Near-surface data assimilation in the NCEP regional GSI system : Use of mesonet data and a new forward operator

Seung-Jae Lee


The U.S. meso-network system provides meteorological observations with high spatial resolution and temporal frequency. In this study, we use surface mesonet data in the NCEP regional Grid-point Statistical Interpolation (GSI). Single time analysis experiments are conducted to test the impact of mesonet data on the analysis system and the results are compared with the GSI system without using mesonet data. The effort is focused on understanding the characteristics of innovations (observed-guess) of the surface mesonet data. Modifications to background errors will also be considered.

On the other hand, the incorporation of a complex near-surface observation operator into the NCEP regional Gridpoint Statistical-Interpolation (GSI) system is presented. The complex near-surface observation operator based on Monin-Obukhov similarity theory was implemented and tested for possible use. The results from this new forward operator are compared with those from the existing simple interpolation. The statistical analysis of observation innovations showed that introduction of the new forward model reduced bias and root-mean-square error in observation increment statistics.