Search the Community
Showing results for tags 'Data Assimilation'.
Found 1 result
Instead of derailing multiple threads, I thought it might be good to have a separate thread for questions and related discussion on numerical weather prediction. I'll start with a few from a recent thread. A few things. For one, data assimilation is an incremental, cumulative process. You are exactly right in that observations are combined with a short term model forecast in as optimal way as possible. In your example, if no observations were assimilated into the 18Z cycle, the 18Z forecast would be identical to the 12Z forecast. There are some technicalities such as the use of later data cut-offs and a catch-up cycle that render this to be not exactly true, but from a conceptual point of view, it is. To your specific questions: What do you mean by "data collection techniques" and "why do we collect so frequently if not critical"? There is such a huge variety of atmospheric observations that are continuously collected. While true that things like radiosondes and surface metars are recorded with a certain cadence, most observations are actually quasi-continuous and/or with a much higher temporal frequency. This is true for radars, satellite sounders, gps radio occultation, etc. Here is an example of observations assimilated within a +/- 3 hour window around 12Z for metars, ships, buoys, radiosondes, satellite AMVs, aircraft, radar winds, wind profilers, pibals, and scatterometer winds: Here is a view of the satellite coverage for the polar orbiters for that same period color coded by satellite: Ignore the bottom right panel for the geo satellites as there is a bunch of stuff missing. Keep in mind that each of these satellites has a variety of sensors on them, some of which actually have thousands of IR channels to get information from different parts of the vertical (AIRS, IASI, and CRIS). All of the polar orbiters have a MW sounder with 15-22 channels which are critical for NWP. There are millions of observations that are assimilated into a single cycle. ECMWF has a pretty good page for looking at data distributions that go into their cycles: http://www.ecmwf.int/en/forecasts/charts/monitoring/dcover For example, here is a plot from their page showing the coverage of another type of satellite observations: gps radio occultation: