Communicating Forecast Uncertainty

Communicating Forecast Uncertainty
gsb12 2019-11-09 18:54:06

Great course.
kclink25 2018-07-24 14:07:49

good course
limpdoc 2018-04-30 05:36:29

Helped me to understand the two-way communication better between end users and forecaster.
2018-04-11 20:44:05

Just not a fan of the format.
donaldrsbr 2018-01-12 13:29:00

2017-12-12 11:08:44

Gives a great idea as to what end users are looking for and how you can alter you DSS to fit their needs
2017-10-25 17:51:49

This is a good exercise in analyzing ensemble data and then meeting the needs of various users. It is very appropriate for those with limited experience with ensemble data, or little experience handling user inquiries. It provides good illustrations of the diversity of needs of differing user groups.
RichardM-B 2017-10-17 03:26:57

Why is this survey here? It should be at the end of the lesson, rather than after the pre-assessment. I haven't seen enough material to make a judgement on how good the lesson is yet...
Cameron13 2017-10-11 17:30:36

It was good
SPC MP 2017-09-26 15:23:02

All good, interesting and dynamic way of presentations.
dcokely 2017-05-15 11:58:25

I think that the use of mm and cm was occasionally incorrect. It certainly confused the issues of what amounts were both forecast and also important to the user, as forecasts never reached 50cm (of precipitation). Confusion of liquid vs frozen amounts in metric clouded the real effort of making more informative forecasts. Sticking to all-liquid should remove this complication and clarify the data for the course attendee.
rhaynes7 2017-05-01 17:03:28

A well done lesson. Taking the role of the forecaster, it's easy to get swept up in focusing on dynamics and certain aspects of the ensemble forecast and forget the position of decision makers asking for weather variables I don't normally always consider immediately when going about analysis. Not sure how much of the information is pulled via direct correspondence versus polling. Polling may lead to some responses where the user is more willing to give information because they think it might be useful and miss other details because they are thinking solely hypothetically - such as probability of precipitation directly affecting road conditions, especially given how probabilities of precipitation tend to get interpreted. Overall, an excellent lesson, but feel it would be more effective if there was a better segue between switching from the forecast role to the decision making role - perhaps better accomplished with section 5 and 6 swapped about. Will definitely keep the lessons learned in mind though.
antony.wisson 2017-03-13 05:00:47

A useful refresher, can be applied to any meteorological service.
jltharp 2016-11-02 08:11:19

Good module overall and on a topic that many meteorologists need to improve upon. However, I do agree with one of the previous reviews that the use of metric units is not appropriate for this scenario given that it is a US based situation and that most US end users are not going to be looking for metric units.
eric.metzger 2016-10-20 13:08:22

The biggest problem with lesson is the use of the metric system. This not, repeat not, a paper where SI units should be used. This is a lesson to teach "real world" application and in the U.S. decision makers use the British system (miles/feet/inches). This is why the NWS sends out its forecasts and products in the British system and no metric. The metric system makes little sense to a lot of people (the bulk of the end users of weather information in the U.S). In some cases, (T, Precip) the British system is better as it is a higher resolution than the metric. This is a brig deal to power companies (which I have directly supported and they have told me this directly). It much harder for them plan electric loads using C compared to F as one degree C can mean as much as three degrees F in some cases. If the temperature is within their "critical" values, one degree F can mean tens of millions. Image if that was a degree C in the same range. The power company would have a big problem. While we as forecasters understand it, it is important to teach a lesson which directly affects our customers in the units our customers would use.
rmarkey 2016-10-18 11:55:15

Great information and understanding in communicating with the general public concerning uncertainty.
2016-09-20 07:42:08

Not specifically meant for Broadcast Meteorologist but can easily be applied to broadcast forecast communications
Daniel Banks 2016-04-20 12:29:20

Excellent module! This educational module is exactly what is needed for forecasters that have used deterministic forecast processes only to understand the principles and products of Ensembles. Great Job COMET! Dan Banks
JoeCourtney 2016-03-30 19:46:05

Essential for all forecasters.