Prof. John J. Qu is a faculty member of the ESGS department at the school of Computational Sciences and is Technical Director of EastFIRE Lab at George Mason University. He is also with NASA Goddard Space Flight Center to support the NPOESS Preparatory Project (NPP) mission. His major research areas are satellite remote sensing, Earth systems science, fire science and GIS applications.
圖書目錄
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