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Andreas Richter Institute of Environmental Physics University of Bremen tel. ++49 421 218 4474

Satellite observations of the atmosphere and the ocean surface Heraeus Summer School “Physics of the Environment”. Andreas Richter Institute of Environmental Physics University of Bremen tel. ++49 421 218 4474 e-mail: richter@iup.physik.uni-bremen.de

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Andreas Richter Institute of Environmental Physics University of Bremen tel. ++49 421 218 4474

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  1. Satellite observations of the atmosphere and the ocean surface Heraeus Summer School “Physics of the Environment” Andreas Richter Institute of Environmental Physics University of Bremen tel. ++49 421 218 4474 e-mail: richter@iup.physik.uni-bremen.de http://www.iup.physik.uni-bremen.de/doas

  2. Lecture Contents • What is Remote Sensing? • Which Quantities can be Measured? • What are the Underlying Physical Principles? • Examples: • Tropospheric Aerosols • Stratospheric Ozone • Tropospheric NO2 • Stratospheric Aerosols • Temperature Profiles • Wind Speed and Direction • Sea Surface Temperature • Sea Ice • Summary A. Richter, Heraeus-Summerschool, 3.9.2005

  3. What is Remote Sensing? • “Remote sensing is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation“ (Lillesand and Kiefer 1987) • “The art of dividing up the world into little multi-coloured squares and then playing computer games with them to release unbelievable potential that's always just out of reach.” (Jon Huntington, Commonwealth Scientific and Industrial Research Organisation Exploration, Geoscience, Australia) A. Richter, Heraeus-Summerschool, 3.9.2005

  4. The Eye as a Remote Sensing Instrument • eye: remote sensing instrument in the visible wavelength region (350 - 750 nm) • signal processing in the eye and in the brain • colour (RGB) and relative intensity are used to identify surface types • large data base and neuronal network used to derive object properties A. Richter, Heraeus-Summerschool, 3.9.2005

  5. The Eye as a Remote Sensing Instrument • eyes are scanning the environment with up to 60 frames per second • 170° field of view, 30° focus A. Richter, Heraeus-Summerschool, 3.9.2005

  6. The Eye as a Remote Sensing Instrument !!! • stereographic view, image processing, and a large data base enables detection of size, distance, and movement A. Richter, Heraeus-Summerschool, 3.9.2005

  7. The Eye as a Remote Sensing Instrument • passive remote sensing instrument, relies on (sun) light scattered from the object • no sensitivity to thermal emission of objects ? 8-14 microns image of a cat A. Richter, Heraeus-Summerschool, 3.9.2005

  8. The Eye as a Remote Sensing Instrument • active remote sensing by use of artificial light sources ? A. Richter, Heraeus-Summerschool, 3.9.2005

  9. Why should we use Remote Sensing? • not all measurement locations are accessible (atmosphere, ice, ocean) • remote sensing facilitates creation of long time series and extended measurement areas • for many phenomena, global measurements are needed • remote sensing measurements usually can be automated • often, several parameters can be measured at the same time • on a per measurement basis, remote sensing measurements usually are less expensive than in-situ measurements A. Richter, Heraeus-Summerschool, 3.9.2005

  10. Why NOT to use Remote Sensing: • remote sensing measurements are always indirect measurements • the electromagnetic signal is often affected by more things than just the quantity to be measured • usually, additional assumptions and models are needed for the interpretation of the measurements • usually, the measurement area / volume is relatively large • validation of remote sensing measurements is a major task and often not possible in a strict sense • estimation of the errors of a remote sensing measurement often is difficult A. Richter, Heraeus-Summerschool, 3.9.2005

  11. Schematic of Remote Sensing Observation Validation Changed Radiation Radiation Sensor Object Measurement A priori information Data Analysis Final Result Forward Model A. Richter, Heraeus-Summerschool, 3.9.2005

  12. Classification of Remote Sensing Techniques • active / passive • platform • wavelength range • spectral resolution • low / medium / high • spatial resolution • low / high • detection technique • absorption, emission or extinction spectroscopy • spectral reflectance A. Richter, Heraeus-Summerschool, 3.9.2005

