Regional climate research

The cool, moist fall and winter climate in Southern California is often disrupted by dry, hot days with strong winds blowing out of the desert.  These "Santa Ana" winds are a dominant feature of the fall and wintertime climate of Southern California, and have important human and ecological impacts.  We investigate the atmospheric conditions that lead to Santa Ana winds using the North American Regional Reanalysis and a 12-year, 6-km resolution regional climate simulation of Southern California (see a more thorough description here).  We first construct a Santa Ana index (SAt) by averaging the offshore component of the surface winds at the exit of the largest gap in the region's topography (Figure 1).  This index shows strong seasonality consistent with previous measures of Santa Ana wind occurrence.

This index is then used to identify the average synoptic conditions associated with Santa Ana events.  Compositing reveals a high pressure anomaly at 700 hPa centered over the west coast of the United States (Figure 2).  The composite pressure anomaly would cause strong offshore geostrophic winds roughly perpendicular to the mountain ranges; an inspection of the 2 km winds incident on the topography shows that many of the strongest Santa Ana days have strong winds in this direction.  These strong offshore winds make strong surface winds more likely through gravity wave transfer of mid-level momentum to the surface.  We find, however, that there are large variations in the synoptic conditions during Santa Ana conditions (e.g., Figure 3), and that there are many days with strong offshore flow and weak synoptic forcing.  This is because of local thermodynamic forcing that causes strong offshore surface flow: a large temperature gradient between the cold desert surface and the warm ocean air at the same altitude causes an offshore pressure gradient at that altitude.  This in turn causes strong offshore flow in a thin layer near the surface.

We quantify the contribution of these two mechanisms using a bivariate linear regression model, with mid-tropospheric offshore wind speed over the desert, u, and the katabatic pressure gradient arising from the local temperature gradient, B, as independent variables.  The regression model allows us to quantify the contribution to SAt variability from u, B, and a covariance term, which arises because the synoptic conditions favorable for large SAt (i.e., strong mid-level offshore winds) also favor the development of strong B because they often bring cold air into the desert.  This model almost perfectly represents variability in SAt (Figure 4), and reveals that the local thermodynamic forcing is the primary control on Santa Ana variability.  Over 50% of the variance of SAt is due to B for days with weak or offshore synoptic conditions, with the remaining half of the variance split approximately equally among u, the covariance term, and the error of the regression model.

download the publication (Hughes and Hall 2009) describing these results in more detail.

Mimi Hughes and Alex Hall performed this research.