Remote Sensing Applications and Decision Support

Tuning of background error statistics through sensitivity experiments and its impact on typhoon forecast

[+] Author Affiliations
Yan-An Liu, Hung-Lung Allen Huang

East China Normal University, Key Laboratory of Geographic Information Science, Ministry of Education, 500 Dongchuan Road, Shanghai 200241, China

University of Wisconsin–Madison, Cooperative Institute for Meteorological Satellite Studies, 1225 West Dayton Street, Madison, Wisconsin 53706, United States

Wei Gao

East China Normal University, Key Laboratory of Geographic Information Science, Ministry of Education, 500 Dongchuan Road, Shanghai 200241, China

Colorado State University, Department of Ecosystem Science and Sustainability, 1231 East Drive, Fort Collins, Colorado 80523, United States

Agnes H. N. Lim

University of Wisconsin–Madison, Cooperative Institute for Meteorological Satellite Studies, 1225 West Dayton Street, Madison, Wisconsin 53706, United States

Chaoshun Liu, Runhe Shi

East China Normal University, Key Laboratory of Geographic Information Science, Ministry of Education, 500 Dongchuan Road, Shanghai 200241, China

J. Appl. Remote Sens. 9(1), 096051 (May 19, 2015). doi:10.1117/1.JRS.9.096051
History: Received October 27, 2014; Accepted April 20, 2015
Text Size: A A A

Abstract.  Background error covariance (B) matrix is critical for variational data assimilation as it greatly affects the analyses of three-dimensional variational assimilation. The National Meteorological Center method was used to estimate the B matrix using the forecasts from the Advanced Research Weather Research and Forecasting regional model. To further understand and evaluate the newly generated regional B matrix, its characteristics were compared with the global B estimated from the Global Forecast System model. Sensitivity experiments were undertaken by changing the horizontal length-scales and standard deviations of the B matrix, and its impacts on the typhoon forecast were also examined. Verification against radiosonde observations showed that the varying horizontal length-scale has a significant positive impact on the 24-h forecast of temperature, specific humidity, u-wind, and v-wind. On the other hand, changing standard deviations of the B matrix has a slight influence only on the specific humidity and wind (u-component) forecast. Compared with the global B, the tuned regional B showed improvements in temperature forecasts. In addition, using the tuned regional B also led to a positive impact on the typhoon (Saola, Damrey, and Haikui) track forecasts as compared with the untuned B and global B.

Figures in this Article
© 2015 Society of Photo-Optical Instrumentation Engineers

Topics

Matrices

Citation

Yan-An Liu ; Hung-Lung Allen Huang ; Wei Gao ; Agnes H. N. Lim ; Chaoshun Liu, et al.
"Tuning of background error statistics through sensitivity experiments and its impact on typhoon forecast", J. Appl. Remote Sens. 9(1), 096051 (May 19, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096051


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.