Remote Sensing of Aerosols, Clouds, and Precipitation compiles recent advances in aerosol, cloud, and precipitation remote sensing from new satellite observations. The book examines a wide range of measurements from microwave (both active and passive), visible, and infrared portions of the spectrum. Contributors are experts conducting state-of-the-art research in atmospheric remote sensing using space, airborne, and ground-based datasets, focusing on supporting earth observation satellite missions for aerosol, cloud, and precipitation studies. A handy reference for scientists working in remote sensing, earth science, electromagnetics, climate physics, and space engineering. Valuable for operational forecasters, meteorologists, geospatial experts, modelers, and policymakers alike.
- Presents new approaches in the field, along with further research opportunities, based on the latest satellite data
- Focuses on how remote sensing systems can be designed/developed to solve outstanding problems in earth and atmospheric sciences
- Edited by a dynamic team of editors with a mixture of highly skilled and qualified authors offering world-leading expertise in the field
Papildus informācija
A thorough compilation of recent advances in remote sensing of aerosols, clouds, and precipitation based on the latest satellite observations
Contributors |
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xi | |
Author Biographies |
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xiii | |
Preface |
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xv | |
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1 Passive Remote Sensing of Aerosol Height |
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2 | (3) |
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2 Aerosol Vertical Distribution |
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5 | (2) |
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3 Passive Remote Sensing Techniques for Retrieval of Aerosol Layer Height |
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7 | (10) |
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4 Conclusions and Outlook |
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17 | (6) |
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18 | (1) |
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18 | (4) |
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22 | (1) |
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2 Vertical Profiling of Aerosol Optical Properties From LIDAR Remote Sensing, Surface Visibility, and Columnar Extinction Measurements |
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23 | (2) |
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2 Characterization of Vertical Variables With Active Remote-Sensing Techniques |
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25 | (7) |
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3 Aerosol Vertical Profile Derived From Passive Remote Sensing |
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32 | (7) |
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4 Applications to the Radiative Impacts of Aerosols |
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39 | (2) |
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41 | (4) |
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41 | (1) |
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42 | (3) |
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3 Remote Sensing of Aerosols From Space: Retrieval of Properties and Applications |
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45 | (3) |
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2 Aerosols: Heterogeneity and Climatic Implications |
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48 | (3) |
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3 Satellite Observations for Aerosol Monitoring: Developments |
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51 | (1) |
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4 Satellite Retrieval of Aerosol Properties |
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52 | (4) |
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5 Satellite Aerosol Database |
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56 | (16) |
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6 Aerosol Remote Sensing Over the Indo-Gangetic Plain, South Asia |
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72 | (4) |
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7 Conclusions and Future Prospects |
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76 | (9) |
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77 | (1) |
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77 | (6) |
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83 | (2) |
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4 Remote Sensing of Heavy Aerosol Pollution Episodes: Smoke and Dust |
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85 | (1) |
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2 Detection of Aerosol Episodes |
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86 | (10) |
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3 Aerosol Retrieval Framework |
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96 | (5) |
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4 Retrieval of Biomass Burning Episodes |
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101 | (2) |
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5 Miscellaneous-Polarization Remote Sensing |
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103 | (2) |
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105 | (4) |
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106 | (3) |
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5 Aerosol and Cloud Bottom Altitude Covariations From Multisensor Spaceborne Measurements |
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109 | (2) |
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111 | (6) |
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117 | (5) |
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4 Summary and Conclusions |
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122 | (7) |
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123 | (1) |
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123 | (6) |
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6 Cloud-Aerosol-Precipitation Interactions Based of Satellite Retrieved Vertical Profiles of Cloud Microstructure |
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129 | (2) |
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2 Physical Considerations in Retrieving Vertical Microphysical Profiles |
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131 | (1) |
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3 The Microstructure of Vertical Profiles of Adiabatic Convective Clouds |
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131 | (5) |
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4 The Observed Microstructure of Convective Clouds Vertical Profiles |
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136 | (1) |
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5 Impacts of CCN and Updrafts on Vertical Microphysical Profiles of Convective Clouds |
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137 | (3) |
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6 Application of re(T) to Observe Anthropogenic Aerosols Suppressing Precipitation |
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140 | (3) |
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7 Application of re(T) to Observe Large Hygroscopic Aerosols Restoring Precipitation |
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143 | (1) |
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8 Impacts of Aerosols on Clouds' Glaciation Temperature and Mixed Phase Precipitation |
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143 | (4) |
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9 Vertical Microphysical Profiles of Severe Convective Storms |
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147 | (1) |
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10 Applications of Vertical Profiles of re(T) to Retrieve Ndb and CCN(S) |
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148 | (1) |
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149 | (4) |
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150 | (2) |
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152 | (1) |
