Remote Sensing of Aerosols, Clouds, and Precipitation

Erscheinungsjahr 2017
ISBN: 978-0-12-810437-8
Verlag: Elsevier Science

Buch, Englisch, 364 Seiten, Format (B × H): 188 mm x 234 mm, Gewicht: 839 g

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.

Autoren/Hrsg.

Islam, Tanvir

Hu, Yongxiang

Kokhanovsky, Alexander A.

Wang, Jun

Fachgebiete

• Geowissenschaften Geologie Geodäsie, Kartographie, Fernerkundung
• Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung
• Geowissenschaften Geologie Meteorologie, Klimatologie

Inhaltsverzeichnis

Section 1 - Remote sensing of aerosols Atmospheric aerosol models Polarimetric aerosol remote sensing Remote sensing of atmospheric aerosol using POLDER Aerosol remote sensing using multispectral imagers Aerosol remote sensing using MODIS Multiangular remote sensing of atmospheric aerosol: MISR experience

Section 2 - Remote sensing of clouds Cloud remote sensing using MODIS Fog detection from a satellite Polarimetric remote sensing of terrestrial clouds Remote sensing of optically thick clouds: theory and applications Cloud top height determination from a satellite

Section 3 - Remote sensing of precipitation Land surface emissivity impact on precipitation remote sensing Passive microwave remote sensing of precipitation Precipitation retrieval using ATMS and SAPHIR Global Precipitation Measurement (GPM) mission Satellite data assimilation for extreme precipitation events

Section 4 - Remote sensing of aerosols-clouds-precipitation interaction Impact of aerosols on clouds and precipitation Aerosol-cloud-precipitation relationships from satellite measurements Cloud microphysics for satellite based precipitation retrieval Changes in precipitation and cloud patterns

Über Autor(innen)

Wang, Jun
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.

Hu, Yongxiang
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. Hu's 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).

Kokhanovsky, Alexander A.
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.