Model Tuning with Canonical Correlation

4 Knowledge of the relationship between model parameters and forecast quantities is 5 useful because it can aid in setting the values of the former for the purpose of having 6 a desired effect on the latter. Here, it is proposed that a well-established multivariate 7 statistical method known as Canonical Correlation Analysis can be formulated to gauge 8 the strength of that relationship. The method is applied to several model parameters in 9 COAMPS R ©1 for the purpose of “controlling” three forecast quantities: 1) convective 10 precipitation, 2) stable precipitation, and 3) snow. It is shown that the model parame11 ters employed here can be set to affect the sum, and the difference between convective 12 and stable precipitation, while keeping snow mostly constant; a different combination 13 of model parameters is shown to mostly affect the difference between stable precipita14 tion and snow, with minimal effect on convective precipitation. In short, the proposed 15 method can not only capture the complex relationship between model parameters and 16 forecast quantities, it can also be utilized to optimally control certain combinations of 17 the latter. 18 COAMPS is a registered trademark of the Naval Research Laboratory. 2