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Lubin, D.  2004.  Thermodynamic phase of maritime Antarctic clouds from FTIR and supplementary radiometric data. Journal of Geophysical Research-Atmospheres. 109   10.1029/2003jd003979   AbstractWebsite

A Fourier Transform Infrared (FTIR) spectroradiometer was deployed at Palmer Station, Antarctica, from 1 September to 17 November 1991. This instrument is similar to the Atmospheric Emitted Radiance Interferometer (AERI) deployed with the U. S. Department of Energy Atmospheric Radiation Measurement (ARM) program. The instrument measured downwelling zenith radiance in the spectral interval 400 2000 cm(-1), at a resolution of 1 cm(-1). The spectral radiance measurements, which can be expressed as spectral brightness temperature T-b(nu), contain information about cloud optical properties in the middle infrared window (800-1200 cm(-1) 1, 8.3-12.5 mm). In this study, this information is exploited to (1) provide additional characterization of Antarctic cloud radiative properties, and (2) demonstrate how multisensor analysis of ARM data can potentially retrieve cloud thermodynamic phase. Radiative transfer simulations demonstrate how T-b(nu) is a function of cloud optical depth tau, effective particle radius r(e), and thermodynamic phase. For typical values of tau and r(e), the effect of increasing the ice fraction of the total optical depth is to flatten the slope of T-b(nu) between 800 1000 cm(-1). For optically thin clouds (tau similar to 3) and larger ice particles (re(ice) > 50 mm) the behavior of T-b(nu) in this interval switches from a decrease with increasing wavenumber n to an increase with nu, once the ice fraction of the total optical depth exceeds similar to0.7. The FTIR spectra alone cannot be interpreted to obtain thermodynamic phase, because a relatively small slope in T-b(nu) between 800-1000 cm(-1) could represent either an optically thin cloud in the ice or mixed phase, or an optically thick cloud radiating as a blackbody. Sky observations and ancillary radiometric data are needed to sort the FTIR spectra into categories of small cloud optical depth, where the mid-IR window data can be interpreted; and larger cloud optical depth, where the FTIR data contain information only about cloud base temperature. Spectral solar ultraviolet (UV) irradiance measurements from the U. S. National Science Foundation's UV Monitor at Palmer Station are used to estimate area-averaged effective cloud optical depth tau(sw), and these estimates are used to sort the FTIR data. FTIR measurements with colocated tau(sw) < 16 are interpreted to estimate cloud thermodynamic phase. Precipitating cloud decks generally show flatter slopes in T-b(ν), consistent with the ice or mixed phase. Altostratus decks show a larger range in T-b(ν) slope than low cloud decks, including increasing slopes with ν, suggesting a more likely occurrence of the ice phase. This study illustrates how cloud thermodynamic phase can be defensibly retrieved from FTIR data if high quality shortwave radiometric data are also available to sort the FTIR measurements by cloud opacity, and both data types are available at the ARM sites.

Lubin, D, Garrity C, Ramseier RO, Whritner RH.  1997.  Total sea ice concentration retrieval from the SSM/I 85.5 GHz channels during the Arctic summer. Remote Sensing of Environment. 62:63-76.   10.1016/s0034-4257(97)00081-3   AbstractWebsite

During the 1994 Arctic Ocean Section, a joint voyage across the Arctic Ocean, by the U.S. Coast Guard Cutter Polar Sea and the Canadian Coast Guard Ship Louis S. St.-Laurent, telemetry from the Defense Meteorological Satellite Program (DMSP) polar orbiters was tracked by a shipboard antenna. Special Sensor Microwave Imager (SSM/I) data was used to generate maps of total sea. ice concentration, using the NASA Team algorithm with the 19 GHz and 37 GHz channels, and using a polarization-based algorithm with the 85.5 GHz channels. When compared with shipboard ice observations, the total sea ice concentration estimated from the 85.5 GHz algorithm are at least as accurate as those from the algorithm that uses only the lower SSM/I frequencies, despite the potential for greater difficulty in dealing with cloud liquid water contamination in the 85.5 GHz signal during the Arctic summer. Near the edge of the ice pack, the 85.5 GHz algorithm often provided more accurate estimates of total ice concentration when compared with surface observations, most likely because of the finer grid spacing at 85.5 GHz (12.5 km vs. 25 km for 37 GHz). However, when using the 85.5 GHz algorithm over regions of lower ice concentration, the reference polarizations in a given image must be chosen with care because over lower sea ice concentration the polarization-based algorithm is more sensitive to cloud opacity and can easily and substantially underestimate the ice concentration. The 85.5 GHz total sea ice retrievals are compared with in situ snow wetness measurements. This comparison suggests that, despite the higher atmospheric opacity at 85.5 GHz, information about sea ice surface properties that affect emissivity can be obtained from these SSM/I channels. (C) Elsevier Science Inc., 1997.