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7 Polarimetric Technique for Satellite Remote Sensing of Superthin Clouds |
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153 | (3) |
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2 Polarization Signature of Light Backscattered by Clouds |
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156 | (6) |
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3 Method for Retrieving Superthin Cloud Optical Depth |
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162 | (8) |
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170 | (5) |
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171 | (1) |
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171 | (4) |
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8 Cloud Screening and Property Retrieval for Hyper-Spectral Thermal Infrared Sounders |
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175 | (1) |
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176 | (1) |
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3 Typical Cloud Detection Techniques |
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177 | (2) |
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4 Cloud Detection Strategy for the Sounders |
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179 | (6) |
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185 | (4) |
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185 | (2) |
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187 | (2) |
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9 Surface Remote Sensing of Liquid Water Cloud Properties |
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189 | (1) |
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2 Principle Method and Basic Assumptions |
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190 | (3) |
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3 Case Study: Using Radiation Measurements for Validation |
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193 | (14) |
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207 | (4) |
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207 | (2) |
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209 | (2) |
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10 Measuring Precipitation From Space |
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211 | (1) |
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2 Infrared and Visible Frequencies Methods |
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212 | (1) |
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3 Microwave-Based Methods |
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212 | (3) |
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4 Methods Based on IR + MW Fusion |
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215 | (1) |
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5 The Tropical Rainfall Measurement Mission (TRMM) |
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216 | (1) |
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6 The Global Precipitation Measuring (GPM) Mission |
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217 | (1) |
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7 The Future of Satellite Estimates of Precipitation |
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217 | (6) |
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219 | (1) |
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219 | (2) |
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221 | (2) |
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11 Measurement of Precipitation from Satellite Radiometers (Visible, Infrared, and Microwave): Physical Basis, Methods, and Limitations |
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223 | (1) |
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2 Satellite Rainfall Estimation Methods |
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224 | (19) |
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243 | (6) |
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245 | (4) |
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12 Development of a Rain/No-Rain Classification Method Over Land for the Microwave Sounder Algorithm |
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249 | (2) |
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251 | (2) |
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3 Comparison of Rain/No-Rain Classification (RNC) Over Land Using the 89-GHz Channel With PR and MSPPS Rain Estimates |
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253 | (2) |
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255 | (8) |
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263 | (4) |
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263 | (1) |
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264 | (3) |
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13 Remote Sensing of Precipitation from Airborne and Spaceborne Radar |
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267 | (2) |
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2 Radar Precipitation Measurement Fundamentals |
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269 | (3) |
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3 The Particle Size Distribution |
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272 | (5) |
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4 Single-Frequency Methods |
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277 | (3) |
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280 | (3) |
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6 Effects of Nonuniform Beam Filling |
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283 | (4) |
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287 | (4) |
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8 Radar-Radiometer Methods |
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291 | (2) |
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293 | (8) |
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294 | (1) |
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294 | (5) |
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299 | (2) |
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14 Status of High-Resolution Multisatellite Precipitation Products Across India |
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301 | (3) |
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2 A Review of Recent Evaluations of High-Resolution MSPPs Across India |
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304 | (1) |
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3 Evaluation of Five High-Resolution MSPPs for the Indian Monsoon 2014 |
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305 | (2) |
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4 Operational Merged Satellite-Gauge Rainfall Product in India |
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307 | (3) |
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310 | (5) |
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312 | (1) |
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312 | (3) |
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15 Real-Time Wind Velocity Retrieval in the Precipitation System Using High-Resolution Operational Multi-radar Network |
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Venkatachalam Chandrasekar |
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315 | (3) |
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2 Multiple-Doppler Methodology for Wind Retrieval |
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318 | (3) |
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3 Real-Time Multiple-Doppler Retrieval System for CASA Radar Networks |
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321 | (9) |
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4 Observations, Results, and Validation |
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330 | (7) |
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337 | (4) |
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338 | (1) |
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338 | (3) |
Index |
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341 | |
Dr. Tanvir Islam is presently with the NASA Jet Propulsion Laboratory, and specializes in remote sensing observations. Currently, he is engaged with the development of advanced microwave calibration and retrieval algorithms for NASAs Earth observing missions.
