Cloudsat and Quikscat - to Observe Clouds and Sea Surface Winds
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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. -
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. -
Cloudsat CALIPSO
www.nasa.gov andSpaceAdministration National Aeronautics & CloudSat CALIPSO Clean air is important to everyone’s health and well-being. Clean air is vital to life on Earth. An average adult breathes more than 3000 gallons of air every day. In some places, the air we breathe is polluted. Human activities such as driving cars and trucks, burning coal and oil, and manufacturing chemicals release gases and small particles known as aerosols into the atmosphere. Natural processes such as for- est fires and wind-blown desert dust also produce large amounts of aerosols, but roughly half of the to- tal aerosols worldwide results from human activities. Aerosol particles are so small they can remain sus- pended in the air for days or weeks. Smaller aerosols can be breathed into the lungs. In high enough con- centrations, pollution aerosols can threaten human health. Aerosols can also impact our environment. Aerosols reflect sunlight back to space, cooling the Earth’s surface and some types of aerosols also absorb sunlight—heating the atmosphere. Because clouds form on aerosol particles, changes in aerosols can change clouds and even precipitation. These effects can change atmospheric circulation patterns, and, over time, even the Earth’s climate. The Air We Breathe The Air We We need better information, on a global scale from satellites, on where aerosols are produced and where they go. Aerosols can be carried through the atmosphere-traveling hundreds or thousands of miles from their sources. We need this satellite infor- mation to improve daily forecasts of air quality and long-term forecasts of climate change. -
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 ................................................................................ -
Master's Thesis
2009:029 MASTER'S THESIS Collocating Satellite-Based Radar and Radiometer Measurements to Develop an Ice Water Path Retrieval Gerrit Holl Luleå University of Technology Master Thesis, Continuation Courses Space Science and Technology Department of Space Science, Kiruna 2009:029 - ISSN: 1653-0187 - ISRN: LTU-PB-EX--09/029--SE Master's Thesis Collocating satellite-based radar and radiometer measurements to develop an ice water path retrieval Gerrit Holl June 11, 2009 Approximate footprints for different sensors 4480 CloudSat MHS 4460 HIRS AMSU−A 4440 4420 4400 4380 UTM y−pos (km) 4360 4340 4320 4300 390 400 410 420 430 440 450 460 470 480 UTM x−pos (km) Abstract Remote sensing satellites can roughly be divided in operational satellites and scientific satellites. Generally speaking, operational satellites have a long lifetime and often several near-identical copies, whereas scientific satellites are unique and have a more limited lifetime, but produce more advanced data. An example of a scientific satellite is the CloudSat, a NASA satellite flying in the so-called "A-Train" formation with other satellites. Examples of operational satellites are the NOAA and MetOp meteorological satellite series. CloudSat carries a 94 GHz nadir viewing radar instrument measuring pro- files of clouds. The NOAA-15 to NOAA-18 and MetOp-A satellites carry radiometers at various frequencies ranging from the infrared (3.76 µm) to around 183 GHz (≈ 1:6 mm). The full range is covered by the High Res- olution Infrared Radiation Sounder (HIRS) and the Advanced Microwave Sounding Units (AMSU-A and AMSU-B). On newer satellites, AMSU-B has been replaced by the Microwave Humidity Sounder (MHS) with nearly the same characteristics. -
Cloudsat-CALIPSO Launch
NATIONAL AERONAUTICS AND SPACE ADMINISTRATION CloudSat-CALIPSO Launch Press Kit April 2006 Media Contacts Erica Hupp Policy/Program (202) 358-1237 NASA Headquarters, Management [email protected] Washington Alan Buis CloudSat Mission (818) 354-0474 NASA Jet Propulsion Laboratory, [email protected] Pasadena, Calif. Emily Wilmsen Colorado Role - CloudSat (970) 491-2336 Colorado State University, [email protected] Fort Collins, Colo. Julie Simard Canada Role - CloudSat (450) 926-4370 Canadian Space Agency, [email protected] Saint-Hubert, Quebec, Canada Chris Rink CALIPSO Mission (757) 864-6786 NASA Langley Research Center, [email protected] Hampton, Va. Eliane Moreaux France Role - CALIPSO 011 33 5 61 27 33 44 Centre National d'Etudes [email protected] Spatiales, Toulouse, France George Diller Launch Operations (321) 867-2468 NASA Kennedy Space Center, [email protected] Fla. Contents General Release ......................................................................................................................... 3 Media Services Information ........................................................................................................ 5 Quick Facts ................................................................................................................................. 6 Mission Overview ....................................................................................................................... 7 CloudSat Satellite .................................................................................................................... -
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. -
GPM Precipitation Estimation and Validation Activities
