[7-1] February 28, 11:10-11:40

[Invited]

Estimating and sampling error variances in coupled models

Malaquias Pena (NOAA), Zoltan Toth and Jie Feng (NOAA-ESRL); Suranjana Saha, Xingren Wu, Jiande Wang, Jack Woolen, Patrick Tripp, Shrinivas Moorthi, Dave Behringer, H-C Lee (NCEP); Steve Penny (UMD)

EMC is undertaking the development of the Unified Global Coupled System (UGCS) for weather to seasonal predictions. While the system is under development, the prospects for multi-scale data assimilation and model parameter optimization are being considered. In parallel with the UGCS's development, a series of diagnostic tools are being prepared to systematically assess its performance on each new model revision. In this talk, I will describe the characteristics and the status of the UGCS, and then will focus on one of the tools to diagnose uncertainty. The tool estimates analysis and short-range forecast error variances based on assumptions about the growth and correlation of errors, and is independent of the data assimilation scheme utilized. In a resent study where the truth is known, it is shown that these estimates are accurate within determined confidence intervals.