B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Remote Sensing I Summer 2007 Björn-Martin Sinnhuber Room NW1 - U3215 Tel

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Lecture 1 Introduction to Remote Sensing Lecture 2 Electromagnetic Radiation Lecture 3Interaction of Radiation with Gases and Matter: Spectroscopy Lecture 4 Atmospheric Radiative Transfer Lecture 5 Retrieval Techniques / Inverse Methods Remote Sensing of the Atmosphere: Lecture 6 Passive Microwave Remote Sensing Lecture 7 Infra-Red Techniques Lecture 8 Optical (UV / Visible) Remote Sensing Lecture 9Active Remote Sensing: Radar and Lidar Remote Sensing of the Earth Surface: Lecture 10 Sea Ice Remote Sensing Lecture 11 Remote Sensing of the Ocean with Satellite Altimeters Lecture 12 Summary Contents

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Lecture 1 Introduction General Introduction Examples of Remote Sensing Applications Introduction to Satellite Orbits

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Photo taken by crew of Apollo 17 7 Dec 1972

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 from maps.google.com

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 A Note on Spatial Resolution The maximum achievable resolution with an optical system is given by with α: opening angle, D: diameter of the optical aperture, λ: wavelength. Because with x: object size and h: sensor height we get α x h (Rayleigh criterion)

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Resolution: An example Assume some typical values: h: 800 km, D: 4m (huge!), λ: 500 nm:

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 ENVISAT: Launched 1 March 2002

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 MERIS/ENVISAT

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 SeaWIFS, 26. Feb. 2000

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 MERIS/ENVISAT, Cloud Top Pressure

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Ocean colour: MERIS/ENVISAT, 443 nm

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Ocean colour: MERIS/ENVISAT, 560 nm

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Ocean colour: MERIS/ENVISAT, Chlorophyll

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Absorption windows of atmospheric constituents

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Observing the Ozone Layer Global measurements of total ozone columns Measurement type:Satellite-based passive remote sensing Instrument:Global Ozone Monitoring Experiment (GOME) / ERS-2 Measured quantity:Total ozone columns (from backscattered solar radiation) Antarctic Ozone Hole

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 The Arctic Ozone Layer Ten years of GOME observtions

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 The Electromagnetic Spectrum 100 m cm MHz 10 m cm -1 Radio 100 MHz 1 m cm -1 1 GHz 10 cm 0.1 cm GHz Microwave 1 cm 1 cm GHz 1 mm 10 cm -1 1 THz sub-mm – Far IR 0.1 mm 100 cm THz 10 μm 1000 cm -1 Thermal IR al IR 100 THz Near IR 1 μm 10 4 cm THz Ultraviolet 100 nm 10 5 cm -1 Wavelength Frequency Wave number Visible nm

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Solar Spectrum and Terrestrial Spectrum

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 MODIS / Terra, Gulfstream Temperature

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007

AMSU-B Data (183 ±1 GHz) Dry areas in the UT (NOAA 16, Channel 18, Figure: Oliver Lemke) Microwave Remote Sensing

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Satellite Limb Sounding (Figure: Oliver Lemke)

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Microwave Limb Sonder (MLS) onboard UARS

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Airborne Microwave Remote Sensing

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 ASUR frequency range and primary species

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 A picture from the SOLVE campaign in Kiruna, Sweden, January 2000

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Validation of satellite data is important...

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Ground-based Radiometer for Atmospheric Measurements (RAM )

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Measured Microwave Spectrum by the RAM

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Pressure Broadening of Spectral Lines 50km / 0.5 hPa 20km / 50 hPa 10km / 200 hPa

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 A Note on Profile Retrieval Often we can describe the relation between the (unknown) atmospheric profile x and the measured spectrum y by a linear equation: The matrix A is also called as the weighting function matrix. Finding x from measured y would require inversion of A: However, this is generally not possible (inverse of A does not exist). Therefore one has to find some „generallized“ inverse of A:

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Lidar In-space Technology Experiment (LITE) on Discovery in September 1994 as part of the STS-64 mission

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Radar Image ENVISAT ASAR 15 April 2005

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Sea ice concentration from AMSR-E 89 GHz 15 April courtesy of Lars Kaleschke

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Sea ice concentration from AMSR-E 89 GHz 15 April False colour image courtesy of Lars Kaleschke

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Example: SCIAMACHY Tropospheric NO 2 biomass burning pollution Courtesy of Andreas Richter

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 NO2 reductions in Europe and parts of the US strong increase over China consistent with significant NO x emission changes 7 years of GOME data DOAS retrieval + CTM-stratospheric correction seasonal and local AMF based on 1997 MOART-2 run cloud screening GOME annual changes in tropospheric NO 2 GOME NO 2 : Temporal Evolution A. Richter et al., Increase in tropospheric nitrogen dioxide over China observed from space, Nature,

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Lightning Flashes, Optical Transient Detector (OTD)

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Lecture 1 Introduction General Introduction Examples of Remote Seinsing Applications Introduction to Satellite Orbits

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Satellite Orbits satellite Earth apogee perigee a: major axis e: excentricity

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 For a circular satellite orbit around a spherically homogenous planet the gravitational force F g and the centrifugal force F c are in balance: For the Earth g=9.81 m/s 2 and R=6380 km.

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 Orbital period given by:

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 From Elachi

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 From Elachi

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 The orbital node changes due to precession, primarily due to the oblateness of the Earth. The rate of change for the orbital node is approximately given by: Here J 2 = is the second harmonic of the Earth geopotential. I is the inclination angle.

B.-M. Sinnhuber, Remote Sensing I, University of Bremen, Summer 2007 From Elachi