Prior to joining NASA/JPL in 2015, he was with the NOAA/NESDIS/STAR, and worked on the development of satellite remote sensing algorithms, with an emphasis on microwave variational inversion techniques (2013-2015). He also held visiting scientist positions at the University of Tokyo, as part of the NASA/JAXA precipitation measurement missions (PMM) algorithm development team, in 2012, and at the University of Calgary, in 2015. He received the Ph.D. degree in remote sensing from the University of Bristol, Bristol, UK, in 2012.
Dr. Islam was the recipient of the Faculty of Engineering Commendation from the University of Bristol (nominated for a University Prize for his outstanding Ph.D. thesis), in 2012, the JAXA visiting fellowship award, in 2012, the CIRA postdoctoral fellowship award, in 2013, the Calgary visiting fellowship award, in 2015, and the Caltech postdoctoral scholar award, in 2015. He has served as a lead guest editor for a special issue on Microwave Remote Sensing for the Physics and Chemistry of the Earth (Elsevier), and currently serving on the editorial board of Atmospheric Measurement Techniques (EGU) and Scientific Reports (Nature). He has published four books and more than 60 peer-reviewed papers in leading international journals. His primary research interests include microwave remote sensing, radiometer calibration, retrieval algorithms, radiative transfer theory, data assimilation, mesoscale modeling, cloud and precipitation system, and artificial intelligence in geosciences. Dr. Hu got his PhD degree from University of Alaska, Fairbanks. Since 1995, Dr. Hu has been a research scientist / senior research scientist at NASA Langley Research Center. Dr. Hu began his career working on radiative transfer and climate modeling in his PhD study. He worked on the ERBE and CERES projects, and then joined the CALIPSO team studying lidar remote sensing. Dr. Hu is currently working on developing innovative remote sensing concepts, such as photon orbital angular momentum measurements and studying sub-diffraction limit telescopes. Dr. Hus primary scientific accomplishment includes: theoretical radiative transfer studies for active and passive remote sensing; discovery of the relation between lidar depolarization and multiple scattering for water cloud droplets; development of highly accurate global cloud phase product using CALIPSO observations; high spatial resolution global ocean surface wind speed retrieval technique and data product using CALIPSO lidar measurements; innovative lidar remote sensing techniques, such as using space-based lidar for studying ocean primary productivity and carbon cycle, as well as deriving value added vegetation canopy, snow and sea ice product from CALIPSO; and theoretical and engineering studies of differential absorption radar concept for measurements of ocean/land surface atmospheric pressure; Dr. Hu author/co-authored more than 150 peer-reviewed scientific journal articles with SCI index is 47 on google scholar (https://scholar.google.com/citations?user=YySlI2oAAAAJ&hl=en) and 39 on ResearcherID (http://www.researcherid.com/rid/K-4426-2012). Dr. Alexander A. Kokhanovsky received the M.S. degree in theoretical physics from the Belarussian State University, Minsk, Belarus, in 1983 and the Ph.D. degree in optical physics from the B. I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Minsk, in 1991. His Ph.D. work was focused on modeling light scattering properties of aerosol media, clouds, and foams.
He is the Editor of Springer Series in Light Scattering and Wiley Series in Atmospheric Physics and Remote Sensing. He is the author of the books Light Scattering Media Optics: Problems and Solutions (Springer-Praxis, 1999, 2001, 2004), Polarization Optics of Random Media (Springer-Praxis, 2003), Cloud Optics (Springer, 2006), and Aerosol Optics (Springer-Praxis, 2008). He has published more than 200 papers in the field of environmental optics, radiative transfer, remote sensing, and light scattering. His research is directed toward the solution of various forward and inverse problems of atmospheric optics. Dr. Kokhanovsky is a member of the European Geophysical Union. Dr. Jun Wang is a Research Scientist at the University of Wisconsin, Madison. He has over 10 years of experience in code development, validation, and application, and his research areas include nuclear thermal hydraulics and safety, severe accident, fuel performance, and advanced reactors. Wang has over 50 peer-review articles published on top nuclear journals and conferences. He also has over 200 peer-review experience in 20 journals and conferences, such as the International Journal of Heat and Mass Transfer, Applied Thermal Engineering, Annals of Nuclear Energy, Nuclear Technology, Nuclear Engineering and Design, and Progress in Nuclear Energy.