Predictability study of the observed and simulated European climate using linear regression ...
Monthly mean temperature anomalies in the regions England, Germany and Scandinavia are predicted by linear regression. Two predictors are selected from monthly mean teleconnection indices, North Atlantic sea surface temperatures (SSTs) projected on the first three empirical orthogonal functions (EOF...
| Main Authors: | , , , |
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| Format: | Text |
| Language: | unknown |
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Royal Meteorological Society
2003
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.48350/158579 https://boris.unibe.ch/158579/ |
| Summary: | Monthly mean temperature anomalies in the regions England, Germany and Scandinavia are predicted by linear regression. Two predictors are selected from monthly mean teleconnection indices, North Atlantic sea surface temperatures (SSTs) projected on the first three empirical orthogonal functions (EOFs), and European climate variables (temperature, sea level pressure, and precipitation) averaged in the three predictand regions. The predictors are chosen separately for each month according to their correlation with the predictand. Observations from 1870–1999 and data from a 600-year integration with the coupled atmosphere– ocean general-circulation model ECHAM/HOPE are used to assess and compare the forecast skill. The skill is measured by the anomaly correlation coefficient (ACC) and the explained variance (EV). For a one-month lead time the ACC for observations is up to 0:6 (EV≈35%) for February–March and August–September in the three regions. The skill for the simulated data is lower (maximum values at ... |
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