Beginner's Guide to GOES-R Series Data
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ISEE 1 and 2 OBSERVATION of the SPATIAL STRUCTURE of a COMPRESSIONAL Pc5 WAVE
GEOPHYSICALRESEARCH LETTERS, VOL. 12, NO. 9, PAGES 613-616, SEPTEMBER1985 ISEE 1 AND 2 OBSERVATION OF THE SPATIAL STRUCTURE OF A COMPRESSIONAL Pc5 WAVE Ka zue Takahashi University of California, Los Alamos National Laboratory ChristopherT. Russell1 Institute of Geophysics and Planetary Physics, University of California Los Angeles Roger R. Anderson Department of Physics and Astronomy, The University of Iowa Abstract. A compressional Pc5 wave was [Russell, 1978]. The da•taare presented in a observed on an ISEE 1 and 2 outbound path on coordinate system where H (9orth) is antiparallel September 28, 1981 at L = 5.6-7.3 near the •to t•he ge•omagneticdipole, D is eastward and magnetic equator at ~10 hr local time during the V = D x H is approximately radially outward. Note recovery phase of a geomagnetic storm. The wave that only deviations from the Olson-Pfizer model propagated westward with a large azimuthal wave field [Olson and Pfttzer, 1977] are plotted. The number of ~30 and exhibited in-phase oscillations total component (not plotted) is essentially the of plasma density and magnetic field magnitude. same as the H component. During this event, component-dependent variations The compressional Pc5 wave was present between in phase and amplitude were observed for the 0400 and 0510 UT. During this interval, the L magnetic field oscillations. The radial and value, local time, and magnetic latitude of the compressional components had a constant phase and satellite changed from (5.6, 0930, 8.2 ø) to (7.3, their amplitude was finite. In contrast, the 1010, 1.9ø). Throughout the wave event the V azimuthal component changed its phase by 180ø and component oscillated without any phase variation its amplitude became zero during the middle of the and had a period of ~400 s. -
Abstract Observation Overview Nustar HXR Imaging Microflare
Imaging and Spectroscopy of Six NuSTAR MicroFlares SH11D-2898 Contact: J. Duncan1, L. Glesener1, I. Hannah2, D. Smith3, B. Grefenstette4 (1Univ, of Minnesota; 2Univ. of Glasgow; 3UC Santa Cruz; 4California Institute of Technology) [email protected] Abstract MicroFlare Time Evolution Hard X-ray (HXR) emission in solar flares originates from regions of high temperature plasma, as well as from non-thermal particle populations [1]. Both of these sources of HXR radiation make solar observation in this band important for study of • NuSTAR observed 6 MicroFlares during this observation. Time evolution is shown in both raw and normalized NuSTAR flare energetics. NuSTAR is the first HXR telescope with direct focusing optics, giving it a dramatic increase in sensitivity countsLivetime acrosscorrection several applied energy ranges for each flare. Counts are livetime-corrected (NuSTAR livetime ranged from 1-14%). Livetime correction applied over previous indirect imaging methods. Here we present NuSTAR observation of six microflares from one solar active Livetime correction applied 5 5 6 5×10 4×10 2.0 10 5 × 4×10 5 region during a period of several hours on May 29th, 2018. In conjunction with simultaneous data from SDO/AIA, data 3×10 5 2-4 keV 2-4 keV 6 3×10 1.5 10 Orbit1, Flare B 4-6 keV 2×105 4-6 keV × 5 counts 2 10 2-4 keV × Orbit1, Flare A 6-8 keV counts Orbit1, Flare C 6-8 keV from this observation has been used to create flare-time images showing the spatial extent of HXR emission. Additionally, 5 5 1 10 1×10 8-10 keV × 8-10 keV 6 4-6 keV 1.0×10 (Left) Estimated GOES A5 flare, with 0 0 1.2 1.2 16:07 16:08 16:09 16:10 16:11 16:46 16:48 16:50 16:52 16:54 NuSTAR lightcurves show time evolution in four different HXR energy ranges over the course of each flare. -
Build a Spacecraft Activity
UAMN Virtual Family Day: Amazing Earth Build a Spacecraft SMAP satellite. Image: NASA. Discover how scientists study Earth from above! Scientists use satellites and spacecraft to study the Earth from outer space. They take pictures of Earth's surface and measure cloud cover, sea levels, glacier movements, and more. Materials Needed: Paper, pencil, craft materials (small recycled boxes, cardboard pieces, paperclips, toothpicks, popsicle sticks, straws, cotton balls, yarn, etc. You can use whatever supplies you have!), fastening materials (glue, tape, rubber bands, string, etc.) Instructions: Step 1: Decide what you want your spacecraft to study. Will it take pictures of clouds? Track forest fires? Measure rainfall? Be creative! Step 2: Design your spacecraft. Draw a picture of what your spacecraft will look like. It will need these parts: Container: To hold everything together. Power Source: To create electricity; solar