea state and wind speed al- timeter information that can complement other data sources included in forecast guidance and air–sea in- teraction studies. -
Articles Upon the Hox Family by Comparing Averages of Days Impacted by These Events with Averages of Non-Impacted 3945–3977, Doi:10.5194/Acp-13-3945-2013, 2013
Atmos. Chem. Phys., 15, 2889–2902, 2015 www.atmos-chem-phys.net/15/2889/2015/ doi:10.5194/acp-15-2889-2015 © Author(s) 2015. CC Attribution 3.0 License. Stratospheric and mesospheric HO2 observations from the Aura Microwave Limb Sounder L. Millán1,2, S. Wang2, N. Livesey2, D. Kinnison3, H. Sagawa4, and Y. Kasai4 1Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, California, USA 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA 3National Center for Atmospheric Research, Boulder, Colorado, USA 4National Institute of Information and Communications Technology, Koganei, Tokyo, Japan Correspondence to: L. Millán ([email protected]) Received: 18 June 2014 – Published in Atmos. Chem. Phys. Discuss.: 8 September 2014 Revised: 17 February 2015 – Accepted: 24 February 2015 – Published: 13 March 2015 Abstract. This study introduces stratospheric and meso- sphere where O3 chemistry is controlled by catalytic cycles spheric hydroperoxyl radical (HO2) estimates from the Aura involving the HOx (HO2, OH and H) family (Brasseur and Microwave Limb Sounder (MLS) using an offline retrieval Solomon, 2005): (i.e. run separately from the standard MLS algorithm). This new data set provides two daily zonal averages, one during X C O3 ! XO C O2 (R1) daytime from 10 to 0.0032 hPa (using day-minus-night dif- O C XO ! O2 C X; (R2) ferences between 10 and 1 hPa to ameliorate systematic bi- ases) and one during nighttime from 1 to 0.0032 hPa. The where the net effect of these two reactions is simply vertical resolution of this new data set varies from about 4 km O C O ! 2O (R3) at 10 hPa to around 14 km at 0.0032 hPa. -
GST Responses to “Questions to Inform Development of the National Plan”
GST Responses to “Questions to Inform Development of the National Plan” Name (optional): Dr. Darrel Williams Position (optional): Chief Scientist, (240) 542-1106; [email protected] Institution (optional): Global Science & Technology, Inc. Greenbelt, Maryland 20770 Global Science & Technology, Inc. (GST) is pleased to provide the following answers as a contribution towards OSTP’s effort to develop a national plan for civil Earth observations. In our response we provide information to support three main themes: 1. There is strong science need for high temporal resolution of moderate spatial resolution satellite earth observation that can be achieved with cost effective, innovative new approaches. 2. Operational programs need to be designed to obtain sustained climate data records. Continuity of Earth observations can be achieved through more efficient and economical means. 3. We need programs to address the integration of remotely sensed data with in situ data. GST has carefully considered these important national Earth observation issues over the past few years and has submitted the following RFI responses: The USGS RFI on Landsat Data Continuity Concepts (April 2012), NASA’s Sustainable Land Imaging Architecture RFI (September 2013), and This USGEO RFI (November 2013) relative to OSTP’s efforts to develop a national plan for civil Earth observations. In addition to the above RFI responses, GST led the development of a mature, fully compliant flight mission concept in response to NASA’s Earth Venture-2 RFP in September 2011. Our capacity to address these critical national issues resides in GST’s considerable bench strength in Earth science understanding (Drs. Darrel Williams, DeWayne Cecil, Samuel Goward, and Dixon Butler) and in NASA systems engineering and senior management oversight (Drs. -
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. -
