(One of the) Wizards at PredictWind - Dr. Jack Katzfey - Interview

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  • Опубликовано: 8 сен 2024

Комментарии • 10

  • @bombadil776
    @bombadil776 3 года назад

    Years of watching the O'Kelly's and now Nick is talking about DEs. Love it.

  • @HandyMan657
    @HandyMan657 3 года назад +2

    Nice, loving these videos. Thanks for making videos that educate us. Cheers bud.

  • @katzfeys
    @katzfeys 3 года назад +1

    Great talk uncle Jack!

  • @bearparts
    @bearparts 3 года назад +1

    I enjoy these "forecast" tech vids, something I need to learn more about. Thanks!

  • @Peter_Herrman
    @Peter_Herrman 3 года назад

    My synoptic modeling parametrically study of gridology and ECMWF causes non-hydrostatic adibiatic gradients in my 8K computationally forecasted fronts every time I try to reef the main. Why is that? Wonderful to see great minds geeking out together! I may not understand it all, but I definitely appreciate the enthusiasm. I have to go do some diffy Q's now...

  • @IrishPirateMusic
    @IrishPirateMusic 3 года назад

    Thanks for putting in the effort to produce these very interesting videos.

  • @rickpatrinellis6558
    @rickpatrinellis6558 3 года назад

    I really enjoyed this video and gained some insight about what goes into the modeling to provide the predictions that Predict Wind Offshore gives us. I was hoping that there would be some discussion on CAPE and the significance it brings to a passage forecast.
    Cruising in the South Pacific we have been reminded more than once of how important a consideration it is. Thanks for the video!

  • @herbdesson6843
    @herbdesson6843 3 года назад

    Thank​ you​ for​ this.​ Given that​ you​ can​ see​ weather​ 8​ kilometers​ away, how​ much​ value​ do​ you​ think​ the​ pro​ version​ has? Also, do​ any​ models have​ confidence​ intervals​ for​ wind​speed?

  • @sailinglacasablanca
    @sailinglacasablanca 3 года назад

    Great talk. Was wondering if or how much machine learning (as used in AI) was used with weather modeling and came across a good article spacenews.com/ai-for-earth-observation-and-numerical-weather-prediction/ which basically echoed the computational resource and big data challenges, but looks like there could be big advances assuming these issues can be resolved over time.