Stewart 1975

Stewart, R.W., 1975: Numerical Experiments on Long-Range Weather Prediction. Ph.D. thesis. Columbia University.

A method is presented for increasing the length of prediction time for intermediate-range forecasting (7 to 30 days). The method is to use the ensemble average of a set of forecasts generated by random perturbations from an observed initial state. The method is applied specifically to the initial state of 9 December 1972.

The effect of the ensemble averaging on the predictability time is investigated by means of a simulation study utilizing a 3-layer general circulation model.

It is found that the technique of ensemble averaging — using the average of a set of forecasts randomly perturbed around an observed state — can lead to an increased predictability time when compared either to a single forecast made from the observed state, or to climatological means.

Specific results are: (1) the distribution of forecasts made from states which are randomly perturbed is Gaussian, within the limits of the numerical experiment; (2) the 3-layer general circulation model is shown "transitive" behavior for the 30 day period of the forecasts; (3) both "amplitude" (root-mean-square) and "phase" (correlation coefficient) predictability times are increased for the ensemble average forecast when compared to the forecast made from the observed intiial state; a two-day (20%) increase in "amplitude" predictability time is calculated for the ensemble-averaged forecast compared to the forecast from the observed plus "climatology". Surface pressure results showed a 7 day increase in predictability time, i.e., nearly two-fold increase. The phase predictability time for ground temperature for the United States region increased from about 10 days to 17 days; (4) the number of forecasts necessary to constitute a usable ensemble lies between four and eight.

In addition, the procedure of ensemble forecasting was applied to averages over space regions ranging from 4×10⁶ km² to 10⁷ km², as well as time averages over periods of 5 days. For forecast periods of 15 to 30 days, a decrease of 1.5°C is found for rms error in the ground temperature averaged over the United States and over 5 day intervals of time, as compared to a single forecast made from the observed state.

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Stewart, R.W.: Numerical Experiments on Long-Range Weather Prediction, Ph.D. thesis, Columbia University, New York, N.Y., 1975.

Stewart, R.W. (1975), Numerical Experiments on Long-Range Weather Prediction, Ph.D. thesis, Columbia University, New York, N.Y.

Stewart, R.W., 1975: Numerical Experiments on Long-Range Weather Prediction. Ph.D. thesis. Columbia University.

Stewart, R.W. 1975, Numerical Experiments on Long-Range Weather Prediction, Ph.D. thesis ( (New York, N.Y.: Columbia University).

Stewart RW. Numerical Experiments on Long-Range Weather Prediction. Ph.D. thesis. New York, N.Y.: Columbia University; 1975.

R.W. Stewart, Numerical Experiments on Long-Range Weather Prediction (Ph.D. thesis, Columbia University, New York, N.Y., 1975).