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Microwave Remote Sensing of Atmospheric Trace Gases

Microwave Remote Sensing of Atmospheric Trace Gases. Remote Sensing I Lecture 6 Summer 2006. J. F(J). Rotational Energy Levels. Rotational Transitions. allowed transitions:. Rotational Transitions. Microwave Spectrum of HCl. Microwave Spectrum of ClO. posible orientations.

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Microwave Remote Sensing of Atmospheric Trace Gases

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  1. Microwave Remote Sensing of Atmospheric Trace Gases Remote Sensing I Lecture 6 Summer 2006

  2. J F(J) Rotational Energy Levels

  3. Rotational Transitions

  4. allowed transitions: Rotational Transitions

  5. Microwave Spectrum of HCl

  6. Microwave Spectrum of ClO

  7. posibleorientations Degeneracies of Rotations J=1

  8. Degeneracies of Rotations J=2 J=3

  9. Intensities of Rotational Lines • Probability for transition between level l and level udepends on the number of molecules in level l • In thermal equilibrium given by Boltzmann distribution: (tends to decrease with increasing J)

  10. Intensities of Rotational Lines • Depends also on degenaracies of the levels: (tends to increase with increasing J) Overall proportional to:

  11. Intensities of Rotational Lines May be used to derivetemperature from observedspectrum

  12. Microwave Spectrum of N2O

  13. The N2O Molecule N N O N2O is a linear molecule

  14. Microwave Spectrum of H2O

  15. The Water Molecule O 0.09578 nm 104.48° H H

  16. Microwave Spectrum of Ozone

  17. Microwave Limb Sounding: MLS / UARS

  18. (Source: MLS Website)

  19. Part 1: Airborne Microwave Remote Sensing of Atmospheric Trace Gases.

  20. Airborne Submillimeter Radiometer (ASUR)

  21. ASUR frequency range and primary species

  22. ASUR onboard the NASA DC-8

  23. Part 2: Ground-based Microwave Remote Sensing of Atmospheric Trace Gases.

  24. Observations in Spitsbergen (79°N)

  25. Observations in Spitsbergen (79°N)

  26. Radiometer for Atmospheric Measurements (RAM)

  27. Schematic Overview of the RAM

  28. Measured Microwave Spectrum by the RAM

  29. Pressure Broadening of Spectral Lines 50km / 0.5 hPa 20km / 50 hPa 10km / 200 hPa

  30. Weighting Functions for Ozone Retrieval

  31. Retrieval techniques / Inverse Modelling Assume that the measured spectrum y is a known function of the atmospheric profile x plus some noise ε. Linearize F (also known as the forward model):

  32. Optimal Estimation However, can not be directly inverted (ill-posed problem) Best estimate given by Optimal Estimation solution: Best guess profile A-priori profile Measurement error covariance matrix A-priori profile covariance matrix

  33. Example Ozone Profile: RAM vs. Ozonesonde

  34. Optimal Estimation: Averaging Kernels Optimal estimation solution: Define: Then: Define Averaging Kernel MatrixA = DK:

  35. Averaging Kernel Functions

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