The expected performance of cloud optical and microphysical properties derived from Suomi NPP VIIRS day/night band lunar reflectance

Journal of Geophysical Research Atmospheres

Volumn 118, Issue 23, 2013, Pages 13,230-13,240

  Walther, Andi ^a   Heidinger, Andrew K ^b   Miller, Steven ^c  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b NOAA/NESDIS/Center for Satellite Applications and Research   (United States)

^c Veterinary Dentistry and Oral Surgery   (United States)

Author keywords

clouds; remote sensing; VIIRS

Indexed keywords

ALGORITHMS; CLIMATE CHANGE; CLOUDS; INFRARED DETECTORS; INFRARED IMAGING; OPTICAL PROPERTIES; PARTICLE SIZE; REFLECTION; REMOTE SENSING;

CLOUD OPTICAL PROPERTIES; CLOUD OPTICAL THICKNESS; DEFENSE METEOROLOGICAL SATELLITE PROGRAMS; GLOBAL DATA RECORDS; MICROPHYSICAL PROPERTY; RADIANCE MEASUREMENT; VIIRS; VISIBLE INFRARED IMAGING RADIOMETER SUITES;

MOON;

ALGORITHM; CLOUD MICROPHYSICS; OPTICAL PROPERTY; PERFORMANCE ASSESSMENT; RADIOMETER; REFLECTANCE; SATELLITE DATA; SENSOR;

EID: 84891274035     PISSN: None     EISSN: 21698996     Source Type: Journal    
DOI: 10.1002/2013JD020478     Document Type: Article

References (19)

1. Elvidge, C. D., K. E. Baugh, E. A. Kihn, H. W. Kroehl, E. R. Davis, and, C. W. Davis, (1997), Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption, Int. J. Remote Sens., 18 (6), 1373-1379.
2. Goddard Space Flight Center (2012), Joint Polar Satellite System (JPSS) VIIRS Radiometric Calibration Algorithm Theoretical Basis Document (ATBD), Rev. B, May 25, 2012 [available online at http://npp.gsfc.nasa.gov].
3. Heidinger, A. K., (2003), Rapid daytime estimation of cloud properties over a large area from radiance distributions, J. Atmos. Oceanic Technol., 20, 1237-1250.
4. Heidinger, A. K., and, M. J. Pavolonis, (2009), Gazing at cirrus clouds for 25 years through a split window, Part 1: Methodology, J. Appl. Meteorol. Climatol., 48 (6), 1100-1116.
5. Heidinger, A. K., A. T. Evan, M. J. Foster, and, A. Walther, (2012), A naive Bayesian cloud-detection scheme derived from CALIPSO and applied within PATMOS-x, J. Appl. Meteorol. Climatol., 51, 1129-1144.
6. Miller, S. D., (2001), Physical decoupling of the GOES daytime 3.9-um channel thermal emission and solar reflection components using total solar eclipse data, Int. Journal of Remote Sensing, 22 (1), 9-34.
7. Miller, S. D., and, R. E. Turner, (2009), A dynamic lunar spectral irradiance dataset for NPOESS/VIIRS Day/Night Band nighttime environmental applications, IEEE Trans. Geosci. Remote Sens., 47 (7), 2316-2329, doi: 10.1109/TGRS.2009.2012696.
8. Miller, S. D., S. P. Mills, C. D. Elvidge, D. T. Lindsey, T. F. Lee, and, J. D. Hawkins, (2012), Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities, Proc. Natl. Acad. Sci. U. S. A., 109 (39), 15,706-15,711.
9. Minnis, P., D. P. Garber, D. F. Young, R. F. Arduini, and, Y. Takano, (1998), Parameterization of reflectance and effective emittance for satellite remote sensing of cloud properties, J. Atmos. Sci., 55, 3313-3339.
10. Nakajima, T., and, M. D. King, (1990), Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: Theory, J. Atmos. Sci., 47, 1878-1893, doi: 10.1175/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2.
11. Pavolonis, M. J., A. K. Heidinger, and, T. Uttal, (2005), Daytime global cloud typing from AVHRR and VIIRS: Algorithm description, validation, and comparisons, J. Appl. Meteorol., 44, 804-826.
12. Platnick, S., and, F. P. J. Valero, (1995), A validation of a satellite cloud retrieval during ASTEX, J. Atmos. Sci., 52, 2985-3001, doi: 10.1175/1520-0469(1995)052<2985:AVOASC>2.0.CO;2.
13. Rodgers, C., (1976), Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation, Rev. Geophys., 14 (4), doi: 10.1029/RG014i004p00609.
14. Roebeling, R. A., A. J. Feijt, and, P. Stammes, (2006), Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17, J. Geophys. Res., 111, D20210, doi: 10.1029/2005JD006990.
15. Saha, S., et al. (2010), The NCEP climate forecast system, Bull. Am. Meteorol. Soc., 91, 1015-1057.
16. Schueler, C., T. F. Lee, and, S. D. Miller, (2013), VIIRS constant spatial-resolution advantages, Int. J. Remote Sens., 34 (16), 5761-5777.
17. Seemann, S. W., E. E. Borbas, R. O. Knuteson, G. R. Stephenson, and, H.-L. Huang, (2008), Development of a global infrared land surface emissivity database for application to clear sky sounding retrievals from multi-spectral satellite radiance measurements, J. Appl. Meteorol. Climatol., 47, 108-123.
18. Walther, A., and, A. K. Heidinger, (2012), Implementation of the daytime cloud optical and microphysical properties algorithm (DCOMP) in PATMOS-x, J. Appl. Meteorol. Climatol., 51, 1371-1390.
19. Wood, R., (2012), Stratocumulus clouds, Mon. Weather Rev., 140, 2373-2423.