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contributor authorEckel, F. Anthony
contributor authorDelle Monache, Luca
date accessioned2017-06-09T17:33:04Z
date available2017-06-09T17:33:04Z
date copyright2016/03/01
date issued2015
identifier issn0027-0644
identifier otherams-87108.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230741
description abstractn analog ensemble (AnEn) is constructed by first matching up the current forecast from a numerical weather prediction (NWP) model with similar past forecasts. The verifying observation from each match is then used as an ensemble member. For at least some applications, the advantages of AnEn over an NWP ensemble (multiple real-time model runs) may include higher efficiency, avoidance of initial condition and model perturbation challenges, and little or no need for postprocessing calibration. While AnEn can capture flow-dependent error growth, it may miss aspects of error growth that can be represented dynamically by the multiple real-time model runs of an NWP ensemble. To combine the strengths of the AnEn and NWP ensemble approaches, a hybrid ensemble (HyEn) is constructed by finding m analogs for each member of a small n-member NWP ensemble, to produce a total of m ? n members.Forecast skill is compared between the AnEn, HyEn, and an NWP ensemble calibrated using logistic regression. The HyEn outperforms the other approaches for probabilistic 2-m temperature forecasts yet underperforms for 10-m wind speed. The mixed results reveal a dependence on the intrinsic skill of the NWP members employed. In this study, the NWP ensemble is underspread for both 2-m temperature and 10-m winds, yet displays some ability to represent flow-dependent error for the former and not the latter. Thus, the HyEn is a promising approach for efficient generation of high-quality probabilistic forecasts, but requires use of a small, and at least partially functional, NWP ensemble.
publisherAmerican Meteorological Society
titleA Hybrid NWP–Analog Ensemble
typeJournal Paper
journal volume144
journal issue3
journal titleMonthly Weather Review
identifier doi10.1175/MWR-D-15-0096.1
journal fristpage897
journal lastpage911
treeMonthly Weather Review:;2015:;volume( 144 ):;issue: 003
contenttypeFulltext


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