Abstract

We investigate the cumulative added value of assimilating temperature, moisture, and wind observations in the three-dimensional non-hydrostatic Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model MM5 and use these forecasts to analyze the relationship between surface forcing and planetary boundary-layer (PBL) depth. A data assimilation methodology focused on the surface and the PBL, previously tested in a one-dimensional version of MM5, is applied to 29 May, 6 June, and 7 June 2002 during the International \(\hbox {H}_{2}\hbox {O}\) Project over the Southern Great Plains. Model-predicted PBL depth is evaluated against PBL depth diagnosed from data across 4,800 km of airborne lidar data (flight tracks 100–300 km long). The forecast with data assimilation verifies better against observations and is thus used to investigate the environmental conditions that govern PBL depth. The spatial structure in PBL depth is found to be most affected by spatial variations in surface buoyancy flux and capping inversion strength. The spatial scales of surface flux forcing reflected in the PBL depth are found through Fourier analysis and multiresolution decomposition. Correlations are \({<}0.50\) at scales of 64 km or less and increase at larger scales for 29 May and 6 June, but on 7 June low correlations are found at all scales, possibly due to greater within-PBL wind speeds, a stronger capping inversion on this day, and clouds. The results suggest a minimum scale, a function of wind speed, below which heterogeneity in surface buoyancy fluxes is not reflected directly in PBL depth.

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