This module, part of the "NWP Training Series: Effective Use of NWP in the Forecast Process", explores how NWP models handle both grid-scale microphysical (precipitation) and convective processes through parameterizations and/or explicit methods, with an emphasis on how model treatment (and errors in the triggering) of these processes affects forecast depiction of precipitation and related forecast variables.
Back in 2000, the subject matter expert for this module was Dr. Ralph Petersen of the National Centers for Environmental Prediction, Environmental Modeling Center (NCEP/EMC). Revisions to the module were made in 2009 by Drs. Bill Bua and Stephen Jascourt, from the NWP team at UCAR/COMET.
After taking this module, the student should be able to:
State the primary purpose of microphysical and convective parameterization schemes in NWP models and the forecast variables directly impacted by them.
Demonstrate knowledge of the differences between simple and complex cloud microphysics schemes.
Adjust sensible weather forecast variables such as 2-m temperature when an NWP forecast contains cloud errors resulting from misforecast mesoscale convective features.
State the impacts of over- and underactive convective schemes on NWP forecasts.
Identify the types of precipitation features that can be forecast well by microphysics schemes.
Identify the elements in NWP models that have the most significant impact on precipitation forecasts in large-scale models.
Identify the characteristics of NWP forecasts using explicitly predicted convection.
June 2020 - The lesson was updated to current internet standards (mp4/html5), with no changes to content.
July 2014: Version 2 of the NWP course is still valid throughout. The most recent data assimilation system used in NCEP models, the Hybrid-EnKF, is not included. This data assimilation system combines 3D-VAR and EnKF into a single system and gets advantages from both.
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