Global circulation models can make useful climatic predictions several months in advance. This would not be possible without (1) a dynamic model of the oceans and (2) ocean-atmosphere coupling. This post takes a look at a simple example of this interaction.
Everyone is familiar with the ebb and flow of tides along coastlines. Newton showed that the variation of lunar and solar gravity around the surface of the earth is responsible for tides. Normally global circulation models (GCMs) do not include gravitational tidal forcing, and therefore Newtonian tides are absent entirely from these models. However, the existence of other periodic effects in sea surface height (SSH) is not ruled out.
Solar heating of the atmosphere produces a daily ~0.1% variation in surface pressure over much of the Earth. These are “atmospheric” tides. They have period 24h, as well as a strong harmonic at the surface of 12h. A map of 12h atmospheric tide height (in hPa, extracted from hourly surface pressure assimilation data for the period 11-19 Nov 2012) is shown below.
Atmospheric tides can induce ocean tides through atmosphere-ocean coupling. There is a mariner’s rule of thumb which says that 1mb (~ 100hPa) drop in atmospheric pressure produces a 1cm increase in sea level. This suggests that an oceanic tide of height ~ 1cm may exist even when the Newtonian tide is absent. Such a small effect is swamped easily by random influences such as wind stresses, air pressure, passage of planetary waves, etc. However it turns out that low-amplitude ocean tides can be detected in SSH assimilation model data. For example, 10 days of hourly data (10-19 Nov 2012) were used to produce the 12h tidal map below.
This map shows phase lines at 1h intervals. Points along a phase line experience high tide at the same time. There are no tides at the points where phase lines converge amphidromic points. The pattern is very similar (though not identical) to normal ocean tides.
It is quite impressive to see how a dynamic ocean model (MOM4) and ocean-atmosphere coupling capture aspects of the earth’s climate system at such a fine level of detail.
We use GCMs at biospherica to assess risks for global agriculture.