Publications

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2017
Smith, WL, Hansen C, Bucholtz A, Anderson BE, Beckley M, Corbett JG, Cullather RI, Hines KM, Hofton M, Kato S, Lubin D, Moore RH, Rosenhaimer MS, Redemann J, Schmidt S, Scott R, Song S, Barrick JD, Blair JB, Bromwich DH, Brooks C, Chen G, Cornejo H, Corr CA, Ham SH, Kittelman AS, Knappmiller S, LeBlanc S, Loeb NG, Miller C, Nguyen L, Palikonda R, Rabine D, Reid EA, Richter-Menge JA, Pilewswskie P, Shinozuka Y, Spangenberg D, Stackhouse P, Taylor P, Thornhill KL, Van Gilst D, Winstead E.  2017.  ARCTIC RADIATION-ICEBRIDGE SEA AND ICE EXPERIMENT The Arctic Radiant Energy System during the Critical Seasonal Ice Transition. Bulletin of the American Meteorological Society. 98:1399-1426.   10.1175/bams-d-14-00277.1   AbstractWebsite

Through ARISE, NASA acquired unique aircraft data on clouds, atmospheric radiation and sea ice properties during the critical period between the sea ice minimum in late summer and autumn and the commencement of refreezing.

2002
Xiong, XZ, Lubin D, Li W, Stamnes K.  2002.  A critical examination of satellite cloud retrieval from AVHRR in the Arctic using SHEBA data. Journal of Applied Meteorology. 41:1195-1209.   10.1175/1520-0450(2002)041<1195:aceosc>2.0.co;2   AbstractWebsite

This study examines the validity and limitations associated with retrieval of cloud optical depth tau and effective droplet size r(e) in the Arctic from Advanced Very High Resolution Radiometer ( AVHRR) channels 2 (0.725-1.10 mum), 3 (3.55-3.93 mum), and 4 (10.3-11.3 mum). The error in r(e) is found to be normally less than 10%, but the uncertainty in tau can be more than 50% for a 10% uncertainty in the satellite- measured radiance. Model simulations show that the satellite- retrieved cloud optical depth tau(sat) is overestimated by up to 20% if the vertical cloud inhomogeneity is ignored and is underestimated by more than 50% if overlap of cirrus and liquid water clouds is ignored. Under partially cloudy conditions, tau(sat) is larger than that derived from surface-measured downward solar irradiance (tau(surf)) by 40%-130%, depending on cloud-cover fraction. Here, tau(sat) derived from NOAA-14 AVHRR data agrees well with tau(surf) derived from surface measurements of solar irradiance at the Surface Heat Budget of the Arctic Ocean (SHEBA) ice camp in summer, but tau(sat) is about 2.3 times tau(surf) before the onset of snowmelt. This overestimate of tau(sat) is mainly due to the high reflectivity in AVHRR channel 2 over snow/ ice surfaces, the presence of partial cloud cover, and inaccurate representation of the scattering phase function for mixed-phase clouds.

1999
Han, W, Stamnes K, Lubin D.  1999.  Remote sensing of surface and cloud properties in the Arctic from AVHRR measurements. Journal of Applied Meteorology. 38:989-1012.   10.1175/1520-0450(1999)038<0989:rsosac>2.0.co;2   AbstractWebsite

Algorithms to retrieve cloud optical depth and effective radius in the Arctic using Advanced Very High Resolution Radiometer (AVHRR) data are developed, using a comprehensive radiative transfer model in which the atmosphere is coupled to the snowpack. For dark surfaces AVHRR channel 1 is used to derive visible cloud optical depth, while for bright surfaces AVHRR channel 2 is used. Independent inference of cloud effective radius from AVHRR channel 3 (3.75 mu m) allows for derivation cloud liquid water path (proportional to the product of optical depth and effective radius). which is a fundamental parameter of the climate system. The algorithms are based on the recognition that the reflection function of clouds at a nonabsorbing wavelength (such as AVHRR channel 1) in the solar spectrum is primarily a function of cloud optical thickness, whereas the reflection function at a liquid water absorbing wavelength (such as AVHRR channel 3) is primarily a function of cloud particle size. For water clouds over highly reflecting surfaces (snow and ice), the reflectance in AVHRR channel 1 is insensitive to cloud optical depth due to the multiple reflections between cloud base and the underlying surface; channel 2 (0.85 mu m) must be used instead for optical depth retrieval. Water clouds over tundra or ocean are more straightforward cases similar to those found at lower latitudes, and in these cases a comprehensive atmospheric radiative transfer model with a Lambertian surface under cloud is used. Thus, for water cloud over tundra and ocean, channel 1 is used for cloud optical depth retrieval. In all cases, channel 3 is used for independent retrieval of cloud droplet effective radius. The thermal component of channel 3 is estimated by making use of channel 4 (11 mu m) and is subtracted from the total channel 3 radiance. Over clear-sky scenes, the bidirectional reflectance properties of snow are calculated directly by the coupled snowpack-atmosphere model. This results in greater overall accuracy in retrieved surface properties as compared with the simplified approach that uses a Lambertian approximation for the surface albedo. To test the physical soundness of the algorithms the authors have applied them to AVHRR data over Barrow, Alaska, from April to August 1992. Downwelling irradiances at the surface calculated using the retrieved cloud optical depth and effective radius are compared with field irradiance measurements, and encouraging agreement is found. The algorithms are also applied to three areas of about 100-km dimension around Barrow, each having a different underlying surface (ocean, tundra, snow).