本书共有两卷，此为第1卷。本卷论及美国宁航局(NSA)用于监测和探测地球变化的主要卫星系统——地球观测系统(EOS)，EOS包括的卫星Terra、Aqua和Aura及其装载的MODIS、AIRS、AMSU、AMSR-E、OMI等遥感仪器，并讨论厂NPP将携带的4个NPOESS系统重要部件：可见光红外成像辐射组件(VIIRS)，航线交叉红外探测器(CrIS)，先进技术微波探测器(ATMS)以及臭氧成图和廓线仪装置(OMPS)，可用于研究地球气候环境和天气变化。

本书内容既包括现代遥感技术的基础知识，义涉及卫星遥感的前沿领域，有广泛的实用性，可作为遥感、地学、环境、空间信息等地球科学领域的专业参考书。

本书共有两卷。此为第1卷，包含20章，主要提供了有关中分辨串成像光谱仪(MODIS)产品的信息和科学应用，介绍了美国国家极轨环境卫系统(NPOESS)和NPOESS预备计划(NPP)，还探讨厂其他卫星遥感装备和应用。有关数据格式、数据处理、数据查询和订购等方面的内容在第2卷中给出。

本卷论及美国宁航局(NSA)用于监测和探测地球变化的主要卫星系统——地球观测系统(EOS)，EOS包括的卫星Terra、Aqua和Aura及其装载的MODIS、AIRS、AMSU、AMSR-E、OMI等遥感仪器，并讨论厂NPP将携带的4个NPOESS系统重要部件：可见光红外成像辐射组件(VIIRS)，航线交叉红外探测器(CrIS)，先进技术微波探测器(ATMS)以及臭氧成图和廓线仪装置(OMPS)，可用于研究地球气候环境和天气变化。

本书作者均为相关领域具有权威性的专家与学者。图书内容既包括现代遥感技术的基础知识，义涉及卫星遥感的前沿领域，有广泛的实用性，可作为遥感、地学、环境、空间信息等地球科学领域的专业参考书。

List of Contributors xv

1 Introduction to Science and Instruments 1

References9

2 Introduction to MODIS and an Overview of Associated Activities 12

2.1 Introduction 12

2.2 Background12

2.3 MODIS History 14

2.4 MODIS Sensor 15

2.5 MODIS Science Team and Data Products 19

2.6 MODIS Data Processing 24

2.7 Status and Follow-On Systems 28

2.7.1 Status 28

2.7.2 Follow-On Systems 29

References 31

MODIS Level-lB Products 33

3.1 Introduction 33

3.2 L1B Data Product Description 34

3.3 L1B Calibration Algorithm 38

3.3.1 Thermal Emissive Bands Algorithm 39

3.3.2 Reflective Solar Bands Algorithm 40

3.4 Code Standards and Properties 45

3.5 Data Processing 46

3.6 Data Product Retrieval 47

3.7 Summary 48

References 48

4 MODIS Geolocation 50

4.1 Introduction 50

4.2 Background 50

4.3 Approach 51

4.3.1 Instrument Geometry 52

4.3.2 Exterior and Interior Orientation 56

4.3.3 Algorithm 57

4.3.4 Error Sources 59

4.3.5 Ground Control Points 60

4.3.6 Geolocation Error Analysis and Reduction Methodology 61

4.4 Results 62

4.4.1 MODIS/Terra Results 62

4.4.2 MODIS/Aqua Results 68

4.5 Conclusion and the Future 70

Acknowledgements 71

References 71

5 Introduction to MODIS Cloud Products 74

5.1 Introduction 74

5.2 MODIS Instrument and Calibration 75

5.3 Level-2 Cloud Products 76

5.3.1 Cloud Masking 77

5.3.2 Cloud Thermodynamic Phase 77

5.3.3 Cloud Top Pressure and Effective Cloud Amount 78

5.3.4 Cloud Optical and Microphysical Properties 79

5.3.5 Cirrus Reflectance Algorithm 84

5.4 Global Gridded (Level-3) Products 84

5.5 Future Algorithm Efforts86

5.5.1 Detection of Multilayered Clouds 86

5.5.2 Improved Ice Cloud Microphysical and Optical Models 87

5.5.3 Improved Land Spectral Albedo Maps 88

5.5.4 Clear-Sky Radiance Maps 88

5.6 Summary 90

References 90

6 MODIS Observation of Aerosol Loading from 2000 to 2004 92

6.1 Introduction92

6.2 Multi-Year Aerosol Datasets93

6.3 MODIS Aerosol Retrieval Algorithm and Expected Accuracy 94

6.4 Characterization of Aerosol Optical Depth Distribution 96

6.5 Global and Hemispheric Analysis 99

6.6 Regional Analysis 101

6.7 Terra vs Aqua 104

6.8 Conclusions 107

References 107

7 MODIS Land Products and Data Processing 110

7.1 Introduction 110

7.2 Land Products and Characteristics 111

7.3 Data Production 114

7.3.1 Data Flows 115

7.3.2 Algorithm Improvements l17

7.3.3 Quality Assurance Approach 119

7.3.4 Validation Approach 119

7.4 Conclusion 120

Acknowledgements 120

References 121

8 Operational Atmospheric Correction of MODIS Visible to Middle Infrared Land Surface Data in the Case of an Infinite ambertian Target 123

8.1 Introduction 123

8.2 Theoretical Background 124

8.3 Operational Implementation 126

8.3.1 Simplification to Account for Surface Pressure 126

8.3.2 Detailed Computations 127

8.4 Input and Ancillary Data 129

8.4.1 Surface Pressure 130

8.4.2 Ozone 130

8.4.3 Water Vapor 131

8.4.4 Aerosol Optical Thickness 131

8.5 Application to MODIS Data and Error Budget 132

8.5.1 Calibration Uncertainties 135

8.5.2 Uncertainties on Ancillary Data Pressure 137

8.5.3 Uncertainties on Ancillary Ozone Amount 139

8.5.4 Uncertainties on the Water Vapor Amount 141

8.5.5 Uncertainties on Empirical Relationship used to Determine the Surface Reflectance at 470 nm and 645 nm 143

8.5.6 Uncertainties on the Aerosol Model 145

8.5.7 Overall Uncertainties 151

8.5.8 Validation of the Atmospheric Correction Algorithm 152

8.6 Conclusions 152

References 152

9 MODIS Snow and Sea Ice Products 154

9.1 Introduction 154

9.2 Snow Products 157

9.2.1 Introduction 157

9.2.2 MODIS Snow-Mapping Approaches 158

9.2.3 Snow Swath Product 160

9.2.4 Daily and 8-Day Composite Gridded Snow (Tile Products) 162

9.2.5 Daily and 8-Day Composite Global Climate-Modeling Grid Products 163

9.2.6 Monthly Snow Products 165

9.2.7 Validation 165

9.3 Sea Ice Products 168

9.3.1 Introduction and Algorithm Description 168

9.3.2 Calculation of Sea Ice-Surface Temperature 170

9.3.3 Swath Products171

9.3.4 Daily and 8-Day Composite Gridded Sea Ice Products (Tile Products) 171

9.3.5 Global-Scale Daily, 8-Day Composite and Monthly Gridded Products 171

9.3.6 Validation 172

9.4 Limitations Inherent in the Snow and Sea Ice Products 174

9.4.1 Land Masking in the Snow and Sea Ice Data Products 174

9.4.2 Cloud Masking 175

9.5 Discussion and Conclusion 176

Acknowledgements 177

References 177

10 The NPOESS Preparatory Project 182

10.1 Introduction 182

10.1.1 Origins of NPP 182

10.1.2 Program Philosophies 183

10.2 Sensor Payload--Providing Continuity and Evolution 184

10.2.1 VIIRS and Terra MODIS Continuity 184

10.2.2 VIIRS and Continuity of Operational Imagers 185

10.2.3 Aqua and Aura Continuity 186

10.2.4 CrlS andAIRS Continuity 186

10.2.5 CrlS and Continuity of Operational Sounders 186

10.2.6 ATMS and Continuity of Operational Sounders 187

10.2.7 OMPS and Continuity of Research Sounders 187

10.3 Spacecraft and Launch Vehicle 188

10.4 Orbit 189

10.5 Ground Segment 190

10.5.1 Data Downlink 190

10.5.2 IDPS 190

10.5.3 SDS 191

10.6 Measurement Requirements 192

10.6.1 lORD 192

10.6.2 NASA Science Requirement 192

10.6.3 Stratification 194

10.6.4 CDR's andEDR's 195

10.7 Science Guidance 197

10.8 Summary 197

References 198

11 The Visible Infrared Imaging Radiometer Suite 199

11.1 Introduction 199

11.1.1 Spectral Band Compliment 200

l 1.2 Design Philosophy 202

11.2.1 Spatial/Temporal Design Drivers 202

11.2.2 Spectral/Radiometric Design Drivers 205

11.3 Follow the Photons 208

11.3.1 Rotating Telescope Assembly 208

11.3.2 HalfAngle Mirror 210

11.3.3 Aft Optics 211

11.3.4 Focal Planes and Dewar 212

11.3.5 On-Board Calibrators 215

ll.4 Opto-Mechanical Systems 217

11.4.1 Structures 217

11.4.2 Cryoradiator 217

11.4.3 Thermal Control and Stray Light 218

11.5 Electronics 219

11.5.1 Signal Processing and Transmission 219

11.5.2 Power Supplies and Control Systems 221

11.5.3 Operational Modes 222

Acknowledgements 222

References 223

12 Conically Scanned Microwave Imager Sounder 224

12.1 Introduction 224

12.2 Instrument Overview 225

12.3 CMIS Risk Reduction Studies with Heritage Sensors,and Proxy Data 234

12.3.1 DMSP-SSMIS 237

12.3.2 Coriolis/WindSat 237

12.3.3 NOAA-15, 16 and 17 AMSU 238

12.4 Discussions 240

Acknowledgements 241

References 241

13 Advanced Technology Microwave Sounder 243

13.1 Introduction 243

13.2 Instrument Overview 243

13.3 ATMS Studies with a Heritage Sensor: AMSU 246

13.3.1 AMSU-A Temperature Profiles for Climate 247

13.3.2 AMSU-A Weather Application 248

13.4 Discussions 252

Acknowledgements 252

References 252

14 Introduction to AIRS and CrIS 254