  13. Active vs. Passive Remote Sensing • Active Remote Sensing: • Artificial source of radiation, the reflected or scattered signal is analysed: • sound: SONAR • radio waves: RADAR (RAdio Detection And Ranging) • laser light: LIDAR (LIght Detection And Ranging) • white light: long path DOAS (Differential Optical Absorption Spectroscopy) • Passive Remote Sensing: • Natural sources of radiation, the attenuated, reflected, scattered, or emitted radiation is analysed: • solar light • lunar light • stellar light • thermal emission A. Richter, Heraeus-Summerschool, 3.9.2005

  14. Remote Sensing Platforms • ground-based measurements • continuous, high accuracy, easy accessibility • local measurement • air-borne measurements (up to 15 km) • fast moving, long distance • expensive, sporadic • sonde / balloon measurements (up to 30 km) • high altitude • logistically difficult, often expensive • rocket measurements (up to 80 km) • very high altitude • expensive, sporadic • Space Shuttle / Space Station measurements • global coverage, limited time coverage, good accessibility • satellite measurements • global coverage • poor accessibility, expensive A. Richter, Heraeus-Summerschool, 3.9.2005

  15. Wavelength Ranges in Remote Sensing • UV: some absorptions + profile information • aerosols • vis: surface information (vegetation) • some absorptions • aerosol information • IR: temperature information • cloud information • water / ice distinction • many absorptions / emissions • + profile information • MW: no problems with clouds • ice / water contrast • surfaces • some emissions + profile information A. Richter, Heraeus-Summerschool, 3.9.2005

  16. Which Quantities are Measured? • absolute intensities in dedicated wavelength intervals • intensities relative to the intensity of a reference source • ratios of intensities at different wavelengths • variations of intensities • degree of polarisation • phase and delay of signal A. Richter, Heraeus-Summerschool, 3.9.2005

  17. Which Quantities can be Determined? Surface height albedo vegetation type surface (water) temperature fires surface roughness wind speed water turbidity / chlorophyll concentrations ice cover ice type Meteorology pressure temperature cloud cover cloud top height cloud type lightning frequency Chemical constitution of the atmosphere aerosol burden aerosol type trace species A. Richter, Heraeus-Summerschool, 3.9.2005

  18. The Electromagnetic Spectrum • nearly all energy on Earth is supplied by the sun through radiation • wavelengths from many meters (radio waves) to nm (X-ray) • small wavelength = high energy • radiation interacts with atmosphere and surface • absorption (heating, shielding) • excitation (energy input, chemical reactions) • re-emission (energy balance) A. Richter, Heraeus-Summerschool, 3.9.2005

  19. Radiative Transfer in the Atmosphere • Contributions: • Direct Solar Ray • Reflection on the Surface • Reflection from Clouds • Scattering in the Atmosphere • Rayleigh Scattering • Mie Scattering • Raman Scattering • Absorption in the Atmosphere • Emission in the Atmosphere • Emission from the Surface • Emission from Clouds A. Richter, Heraeus-Summerschool, 3.9.2005

  20. Radiative Transfer in the Atmosphere Emission from a cloud Scattering from a cloud Transmission through a cloud Cloud Scattering within a cloud Scattering / reflection oh a cloud Transmission through a cloud Emission from the ground Scattering / Reflection on the ground Absorption on the ground Atmosphere Absorption Scattering Emission Aerosol / Molecules A. Richter, Heraeus-Summerschool, 3.9.2005

  21. Scattering in the Atmosphere • Depending on the ratio of the size of the scattering particle (r) to the wavelength () of the radiation: • Mie parameter = 2 r / , • different regimes of atmospheric scattering can be distinguished. => different wavelengths probe different parts of the atmosphere / surface A. Richter, Heraeus-Summerschool, 3.9.2005

  22. What is the Optimal Instrument? • A compromise must be found to get the optimum amount of information out of the limited number of photons available under the given boundary conditions: • instrument size and price • satellite orbit • measurement quantity • data rate • measurement error spatial coverage spatial resolution time resolution vertical resolution time coverage spectral resolution spectral coverage A. Richter, Heraeus-Summerschool, 3.9.2005

