By Eugenia Kalnay
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Additional info for Atmospheric Modeling, Data Assimilation and Predictability
The TS, also known as critical success index (CSI) is a particularly useful score for quantities that are relatively rare. Fig. 2 indicates that the forecasters skill in predicting accumulated precipitation has been increasing with time, and that the current average skill in the 2-d forecast is as good as the 1-d forecasts were in the 1970s. Beyond the ﬁrst 6–12 h, the forecasts are based mostly on numerical guidance, so that the improvement reﬂects to a large extent improvements of the numerical forecasts, which the human forecasters in turn improve upon based on their knowledge and expertise.
The second goal of the ensemble forecasting, to provide guidance on the uncertainty of each forecast, is accomplished best by the use of two types of plots. The “spaghetti” plots show a single contour line for all 17 forecasts, and the probabilistic plots show, for example, what percentage of the ensemble predicts 24-h accumulated precipitation of more than 1 inch at each grid point (for probabilistic Quantitative Precipitation Forecasts or pQPF). Both of them provide guidance on the reliability of the forecasts in an easy-to-understand way.
1 Historical overview of numerical weather prediction 18 model to an octagonal grid covering the Northern Hemisphere down to 9–15◦ N. These changes resulted in numerical forecasts that for the ﬁrst time were competitive with subjective forecasts, but in order to implement them JNWPU had to wait for the acquisition of a more powerful supercomputer, an IBM 704, to replace the previous IBM 701. This pattern of forecast improvements which depend on a combination of the better use of the data and better models, and would require more powerful supercomputers in order to be executed in a timely manner has been repeated throughout the history of operational NWP.