La Nature vue de (très) près

Sommaire

Remerciements v
List of acronyms ix
Introduction 1
1 Atmospheric remote sensing 5
1.1 Milestones in atmospheric experimentation . . . . . . . . 5
1.1.1 The in situ atmospheric measurements precursors 5
1.1.2 The advent of ground-based atmospheric remote
sensing . . . . . . . . . . . . . . . . . . . . . . . . 7
1.1.3 Spaceborne atmospheric instruments . . . . . . . . 9
1.2 Importance of vertically resolved information . . . . . . . 11
1.2.1 Stratospheric ozone trends . . . . . . . . . . . . . . 12
1.2.2 Dispersion of the measurements . . . . . . . . . . . 14
1.2.3 Spatio-temporal sampling bias . . . . . . . . . . . 15
1.2.4 Vertically-resolved data and atmospheric models . 16
1.3 The radiative transfer problem for limb scattering instruments
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.3.1 The photon transport equation . . . . . . . . . . . 18
1.3.2 Rayleigh scattering phase function . . . . . . . . . 21
1.3.3 Rayleigh scattering cross-section . . . . . . . . . . 22
1.3.4 Transport equation in a purely Rayleigh scattering
atmosphere . . . . . . . . . . . . . . . . . . . . . . 23
1.3.5 Molecular absorption . . . . . . . . . . . . . . . . . 25
1.3.6 Radiative transfer equation for a single scattering
and absorbing atmosphere . . . . . . . . . . . . . . 25
1.3.7 Typical limb-scatter radiance profile . . . . . . . . 27
1.4 From radiance to concentration profiles: the inverse problem 29
2 Imaging and atmospheric remote sensing—The refracted
Sun case 35
2.1 Quantitative atmospheric information based on imaging
techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.2 Scope of the theoretical work: pressure profile retrieval
from the apparent flattening of the solar disk . . . . . . . 36
2.3 Sun image simulation . . . . . . . . . . . . . . . . . . . . 37
2.3.1 Virtual instrument definition . . . . . . . . . . . . 37
2.3.2 Solar limb darkening . . . . . . . . . . . . . . . . . 38
2.3.3 Atmospheric refractive index . . . . . . . . . . . . 39
2.3.4 1-D ray tracing problem . . . . . . . . . . . . . . . 39
2.3.5 2-D ray tracing problem . . . . . . . . . . . . . . . 41
2.4 Zernike moments . . . . . . . . . . . . . . . . . . . . . . . 44
2.5 Pressure profiles retrieval . . . . . . . . . . . . . . . . . . 46
2.5.1 Training dataset . . . . . . . . . . . . . . . . . . . 48
2.5.2 Test cases . . . . . . . . . . . . . . . . . . . . . . . 52
2.5.3 Impact of error sources . . . . . . . . . . . . . . . 57
2.6 Adequacy of the proposed method and future work . . . . 58
3 Spectral imaging and atmospheric remote sensing—The
ALTIUS mission 61
3.1 The pointing problem of atmospheric profiling instruments 61
3.1.1 Imaging as an answer to pointing uncertainty . . . 63
3.2 The ALTIUS concept . . . . . . . . . . . . . . . . . . . . . 64
3.3 Nominal orbit and measurement geometries . . . . . . . . 68
3.4 Synthetic limb-scatter radiance . . . . . . . . . . . . . . . 70
3.5 Major payload and platform requirements . . . . . . . . . 71
3.5.1 Signal-to-noise ratio . . . . . . . . . . . . . . . . . 73
3.5.2 Pointing error . . . . . . . . . . . . . . . . . . . . . 73
3.5.3 Wavelength misregistration . . . . . . . . . . . . . 74
3.6 O3 retrieval in bright limb . . . . . . . . . . . . . . . . . . 74
3.6.1 O3 measurements . . . . . . . . . . . . . . . . . . . 74
3.6.2 Measurement error . . . . . . . . . . . . . . . . . . 78
3.6.3 Statement of the inverse problem . . . . . . . . . . 79
3.6.4 Retrieved profile . . . . . . . . . . . . . . . . . . . 83
3.6.5 Vertical resolution . . . . . . . . . . . . . . . . . . 84
3.6.6 Pointing uncertainty . . . . . . . . . . . . . . . . . 86
3.6.7 Spectral uncertainty . . . . . . . . . . . . . . . . . 88
3.6.8 Final O3 retrieval performance budget . . . . . . . 89
3.7 NO2 retrieval in bright limb . . . . . . . . . . . . . . . . . 91
3.7.1 NO2 measurements . . . . . . . . . . . . . . . . . . 91
3.7.2 Statement of the inverse problem . . . . . . . . . . 93
3.7.3 Retrieved profile . . . . . . . . . . . . . . . . . . . 94
3.7.4 Pointing uncertainty . . . . . . . . . . . . . . . . . 96
3.7.5 Spectral uncertainty . . . . . . . . . . . . . . . . . 97
3.7.6 Final NO2 retrieval performance budget . . . . . . 97
4 Acousto-optical tunable filters 99
4.1 Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.2 Theoretical background . . . . . . . . . . . . . . . . . . . 100
4.2.1 Optical waves in birefringent crystals . . . . . . . . 100
4.2.2 Acoustic waves in crystals . . . . . . . . . . . . . . 103
4.2.3 Elasto-optic effect and coupled wave equations . . 105
4.2.4 Basic AOTF parameters . . . . . . . . . . . . . . . 109
4.3 Application to NO2 absorption cross-section measurement 121
4.3.1 Commercial TeO2 AOTF . . . . . . . . . . . . . . 122
4.3.2 Experimental setup . . . . . . . . . . . . . . . . . . 123
4.3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . 124
4.4 KDP-based AOTF for hyperspectral imaging in UV . . . 125
4.4.1 Main AOTF parameters . . . . . . . . . . . . . . . 126
4.4.2 Temperature dependence . . . . . . . . . . . . . . 131
5 AOTF-based hyperspectral imager — Application to the
remote sensing of NO2 in industrial smokes 137
5.1 Instrument description . . . . . . . . . . . . . . . . . . . . 138
5.2 Smokestack experiment . . . . . . . . . . . . . . . . . . . 140
5.2.1 Experimental conditions . . . . . . . . . . . . . . . 140
5.2.2 Measurement principle . . . . . . . . . . . . . . . . 142
5.2.3 Data acquisition and correction . . . . . . . . . . . 144
5.2.4 Results . . . . . . . . . . . . . . . . . . . . . . . . 146
Conclusion and future research 151
A Error covariance of limb-scatter measurements 155
A.1 Limb scattering measurement uncertainty . . . . . . . . . 156
A.2 Image ratio covariance . . . . . . . . . . . . . . . . . . . . 157
B The MAP log-normally distributed solution 161
C Acousto-optic interaction and polarization aspects 163
Bibliography 169