  23. Satellite Orbits • (Near) Polar Orbit: • orbits cross close to the pole • global measurements are possible • low earth orbit LEO (several 100 km) • ascending and descending branch • special case: sun-synchronous orbit: • overpass over given latitude always at the same local time, providing similar illumination • for sun-synchronous orbits: day and night branches • Geostationary Orbit: • satellite has fixed position relative to the Earth • parallel measurements in a limited area from low to middle latitudes • 36 000 km flight altitude, equatorial orbit http://www2.jpl.nasa.gov/basics/bsf5-1.htm http://www.ccrs.nrcan.gc.ca/ccrs/learn/tutorials/fundam/chapter2/chapter2_2_e.html A. Richter, Heraeus-Summerschool, 3.9.2005

  24. How can Vertical Information be Derived? • In many atmospheric application, vertical profiles of quantities are needed. • Approaches: • Vertical Scanningsequential of parallel measurements at different altitudes=> e.g. SCIAMACHY limb profiles • Pressure / Temperature dependence of signal (e.g. line shape)inversion of signal using a priori information on e.g. vertical p-profile=> e.g. microwave sounding • Saturation Effects at different wavelengths (frequencies)using spectral regions with different penetration depths=> e.g. SBUV ozone profile measurements • Time Resolved measurementsusing pulsed signals and photon flight time information=> e.g. LIDAR • Combination of different types of measurements, instruments or models=> e.g. GOME tropospheric NO2 measurements A. Richter, Heraeus-Summerschool, 3.9.2005

  25. How can Vertical Information be Derived? • In many atmospheric application, vertical profiles of quantities are needed. • Approaches: • Vertical Scanningsequential of parallel measurements at different altitudes • Nadir: observation of scattered and reflected light, total column determination (and O3 profile), good spatial resolution, global coverage, good SNR • Limb: observation of scattered light, stratospheric and upper atmosphere profiles, poor spatial resolution, near global coverage, SNR decreases with altitude • Occultation: direct observation of sun or moon at horizon, stratospheric profiles, poor spatial resolution, limited coverage (close to terminator), high SNR but low UV sensitivity • Limb Nadir Matching: combination of nadir and limb measurements to estimate the tropospheric column of a trace gas http://www.sciamachy.de A. Richter, Heraeus-Summerschool, 3.9.2005

  26. How can Vertical Information be Derived? low p high p T-profile p-profile Measured Spectrum trace gas profile • In many atmospheric application, vertical profiles of quantities are needed. • Approaches: • Pressure / Temperature dependence of signal (e.g. line shape) pressure broadening: inversion http://www.ram.uni-bremen.de/index_ram.html A. Richter, Heraeus-Summerschool, 3.9.2005

  27. How can Vertical Information be Derived? 331 nm 297 nm 306 nm • In many atmospheric application, vertical profiles of quantities are needed. • Approaches: • Saturation Effects at different wavelengths (frequencies)Example: ozone profiling in the UV (e.g. SBUV, GOME)Ozone absorption is increasing by orders of magnitude over 50 nm in the UV, and virtually no photons reach the surface below 300 nm. By measuring ozone at different wavelengths, different sub-columns are determined => profile A. Richter, Heraeus-Summerschool, 3.9.2005

  28. How can the desired signal be isolated? • In most measurements, several effects on the signal interfere and need to be corrected. • Example: retrieval of NO2 by UV/vis absorption spectroscopy of scattered sun light • NO2 absorption • absorption by other species (O3, O4, H2O, ...)=> use of measurements at many wavelengths and characteristic absorption spectrum for correction • colour of the surface (e.g. ocean colour)=> use of measurements at many wavelengths and characteristic absorption spectrum for correction • scattering by aerosols • => fit of broad band contribution • elastic scattering by air molecules=> fit of broad band contribution • inelastic scattering by air molecules • => explicit correction by modelling the effect • => in many cases, measurements at several wavelengths / frequencies help A. Richter, Heraeus-Summerschool, 3.9.2005