Berque, J, Lubin D, Somerville RCJ.  2011.  Transect method for Antarctic cloud property retrieval using AVHRR data. International Journal of Remote Sensing. 32:2887-2903.   10.1080/01431161003745624   AbstractWebsite

For studies of Antarctic climate change, the Advanced Very High Resolution Radiometer (AVHRR) offers a time series spanning more than two decades, with numerous overpasses per day from converging polar orbits, and with radiometrically calibrated thermal infrared channels. However, over the Antarctic Plateau, standard multispectral application of AVHRR data for cloud optical property retrieval with individual pixels is problematic due to poor scene contrasts and measurement uncertainties. We present a method that takes advantage of rapid changes in radiances at well-defined cloud boundaries. We examine a transect of AVHRR-measured radiances in the three thermal infrared channels across a boundary between cloudy and cloud-free parts of the image. Using scatter diagrams, made from the data along this transect, of the brightness temperature differences between channels 3 and 4, and channels 4 and 5, it is possible to fit families of radiative transfer solutions to the data to estimate cloud effective temperature, thermodynamic phase, and effective particle radius. The major approximation with this method is that along such a transect, cloud water path has considerable spatial variability, while effective radius, phase, and cloud temperature have much less variability. To illustrate this method, two AVHRR images centred about the South Pole are analysed. The two images are chosen based on their differing contrasts in brightness temperature between clear and cloud-filled pixels, to demonstrate that our method can work with varying cloud top heights. In one image the data are consistent with radiative transfer simulations using ice cloud. In the other, the data are inconsistent with ice cloud and are well simulated with supercooled liquid water cloud at 241.5 K. This method therefore has potential for climatological investigation of the radiatively important phase transition in the extremely cold and pristine Antarctic environment.

Bromwich, DH, Nicolas JP, Hines KM, Kay JE, Key EL, Lazzara MA, Lubin D, McFarquhar GM, Gorodetskaya IV, Grosvenor DP, Lachlan-Cope T, van Lipzig NPM.  2012.  Tropospheric clouds in Antarctica. Reviews of Geophysics. 50   10.1029/2011rg000363   AbstractWebsite

Compared to other regions, little is known about clouds in Antarctica. This arises in part from the challenging deployment of instrumentation in this remote and harsh environment and from the limitations of traditional satellite passive remote sensing over the polar regions. Yet clouds have a critical influence on the ice sheet's radiation budget and its surface mass balance. The extremely low temperatures, absolute humidity levels, and aerosol concentrations found in Antarctica create unique conditions for cloud formation that greatly differ from those encountered in other regions, including the Arctic. During the first decade of the 21st century, new results from field studies, the advent of cloud observations from spaceborne active sensors, and improvements in cloud parameterizations in numerical models have contributed to significant advances in our understanding of Antarctic clouds. This review covers four main topics: (1) observational methods and instruments, (2) the seasonal and interannual variability of cloud amounts, (3) the microphysical properties of clouds and aerosols, and (4) cloud representation in global and regional numerical models. Aside from a synthesis of the existing literature, novel insights are also presented. A new climatology of clouds over Antarctica and the Southern Ocean is derived from combined measurements of the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites. This climatology is used to assess the forecast cloud amounts in 20th century global climate model simulations. While cloud monitoring over Antarctica from space has proved essential to the recent advances, the review concludes by emphasizing the need for additional in situ measurements.