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Two Types of Ice Clouds (TICs) have been characterized in the Arctic during the polar night and early spring. TIC-1 are composed by non-precipitating small ice crystals of less than 30 µm in diameter. The second type, TIC-2, are characterized by a low concentration of large precipitating ice crystals (>30 µm). Here, we evaluate the Weather Research and Forecasting (WRF) model performance both in space and time after implementing a parameterization based on a stochastic approach dedicated to the simulation of ice clouds in the Arctic. Well documented reference cases provided us in situ data from the spring of 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) campaign over Alaska. Simulations of the microphysical properties of the TIC-2 clouds on 15 and 25 April 2008 (polluted or acidic cases) and TIC-1 clouds on non-polluted cases are compared to DARDAR (raDAR/liDAR) satellite products. Our results show that the stochastic approach based on the classical nucleation theory, with the appropriate contact angle, is better than the original scheme in WRF model to represent TIC-1 and TIC-2 properties (ice crystal concentration and size) in response to the IN acidification.
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Abstract. In the Arctic, during polar night and early spring, ice clouds are separated into two leading types of ice clouds (TICs): (1) TIC1 clouds characterized by a large concentration of very small crystals and TIC2 clouds characterized by a low concentration of large ice crystals. Using a suitable parameterization of heterogeneous ice nucleation is essential for properly representing ice clouds in meteorological and climate models and subsequently understanding their interactions with aerosols and radiation. Here, we describe a new parameterization for ice crystal formation by heterogeneous nucleation in water-subsaturated conditions coupled to aerosol chemistry in the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The parameterization is implemented in the Milbrandt and Yau (2005a, b) two-moment cloud microphysics scheme, and we assess how the WRF-Chem model responds to the run-time interaction between chemistry and the new parameterization. Well-documented reference cases provided us with in situ data from the spring 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) over Alaska. Our analysis reveals that the new parameterization clearly improves the representation of the ice water content (IWC) in polluted or unpolluted air masses and shows the poor performance of the reference parameterization in representing ice clouds with low IWC. The new parameterization is able to represent TIC1 and TIC2 microphysical characteristics at the top of the clouds, where heterogenous ice nucleation is most likely occurring, even with the known bias of simulated aerosols by WRF-Chem over the Arctic.