panels, batteries, etc. Scientific Instruments: This is the why you launched your satellite in the first place! Instruments could include cameras, particle collectors, or magnometers. Communication Device: To relay information back to Earth. Image: NASA SpacePlace. Orientation Finder: A sun or star tracker to show where the spacecraft is pointed. Step 3: Build your spacecraft! Use any craft materials you have available. Let your imagination go wild. Step 4: Your spacecraft will need to survive launching into orbit. Test your spacecraft by gently shaking or spinning it. How well did it hold together? Adjust your design and try again! Model spacecraft examples. Courtesy NASA SpacePlace. Activity adapted from NASA SpacePlace: spaceplace.nasa.gov/build-a-spacecraft/en/ UAMN Virtual Early Explorers: Amazing Earth Studying Earth From Above NASA is best known for exploring outer space, but it also conducts many missions to investigate Earth from above. -
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. -
A New Data Model, Programming Interface, and Format Using HDF5
NetCDF-4: A New Data Model, Programming Interface, and Format Using HDF5 Russ Rew, Ed Hartnett, John Caron UCAR Unidata Program Center Mike Folk, Robert McGrath, Quincey Kozial NCSA and The HDF Group, Inc. Final Project Review, August 9, 2005 THG, Inc. 1 Motivation: Why is this area of work important? While the commercial world has standardized on the relational data model and SQL, no single standard or tool has critical mass in the scientific community. There are many parallel and competing efforts to build these tool suites – at least one per discipline. Data interchange outside each group is problematic. In the next decade, as data interchange among scientific disciplines becomes increasingly important, a common HDF-like format and package for all the sciences will likely emerge. Jim Gray, Distinguished “Scientific Data Management in the Coming Decade,” Jim Gray, David Engineer at T. Liu, Maria A. Nieto-Santisteban, Alexander S. Szalay, Gerd Heber, Microsoft, David DeWitt, Cyberinfrastructure Technology Watch Quarterly, 1998 Turing Award Volume 1, Number 2, February 2005 winner 2 Preservation of scientific data … the ephemeral nature of both data formats and storage media threatens our very ability to maintain scientific, legal, and cultural continuity, not on the scale of centuries, but considering the unrelenting pace of technological change, from one decade to the next. … And that's true not just for the obvious items like images, documents, and audio files, but also for scientific images, … and MacKenzie Smith, simulations. In the scientific research community, Associate Director standards are emerging here and there—HDF for Technology at (Hierarchical Data Format), NetCDF (network the MIT Libraries, Common Data Form), FITS (Flexible Image Project director at Transport System)—but much work remains to be MIT for DSpace, a groundbreaking done to define a common cyberinfrastructure. -
Nustar and XMM-Newton Observations of the Hard X-Ray Spectrum of Centaurus A
Downloaded from orbit.dtu.dk on: Sep 27, 2021 NuSTAR and XMM-Newton Observations of the Hard X-Ray Spectrum of Centaurus A Fürst, F.; Müller, C.; Madsen, K. K.; Lanz, L.; Rivers, E.; Brightman, M.; Arevalo, P.; Balokovi, M.; Beuchert, T.; Boggs, S. E. Total number of authors: 31 Published in: The Astrophysical Journal Link to article, DOI: 10.3847/0004-637X/819/2/150 Publication date: 2016 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Fürst, F., Müller, C., Madsen, K. K., Lanz, L., Rivers, E., Brightman, M., Arevalo, P., Balokovi, M., Beuchert, T., Boggs, S. E., Christensen, F. E., Craig, W. W., Dauser, T., Farrah, D., Graefe, C., Hailey, C. J., Harrison, F. A., Kadler, M., King, A., ... Zhang, W. W. (2016). NuSTAR and XMM-Newton Observations of the Hard X-Ray Spectrum of Centaurus A. The Astrophysical Journal, 819(2), [150]. https://doi.org/10.3847/0004- 637X/819/2/150 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. -
Using Netcdf and HDF in Arcgis
