Tuesday, 24 January 2017
4E (Washington State Convention Center )
The mixing layer height (MLH) is an important parameter in the evaluation of wind gusts, turbulence, and aerosol dispersion in numerical weather prediction (NWP) models. It is also one of the most challenging parameters to represent accurately within NWP, especially in the Arctic where limited observations are available for model development and evaluation. In an effort to improve weather forecast services in the Arctic, Environment and Climate Change Canada established a comprehensive automated and continuous weather observation site located next to the Iqaluit airport, Nunavut (64oN, 69oW), in the winter of 2016. New data products from a Vaisala CL31 ceilometer and HALO Photonics Doppler lidar are used to evaluate the High Resolution Deterministic Prediction System (HRDPS) MLH at Iqaluit under a variety of weather conditions. The minimum first derivative of Gaussian-filtered backscatter profiles is calculated to estimate depth and variability of the MLH from ceilometer and Doppler lidar backscatter profiles. Modeled and ground-based MLHs are further compared to MLHs derived from twice-daily radiosonde profiles launched at the Iqaluit site. Under clear-sky conditions, modeled and ground-based MLHs show good agreement, with greater MLH variability observed by the ceilometer. Case studies suggest that backscatter-based MLH retrieval produces higher MLH values in overcast conditions compared to radiosonde and modeled estimates, which highlights the challenge this method has in differentiating between MLH and cloud base height. During blowing snow conditions, ceilometer and lidar MLH estimates correspond well with the top of the blowing snow layer, and are in good agreement with HRDPS MLH output. Case studies where modelled MLH significantly differs from observations provide a basis for future work on MLH parameterization in the Arctic.
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