Data Assimilation in the Planetary Boundary Layer
Description
This work focuses on finding ways to better use surface
observations (e.g. mesonet) in NWP . Ensemble data
assimilation appears promising because is uses dynamic error
covariance estimates, and of course we get an ensemble forecast as
a by-product. For efficient research, a column model that
uses Weather Research and Forecast (WRF) model schemes for
parameterizing the lower boundary (soil), the surface layer, and
the PBL has been coupled to the NCAR Data Assimilation Research
Testbed (DART)
software.
Publications and Submitted Manuscripts
Hacker, J. P. and D. Rostkier-Edelstein, 2007: PBL state estimation
with surface observations, a column model, and an ensemble
filter. Mon. Wea.
Rev., revised manuscript under review. [pdf manuscript]
Pagowski, M., J. Hacker, and D. Rostkier-Edelstein, 2007: Behavior
of Weather Research and Forecasting (WRF) model boundary layer and
surface parameterizations in 1-D simulations during the BAMEX field
campaign. Bound.-Layer.
Meteor., under review.
Hacker, J. P., J. Anderson, and M. Pagowski, 2006: Improved
vertical covariance estimates for ensemble-filter assimilation of
near-surface observations. Mon. Wea. Rev., in press. [pdf manuscript]
Hacker, J. P. and C. Snyder, 2005: Ensemble Kalman filter
assimilation of fixed screen-height observations in a parameterized
PBL. Mon. Wea. Rev.,
133, 3260-3275. [link
to AMS holding]
Documentation
Documentation for the column model is embarassingly out of date and
not worth posting, but some DART documentation is available
here.