Kokhanovsky Satellite Aerosol Remote Sensing Over Land

1. Auflage 2009
ISBN: 978-3-540-69397-0
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 388 Seiten

Aerosols have a significant influence on the Earth's radiation budget, but there is considerable uncertainty about the magnitude of their effect on the Earth's climate. Currently, satellite remote sensing is being increasingly utilized to improve our understanding of the effect of atmospheric aerosols on the climate system. Satellite Aerosol Remote Sensing Over Land is the only book that brings together in one volume the most up-to-date research and advances in this discipline. As well as describing the current academic theory, the book presents practical applications, utilizing state-of-the-art instrumentation, invaluable to the work of environmental scientists. With contributions by an international group of experts and leaders of correspondent aerosol retrieval groups, the book is an essential tool for all those working in the field of climate change.

Alexander Kokhanovsky: For the last two decades Dr Alexander Kokhanovsky has worked in the Laboratory of Light Scattering Media Optics in the Institute of Physics in Minsk. He is currently working with the SCIAMACHY algorithm development team at the Institute of Environmental Physics in Bremen (Germany). The main thrust of the research is the development of new cloud retrieval algorithms for water and ice clouds as seen by the spectrometer SCIAMACHY (in space from 2002). He is the editor of three volumes of Light Scattering Reviews - 1, 2 and 3 (the latter is due in January 2008), and is the author of several Springer Praxis books, including: Light Scattering Media Optics (1999, 2001, 2004), Polarization Optics of Random Media (2003), Cloud Optics (2006) and Aerosol Optics, due in November 2007. Gerrit de Leeuw: Following professorships at the Universities of Sunderland and Leeds in the UK, Professor Gerrit de Leeuw was appointed professor at the University of Helsinki in 2007. He currently works at both that university and the Finnish Meteorological Institute (FMI) and is also Associate Editor to the AGU Journal of Geophysical Research - Atmospheres. His primary interest is in the physical processes in the atmosphere, with applications in the fields of radiative effects of the atmosphere (climate), pollution (air and water: effect on eco-systems and air quality) and atmospheric effects on electro-optical systems performance. Gerrit de Leeuw's main expertise is in the field of the physics of air-sea exchange: aerosols, gases (in particular CO2), momentum, heat and water vapor. He has contributed to many international and multidisciplinary field and laboratory experiments and his remote sensing expertise has frequently been called upon for ESA and EU projects, both as regards instrument development and applications to climate change and air quality.

Autoren/Hrsg.

