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Lubin, D, Jensen EH.  1995.  Effects of Clouds and Stratospheric Ozone Depletion on Ultraviolet-Radiation Trends. Nature. 377:710-713.   10.1038/377710a0   AbstractWebsite

ANTHROPOGENIC depletion of ozone in the lower stratosphere has been of global environmental concern for two decades, but the environmentally relevant quantity-the flux of solar ultraviolet radiation (UVR) reading the Earth's surface-remains poorly quantified on a global basis. The three most important parameters governing surface UVR fluxes and trends are solar elevation, total vertically integrated ozone abundance and cloud opacity. Here we use global satellite measurements of total ozone abundance and cloud reflectance to examine how the trends in UVR resulting from established trends in total ozone abundance(1,2) compare with the potentially large natural variability in UVR that results from variations in cloud opacity. We find that throughout many temperate regions-including large parts of continental Europe, North and South America, New Zealand, Australia and southern Africa-interannual variability in cloud opacity is sufficiently small that by the end of this century, trends in summer average local-noon UVR dose rates relevant to mammalian skin cancer or plant damage should be significant with respect to cloud variability.

Xiong, XZ, Li W, Lubin D, Stamnes K.  2002.  Evaluating the principles of cloud remote sensing with AVHRR and MAS imagery over SHEBA. Journal of Geophysical Research-Oceans. 107   10.1029/2000jc000424   AbstractWebsite

[1] A rigorous discrete ordinates radiative transfer formulation has been applied to two Advanced Very High Resolution Radiometer (AVHRR) images extracted from telemetry collected by the CCGS Des Groseilliers satellite tracking system during SHEBA to estimate cloud optical depth and effective radius of the cloud droplet size distribution. The two cases, from 2 and 3 June 1998, were chosen for analysis because (1) the images contained mostly liquid water clouds and (2) contemporaneous MODIS Airborne Simulator (MAS) overflight imagery was available for these AVHRR overpasses. The objective is to apply the same detailed radiative transfer formulation to both the MAS and AVHRR data so that the quality of the retrievals from the latter can be evaluated. Retrievals of cloud optical properties from MAS are assumed to be more reliable, because (1) all MAS channels have direct radiometric calibration, (2) the higher spatial resolution of MAS (50 m nadir versus 1.1 km nadir with AVHRR) should yield smaller uncertainties related to partially cloudy pixels in a given study area, and (3) effective droplet radius can be retrieved directly from the MAS 1.62-mum m channel without additional uncertainties involved with subtracting a thermal radiance component. Examination of the retrievals from both sensors in these two cases reveals considerable spatial variability (more than a factor of 2) in cloud optical depth, on a variety of scales ranging from tens of meters to tens of kilometers, even for relatively uniform liquid water clouds. Retrievals of cloud effective droplet radius from AVHRR are generally consistent with those from MAS, suggesting that AVHRR can be reliably used to estimate this quantity. However, AVHRR-based retrievals of cloud optical depth are subject to large errors that result from small uncertainties in the absolute radiometric calibration of AVHRR channel 2. Using recalibration coefficients from one of the more robust AVHRR postlaunch calibration efforts, the cloud optical depths that we retrieved from NOAA 14 AVHRR channel 2 are consistently 30-50% larger than those obtained from MAS. The intercomparison of MAS and AVHRR retrievals of cloud optical depth also revealed errors with AVHRR due to partial cloud cover, and these errors are not immediately apparent when examining the AVHRR retrievals alone. If the AVHRR retrievals are averaged to spatial resolutions of order 10-30 km, they appear to become more stable for use in applications such as atmospheric energy budget calculations.

Lubin, D, Morrow E.  1998.  Evaluation of an AVHRR cloud detection and classification method over the Central Arctic Ocean. Journal of Applied Meteorology. 37:166-183.   10.1175/1520-0450(1998)037<0166:eoaacd>2.0.co;2   AbstractWebsite

A cloud classification method that uses both multispectral and textural features with a maximum likelihood discriminator is applied to full-resolution AVHRR (Advanced Very High Resolution Radiometer) data from 100 NOAA polar-orbiter overpasses tracked from an icebreaker during the 1994 Arctic Ocean Section. The cloud classification method is applied to the 32 x 32 pixel cell centered about the ship's position during each overpass. These overpasses have matching surface weather observations in the form of all-sky photographs or, during a period of heavy weather, an objective record that the sky was overcast with low water clouds. The cloud classifications from the maximum likelihood method are compared with the surface weather observations to determine if the automated satellite cloud classifier actually produces realistic descriptions of the scene. These comparisons are favorable in most cases, with the exception of a frequent error in which the classifier confuses Ci/Cc/Ac with extensive low water clouds over sea ice. This overall evaluation does not change appreciably if global area coverage resolution is used instead of full resolution or if the authors attempt to recalibrate the data to the NOAA-7 data for which the algorithm was originally developed. The authors find that the Ci/Cc/Ac cloud error can usually be avoided by 1) modifying the textural feature values for some cloud-over-ice categories and 2) applying a threshold value of 30% to the AVHRR channel 2 albedo averaged over the cell (and normalized by the cosine of the solar zenith angle). For a cell that the classifier identifies as containing Ci/Cc/Ac over sea ice, a cell-average channel 2 albedo greater than 30% usually indicates that the cell instead contains extensive low water clouds. When compared to the surface weather observations, the skill score of the satellite cloud classifier thus modified is 81%, which is very close to that claimed by its original author, This study suggests that satellite cloud detection and classification schemes based on both spectral signatures and texture recognition may indeed yield realistic results.

Lubin, D, Vogelmann AM.  2007.  Expected magnitude of the aerosol shortwave indirect effect in springtime Arctic liquid water clouds. Geophysical Research Letters. 34   10.1029/2006gl028750   AbstractWebsite

Radiative transfer simulations are used to assess the expected magnitude of the diurnally-averaged shortwave aerosol first indirect effect in Arctic liquid water clouds, in the context of recently discovered longwave surface heating of order 3 to 8 W m(-2) by this same aerosol effect detected at the Barrow, Alaska, ARM Site. We find that during March and April, shortwave surface cooling by the first indirect effect is comparable in magnitude to the longwave surface heating. During May and June, the shortwave surface cooling exceeds the longwave heating. Due to multiple reflection of photons between the snow or sea ice surface and cloud base, the shortwave first indirect effect may be easier to detect in surface radiation measurements than from space.