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Notario, J. J.

Publications and source records attributed to Notario, J. J..

Monthly mean simulation experiments with a course-mesh global atmospheric model

Substitution of observed monthly mean sea-surface temperatures (SSTs) as lower boundary conditions, in place of climatological SSTs, failed to improve the model simulations. While the impact of SST anomalies on the model output is greater at sea level than at upper levels the impact on the monthly mean simulations is not beneficial at any level. Shifts of one and two days in initialization time produced small, but non-trivial, changes in the model-generated monthly mean synoptic fields. No improvements in the mean simulations resulted from the use of either time-averaged initial data or re-initialization with time-averaged early model output. The noise level of the model, as determined from a multiple initial state perturbation experiment, was found to be generally low, but with a noisier response to initial state errors in high latitudes than the tropics.

Spar, J.↗

An initial state perturbation experiment with the GISS model

Monthly mean global forecasts for January 1975 have been computed with the Goddard Institute for Space Studies model from four slightly different sets of initial conditions - a 'control' state and three random perturbations thereof - to simulate the effects of initial state uncertainty on forecast quality. Differences among the forecasts are examined in terms of energetics, synoptic patterns and forecast statistics. The 'noise level' of the model predictions is depicted on global maps of standard deviations of sea level pressures, 500 mb heights and 850 mb temperatures for the set of four forecasts. Initial small-scale random errors do not appear to result in any major degradation of the large-scale monthly mean forecast beyond that generated by the model itself, nor do they appear to represent the major source of large-scale forecast error.

Spar, J.↗