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Multi-sensor Advection Diffusion nowCast (MADCast) for cloud analysis and short-term prediction

by Descombes, Gaël; Auligné, Thomas; Lin, Hui-Chuan; Xu, Dongmei; Schwartz, Craig; Vandenberghe, François; National Center for Atmospheric Research (U.S.) Research Applications laboratory, .
Series: NCAR technical note ; NCAR/TN-509+STR. Publisher: Boulder, Colo. : National Center for Atmospheric Research, 2014ISSN: 2153-2397; 2153-2400.Subject(s): MADCast | Numerical Weather Prediction | Cloud Fraction Retrieval | Cloud nowcastingOnline resources: Click here to access online Summary: A new approach designed for the analysis and short-term forecasting of clouds,called Multi-sensor Advection-Diffusion nowCast (MADCast), has been implemented within the Weather Research and Forecasting (WRF) model and data assimilation platforms. In thisapproach, profiles of cloud fractions are retrieved from multiple infrared sensors using the Multivariate Minimum Residual (MMR) scheme. These profiles are then projected to the grid of the numerical weather prediction model, which is used to dynamically transport and diffuse the clouds in three dimensions.
Item type Location Call number Status Date due
REPORT REPORT Mesa Lab 03710 (Browse shelf) Available

2014 July

A new approach designed for the analysis and short-term forecasting of clouds,called Multi-sensor Advection-Diffusion nowCast (MADCast), has been implemented within the Weather Research and Forecasting (WRF) model and data assimilation platforms. In thisapproach, profiles of cloud fractions are retrieved from multiple infrared sensors using the Multivariate Minimum Residual (MMR) scheme. These profiles are then projected to the grid of the numerical weather prediction model, which is used to dynamically transport and diffuse the clouds in three dimensions.

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