Access the full text.
Sign up today, get DeepDyve free for 14 days.
M. Jin (2004)
ANALYSIS OF LAND SKIN TEMPERATURE USING AVHRR OBSERVATIONSBulletin of the American Meteorological Society, 85
K. Mitchell, D. Lohmann, P. Houser, E. Wood, J. Schaake, A. Robock, B. Cosgrove, J. Sheffield, Q. Duan, L. Luo, R. Higgins, R. Pinker, J. Tarpley, D. Lettenmaier, C. Marshall, J. Entin, M. Pan, W. Shi, V. Koren, J. Meng, B. Ramsay, Andrew Bailey (2004)
The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling systemJournal of Geophysical Research, 109
(2013)
andA.Walther, 2013:ThePathfinderAtmospheres– Extended (PATMOS-x) AVHRR climate dataset
A. Heidinger, A. Evan, M. Foster, A. Walther (2012)
A Naive Bayesian Cloud-Detection Scheme Derived fromCALIPSOand Applied within PATMOS-xJournal of Applied Meteorology and Climatology, 51
C. Meng, R. Pinker, J. Tarpley, I. Laszlo (2003)
A satellite approach for estimating regional land surface energy budget for GCIP/GAPP : GEWEX Continental-Scale International Project, Part 3 (GCIP3)Journal of Geophysical Research, 108
S. Saha, S. Moorthi, Hua-Lu Pan, Xingren Wu, Jiande Wang, S. Nadiga, P. Tripp, Robert Kistler, J. Woollen, D. Behringer, Haixia Liu, Diane Stokes, R. Grumbine, G. Gayno, Jun Wang, Yu-Tai Hou, Hui-Ya Chuang, H.‐M. Juang, Joe Sela, M. Iredell, R. Treadon, D. Kleist, P. Delst, Dennis Keyser, J. Derber, Michael Ek, J. Meng, Helin Wei, Rongqian Yang, Stephen Lord, H. Dool, Arun Kumar, Wanqiu Wang, Craig Long, M. Chelliah, Y. Xue, Boyin Huang, J. Schemm, W. Ebisuzaki, R. Lin, Pingping Xie, Mingyue Chen, Shuntai Zhou, W. Higgins, Cheng-Zhi Zou, Quanhua Liu, Yong Chen, Yong Han, L. Cucurull, R. Reynolds, Glenn Rutledge, Mitch goLdberg (2010)
The NCEP Climate Forecast System ReanalysisBulletin of the American Meteorological Society, 91
Kaicun Wang, S. Liang (2009)
Evaluation of ASTER and MODIS land surface temperature and emissivity products using long-term surface longwave radiation observations at SURFRAD sitesRemote Sensing of Environment, 113
S. Hannon, L. Strow, W. McMillan (1996)
Atmospheric infrared fast transmittance models: a comparison of two approaches, 2830
A. Pinheiro, J. Privette, R. Mahoney, C. Tucker (2004)
Directional effects in a daily AVHRR land surface temperature dataset over AfricaIEEE Transactions on Geoscience and Remote Sensing, 42
Noaa Nesdis (2010)
GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document For Land Surface Temperature
Yunyue Yu, D. Tarpley, J. Privette, M. Goldberg, M. Raja, K. Vinnikov, Hui Xu (2009)
Developing Algorithm for Operational GOES-R Land Surface Temperature ProductIEEE Transactions on Geoscience and Remote Sensing, 47
J. Tarpley (1994)
Monthly Evapotranspiration from Satellite and Conventional Meteorological ObservationsJournal of Climate, 7
P. Minnis, M. Khaiyer (2000)
Anisotropy of Land Surface Skin Temperature Derived from Satellite DataJournal of Applied Meteorology, 39
C. Rao, J. Sullivan, C. Walton, James Brown, R. Evans (1993)
Nonlinearity corrections for the thermal infrared channels of the advanced very high resolution radiometer: assessment and recommendations
Kaicun Wang, Z. Wan, Pucai Wang, M. Sparrow, Jing-miao Liu, Xiuji Zhou, S. Haginoya (2005)
Estimation of surface long wave radiation and broadband emissivity using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature//emissivity productsJournal of Geophysical Research, 110
G. Diak, J. Mecikalski, Martha Anderson, J. Norman, W. Kustas, R. Torn, Rebecca Dewolf (2004)
Estimating land surface energy budgets from space: Review and current efforts at the University of Wisconsin-Madison and USDA-ARSBulletin of the American Meteorological Society, 85
S. Seemann, E. Borbas, R. Knuteson, G. Stephenson, Hung-Lung Huang (2008)
Development of a Global Infrared Land Surface Emissivity Database for Application to Clear Sky Sounding Retrievals from Multispectral Satellite Radiance MeasurementsJournal of Applied Meteorology and Climatology, 47
Because of spectral shifts from instrument to instrument in the operational NOAA satellite imager longwave infrared channels, the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) has developed a single-channel land surface temperature (LST) algorithm based on the observed 11- μ m radiances, numerical weather prediction data, and radiative transfer modeling that allows for consistent results from the Geostationary Operational Environmental Satellite-I/L (GOES-I/L), GOES-M–P, and Advanced Very High Resolution Radiometer (AVHRR)/1 through 3 sensor versions. This approach is implemented in the real-time NESDIS processing systems (GOES Surface and Insolation Products (GSIP) and Clouds from AVHRR Extended (CLAVR-x)), and in the Pathfinder Atmospheres–Extended (PATMOS-x) climate dataset. An analysis of the PATMOS-x LST against that derived from the upwelling broadband longwave flux at each Surface Radiation Network (SURFRAD) site showed that biases in PATMOS-x were approximately 1 K or less. The standard deviations of the PATMOS-x minus SURFRAD LST biases are generally 2.5 K or less at all sites for all sensors. Using the PATMOS-x minus SURFRAD LST distributions to validate the PATMOS-x cloud detection, the PATMOS-x cloud probability of correct detection values were shown to meet the GOES-R specifications for all sites.
Journal of Atmospheric and Oceanic Technology – American Meteorological Society
Published: Feb 11, 2013
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.