Instrumentation

1. Retrieving cloud optical depth and ice particle size using thermal infrared radiometry: Application to the monitoring of thin ice clouds in an arctic environment Yann Blanchard, Alain Royer, Norm O’Neill Centre d’Applications et de Recherches en Télédétection, Université de Sherbrooke, QC, Canada Abstract: The cloud optical depth (COD) and ice particle size of thin ice clouds are two key parameters whose variations could strongly influence radiative effects and climate in the Arctic environment. Our objective is to assess the potential of using multi-band thermal radiance measurements of zenith sky radiance for retrieving COD and effective particle diameter (Deff) of thin ice cloud (TIC) in the Arctic. We present preliminary retrievals applied to ground-based thermal infrared data acquired at the high-Arctic PEARL observatory in Eureka, Nunavut, Canada and validated using LIDAR and RADAR data. The results of the retrieval method were used to separate TIC into two types : TIC1 characterized by small crystals (Deff < 30 µm) and TIC2 by large ice crystals (Deff > 30 µm, up to 300 µm). Inversions were performed across two polar winters for 100 TICs. Instrumentation The methodology is based on zenith radiance measurements in 6 channels (8.3, 8.7, 9.1, 10.8, 11.4 and 13µm, as is currently employed in the CIMEL CE-312 radiometer) extracted from band integrated P-AERI spectra (provided by NOAA). The radiance in these bands are sensitive to the COD and ice particle Deff as shown in the MODTRAN brightness temperatures simulations below. • Environmental issues • Thin Ice Clouds (TIC) could have significant climate effects in the Arctic depending on their COD and ice crystal size(Deff). • The presence of sulfuric-acid bearing aerosols (Arctic haze), for example, can significantly change ice-particle formation and precipitation properties leading to significant cooling (relative to the ice-particle generation by more pristine aerosols) during the Polar-winter. This dehydration greenhouse feedback (DGF) effect was proposed by J. P. Blanchet's UQAM group to explain this phenomenon (Blanchet and Girard, Nature, 1994).Two types of thin ice clouds were defined by the UQAM group: • TIC1 : non-polluted (low sulfate aerosols), small crystals (Deff < 30 µm), with slow sedimentation rates. Seen by the LIDAR but not by the RADAR • TIC2 : high sulfate (acidic) aerosols, large ice crystals (Deff > 30 µm, up to 300 µm), fast sedimentation rates. Seen by both LIDAR and RADAR Results, Validation and Monitoring We applied the retrieval algorithm to 100 TICs measured at Eureka and compared the results with the LIDAR and LIDAR/RADAR products. We also studied the occurrence of the TIC1 and TIC2 classes in association with the COD amplitudes, looking for trends in relation to SO42- concentration. COD retrievals Deff retrievals Radiometer Overall accuracy = 82% Methodology Our algorithm is based on a multi-spectral zenith radiance comparison between radiative transfer simulations and measurements. Climatology Comparison with SO42- Study Site Located on Ellesmere Island in the Canadian Arctic (80°N, 86°W), the Polar Environmental Research Laboratory (PEARL) hosts many atmospheric instruments facilitating the validation of our methodology as well as supplying critical supporting data. Comparison between simulations and measurements Thermal infrared measurements 6 channels Cloud Altitude and thickness (from LIDAR) Radiative transfer simulations (using MODTRAN 4) Inversion for COD and Deff Look-up tables built by varying COD and Deff of ice cloud model P, T, Td (from Radiosonde) • In order to validate our methodology, we use : • LIDAR+RADAR products to estimate Deff (Eloranta et al., IGARSS, 2007) • LIDAR inversion to estimate COD Conclusion: By exploiting the sensitivity of multi-band thermal IR radiometry to ice clouds, we showed it is possible to retrieve COD with relatively good accuracy (R²=0.91 and RMSE=0.24) and classify TIC1 / TIC2 clouds with moderate classification accuracy (82%). Results over two winters were validated with respect to LIDAR and RADAR products. Our retrievals (and hopefully future retrievals) permit the monitoring of  the temporal evolution of TICs in the Arctic. Further studies are required to better understand the interaction between aerosols and TICs and subsequently to improve the TIC1/TIC2 classification accuracy. We will continue to investigate the correlation between our retrievals and key auxiliary measurements such as the sulfate concentrations made using the AMS. We acknowledge the technical support of the CANDAC operators at PEARL Supporting institutions Contact e-mail : yann.blanchard@usherbrooke.ca