What this is not.

This model is intended purely as research tool, for people who are doing research into sailing a long ocean passage.

Do NOT use this model to obtain forecast data, to answer questions such a “what will the weather be like two weeks from now?” The answer to that question is unknowable.

Do NOT use this model while sailing a passage to get data which is just a little longer in duration. For the first 16 days, the quality of this data is not a good as GFS.

This CFS model is a research tool. Please do not use this data unless you understand its limitations.

Having given those warnings - sailors may find this model extremely useful in planning possible routes for long ocean passages. Feedback on this topic is welcome.

Why provide this model?

It is generally accepted that numerical weather prediction has advanced to the point where the first several days of forecast data is pretty reliable. The global forecast system can produce forecast data for up to 16 days. Nobody would rely on the 16 day forecast accuracy. Its is simply not possible to create accurate weather forecasts this far into the future.

However, when in the initial planning stages of a long ocean passage, it is often more useful to use poor quality data than to have an automated weather router fail to create a route.

Creating a poor quality route can still help with questions such as: roughly how long will this route be? What are some of the possible shapes for the route?

For example, sailors who sail from the mainland of the USA to Hawaii, or back again, in a normal cruising boat, will typically take longer than 16 days to complete their passage. When doing rough, back of the envelope planning, it would be nice if the weather routing system had access to a sufficient amount of wind data so that it could complete most of the potential sailing routes.

What is the CFS?

NOAA has been running a Climate Forecast System for years. This model is meant to provide seasonal guidance.

The CFS produces six months of forecast data. A note on the word forecast. Nobody would use this model to provide information on what the conditions will be at a place and time, far into the future. However, this model does create realistic weather systems which start with the current atmospheric conditions. While the CFS data should not be used as a forecast to answer questions such as “what will the weather be at some far future point in time”, it will produce realistic transitions from day to day, with one weather system changing dynamically into another.

There are no numerical weather prediction (NWP) systems available which can create accurate forecasts six months out. What will the winds be at this point 5 months from now? Who knows. However, if you want to explore traveling through one of the possible weather systems, far into the future, this model can provide a source for that weather data.

A note on the data provided. The CFS does not generate wind data at the surface. The model does produce wind at 1000mb, along with the height of the 1000mb winds above the surface. LuckGrib performs a rough approximation of what the 10m winds would be when given the 1000mb height and winds. This is only a rough approximation. In order for the CFS data to be used by the LuckGrib Weather Routing solver, you must download both the wind and height fields.

How to use it?

This model may be of interest to sailors exploring long passages, not as a way to know what they will experience, but as a way to experiment with many possible different routes and to get a flavor of some of the distances and times involved.

As an example, a sailor planning on sailing from New Zealand to Hawaii, in a cruising boat, may be curious about possible routes, distances and times. This passage may take 40 to 50 days, and there is no way to explore this route using actual forecast data.

Using CFS data, its easy to setup a Weather Routing system to generate departures every few days, starting a few months from now, for a long passage. If 5 or 10 departures are generated, you will obtain a range of possible solutions. There is no route in this range which will be the route you would sail, but the range of answers may help in your understanding the possibilities in the route.

This CFS data can be useful in the pre-planning stages of a passage. When doing actual departure planning, or when making decisions while underway, you will NOT be using the CFS data. Use one of the other weather models to help with actual navigation decisions.

Comparison to an ensemble

There can be a lot of forecast uncertainty when planning a long sailing passage. One of the ways to study uncertainty in LuckGrib is to download all of the available wind fields from the GEFS ensemble, 30 members. If all of these wind fields are used by the Weather Router to generate routes, you can get a feel for the spread of possibilities. None of the routes may be exactly the route which you will sail, but seeing the range of possibilities is useful in studying the passage, while in the pre-planning stage.

The GEFS provides forecast data out to 16 days. CFS provides up to 6 months of data.

Climate averages.

I know of a few Weather Routing systems which can operate on climate data. This is processed data, averaging the conditions at a point through a multi-year data set. This can be useful when studing long routes, however, it does not provide a spread of possibilities.

Averages tend to wash out extremes. When averaging, you tend to filter out maximums and minimums, moving all values toward the middle (by definition.) However, when sailing, its interesting to see some of the possible extremes, the range of possibilities.

You can see this detail loss happening by studying the GEFS ensemble, and watching the mean (average) field and seeing how it relates to the individual members. The average field appears smoother, with no extreme highs or lows. Look into the individual members for the more extreme weather possibilities.

Nobody ever sails in a climate average weather system. Nobody will ever sail in any of the weather systems forecast by CFS either, however the CFS data does represent maximums and minimums, presenting you with more realistic challenges.

Historic data.

The best approach for this problem may be to download actual weather data, from previous years. If you are studying a July departure for some event, if you could gain access to all July data for the previous 10 years, that might be useful.

For now, this remains as a possible future project for LuckGrib. Let me know if you would find this useful (and how much you would be willing to pay for it.)