  29. Validation of Remote Sensing Measurements • Remote Sensing measurements are indirect measurements, and need validation! • The perfect validation measurements should • measure the same quantity • integrate over the same volume • measure at the same time • use an independent technique • have higher accuracy and precision than the measurement to be validated • cover a large range of geophysical conditions • have no location bias such as measurements • only over land, • only during clear weather or • mostly in the Northern Hemisphere • not be too expensive • => such measurements do usually not exist! A. Richter, Heraeus-Summerschool, 3.9.2005

  30. Problems for Validation • Example: Stratospheric NO2 measurements from SCIAMACHY: • Amount of data: SCIAMACHY provides about 150 000 NO2 measurements per day or more than 50 000 000 measurements per year. To validate even a small part of these data necessitates a large number of validation measurements • Global coverage: hardly any validation measurements are truly global in coverage but usually biased over land in NH mid-latitudes • Averaging volume: even a “small” SCIAMACHY ground pixel is 30 x 60 km2 large and at high sun vertically integrated over the whole atmosphere. Sampling this volume at 3 km resolution horizontally and vertically (up to 20 km) would take many hours in an aircraft. • Inhomogeneity in time and space: many validation measurements do not coincide exactly in time and space with the remote sensing measurement. Horizontal variability as well as changes over time often are the largest uncertainty in validation • Errors of validation measurements: validation measurements often have themselves relatively large random and systematic errors, in particular if they are remote sensing measurements (example: neglect of temperature dependence of ozone cross-section in Brewer measurements, interference by PAN and other compounds with in-situ NO2 measurements, pump rate problems at high altitudes in ozone-sonde measurements, ...) A. Richter, Heraeus-Summerschool, 3.9.2005

  31. Validation Example • Example: • Validation of SCIAMACHY NO2 total columns with ground-based DOAS zenith-sky measurements • Results: • validation at several stations (latitudes) • validation of complete seasonal cycle • comparable measurement volume • good agreement • Problems: • ground-based measurements AM / PM twilight, SCIAMACHY at 10:00 LT • zenith-sky measurements not sensitive to tropospheric pollution • zenith-sky measurement is also remote sensing measurement, not truly independent technique A. Richter, Heraeus-Summerschool, 3.9.2005

  32. LIDAR Measurements of tropospheric aerosols • Target Quantity: Tropospheric aerosol concentrations • Measurement Quantity: Backscatter ratio at 532 nm and time lag • Instrument type: LIDAR • Instrument: LITE on Space Shuttle, September 1994 A. Richter, Heraeus-Summerschool, 3.9.2005

  33. LIDAR (LIght Detection And Ranging) • Idea: • Use of an active system that emits light pulses and measures the intensity of the backscattered light (from air molecules, aerosols, thin clouds) as a function of time (optical Radar) • Instrument: • a strong laser with short pulses • possibly several wavelengths emitted • a large telescope to collect the weak signal • Measurement quantity: • time lag gives altitude information • signal intensity gives information on backscattering at given altitude and extinction along the light path • measurements at different wavelengths provide information on absorbers and aerosol types • polarisation measurements provide information on phase of scatterers • => Very good vertical resolution can be achieved! A. Richter, Heraeus-Summerschool, 3.9.2005

  34. Lidar In-space Technology Experiment (LITE) • Instrument: • flashlamp-pumped Nd:YAG laser • 1064 nm, 532 nm, and 355 nm • 1-meter diameter lightweight telescope • PMT for 355 nm and 532 nm avalanche photodiode (APD) for 1064 nm • Mission Aims: • test and demonstrate lidar measurements from space • collect measurements on • clouds • aerosols (stratospheric & tropospheric) • surface reflectance • Operation: • on Discovery in September 1994 as part of the STS-64 mission • 53 hours operation http://www-lite.larc.nasa.gov/index.html A. Richter, Heraeus-Summerschool, 3.9.2005

  35. LITE: Example of Aerosol Measurements • 5 minutes of LITE data over the Sahara • low maritime aerosol layer • high complex aerosol layer over Sahara • Atlas Mountains separate two regimes • clouds close to the ITCZ Clouds (ITCZ) Atlas mountains complex aerosol layer maritime aerosol layer http://www-lite.larc.nasa.gov/index.html A. Richter, Heraeus-Summerschool, 3.9.2005

  36. UV absorption measurements of stratospheric O3 • Target Quantity: Stratospheric Ozone columns • Measurement Quantity: Differential absorption of backscattered UV radiation • Instrument type: low resolution nadir viewing UV spectrometer • Instrument: TOMS (Total Ozone Mapping Spectrometer ) A. Richter, Heraeus-Summerschool, 3.9.2005

  37. Total Ozone Mapping Spectrometer TOMS • Idea: • global measurements of ozone columns using differential measurements in the UV • good spatial resolution through fast measurements • additional products (SO2, aerosols) by clever selection of wavelengths • continuous measurements, long time series, high consistency, little changes in instrumentation => trends • The TOMS programme: • Satellite Period Orbit • Nibus 7 Oct 78 – May 93 955 km • Meteor3 Aug 91 – Dec 94 • Adeos Aug 96 – Jun 97 830 km • Earth Probe (EP) Jul 96 – Dec 97 500 km • Dec 97 – today 740 km • Wavelengths: • 380.0 339.7 331.0 317.4 312.3 308.6 nm http://jwocky.gsfc.nasa.gov/ A. Richter, Heraeus-Summerschool, 3.9.2005

  38. TOMS: Observation of the Ozone Hole • The Ozone Hole • forms in the Antarctic winter / spring • formation of Polar Stratospheric Clouds PSC in the extremely cold vortex • heterogeneous activation of chlorine reservoirs on the cold PSC surfaces • rapid ozone destruction by ClO and BrO as the sun rises • end of ozone destruction after warming when chlorine is transformed back to its reservoirs HCl and ClONO2 and vortex air mixes with ozone rich air http://jwocky.gsfc.nasa.gov/ A. Richter, Heraeus-Summerschool, 3.9.2005

  39. UV/vis absorption measurements of tropospheric NO2 • Target Quantity: Tropospheric Nitrogen Dioxide columns • Measurement Quantity: Differential absorption of backscattered radiation • Instrument type: medium resolution nadir viewing UV/vis spectrometer • Instrument: GOME (Global Ozone Monitoring Experiment) on ERS-2 A. Richter, Heraeus-Summerschool, 3.9.2005

  40. Global Ozone Monitoring Experiment (GOME) • Idea: • simultaneous measurements from the UV to the near IR • good spectral resolution (0.2 – 0.4 nm) • use of DOAS to retrieve columns of several species (O3, NO2, OClO, BrO, HCHO, SO2, H2O) • use of UV wavelengths to retrieve ozone profiles • global coverage • Launch: April 1995 on ERS-2 (sun synchronous) • GOME successor instruments: • Instrument Satellite Launch • SCIAMACHY ENVISAT March 2002 • OMI EOS-Aura Spring 2004 • GOME-2 Metop-1 .. Metop-3 2006 – 2020 http://www.iup.physik.uni-bremen.de/gome/ A. Richter, Heraeus-Summerschool, 3.9.2005

  41. GOME: tropospheric NO2 excess • NOx plays a key role in the formation of photochemical ozone smog • sources of NOx are both anthropogenic (combustion of fossil fuels, biomass burning) and natural (fires, soil emissions, lightning) • NOx emissions are changing as result of • changes in land use • improvements in emission control • economic development (e.g. China) • GOME data provided the first global maps of tropospheric NO2 • Data analysis: • cloud screening • DOAS retrieval of total slant columns • subtraction of clean Pacific sector to derive tropospheric slant columns • application of tropospheric airmass factor to compute tropospheric vertical column A. Richter, Heraeus-Summerschool, 3.9.2005

  42. UV/vis Measurements of Stratospheric Aerosols • Target Quantity: stratospheric aerosol concentrations • Measurement Quantity: backscattered radiation • Instrument type: solar occultation viewing UV/vis spectrometer • Instrument: SAGE-2 (Stratospheric Aerosol and Gas Experiment) A. Richter, Heraeus-Summerschool, 3.9.2005

