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.