Evaluation of a Sub-Grid Topographic Drag Parameterizations for Modeling Surface Wind Speed During Storms Over Complex Terrain in the Northeast U.S.

Thursday, 17 December 2015
Poster Hall (Moscone South)
Maria Eugenia Frediani1, Joshua Hacker2, Emmanouil N Anagnostou3 and Thomas M Hopson2, (1)University of Connecticut, Storrs Mansfield, CT, United States, (2)National Center for Atmospheric Research, Boulder, CO, United States, (3)University of Connecticut, Department of Civil & Environmental Engineering, Groton, CT, United States
This study aims at improving regional simulation of 10-meter wind speed by verifying PBL schemes for storms at different scales, including convective storms, blizzards, tropical storms and nor'easters over complex terrain in the northeast U.S. We verify a recently proposed sub-grid topographic drag scheme in stormy conditions and compare it with two PBL schemes (Mellor-Yamada and Yonsei University) from WRF-ARW over a region in the Northeast U.S. The scheme was designed to adjust the surface drag over regions with high subgrid-scale topographic variability. The schemes are compared using spatial, temporal, and pattern criteria against surface observations. The spatial and temporal criteria are defined by season, diurnal cycle, and topography; the pattern, is based on clusters derived using clustering analysis. Results show that the drag scheme reduces the positive bias of low wind speeds, but over-corrects the high wind speeds producing a magnitude-increasing negative bias with increasing speed. Both other schemes underestimate the most frequent low-speed mode and overestimate the high-speeds. Error characteristics of all schemes respond to seasonal and diurnal cycle changes. The Topo-wind experiment shows the best agreement with the observation quantiles in summer and fall, the best representation of the diurnal cycle in these seasons, and reduces the bias of all surface stations near the coast. In more stable conditions the Topo-wind scheme shows a larger negative bias. The cluster analysis reveals a correlation between bias and mean speed from the Mellor-Yamada and Yonsei University schemes that is not present when the drag scheme is used. When the drag scheme is used the bias correlates with wind direction; the bias increases when the meridional wind component is negative. This pattern corresponds to trajectories with more land interaction with the highest biases found in northwest circulation clusters.