Using netCDF and HDF in ArcGIS Nawajish Noman Dan Zimble Kevin Sigwart Outline • NetCDF and HDF in ArcGIS • Visualization and Analysis • Sharing • Customization using Python • Demo • Future Directions Scientific Data and Esri • Direct support - NetCDF and HDF • OPeNDAP/THREDDS – a framework for scientific data networking, integrated use by our customers • Users of Esri technology • National Climate Data Center • National Weather Service • National Center for Atmospheric Research • U. S. Navy (NAVO) • Air Force Weather • USGS • Australian Navy • Australian Bur.of Met. • UK Met Office NetCDF Support in ArcGIS • ArcGIS reads/writes netCDF since version 9.2 • An array based data structure for storing multidimensional data. T • N-dimensional coordinates systems • X, Y, Z, time, and other dimensions Z Y • Variables – support for multiple variables X • Temperature, humidity, pressure, salinity, etc • Geometry – implicit or explicit • Regular grid (implicit) • Irregular grid • Points Gridded Data Regular Grid Irregular Grid Reading netCDF data in ArcGIS • NetCDF data is accessed as • Raster • Feature • Table • Direct read • Exports GIS data to netCDF CF Convention Climate and Forecast (CF) Convention http://cf-pcmdi.llnl.gov/ Initially developed for • Climate and forecast data • Atmosphere, surface and ocean model-generated data • Also for observational datasets • The CF conventions generalize and extend the COARDS (Cooperative Ocean/Atmosphere Research Data Service) convention. • CF is now the most widely used conventions for geospatial netCDF data. It has the best coordinate system handling. NetCDF and Coordinate Systems • Geographic Coordinate Systems (GCS) • X dimension units: degrees_east • Y dimension units: degrees_north • Projected Coordinate Systems (PCS) • X dimension standard_name: projection_x_coordinate • Y dimension standard_name: projection_y_coordinate • Variable has a grid_mapping attribute. -
A COMMON DATA MODEL APPROACH to NETCDF and GRIB DATA HARMONISATION Alessandro Amici, B-Open, Rome @Alexamici
A COMMON DATA MODEL APPROACH TO NETCDF AND GRIB DATA HARMONISATION Alessandro Amici, B-Open, Rome @alexamici - http://bopen.eu Workshop on developing Python frameworks for earth system sciences, 2017-11-28, ECMWF, Reading. alexamici / talks MOTIVATION: FORECAST DATA AND TOOLS ECMWF Weather forecasts, re-analyses, satellite and in- situ observations N-dimensional gridded data in GRIB Archive: Meteorological Archival and Retrieval System (MARS) A lot of tools: Metview, Magics, ecCodes... alexamici / talks MOTIVATION: CLIMATE DATA Copernicus Climate Change Service (C3S / ECMWF) Re-analyses, seasonal forecasts, climate projections, satellite and in-situ observations N-dimensional gridded data in many dialects of NetCDF and GRIB Archive: Climate Data Store (CDS) alexamici / talks HARMONISATION STRATEGIC CHOICES Metview Python Framework and CDS Toolbox projects Python 3 programming language scientic ecosystems xarray data structures NetCDF data model: variables and coordinates support for arbitrary metadata CF Conventions support on IO label-matching broadcast rules on coordinates parallelized and out-of-core computations with dask alexamici / talks ECMWF NETCDF DIALECT >>> import xarray as xr >>> ta_era5 = xr.open_dataset('ERA5-t-2016-06.nc', chunks={}).t >>> ta_era5 <xarray.DataArray 't' (time: 60, level: 3, latitude: 241, longitude: 480)> dask.array<open_dataset-..., shape=(60, 3, 241, 480), dtype=float64, chunksize=(60, 3, Coordinates: * longitude (longitude) float32 0.0 0.75 1.5 2.25 3.0 3.75 4.5 5.25 6.0 ... * latitude (latitude) float32 90.0 89.25 88.5 87.75 87.0 86.25 85.5 ... * level (level) int32 250 500 850 * time (time) datetime64[ns] 2017-06-01 2017-06-01T12:00:00 .. -
ASTRONAUTICS and AERONAUTICS, 1977 a Chronology
NASA SP--4022 ASTRONAUTICS AND AERONAUTICS, 1977 A Chronology Eleanor H. Ritchie ' The NASA History Series Scientific and Technical Information Branch 1986 National Aeronautics and Space Administration Washington, DC Four spacecraft launched by NASA in 1977: left to right, top, ESA’s Geos 1 and NASA’s Heao 1; bottom, ESA’s Isee 2 on NASA’s Isee 1, and Italy’s Wo. (NASA 77-H-157,77-H-56, 77-H-642, 77-H-484) Contents Preface ...................................................... v January ..................................................... 1 February .................................................... 21 March ...................................................... 47 April ....................................................... 61 May ........................................................ 77 June ...................................................... 101 July ....................................................... 127 August .................................................... 143 September ................................................. 165 October ................................................... 185 November ................................................. 201 December .................................................. 217 Appendixes A . Satellites, Space Probes, and Manned Space Flights, 1977 .......237 B .Major NASA Launches, 1977 ............................... 261 C. Manned Space Flights, 1977 ................................ 265 D . NASA Sounding Rocket Launches, 1977 ..................... 267 E . Abbreviations of References -
MATLAB Tutorial - Input and Output (I/O)
