Technological advances will provide new tools for the analysis and forecasting environment that will need to be incorporated into our suite of scientific training. The trend of the operational community towards digital products and services (such as the NWS IFPS) will be a major driver for training requirements. To this end, we expect to incorporate greater use of geographic information systems (GIS) in training the forecast community. The emergence of the high-resolution WRF model and the increasing use of model ensemble forecasts will necessitate an increased emphasis on the utility and limitations of mesoscale models and ensembles in training on the forecast process. High-resolution model output and conceptual models for local/orographic flows will be needed to correct the basic grids that are the starting point for IFPS, for example.
Operational implementation of high-resolution and polarized radar products, as well as the introduction of dozens of new satellite data products, will necessitate continued emphasis on integration of in-situ- and remotely-sensed systems. We are also likely to see an increasing trend toward probabilistic forecast products, especially with the integration of the ensemble approach into many portions of the forecast process.
With so many new tools and data sources becoming available, it is likely that the forecaster will be unable to process all of the information at her/his disposal. As a result, we expect forecasters will need to be trained on what tools are most relevant for particular weather scenarios. Training will need to equip the forecaster with the appropriate knowledge to determine the suite of tools required for the situation at hand. Although a forecast funnel approach will still be valid, we believe that the above scientific and technological advances point to a critical need to update the aging forecast process module to make it relevant to contemporary forecast operations.
With some sponsors considering consolidation of forecast operations, new or updated training approaches must be employed to compensate for the loss of local expertise. We expect to emphasize “best practice” methodology applied to weather forecasting and information management. This will likely be reflected in increased use of highly-interactive simulations such as WES in our scientific training.
In spite of all of the new tools available, our training should never lose sight of the importance of diagnostic analysis and basic principles of weather forecasting. However, with the increased emphasis on customer service, we anticipate some training that will focus on the societal impacts of forecasts as well. In addition, we expect to collaborate with other trainers to give operational training officers much-needed background on effective methodologies to be employed in on-station training of forecasters. This will be essential to the successful delivery of blended learning courses (such as the Distance Learning Aviation Course) to remote forecast sites.
Finally, the sponsor community is demanding greater accountability of training programs and we will need to look for innovative ways to quantify the impact of training on operational forecasting. Historically, this has been a difficult problem for the training community to address, but we expect that multiple sponsors will require it in the next few years. We will look for ways to step beyond simple pre- and post-testing for training modules, perhaps exploring creative use of tools such as WES to give a more thorough assessment of the impacts of our training endeavors.
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