Data Assimilation Strategies in the Planetary Boundary Layer

Details Data Assimilation Strategies in the Planetary Boundary Layer Data Assimilation Strategies in the Planetary Boundary Layer

Nov 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010bolme.137..237r&link_type=abstract

Boundary-Layer Meteorology, Volume 137, Issue 2, pp.237-269

Computer Science

Atmospheric Boundary Layer, Data Assimilation, Land-Surface Heterogeneity, Land-Surface Model, Mesoscale Modelling, Observational Nudging

Scientific paper

We investigate the effect of the assimilation of surface and boundary-layer mass-field observations on the planetary boundary layer (PBL) within a one-dimensional (1D) version of the non-hydrostatic Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5). We focus on the vertical extent and effects of mass-field nudging within the PBL based on surface observations, and the added value of assimilating column mass observations within the PBL. Model experiments for dynamic initialization and dynamic analysis are conducted and composited for 29 May, 6 June, and 7 June 2002 during the International H2O Project (IHOP) over the Southern Great Plains, U.S.A. Advantages are found when the data assimilation uses the innovation (the difference between the modelled value and the observed value) calculated by comparing the surface mass-field observation to the model value at the 2-m observation height rather than at the lowest model level. It is shown that this innovation can be applied throughout the model-diagnosed PBL via nudging during free-convective conditions because of the well-mixed nature of the PBL. However, in stable conditions, due to decreased vertical mixing the surface innovation may be best applied only in a shallow layer adjacent to the surface. Surface air-temperature innovations were also applied to the top soil-layer temperature to minimize disruption to the surface energy balance. In combination with the surface observations, the use of within-PBL mass-field data assimilation improves the simulated PBL structure.

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