Data derived at the National Centers for Environmental Prediction via
four-dimensional data assimilation using the Era Model were evaluated
against surface observations from two observational arrays, one locate
d in the semihumid, continental climate of Oklahoma and Kansas and the
second in the semiarid climate of southern Arizona. Comparison was ma
de for the period of the Global Energy Water-cycle Experiment Continen
tal-scale International Project's ''GIST'' dataset in 1994 and their '
'ESOP-95'' dataset in 1995, and for the months of March and May in 199
6. Coding errors in the Eta Model's postprocessor used to diagnose nea
r-surface temperature and humidity are shown to have compromised the G
IST and ESOP-95 near-surface data. A procedure was devised to correct
the GIST and ESOP-95 near-surface fields by mimicking the corrected co
de used in the Era Model since January 1996. Comparison with observati
ons revealed that modeled surface solar radiation is significantly ove
restimated except in clear-sky conditions. This discrepancy in cloudy-
sky solar radiation was altered little by the substantial January 1996
revisions to Era Model physics, but the revisions are shown to have g
reatly improved the model's ability to capture daily and seasonal vari
ations in near-surface air temperature, specific humidity, and wind sp
eed. The poorly modeled surface radiation complicates evaluation of mo
deled surface energy fluxes, but comparison with observations suggests
that the modeled daytime Bowen ratio may be systematically high. This
study clearly demonstrates the strong sensitivity of model-calculated
, near-surface variables to the physics used to describe surface inter
actions in the data assimilation model. To mitigate against this and t
o aid intercomparisons between other data, it is recommended that mode
l-derived data always include sufficient information to allow potentia
l users to recalculate the extrapolation to the surface using a user-d
efined model of surface-atmosphere exchanges.