  43. Stratospheric Aerosol and Gas Experiment (SAGE) • Measurement Geometry: solar occultation • Instrument: grating spectrometer with Si-detectors • Spectral coverage: 7 wavelengths between 385 – 1020 nm: • 1020, 940, 600, 525, 453, 448 und 385 nm • Data analysis: onion peeling • Measurement targets: vertical profiles of O3, NO2, H2O and aerosol extinction (at 385, 453, 525 and 1020 nm) • Measurement range: stratosphere, at low stratospheric aerosol loading and outside the tropics also the upper troposphere • The SAGE programme: • SAM II 1978 • SAGE I 1979-1981 • SAGE II 1984 - today • SAGE III 2001 - today • 280 – 1030 nm, 1-2 nm spectral resolution CCD detector, lunar + solar occultation http://www-sage3.larc.nasa.gov/ A. Richter, Heraeus-Summerschool, 3.9.2005

  44. SAGE: Stratospheric Aerosols • Stratospheric aerosols are dominated by volcanic input (H2SO4). • Large eruptions inject ash and SO2 directly into the stratosphere. • Transport towards poles within one year. • Exponential decay over many years • 1985: Nevado del Ruiz, Columbia • 1990: Kelut, Indonesia • 1991: Mt. Pinatubo http://aerosols.larc.nasa.gov/optical_depth.html A. Richter, Heraeus-Summerschool, 3.9.2005

  45. Radio Occultation Measurements of Temperature Profiles • Target Quantity: temperature profiles • Measurement Quantity: excess phase of GPS signals • Instrument type: GPS occultation • Instrument: CHAMP (CHAllenging Minisatellite Payload) A. Richter, Heraeus-Summerschool, 3.9.2005

  46. CHAMP radio occultation • Principle: • GPS receiver observes GPS satellite during occultation • high accuracy time information provides excess phase • this is related to the bending angle profile α • which depends on refractive index n • which is a function of p, T and humidity • good vertical resolution • large number of measurements • good sampling • assumptions on 2 of the three variables necessary • problems with critical layers http://www.copernicus.org/EGU/acp/acpd/4/7837/acpd-4-7837_p.pdf A. Richter, Heraeus-Summerschool, 3.9.2005

  47. QBO Temperature Anomalies from CHAMP Radio Occultation • downward propagation of temperature anomalies in the tropical stratosphere • QBO (Quasi Biannual Oscillation) signal • maximum amplitude of +/- 4.5 K • impact on stratospheric ozone columns http://www.copernicus.org/EGU/acp/acpd/4/7837/acpd-4-7837_p.pdf A. Richter, Heraeus-Summerschool, 3.9.2005

  48. Microwave Measurements of Wind Speed and Direction • Target Quantity: wind speed and direction • Measurement Quantity: reflected microwave intensity and polarisation • Instrument type: active microwave • Instrument: Synthetic Aperture Radar (SAR). A. Richter, Heraeus-Summerschool, 3.9.2005

  49. How to derive wind speed from Radar signals • Idea:Bragg-like resonance of cm-size ocean waves with Radar signals depends monotonically on surface wind speed • => wind speed over oceans can be determined from scatterometer measurements if wind direction is known from model or other measurements Validation: Relationship between radar backscatter and surface wind speed for C-band (5.3 Hz),vertical polarization at 45° off nadir angle. http://fermi.jhuapl.edu/sar/stormwatch/user_guide/bealguide_072_V3.pdf A. Richter, Heraeus-Summerschool, 3.9.2005

  50. Wind Speed from Radarsat SAR Polar low imaged by 430 km wide swath mode of Radarsat SAR, before application of wind algorithm, 0602 GMT 05 Feb 1998. Polar low of 05 Feb 1998 after application of wind algorithm, embedded in NOGAPS model wind field (arrows). http://fermi.jhuapl.edu/sar/stormwatch/user_guide/bealguide_072_V3.pdf A. Richter, Heraeus-Summerschool, 3.9.2005

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