LuckGrib macOS v3.3 and iOS v1.4 now have support for ensemble statistical information, as well as being able to show the original control member at the same time as the ensemble average. This new ability should be of interest to everyone interested in studying long range weather forecasts
GFS has two parameters representing sea level pressure: PRMSL and MSLET. LuckGrib is using MSLET to represent sea level pressure. This tutorial explains why that is and how the data is delivered to you
The National Blend of Models (NBM) is available in several different domains. The oceanic domain contains probabilistic data, which is an interesting new source of information. This article discusses probabilisic wind data briefly
LuckGrib version 1.2 introduced some new features to help support passage planning. This tutorial demonstrates how some of these functions work, using a passage the author completed in November 2015 as an example.
One of the main scenarios where import directories are intended to be used is when you have your own source of GRIB files and you want LuckGrib to import them with the minimum amount of effort.
The points on weather maps that identify highs and lows have the more general name of stationary point. The discovery and positioning of stationary points is one more area that LuckGrib excels - however this comes with one little caveat, and a bit of an apology…
Math is wonderful. However, if application developers are not careful with how they use it, an application can report wildly incorrect results for common weather features. LuckGrib doesn’t have this problem. Some other GRIB viewers do.
The contours generated by LuckGrib are much higher quality than in most other GRIB viewers. Read on to understand a little more about one of the techniques behind this advantage.
While LuckGrib has been designed to be easy to use, there are still a few things you can learn to make your initial experience more pleasant.