Cassini RADAR Sequence Planning and Instrument Performance Richard D
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 47, NO. 6, JUNE 2009 1777 Cassini RADAR Sequence Planning and Instrument Performance Richard D. West, Yanhua Anderson, Rudy Boehmer, Leonardo Borgarelli, Philip Callahan, Charles Elachi, Yonggyu Gim, Gary Hamilton, Scott Hensley, Michael A. Janssen, William T. K. Johnson, Kathleen Kelleher, Ralph Lorenz, Steve Ostro, Member, IEEE, Ladislav Roth, Scott Shaffer, Bryan Stiles, Steve Wall, Lauren C. Wye, and Howard A. Zebker, Fellow, IEEE Abstract—The Cassini RADAR is a multimode instrument used the European Space Agency, and the Italian Space Agency to map the surface of Titan, the atmosphere of Saturn, the Saturn (ASI). Scientists and engineers from 17 different countries ring system, and to explore the properties of the icy satellites. have worked on the Cassini spacecraft and the Huygens probe. Four different active mode bandwidths and a passive radiometer The spacecraft was launched on October 15, 1997, and then mode provide a wide range of flexibility in taking measurements. The scatterometer mode is used for real aperture imaging of embarked on a seven-year cruise out to Saturn with flybys of Titan, high-altitude (around 20 000 km) synthetic aperture imag- Venus, the Earth, and Jupiter. The spacecraft entered Saturn ing of Titan and Iapetus, and long range (up to 700 000 km) orbit on July 1, 2004 with a successful orbit insertion burn. detection of disk integrated albedos for satellites in the Saturn This marked the start of an intensive four-year primary mis- system. Two SAR modes are used for high- and medium-resolution sion full of remote sensing observations by a dozen instru- (300–1000 m) imaging of Titan’s surface during close flybys. -
NASA Earth Science Research Missions NASA Observing System INNOVATIONS
NASA’s Earth Science Division Research Flight Applied Sciences Technology NASA Earth Science Division Overview AMS Washington Forum 2 Mayl 4, 2017 FY18 President’s Budget Blueprint 3/2017 (Pre)FormulationFormulation FY17 Program of Record (Pre)FormulationFormulation Implementation MAIA (~2021) Implementation MAIA (~2021) Landsat 9 Landsat 9 Primary Ops Primary Ops TROPICS (~2021) (2020) TROPICS (~2021) (2020) Extended Ops PACE (2022) Extended Ops XXPACE (2022) geoCARB (~2021) NISAR (2022) geoCARB (~2021) NISAR (2022) SWOT (2021) SWOT (2021) TEMPO (2018) TEMPO (2018) JPSS-2 (NOAA) JPSS-2 (NOAA) InVEST/Cubesats InVEST/Cubesats Sentinel-6A/B (2020, 2025) RBI, OMPS-Limb (2018) Sentinel-6A/B (2020, 2025) RBI, OMPS-Limb (2018) GRACE-FO (2) (2018) GRACE-FO (2) (2018) MiRaTA (2017) MiRaTA (2017) Earth Science Instruments on ISS: ICESat-2 (2018) Earth Science Instruments on ISS: ICESat-2 (2018) CATS, (2020) RAVAN (2016) CATS, (2020) RAVAN (2016) CYGNSS (>2018) CYGNSS (>2018) LIS, (2020) IceCube (2017) LIS, (2020) IceCube (2017) SAGE III, (2020) ISS HARP (2017) SAGE III, (2020) ISS HARP (2017) SORCE, (2017)NISTAR, EPIC (2019) TEMPEST-D (2018) SORCE, (2017)NISTAR, EPIC (2019) TEMPEST-D (2018) TSIS-1, (2018) TSIS-1, (2018) TCTE (NOAA) (NOAA’S DSCOVR) TCTE (NOAA) (NOAA’SXX DSCOVR) ECOSTRESS, (2017) ECOSTRESS, (2017) QuikSCAT (2017) RainCube (2018*) QuikSCAT (2017) RainCube (2018*) GEDI, (2018) CubeRRT (2018*) GEDI, (2018) CubeRRT (2018*) OCO-3, (2018) CIRiS (2018*) OCOXX-3, (2018) CIRiS (2018*) CLARREO-PF, (2020) EOXX-1 CLARREOXX XX-PF, (2020) EOXX-1 -
Evaluation of Quikscat Data for Monitoring Vegetation Phenology
