scholarly journals Canonical correlation analysis (CAA) model for long-range forecasts of sub-divisional monsoon rainfall over India

MAUSAM ◽  
2021 ◽  
Vol 50 (2) ◽  
pp. 145-152
Author(s):  
R. M. RAJEEVAN ◽  
V. THAPLIYAL ◽  
S. R. PATIL ◽  
U. S. DE
Keyword(s):  
Correlation Analysis ◽  
Long Range ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Monsoon Rainfall ◽  
Forecast Model ◽  
Predictive Skill ◽  
Skill Scores ◽  
High Skill ◽  
Range Forecasts

Using the canonical correlation analysis (CCA) approach, a forecast model for long range forecasts of monsoon (June-September) rainfall of 27 meteorological sub-divisions over India was developed, A set of 12 parameters, which have significant correlation with Indian monsoon rainfall, was used as predictors, The model was developed with the data of the period 1958-1994 and by retaining three significant canonical modes, The model showed useful predictive skill in of respect of meteorological sub-divisions over central parts of India and NW India with low errors and high skill scores for categorical forecasts, The model showed no predictive skill in respect of meteorological sub-division over south peninsula, Orissa, West Bengal and Bihar. The CCA model has been also found to perform better than another statistical model developed using the 12 same predictors, The CCA model also showed moderate skill in forecasting excess and deficient rainfall categories of sub-divisional monsoon rainfall during the extreme years.

Analysis of Maximum Expiratory Flow Volume Curves Using Canonical Correlation Analysis

1985 ◽  
Vol 24 (02) ◽  
pp. 91-100 ◽  
Author(s):  
W. van Pelt ◽  
Ph. H. Quanjer ◽  
M. E. Wise ◽  
E. van der Burg ◽  
R. van der Lende
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Flow Volume ◽  
Non Linear ◽  
Maximum Expiratory Flow ◽  
Expiratory Flow ◽  
Relationship Of ◽  
The Relationship ◽  
Age And Sex

SummaryAs part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.

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