Kokhanovsky, Alexander

Inhaltsverzeichnis

1;Table of contents;5
2;List of contributors;13
3;Foreword;17
4;1 Introduction;18
4.1;Land surface reflectance effects;21
4.2;Aerosol retrieval methods;22
4.3;Radiative transfer;23
4.4;Book outline;25
4.5;Appendix: Characteristics of optical instruments used in aerosol retrieval;30
4.6;References;32
5;2 The dark-land MODIS collection 5 aerosol retrieval: algorithm development and product evaluation;36
5.1;1. Introduction;36
5.2;2. Properties of aerosols;37
5.3;3. Aerosol remote sensing from MODIS;47
5.4;4. Evaluation of MODIS c005 products;71
5.5;5. Summary/Conclusion;79
5.6;References;80
6;3 The time series technique for aerosol retrievals over land from MODIS;86
6.1;1. Introduction;86
6.2;2. MAIAC overview;88
6.3;3. Radiative transfer basis;90
6.4;4. Aerosol algorithm;94
6.5;pFk;95
6.6;5. Atmospheric correction;97
6.7;6. MAIAC cloud mask;101
6.8;7. MAIAC examples and validation;108
6.9;8. Concluding remarks;113
6.10;References;115
7;4 Iterative procedure for retrieval of spectral aerosol optical thickness and surface reflectance from satellite data using fast radiative transfer code and its application to MERIS measurements;117
7.1;1. Introduction;117
7.2;2. The aerosol retrieval technique;118
7.3;3. Results;135
7.4;Appendix: The vector radiative transfer code;143
7.5;References;148
8;5 Aerosol retrieval over land using the (A)ATSR dual-view algorithm;150
8.1;1. Introduction;150
8.2;2. AATSR instrument;151
8.3;3. Aerosol retrieval;151
8.4;4. Cloud screening;152
8.5;5. Inversion model;155
8.6;6. Forward model;160
8.7;7. Aerosol description;161
8.8;8. Results and evaluation;163
8.9;9. Conclusion;171
8.10;References;172
9;6 Aerosol optical depth from dual-view (A)ATSR satellite observations;175
9.1;1. Introduction;175
9.2;2. Remote sensing of aerosols;178
9.3;3. Model inversion for the retrieval of aerosol optical depth;181
9.4;4. AATSR AOD retrieval and algorithm validation;192
9.5;5. Avenues for future research;200
9.6;6. Summary;201
9.7;References;202
10;7 Oxford-RAL Aerosol and Cloud (ORAC): aerosol retrievals from satellite radiometers;207
10.1;1. Introduction;207
10.2;2. Instrument descriptions;207
10.3;3. The ORAC forward model;209
10.4;4. Surface reflectance;213
10.5;5. The Lambertian fast forward model;215
10.6;6. The BRDF fast forward model;216
10.7;7. The thermal infrared forward model;220
10.8;8. The retrieval algorithm;223
10.9;9. Aerosol speciation;224
10.10;10. Example results;225
10.11;11. Conclusion;237
10.12;References;238
11;8 Benefits and limitations of the synergistic aerosol retrieval SYNAER;240
11.1;1. Introduction;240
11.2;2. SYNAER: exploited satellite instruments and information content analysis;241
11.3;3. The retrieval method;247
11.4;4. Validation and applications;267
11.5;5. Discussion and conclusions;273
11.6;References;277
12;9 Retrieval of aerosol properties over land using MISR observations;280
12.1;1. Introduction;280
12.2;2. MISR specifications and operation;281
12.3;3. Aerosol retrieval data set requirements;282
12.4;4. Methodology for aerosol retrieval over land;286
12.5;5. MISR cloud screening over land;291
12.6;6. Aerosol retrieval results using MISR;296
12.7;7. Discussion and conclusion;301
12.8;References;304
13;10 Polarimetric remote sensing of aerosols over land surfaces;307
13.1;1. Introduction;307
13.2;2. Measuring polarization;308
13.3;3. Surface polarization;313
13.4;4. Modelling atmosphere–surface interactions;320
13.5;5. Aerosol retrievals using polarimetric observations;324
13.6;6. Conclusions;334
13.7;References;335
14;11 Optimal estimation applied to the joint retrieval of aerosol optical depth and surface BRF using MSG/SEVIRI observations;338
14.1;1. Introduction;338
14.2;2. Characterization of surface a priori information;339
14.3;3. Overview of the optimal estimation retrieval method;341
14.4;4. Forward modelling;341
14.5;5. Inverse problem;345
14.6;6. Interpretation of the error and autocorrelation matrices;356
14.7;7. Temporal analysis of prior information update;360
14.8;8. Quantitative effects of prior updating;366
14.9;9. Discussion and conclusion;367
14.10;References;369
15;12 Remote sensing data combinations: superior global maps for aerosol optical depth;372
15.1;1. Introduction;372
15.2;2. Satellite AOD datasets;373
15.3;3. AOD data reference;376
15.4;4. Regional stratification;376
15.5;5. Regional comparisons;377
15.6;6. Scoring concept;378
15.7;7. Global scores;379
15.8;8. Satellite composite;381
15.9;9. Enhanced composite;386
15.10;10. Global modeling;387
15.11;11. Conclusion;389
15.12;References;391
15.13;Index;393