Abstract
Abstract. Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.
Highlights
Predictions of future climate change and its regional and global impacts require that a better understanding of the radiative transfer interactions between clouds, water vapor and precipitation are incorporated into appropriate models
The passive Deff retrievals show a roughly similar trend from 20:00 to 23:00. The insensitivity of the latter retrieval to larger size particles during the period from about 19:00 to 22:30 and the sudden jump in retrieved Deff value after that time is the result of the type of asymptotic ceiling that one sees in Fig. 3b and the choices made in the lookup table (LUT) algorithm retrieval: as one approaches the asymptotic ceiling from smaller Deff values, there is clearly a progressive increase in the range of acceptable Deff values for a given
Our retrieval technique was applied to 150 thin ice clouds measured at the Polar Environment Atmospheric Research Laboratory (PEARL) observatory (Nunavut, Canada)
Summary
Predictions of future climate change and its regional and global impacts require that a better understanding of the radiative transfer interactions between clouds, water vapor and precipitation are incorporated into appropriate models. Recent CMIP5 model intercomparisons (the Coupled Model Intercomparison Project as described in Jiang et al, 2012) indicate large variability in ice cloud parameters (for example ice water content) amongst high-latitude models. Shortcomings in ice cloud parameterization (Baran, 2012) impact their representation of radiative effects as well as water cycles and lead to uncertainties in quantifying cloud feedbacks in the context of climate change (Waliser et al, 2009). Highaltitude thin ice clouds consisting of pure ice crystals, which cover between 20 to 40 % of the Earth (Wylie and Menzel, 1999), can, for example, have opposing effects on the radiative properties of the Earth. The macrophysical and microphysical properties of thin ice clouds deter-
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