Hodges, K. I., 1996: Spherical Nonparametric Estimators
Applied to the UGAMP Model Integration for AMIP, Monthly Weather Review,
124, 2914-2915.
The aim of this paper is essentially twofold: first, to
describe the use of spherical nonparametric estimators for determining
statistical diagnostic fields from ensembles of feature tracks on a global
domain, and second, to report the application of these techniques to data
derived from a modem general circulation model. New spherical kernel functions
are introduced that are more efficiently computed than the traditional
exponential kernels. The data-driven techniques of cross-validation to
determine the amount of smoothing objectively, and adaptive smoothing to
vary the smoothing locally, are also considered. Also introduced are techniques
for combining seasonal statistical distributions to produce longer-term
statistical distributions. Although all calculations are performed globally,
only the results for the Northern Hemisphere winter (December, January,
February) and Southern Hemisphere winter (June, July, August) cyclonic
activity are presented, discussed, and compared with previous studies.
Overall, results for the two hemispheric winters are in good agreement
with previous studies, both for model- based studies and observational
studies.