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A canonical ensemble correlation prediction model for seasonal precipitation anomaly
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Lau, William K. M. Kim, Kyu-Myong Shen, Samuel S. P. Li, Guilong |
| Copyright Year | 2001 |
| Description | This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature. |
| File Size | 2307500 |
| Page Count | 68 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_20010102849 |
| Archival Resource Key | ark:/13960/t1rg0pm9d |
| Language | English |
| Publisher Date | 2001-09-01 |
| Access Restriction | Open |
| Subject Keyword | Meteorology And Climatology Long Range Weather Forecasting Mean Square Values Error Analysis Annual Variations Canonical Forms Orthogonal Functions Mathematical Models Sea Surface Temperature Precipitation Meteorology Spectral Correlation Weighting Functions Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
