Grid length and Resolution in Weather Prediction

One of the most important approximations insofar as we sailors are concerned is the Grid Length. NWP cannot calculate the atmosphere as the continuum which it is. Models have to represent the atmosphere at a 3 - dimensional grid of points. The nearer the points are together, the better will the model be able to represent the atmosphere and the topography that is a major driver of effects such as sea breezes on all scales..

There are two limitations to the grid length spacing. First is the computing power available. Secondly, there is the amount of meteorological and topographic information. For day to day forecasting with outlooks for the next few days a global model is needed. At the time of writing these have a grid length, typically, about 25 km (~15 NM) for the Met Office model in June 2010 and planned for the US GFS.

For short period, local forecasting then much smaller grid lengths can be used over smaller areas. The UK Met Office currently runs a meso-scale, limited area model for much of the North Atlantic from the east of the USA to Western Europe. This has a grid length of about 10 km (6 NM). For more detailed very short period forecasts for a few hours ahead then models can be run with even shorter grid lengths. The UK Met Office uses a model with a 4 km (2 NM) grid length model just for the area of the UK. This now has a smaller area nested within it using a 1.5 km (1 NM) grid.

The US Navy runs an operational Coupled Ocean/Atmosphere Meso-scale Prediction System (COAMPS) model with a 6 NM grid length. Meso-scale models are run by a number of research institutions both for research and on behalf of private sector firms.

There are two limitations on the value of such limited or local area models. First, of course, is the computing power that limits the area covered. Computing power requirements increase by a factor of about 16 every time that the grid length is halved. Secondly, there is the uncertainty of what is moving into an area and the effects of large scale weather features which are unlikely, in themselves, to be forecast precisely . The model may be very good at dealing with the local topographic effects on the sea breeze, say, but the results will be compromised if the larger scale model that is bringing cloud across gets the amount of cloud wrong!

An important consequence of the grid length is the size of weather and topographic features that can be described and modelled. As a rough guide, this is between four and five times the grid length. In other words, a 20 NM grid for global models cam only cope with weather and topography some 100 NM size. Such models do not even know that the Isle of Man exists!

As will be seen here, there can be at most two grid points over the IOM and, quite possibly only one. It would need a grid lngth of about 2 NM to give a general outline of the island and, even then, it would not represent the headlands and bays.

With just on grid point over the island, the computer will think that it looks something like this -

Now imagine a 6 NM grid over Torbay or the Solent nd you will see that meso-scale models with hese grid lenghts will not deal with the topography of those areas.

The UK and several other Meso-scale models with 10 KM grid lengths can deal with features down to about 40 - 50 KM. They cannot cope with many of our favourite sailing waters such as the Solent or the Clyde. To model the Tor Bay sea breeze would need a grid length of about 1 KM or less, The Solent would need a model with grid lengths of around 300 metres or less. To model Start Point would need a grid length measures in 10s of metres, perhaps 100 metres at most.

It is all too easily to get carried away by the power of the models and lose sight of the realities of the atmosphere. I would like to think that sailors are able to make sensible use of model output and not be discouraged because GRIB or other objective forecasts do not describe what they observe. There are variations in wind that the best models cannot know exist, let alone predict. I have never worked as a modeller but as a senior forecaster, I have worked with modellers on data input, assimilation and interpretation of output. What follows is based on my discussions with some of the best scientists in the field.

First and foremost, NWP models cannot fully resolve features occurring on the scale of their grid lengths. Consequently there has to be some filtering to remove energy from very short wavelengths. For the same reason, topographic effects must also be smoothed. As a result, information on scales below about 5 grid lengths is damped. If this is not done, then computational noise will swamp the meteorological signal.

Thus a 0.1 degree (6 NM) grid length model provides an un-damped forecast only for features of scale 0.5 degree or more ie 30 NM or more.

I would expect such features to have a natural predictability of, perhaps, 6 to 12 hours at best.

A model with a grid length of 1 or 2 NM will only deal with features between 5 and 10 NM and only for a very few hours. (Just watch a large cumulus cloud grow and disappear within a matter of a couple of hours or so.) Where such features are forced, e.g. a synoptically forced trough or a topographically forced sea breeze, the predictability should be commensurate with that of the forcing scale. Synoptic scale features of 100-500 NM will have a predictability of more than one day. The time scale of a topographic heating is measured in hours and the effects of the sea breeze on a similar scale.

Note that "predictability" here means predictable with a "perfect" model and a "perfect" observing system. In reality, accurate forecasts will be achieved up to these limits only on favourable occasions. A small error in the large scale synoptic pattern might well create large (in relative terms) errors in small scale detail. A small error in cloud amount on the scale of a sea breeze coast will have a catastrophic effect on a sea breeze forecast.

Even if detail at, say, a 1 km (0.5 NM) scale could be observed (which it cannot), and we had a perfect prediction model (which we have not), it is unlikely that it (ie the detail) would still be there by the time a user obtained the analysis information, and certainly not by the time that a 6-hour forecast was produced.

The biggest benefits from a model with a very short grid length will thus be in the one day or so ahead prediction of topographically forced weather features, up to one day prediction of sub-synoptic troughs forced by the synoptic flow, and 6 - 12 hour prediction of organised convective systems.

The same arguments apply to the observed data. Where the features of interest are largely forced by topography or synoptic scale structures, the most important observations are those that define the synoptic scale.

For locally generated features, we have to rely on those sources of observations that are truly on the very small scale - eg satellite and radar imagery. These both give an effective observation spacing of around 5 km. Over the sea, of course radar data are only available to a fairly short distance from the coast.

In practice, there are, quite simply, not enough data to define the very small weather detail that sailors observe over the sea. Satellite (ASCAT) winds are not available often enough and have problems near coasts and in cloudy areas anyway. Over land, data from radar can be used to help predict small scale and short lived detail.

There is also the pragmatic observation that reducing the grid length has enabled improved performance in predicting the larger scale evolution. It is for this reason that global forecasting centres continue to move to finer grid lengths in global models. For example, if a hurricane can be predicted more accurately by resolving its circulation better, then a correct prediction becomes more likely of whether re-curvature will occur, where it will engage in the mid-latitude flow, and hence the synoptic evolution over the UK at 4-5 days ahead.

How much grid lengths can be reduced in global models is uncertain and will depend on observational data - as well as computer power. The future is likely to be one of finer resolution global models but with not a great improvement on short term, small detail over the sea.

The major benefits of fine scale models are likely to be for prediction of heavy showers over land, clearing skies leading to fog or ice on roads. To focus on the specific needs of sailors. a NWP model with very short grid lengths will offer improvements in the following areas:

• More realistic representation of the impact of topography on coastal winds and weather on such scales as the strong winds through the Dover Strait.

• More reliable forecasts of small scale thundery troughs and the like..
• More reliable forecasts of the development of organised convection systems, with associated severe weather.

Useful gains might be longest for the first area, less for the second, and perhaps only 12 hours for the third.