Sitemap  |  Contact  |  Home  |  CAS  |  中文
Search Chinese
About Us
International Cooperation
Education & Training
Join Us
Location: Home > Announcements

[Seminar on Nov. 3] Spatially extended estimates of analysis and short-range forecast error variances

Dr. Jie Feng

University of Oklahoma, USA

Room 303, Keyan Building

10am, Nov. 3, 2017


Accurate estimates of analysis and short-range forecast error variances are critical for successful data assimilation and ensemble forecasting applications. Pena and Toth (2014, PT14) introduced a statistical minimization algorithm for the unbiased estimation of the variance between “truth” interpolated to a Numerical Weather Prediction (NWP) model grid and the NWP analysis or forecast (i.e., “true” errors). The method uses variances between NWP forecasts and analyses (i.e., “perceived” forecast errors) and assumptions about the growth and correlation of errors. After demonstrating in simple model experiments that the method produces unbiased error variance estimates, PT14 estimated the mean of true analysis and forecast error variances for NWP systems over large domains.

The present study expands on PT14 by (a) introducing a more suitable minimization algorithm, and by (b) deriving gridpoint based error variance estimates via a global minimization. Preliminary spatially-extended error variance estimates will be presented for (a) controlled analysis forecast experiments with a quasigeostrophic model, and (b) the NCEP operational Global Forecast System (GFS). Potential use of the spatially-extended error variance estimates include the specification of (a) background error variances in data assimilation (DA) independent of the DA schemes themselves and (b) initial ensemble perturbation variance.


LINKS CONTACT US SITEMAP Message to the Director General
  ©Copyright 2014-2024 IAP/CAS, All rights reserved.
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, People's Republic of China
Tel: +86-10-62028608 82995018 Fax: +86-10-62028604 E-mail: