Zobrazeno 1 - 10
of 229
pro vyhledávání: '"K, Heidinger"'
Publikováno v:
Remote Sensing, Vol 16, Iss 13, p 2487 (2024)
Long-term (1982–2019) satellite climate data records (CDRs) of aerosols and clouds, reanalysis data of meteorological fields, and machine learning techniques are used to study the aerosol effect on deep convective clouds (DCCs) over the global ocea
Externí odkaz:
https://doaj.org/article/700b72257d864354a929fb86638faf38
Publikováno v:
Atmospheric Measurement Techniques, Vol 14, Pp 3371-3394 (2021)
Cloud properties are critical to our understanding of weather and climate variability, but their estimation from satellite imagers is a nontrivial task. In this work, we aim to improve cloud detection, which is the most fundamental cloud property. We
Externí odkaz:
https://doaj.org/article/e903e6fba30244a3802fe0228bb9573e
Publikováno v:
Atmospheric Measurement Techniques, Vol 13, Pp 4035-4049 (2020)
Retrieval of semitransparent ice cloud properties from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensor on the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 platforms is challenging due to the absence of infrared
Externí odkaz:
https://doaj.org/article/c92489b836fc4f4e90ac6fd905071d6b
Autor:
Steven D. Miller, Yoo‐Jeong Noh, Lewis D. Grasso, Curtis J. Seaman, Alexander Ignatov, Andrew K. Heidinger, SungHyun Nam, William E. Line, Boris Petrenko
Publikováno v:
Earth and Space Science, Vol 9, Iss 2, Pp n/a-n/a (2022)
Abstract Marine boundary layer (MBL) clouds, ubiquitous to the world’s oceans, help govern the radiative balance of Earth’s climate system. Satellite remote sensing provides the most practical means to monitor cloud worldwide. Whereas visible‐b
Externí odkaz:
https://doaj.org/article/bd9314461cbd4b389cf5c82124c305e5
Autor:
Yoo-Jeong Noh, John M. Haynes, Steven D. Miller, Curtis J. Seaman, Andrew K. Heidinger, Jeffrey Weinrich, Mark S. Kulie, Mattie Niznik, Brandon J. Daub
Publikováno v:
Remote Sensing, Vol 14, Iss 21, p 5524 (2022)
Satellites have provided decades of valuable cloud observations, but the data from conventional passive radiometers are biased toward information from at or near cloud top. Tied with the Joint Polar Satellite System (JPSS) Visible Infrared Imaging Ra
Externí odkaz:
https://doaj.org/article/45890cc4b50746e583130bdf8563f39f
Publikováno v:
Atmospheric Measurement Techniques, Vol 12, Pp 6557-6577 (2019)
For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With t
Externí odkaz:
https://doaj.org/article/62a54b6293af4492af1d54ced52b6397
Publikováno v:
Remote Sensing, Vol 14, Iss 15, p 3630 (2022)
The availability of onboard calibration for solar reflectance channels on recently launched advanced geostationary imagers provides an opportunity to revisit the calibration of the visible channels on past geostationary imagers, which lacked onboard
Externí odkaz:
https://doaj.org/article/53e6c0c4f08c461085fe2063176edc8d
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-9
Autor:
S. Song, K. S. Schmidt, P. Pilewskie, M. D. King, A. K. Heidinger, A. Walther, H. Iwabuchi, G. Wind, O. M. Coddington
Publikováno v:
Atmospheric Chemistry and Physics, Vol 16, Pp 13791-13806 (2016)
In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields
Externí odkaz:
https://doaj.org/article/e0f47eb3ec474280aa0f4fb5093c5c75
Publikováno v:
Remote Sensing, Vol 12, Iss 5, p 823 (2020)
Long-term satellite climate data records (CDRs) of clouds and aerosols are used to investigate the aerosol indirect effect (AIE) of cirrus clouds over the global oceans from a climatology perspective. Our study focuses on identifying the sensitive re
Externí odkaz:
https://doaj.org/article/7e4e13a480ce41e2900778b30e03a126