What is it about?

Scientists are always looking for a way to improve weather forecast. How do we do it most effectively? The key is to find out the most sensitive element of the weather forecast system. CIRES and NOAA scientists tested the sensitivity of NCEP Global Forecast System to changes in a) the observation input, b) the data assimilation method, and c) the forecast model. In general, the forecast errors were found to be only slightly sensitive to the additional observations during the 2015/16 El Nino event, more sensitive to the data assimilation methods, and most sensitive to the inclusion of stochastic parameterizations in the model. Using the stochastic parameterizations in the forecast model is thus recommended for improving weather forecast.

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Why is it important?

This study described a logical way to find out the most sensitive element of a weather forecast system, which can be used as a guidance for future system development.


If I am going to devote resources to developing future weather forecast system, I would like to first figure out what part of the system can be "fixed" most effectively to provide better weather forecast.

Jih-Wang Wang
University of Colorado

Read the Original

This page is a summary of: Sensitivities of the NCEP Global Forecast System, Monthly Weather Review, April 2019, American Meteorological Society,
DOI: 10.1175/mwr-d-18-0239.1.
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