Residual delay maps unveil global patterns of atmospheric nonlinearity and produce improved local forecasts
Open Access
- 7 December 1999
- journal article
- research article
- Published by Proceedings of the National Academy of Sciences in Proceedings of the National Academy of Sciences
- Vol. 96 (25) , 14210-14215
- https://doi.org/10.1073/pnas.96.25.14210
Abstract
We use residual-delay maps of observational field data for barometric pressure to demonstrate the structure of latitudinal gradients in nonlinearity in the atmosphere. Nonlinearity is weak and largely lacking in tropical and subtropical sites and increases rapidly into the temperate regions where the time series also appear to be much noisier. The degree of nonlinearity closely follows the meridional variation of midlatitude storm track frequency. We extract the specific functional form of this nonlinearity, a V shape in the lagged residuals that appears to be a basic feature of midlatitude synoptic weather systems associated with frontal passages. We present evidence that this form arises from the relative time scales of high-pressure versus low-pressure events. Finally, we show that this nonlinear feature is weaker in a well regarded numerical forecast model (European Centre for Medium-Range Forecasts) because small-scale temporal and spatial variation is smoothed out in the grided inputs. This is significant, in that it allows us to demonstrate how application of statistical corrections based on the residual-delay map may provide marked increases in local forecast accuracy, especially for severe weather systems.Keywords
This publication has 27 references indexed in Scilit:
- Local optimal prediction: exploiting strangeness and the variation of sensitivity to initial conditionPhilosophical Transactions A, 1994
- Nonlinear prediction as a way of distinguishing chaos from random fractal sequencesNature, 1992
- Distinguishing error from chaos in ecological time seriesPhilosophical Transactions Of The Royal Society B-Biological Sciences, 1990
- Nonlinear forecasting as a way of distinguishing chaos from measurement error in time seriesNature, 1990
- Global Properties and Local Structure of the Weather Attractor over Western EuropeJournal of the Atmospheric Sciences, 1989
- Predicting chaotic time seriesPhysical Review Letters, 1987
- Do climatic attractors exist?Nature, 1986
- Vorticity balances in the tropics during the 1982-83 El Niño-Southern Oscillation eventQuarterly Journal of the Royal Meteorological Society, 1985
- Characterization of Strange AttractorsPhysical Review Letters, 1983
- Some simple solutions for heat‐induced tropical circulationQuarterly Journal of the Royal Meteorological Society, 1980