A  neural network nonlinear multi-model ensemble for predicting precipitation over ConUS

Krasnopolʹsky, V. M.; Lin, Ying

i

A neural network nonlinear multi-model ensemble for predicting precipitation over ConUS

2012
By Krasnopolʹsky, V. M. ; Lin, Ying
Series: Office note (National Centers for Environmental Prediction (U.S.)) 470

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Personal Author:

Krasnopolʹsky, V. M. ; Lin, Ying
Corporate Authors:

National Centers for Environmental Prediction (U.S.)
NOAA Program & Office:

NWS (National Weather Service) ; NCEP (National Centers for Environmental Prediction)
Description:

A novel multi-model ensemble approach based on the neural network (NN) technique is formulated and applied for improving 24-hour precipitation forecasts over the continental US. The developed nonlinear approach allowed us to account for nonlinear correlation between ensemble members and 'optimal' forecast represented by a nonlinear NN ensemble mean. The NN approach is compared with the regular multi-model ensemble, with multiple linear regression ensemble approaches, and with results obtained by human forecasters. The NN multi-model ensemble improves upon regular multi-model and multiple linear regression ensembles: (1) it significantly reduces high bias at low precipitation level; (2) it significantly reduces low bias at high precipitation level, and (3) it sharpens features making them closer to the observed ones. The NN multi-model ensemble performs at least as well as human forecasters supplied with the same information. The developed NN approach is a generic approach that can be applied to other multi-model ensemble fields as well as to single model ensembles.
Content Notes:

V.M. Krasnopolsky and Y. Lin.

"MMAB Contribution No. 296."

"January 2012."

System requirements: Adobe Acrobat Reader.

Includes bibliographical references (pages 25-27).
Keywords:

Mathematical Models Numerical Weather Forecasting Precipitation Forecasting Simulation Methods Weather Forecasting Mathematical Models Numerical Weather Forecasting Precipitation Forecasting Simulation Methods Weather Forecasting
Series:

Office note (National Centers for Environmental Prediction (U.S.)) 470
Document Type:

Office Note
Place as Subject:

United States
Rights Information:

Public Domain
Compliance:

Library
Main Document Checksum:

urn:sha-512:e69ce1500936b4d8264a6f673e5d458b4c0bc6039b384756acd9b6bcdb85d8f9e8ca841d1d637acf5da2bc2d214ce6687038fa443317590214ecaedb714f2cc0
Download URL:

https://repository.library.noaa.gov/view/noaa/6943/noaa_6943_DS1.pdf
File Type:

[PDF - 1.09 MB ]

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