City University of New York (CUNY) CUNY Academic Works Dissertations and Theses City College of New York 2011 Evaluation of QuikSCAT data for Monitoring Vegetation Phenology Doralee Pellot CUNY City College How does access to this work benefit ou?y Let us know! More information about this work at: https://academicworks.cuny.edu/cc_etds_theses/27 Discover additional works at: https://academicworks.cuny.edu This work is made publicly available by the City University of New York (CUNY). Contact: [email protected] Evaluation of QuikSCAT data for Monitoring Vegetation Phenology Thesis Submitted in partial fulfillment of the requirements for the degree Master of Engineering (Civil) at The City College of New York of The City University of New York by Doralee Pellot May 2012 ____________________________________________ Professor Reza Khanbilvardi Dr. Tarendra Lakhankar Department of Civil Engineering Table of Contents List of Figures ................................................................................................................................. 1 Abstract ........................................................................................................................................... 3 1 Introduction ............................................................................................................................. 4 2 Data Sources ........................................................................................................................... 6 2.1 Radar Backscatter from QuikSCAT ................................................................................ -
Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique
sensors Article Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique Bingyi Li 1, Hao Shi 1,2,* ID , Liang Chen 1,*, Wenyue Yu 1, Chen Yang 1 ID , Yizhuang Xie 1, Mingming Bian 3, Qingjun Zhang 3 and Long Pang 4 1 Beijing Key Laboratory of Embedded Real-Time Information Processing Technology, Beijing Institute of Technology, Beijing 100081, China; [email protected] (B.L.); [email protected] (W.Y.); [email protected] (C.Y.); [email protected] (Y.X.) 2 Department of Electronic Engineering, Tsinghua University, Beijing 100084, China 3 Beijing Institute of Spacecraft System Engineering, Beijing 100094, China; [email protected] (M.B.); [email protected] (Q.Z.) 4 School of Information Engineering, Communication University of China, Beijing 100024, China; [email protected] * Correspondence: [email protected] (H.S.); [email protected] (L.C.); Tel.: +86-186-1166-1399 (H.S.) Received: 28 December 2017; Accepted: 5 February 2018; Published: 28 February 2018 Abstract: With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. -
Sea Surface Wind Retrievals from SIR-C/X-SAR Data: a Revisit
Remote Sens. 2015, 7, 3548-3564; doi:10.3390/rs70403548 OPEN ACCESS remote sensing ISSN 2072-4292 www.mdpi.com/journal/remotesensing Article Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit Yongzheng Ren 1, Xiao-Ming Li 1,* and Guoqing Zhou 2 1 Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; E-Mail: [email protected] 2 Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel./Fax: +86-10-8217-8168. Academic Editors: Richard Gloaguen and Prasad S. Thenkabail Received: 22 November 2014 / Accepted: 17 March 2015 / Published: 26 March 2015 Abstract: The Geophysical Model Function (GMF) XMOD1 provides a linear algorithm for sea surface wind field retrievals for the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR). However, the relationship between the normalized radar cross section (NRCS) and the sea surface wind speed, wind direction and incidence angles is non-linear. Therefore, in this paper, XMOD1 is revisited using the full dataset of X-SAR acquired over the ocean. We analyze the detailed relationship between the X-SAR NRCS, incidence angle and sea surface wind speed. Based on the C-band GMF CMOD_IFR2, an updated empirical retrieval model of the sea surface wind field called SIRX-MOD is derived. In situ buoy measurements and the scatterometer data of ERS-1/SCAT are used to validate the retrieved sea surface wind speeds from the X-SAR data with SIRX-MOD, which respectively yield biases of 0.13 m/s and 0.16 m/s and root mean square (RMS) errors of 1.83 m/s and 1.63 m/s.