2018 EJRNL PPZHENJUA HUO 1. pdf
Terbatas Rita Nurainni, S.I.Pus
» ITB
Terbatas Rita Nurainni, S.I.Pus
» ITB
ABSTRACT
This paper preliminarily investigates the application of the orthogonal conditional nonlinear optimal perturbations
(CNOPs)–based ensemble forecast technique in MM5 (Fifth-generation Pennsylvania State University–National Center for
Atmospheric Research Mesoscale Model). The results show that the ensemble forecast members generated by the orthogonal
CNOPs present large spreads but tend to be located on the two sides of real tropical cyclone (TC) tracks and have good agreements
between ensemble spreads and ensemble-mean forecast errors for TC tracks. Subsequently, these members reflect
more reasonable forecast uncertainties and enhance the orthogonal CNOPs–based ensemble-mean forecasts to obtain higher
skill for TC tracks than the orthogonal SVs (singular vectors)–, BVs (bred vectors)– and RPs (random perturbations)–based
ones. The results indicate that orthogonal CNOPs of smaller magnitudes should be adopted to construct the initial ensemble
perturbations for short lead–time forecasts, but those of larger magnitudes should be used for longer lead–time forecasts due
to the effects of nonlinearities. The performance of the orthogonal CNOPs–based ensemble-mean forecasts is case-dependent,
which encourages evaluating statistically the forecast skill with more TC cases. Finally, the results show that the ensemble
forecasts with only initial perturbations in this work do not increase the forecast skill of TC intensity, which may be related
with both the coarse model horizontal resolution and the model error.