CGMS-36, NASA-WP-02 Prepared by NASA Agenda Item: WGII/4 Discussed in Working Groups GPM Precipitation Estimation and Validation Activities Precipitation estimation and validation activities of the Global Precipitation Measurement (GPM) mission, a NASA/JAXA joint satellite effort is reported as requested in CGMS-35 Action Item 35.22. An introduction to GPM, a status of GPM estimation and validation activities, and future plans are provided. CGMS-36, NASA-WP-02 1 Introduction The center piece of NASA’s activities on precipitation estimation and validation is its role in the Global Precipitation Measurement (GPM) mission, being developed primarily by NASA and the Japan Aerospace and Exploration Agency (JAXA). GPM marks an evolution from the current effort built around uncoordinated individual satellite missions towards one coordinated, inter-calibrated satellite constellation providing uniform global precipitation products. An important component as a starting point in creating this coordinated precipitation- measuring constellation already exists, in the form of the highly successful U.S.-Japan Tropical Rainfall Measuring Mission (TRMM), in operation since 1997, which continues to provide first-generation tropical precipitation estimates used in both societal applications and scientific research. The GPM mission will serve as the cornerstone for international collaboration on satellite precipitation algorithm research, ground validation, data processing, and product dissemination. To these ends, NASA is working with the international science community to develop a consensus reference standard for cross-calibration of microwave radiometers to produce uniform global precipitation products. NASA and JAXA have devoted substantial resources through TRMM and GPM in data processing and science team support, to include the development of Level 1C prototypes for intercalibration of current radiometers using the TRMM PR and TMI as a reference. -
Cloudsat Overview
CloudSat Overview CloudSat will provide, from space, the first global survey of cloud profiles and cloud physical properties, with seasonal and geographical variations, needed to evaluate the way clouds are parameterized in global models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. CloudSat will measure the vertical structure of clouds and precipitation from space primarily through 94 GHz radar reflectivity measurements, but also by using a combination of observations from the EOS-PM Constellation of satellites (A-Train). CloudSat will fly in on-orbit formation with the Aqua and CALIPSO satellites, providing a unique, multi-satellite observing system particularly suited for studying the atmospheric processes of the hydrological cycle. 1. Science Objectives • Evaluate the representation of clouds in weather and climate prediction models. CloudSat will provide a global survey of the vertical structure of cloud systems: This vertical structure is fundamentally important for understanding how clouds affect both their local and large-scale atmospheric and radiative environments. • Evaluate the relationship between cloud liquid water and ice content and the radiative properties of clouds. CloudSat will estimate the profiles of cloud liquid water and ice water content. These are the quantities predicted by cloud-process and global-scale models alike and determine practically all important cloud properties, including precipitation and cloud optical properties. CloudSat will provide coincident profile information on the bulk cloud microphysical properties matched to cloud optical properties. Optical properties contrasted against cloud liquid water and ice contents provide a critical test of key parameterizations that enable calculation of flux profiles and radiative heating rates throughout the atmospheric column. -
U.S. Earth Observation/Environmental Satellites
U.S. Earth Observation/Environmental Satellites •NOAA Geostationary Operational Environmental Satellite System (GOESS) • NOAA Polar Operational Environmental Satellite System (POESS) •DOD Defense Meteorological Satellite Program (DMSP) •NASA Earth Observing System (EOS) Satellites John “JC” Coffey February 2012 NOAA Geostationary Operational Environmental Satellite System (GOESS) ♦ The system uses two satellites in geosynchronous orbits 19340 nm above the earth, one over the east coast of the US and one over the west coast providing overlapping continuous coverage of the US, Atlantic to the west coast of Africa, and eastern Pacific to 140 degrees west longitude ♦ Satellite instrumentation consists of an imager and sounder • The imager provides 1 channel of visible and 4 channels of infrared images with a scan rate for full earth disc of less than or equal to 26 minutes • The sounder provides temperature and moisture profiles of the atmosphere ♦ Data is continuously transmitted to ground terminals for processing and rebroadcast to primary weather service offices in the US and around the world and to the global research community 2 NOAA Polar Operational Environmental Satellite System (POESS) ♦ The system uses two satellites in sun synchronous, nearly polar orbits 470 nm above the earth. Each satellite provides global coverage every 14.1 hours. ♦ Satellite instrumentation includes an Advanced Very High Resolution Radiometer (AVHRR), a High Resolution Infrared Radiation Sounder (HIRS), Advanced Microwave Sounding Unit-A (AMSU-A) and Advanced Microwave Sounding Unit-B (AMSU-B) • AVHRR provides visible and infrared images of the Earth and its atmosphere • HIRS provides data to calculate vertical temperature profiles from the Earth’s surface to an altitude of approximately 22 nm.