English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Dynamic analogue initialization for ensemble forecasting

Li, S., Xingyao, R., Yun, L., Zhengyu, L., & Fraedrich, K. F. (2013). Dynamic analogue initialization for ensemble forecasting. Advances in Atmospheric Sciences, 30, 1406-1420. doi:10.1007/s00376-012-2244-z.

Item is

Files

show Files
hide Files
:
10.1007-s00376-012-2244-z.pdf (Publisher version), 2MB
 
File Permalink:
-
Name:
10.1007-s00376-012-2244-z.pdf
Description:
-
OA-Status:
Visibility:
Restricted (Max Planck Institute for Meteorology, MHMT; )
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Li, Shan, Author
Xingyao, Rong, Author
Yun, Liu, Author
Zhengyu, Liu, Author
Fraedrich, Klaus F.1, Author           
Affiliations:
1Max Planck Fellows, MPI for Meteorology, Max Planck Society, ou_913548              

Content

show
hide
Free keywords: initialization, ensemble forecast, analogue, error growth
 Abstract: This paper introduces a new approach for the initialization of ensemble numerical forecasting: Dynamic Analogue Initialization (DAI). DAI assumes that the best model state trajectories for the past provide the initial conditions for the best forecasts in the future. As such, DAI performs the ensemble forecast using the best analogues from a full size ensemble. As a pilot study, the Lorenz63 and Lorenz96 models were used to test DAI's effectiveness independently. Results showed that DAI can improve the forecast significantly. Especially in lower-dimensional systems, DAI can reduce the forecast RMSE by similar to 50% compared to the Monte Carlo forecast (MC). This improvement is because DAI is able to recognize the direction of the analysis error through the embedding process and therefore selects those good trajectories with reduced initial error. Meanwhile, a potential improvement of DAI is also proposed, and that is to find the optimal range of embedding time based on the error's growing speed.

Details

show
hide
Language(s): eng - English
 Dates: 2013-092013-09
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s00376-012-2244-z
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Advances in Atmospheric Sciences
  Other : Adv. Atmos. Sci.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Beijing, China : China Ocean Press
Pages: - Volume / Issue: 30 Sequence Number: - Start / End Page: 1406 - 1420 Identifier: ISSN: 0256-1530
CoNE: https://pure.mpg.de/cone/journals/resource/954925496032