>jonathan 2019-07-14 19:27:48

Muy bueno el modulo, me ayudo a entender los posibles errores que se pueden encontrar en los diferentes modelos

29445620 2018-02-26 07:42:35

i strongly recommend to others

27848167 2018-02-19 01:42:50

i strongly recommend these lesson to others

Tryan18 2018-01-28 19:34:28

too long!!!!!

kamil 2017-01-17 07:43:22

This is an excellent way to get in touch with model parametrization..

2017-01-17 01:42:51

this course is very good for learning the topic. thanks

ranamatif 2017-01-16 19:29:00

The course is designed properly to understand the topic.

nispo 2012-12-21 18:48:27

This module started out very technical. Much detail is given on very specific Cloud Schemes and Convective Parameterization techniques. These at first seem a little muddled, as each is riddled with strengths and weaknesses that aren't always easy to differentiate. However, as I have found with many of the modules dealing with NWP, once real weather examples are given it all becomes much clearer. This modules gives some situations in which one may have to modify a forecast based on a Convective Parameterization's effect on it. That above all else I found to be the information that came through the strongest.

After taking this module, the student should be able to: 1. State the primary purpose of microphysical and convective parameterization schemes in NWP models and the forecast variables directly impacted by them. 2. Demonstrate knowledge of the differences between simple and complex cloud microphysics schemes. 3. Adjust sensible weather forecast variables such as 2-m temperature when an NWP forecast contains cloud errors resulting from misforecast mesoscale convective features. 4. State the impacts of over- and underactive convective schemes on NWP forecasts. 5. Identify the types of precipitation features that can be forecast well by microphysics schemes. 6. Identify the elements in NWP models that have the most significant impact on precipitation forecasts in large-scale models. 7. Identify the characteristics of NWP forecasts using explicitly predicted convection.

NWP, numerical weather prediction, microphysics, convective parameterization, convection scheme, explicit convection, grid-scale precipitation, grid-scale convection, convective feedback, precipitation, convection, Arakawa-Schubert, Kain-Fritsch, Kuo, Betts-Miller-Janjic, simple cloud, complex cloud

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. More discussion of the Hybrid-EnKF system can be found in the GFS May 2012 "splash' announcement at http://www.meted.ucar.edu/nwp/pcu2/GFS_20120522_HybEnKF3DVAR.htm.