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Cloud Statistics from Calipso Lidar Data for the ... - espace-tum.de

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Contents<br />

Declaration of Authorship<br />

iii<br />

Abstract<br />

vii<br />

Acknowledgements<br />

ix<br />

List of Figures<br />

List of Tables<br />

Abbreviations<br />

SI Units and Abbreviations<br />

Symbols<br />

xiii<br />

xv<br />

xvii<br />

xix<br />

xxi<br />

1 Introduction and motivation 1<br />

1.1 The MERLIN mission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1<br />

1.1.1 Methane as an important trace-gas . . . . . . . . . . . . . . . . . . 1<br />

1.1.2 The global methane budget . . . . . . . . . . . . . . . . . . . . . . 3<br />

1.1.3 In-situ measurements and remote sensing . . . . . . . . . . . . . . 3<br />

1.1.4 Scientific challenges and measurement strategy . . . . . . . . . . . 6<br />

1.2 The CALIPSO mission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8<br />

1.2.1 Global cloud coverage by lidar measurements <strong>from</strong> space . . . . . . 8<br />

1.2.2 Scientific challenges and limits of CALIPSO . . . . . . . . . . . . . 8<br />

1.3 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10<br />

2 Background in<strong>for</strong>mation and methodology of CALIPSO 11<br />

2.1 The fundamental equations . . . . . . . . . . . . . . . . . . . . . . . . . . 11<br />

2.2 The CALIOP payload . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15<br />

2.3 The <strong>Cloud</strong> Detection Algorithm of CALIPSO . . . . . . . . . . . . . . . . 16<br />

2.4 CALIPSO data sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18<br />

2.5 CALIPSO lidar surface return . . . . . . . . . . . . . . . . . . . . . . . . . 22<br />

3 Methodology behind cloud free and cloud gap statistics 24<br />

xi

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