14.1 Introduction and Overview 254

14.2 The Radiative Transfer Equation 257

14.3 Results usingAIRS/AMSU Data 262

14.4 Forecast Impact Experiments 269

14.5 Comparison ofCrlS andAIRS 273

14.6 Summary 277

References 278

15 The Ozone Mapping and Profiler Suite 279

15.1 Introduction 279

15.2 Nadir Sensors 280

15.3 Nadir Retrieval Algorithms 282

15.3.1 Total Column Ozone Algorithm 282

15.3.2 Nadir Profile Ozone Algorithm 284

15.4 Limb Profiler Sensor 285

15.5 Limb Profiler Ozone Algorithm 287

15.6 Limb Retrieval Challenges 292

Acknowledgements and Disclaimer 294

References 295

16 Estimating Solar UV-B Irradiance at the Earth's Surface Using Multi-Satellite Remote Sensing Measurements 297

16.1 Introduction 297

16.2 Satellite Remote Sensing Measurements 298

16.2.1 Satellite TOMS Ozone and Backscatter Ultraviolet Measurements 298

16.2.2 Shuttle Solar Backscatter Ultraviolet Measurements 299

16.2.3 Satellite Cloud Observations 300

16.2.4 Satellite Aerosol Observations 300

16.3 Ultraviolet Radiative Transfer Models 301

16.3.1 Scheme of UV-B Radiation Model 301

16.3.2 Two-Stream UV-B Radiation Transfer Models 303

16.4 Sensitivity Study 304

16.4.1 Sensitivity to Solar Zenith Angle 304

16.4.2 Sensitivity to Atmospheric Ozone 304

16.4.3 Sensitivity to Surface Reflectivity 305

16.4.4 Sensitivity to Cloud Optical Depth 306

16.4.5 Sensitivity to Atmospheric Aerosols 307

16.5 The Effects of Clouds and Aerosols on UV-B Irradiance 309

16.5.1 The Effects of Cloud on the Surface UV-B h-radiance 309

16.5.2 The Effects of Aerosol on the Surface UV-B Irradiances 310

16.5.3 Model Calibration 310

16.6 Summary and Conclusions 312

Acknowledgements 313

References 313

17 Surface Rain Rates from Tropical Rainfall Measuring Mission Satellite Algorithms 317

17.1 Introduction 317

17.2 Satellite Algorithms and Data 318

17.2.1 V5 Algorithms 319

17.2.2 V6 Algorithms 320

17.3 Results 322

17.3.l Annual Means and Paired t-Tests 322

17.3.2 Seasonal Differences 327

17.3.3 Interannual Variations 329

17.4 Summary and Discussion 332

Acknowledgements 334

References 334

18 Use of Satellite Remote Sensing Data for Modeling Carbon Emissions from Fires: A Perspective in North America 337

18.1 Introduction 337

18.2 Carbon Emission Estimation 338

18.3 Fire Emission Parameters and Modeling 339

18.3.1 Burned Area 339

18.3.2 Spatial Fragmentation and Temporal Expansion of Burned Area 344

18.3.3 Fuel Loading 346

18.3.4 Fuel Type 349

18.3.5 Fraction of Fuels Consumed 350

18.3.6 Emission Factor 353

18.3.7 Fuel Moisture Content 355

18.4 Summary 355

References 356

19 TRMM Fire Algorithm, Product and Applications 363

19.1 Introduction 363

19.1.1 Satellite Fire Products 363

19.1.2 Satellite Aerosol Product 365

19.2 TSDIS Fire Algorithms 366

19.2.1 Nighttime Algorithm 367

19.2.2 Daytime Algorithm 368

19.3 TSDIS Fire Products 370

19.4 Seasonal and Interannual Variability 373

19.4.1 Fire and Aerosol Comparison 373

19.4.2 Statistical EOF Analysis 377

19.5 Diurnal Cycle and Intraseasonal Variability 381

19.5.1 Diurnal CycleAliasing 382

19.5.2 Single Spectrum Analysis 384

19.6 Interaction between Fire and Rainfall 386

19.7 Summary 388

Acknowledgements 388

References 389

20 China's Current and Future Meteorological Satellite Systems 392

20.1 Introduction 392

20.2 The Polar Orbiting Meteorological Satellites of China 393

20.2.1 The First Generation of Polar Orbiting Operational Meteorological Satellites of China 393

20.2.2 The Second Generation of Polar Orbiting Operational Environmental Satellites of China: FY-3 Series 395

20.2.3 Payloads Onboard FY-3A 397

20.2.4 Complementary Mission 403

20.3 The First Generation Geostationary Meteorological Satellites of China 406

20.3.1 The FY-2A and FY-2B Satellites 406

20.3.2 The First Generation of Chinese Geostationary Operational Satellite: FY-2C Series 409

20.4 The Planning of the Second Generation Geostationary Meteorological Satellites of China: FY-4 412

20.5 Summary 413

References 413

Index 414