Saturday, June 28, 2008

Atmospheric prediction caught in quicksand.

Oh tell me, designer of desert,

Geometrician of quicksand,

Is that true that boundless lines

Are stronger than blowing wind?

0 . Mandelshtam, 1933

In forecasting,the comparison with reality can be made only at the moment when the prediction comes true. At the time of its formulation, it cannot be tested and, therefore, in its most general form, it has no scientific status.
Logical Analysis of the Problem of Forecasting


DRAFT March 29, 2006
Spotlight on Global Temperature
by James Hansen, Makiko Sato, Reto Ruedy, Ken Lo, David Lea and Martin Medina-Elizalde

Early model predictions of global warming proved accurate,the Pacific Ocean seems charged for a potential super-El Nino, and global temperature is poised to reach record, perhaps dangerous, levels.

SUPER EL NINO IN 2006-2007? We suggest that an El Nino is likely to originate in 2006 and that there is a good chance it will be a "super El Nino", rivaling the 1983 and 1997-1998 El Ninos, which were successively labeled the "El Nino of the century" as they were of unprecedented strength in the previous 100 years (Fig. 1 of Fedorov and Philander 2000). Further, we argue that global warming causes an increase of such "super El Ninos". Our rationale is based on interpretation of dominant mechanisms in the ENSO (El Nino Southern Oscillation) phenomenon, examination of historical SST data, and observed Pacific Ocean SST anomalies in February 2006.

As we see the prediction was inverted by a La Nina or out in its trajectory by 180 degrees.Why?Model error.

One of the more interesting attributes of the weather atmospheric forecasting community is its evolutionary skill. As we have previously seen the “idea”of increased computer power and model integration is seen as the solution of the open problem of forecast, or predictive capabilities.

At first glance this would be seen as logically correct, however the atmosphere (weather –climate system) is a complex system not in thermodynamic equilibrium(often far from TDE) and in a perpetual state of reorganization .Here the rules of the game, where idealistic assumptions for the instantaneous state of the atmosphere are not valid when the equations of motion(transformation) to a future state are presently applied.

This is evident when seen in the evolution of the weather forecast model ability of the ECMWF.A widely used model producing forecasts in the range for a few days to a number of weeks. The preparation base is a n-day forecast with n= 10 days of the global atmospheric state.

In any forecast there is an error dependent on initial conditions (due to arbitrary assumptions/estimates of unknown qualities) with the ECMWF model over the last 20 or so years in a paradox the model error has increased.

In 1982 in a seminal paper in which ECMWF data was first used ,to measure predictive ability. Edward Lorenz found the mean error evolution (doubling time of initial error) was two days, presently has dropped to 1.2 days.

This suggest that there is a limiting of predictive capabilities for long range weather forecasting with models of increasing sophistication ,owing to interconnected complexity in the atmospheric dynamics.

Sensitivity to the initial conditions-the principle signature of deterministic chaos-is thus not an artifact arising from when lower order models are used but is, rather, deeply rooted in the physics of the atmosphere.

Nicolis and Nicolis Foundations of complex systems page 223.


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