MATLAB Tutorial - Input and Output (I/O) Mathieu Dever NOTE: at any point, typing help functionname in the Command window will give you a description and examples for the specified function 1 Importing data There are many different ways to import data into MATLAB, mostly depending on the format of the datafile. Below are a few tips on how to import the most common data formats into MATLAB. • MATLAB format (*.mat files) This is the easiest to import, as it is already in MATLAB format. The function load(filename) will do the trick. • ASCII format (*.txt, *.csv, etc.) An easy strategy is to use MATLAB's GUI for data import. To do that, right-click on the datafile in the "Current Folder" window in MATLAB and select "Import data ...". The GUI gives you a chance to select the appropriate delimiter (space, tab, comma, etc.), the range of data you want to extract, how to deal with missing values, etc. Once you selected the appropriate options, you can either import the data, or you can generate a script that imports the data. This is very useful in showing the low-level code that takes care of reading the data. You will notice that the textscan is the key function that reads the data into MATLAB. Higher-level functions exist for the different datatype: csvread, xlsread, etc. As a rule of thumb, it is preferable to use lower-level function are they are "simpler" to understand (i.e., no bells and whistles). \Black-box" functions are dangerous! • NetCDF format (*.nc, *.cdf) MATLAB comes with a netcdf library that includes all the functions necessary to read netcdf files. -
Physics of the Cosmic Microwave Background Anisotropy∗
Physics of the cosmic microwave background anisotropy∗ Martin Bucher Laboratoire APC, Universit´eParis 7/CNRS B^atiment Condorcet, Case 7020 75205 Paris Cedex 13, France [email protected] and Astrophysics and Cosmology Research Unit School of Mathematics, Statistics and Computer Science University of KwaZulu-Natal Durban 4041, South Africa January 20, 2015 Abstract Observations of the cosmic microwave background (CMB), especially of its frequency spectrum and its anisotropies, both in temperature and in polarization, have played a key role in the development of modern cosmology and our understanding of the very early universe. We review the underlying physics of the CMB and how the primordial temperature and polarization anisotropies were imprinted. Possibilities for distinguish- ing competing cosmological models are emphasized. The current status of CMB ex- periments and experimental techniques with an emphasis toward future observations, particularly in polarization, is reviewed. The physics of foreground emissions, especially of polarized dust, is discussed in detail, since this area is likely to become crucial for measurements of the B modes of the CMB polarization at ever greater sensitivity. arXiv:1501.04288v1 [astro-ph.CO] 18 Jan 2015 1This article is to be published also in the book \One Hundred Years of General Relativity: From Genesis and Empirical Foundations to Gravitational Waves, Cosmology and Quantum Gravity," edited by Wei-Tou Ni (World Scientific, Singapore, 2015) as well as in Int. J. Mod. Phys. D (in press). -
GALEX: Galaxy Evolution Explorer
GALEX: Galaxy Evolution Explorer Barry F. Madore Carnegie Observatories, Pasadena CA 91101 Abstract. We review recent scientific results from the Galaxy Evolution Explorer with special emphasis on star formation in nearby resolved galaxies. INTRODUCTION The Satellite The Galaxy Evolution Explorer (GALEX) is a NASA Small Explorer class mission. It consists of a 50 cm-diameter, modified Ritchey-Chrétien telescope with four operating modes: Far-UV (FUV) and Near-UV (NUV) imaging, and FUV and NUV spectroscopy. Æ The telescope has a 3-m focal length and has Al-MgF2 coatings. The field of view is 1.2 circular. An optics wheel can position a CaF2 imaging window, a CaF2 transmission grism, or a fully opaque mask in the beam. Spectroscopic observations are obtained at multiple grism-sky dispersion angles, so as to mitigate spectral overlap effects. The FUV (1528Å: 1344-1786Å) and NUV (2271Å: 1771-2831Å) imagers can be operated one at a time or simultaneously using a dichroic beam splitter. The detector system encorporates sealed-tube microchannel-plate detectors. The FUV detector is preceded by a blue-edge filter that blocks the night-side airglow lines of OI1304, 1356, and Lyα. The NUV detector is preceded by a red blocking filter/fold mirror, which produces a sharper long-wavelength cutoff than the detector CsTe photocathode and thereby reduces both zodiacal light background and optical contamination. The peak quantum efficiency of the detector is 12% (FUV) and 8% (NUV). The detectors are linear up to a local (stellar) count-rate of 100 (FUV), 400 (NUV) cps, which corresponds to mAB 14 15.