To investigate this question we analyzed precipitation over the Olympic Mountains of Washington State as simulated at 4km resolution by a mesoscale weather prediction model (the MM5). Model results from individual storms and precipitation totals over two years calculated from twice-daily model integrations show a consistent pattern of precipitation that is closely related to the topography. On the southwest flank (typically the upwind side), simulated precipitation totals on ridges are consistently 2-4 times those in adjacent valleys in annual totals and individual storms. Rainfall totals for major and moderate storms show remarkably little variability in the patterns of precipitation despite variability in wind speed and direction, and the temperature and humidity of the incoming air. In order to evaluate the precipitation patterns predicted by the MM5, we established a rain and snow gauge network in October of 2003 to measure gradients in precipitation across the ridge south of the Queets River. Preliminary results from this network support the spatial pattern of precipitation predicted by the MM5.
River networks set the pace of erosion in mountain landscapes. River erosion rates are determined by the slope of the river and the stream flow (i.e., water discharge). Slope and stream flow tend to trade off to maintain a uniform erosion rate along the course of a river (the long-profile). River long-profile evolution can be simply modeled with the erosion rate set by the product of local slope and water discharge. We used this model to compare the form of a long-profile that evolved under spatially uniform precipitation versus one that evolved with a pattern of precipitation like that predicted by the MM5 and found a profound difference. If precipitation is concentrated on ridges, the relatively large discharge at high elevations is balanced by lower slopes. These low slope ridges create a modeled topography with ridges roughly 2/3 the height of ridges in a case with uniform precipitation. We are using more sophisticated, three-dimensional landscape evolution models together with MM5 integrations over the evolving topography to further evaluate the co-evolution of precipitation and topography at these spatial scales.