| description abstract | The question of whether rain gauge data from complex terrain are suitable to test physical models of orographic precipitation or to estimate free parameters is addressed. Data from three projects are considered: the Intermountain Precipitation Experiment (IPEX) and the California Land-falling Jets Experiment (CALJET), both in the United States, and the Mesoscale Alpine Programme (MAP) in the European Alps. As a prototype physical model, a new linear theory including airflow dynamics, condensed water advection, and leeside evaporation was employed. Theoretical considerations using the linear model showed sensitivity of point measurements across an ideal hill. To assist in model evaluation with real data, a new measure of ?goodness of fit? was defined. This measure, ?location sensitivity skill? (LSS), rewards detail as well as accuracy. For real data comparison, the linear model predictions show skill using traditional methods and the new LSS measure. The findings show that the wind direction and stability, and especially the cloud time delay (tau), are the sensitive parameters for point precipitation. The cloud time delay was the primary controller of point precipitation amplitude, and the stability tended to shift the precipitation pattern. Direct measures of tau are generally not obtainable, but this study indirectly constrained tau to 0?1000 s. The need for a denser observational network with tighter time control was revealed. | |
