Abstract
The most intense orographic precipitation event over the subtropical central Andes (36°–30°S) during winter 2005 was examined using observational data and a regional model simulation. The Eta-Programa Regional de Meteorología (PRM) model forecast was evaluated and used to explore the airflow structure that generated this heavy precipitation event, with a focus on orographic influences. Even though the model did not realistically reproduce any near-surface variables, nor the precipitation shadow in the leeside lowlands, its reliable forecast of heavy precipitation over the windward side and the wind fields suggests that it can be used as a valuable forecasting tool for such events in the region.
The synoptic flow of the 26–29 August 2005 storm responded to a well-defined dipole from low to upper levels with anomalous low (high) geopotential heights at midlatitudes (subtropical) latitudes located off the southeast Pacific coast, resulting in a large meridional geopotential height gradient that drove a strong anomalous cross-barrier flow. Precipitation enhancement in the Andes was observed during the entire event; however, the highest rates were in the prefrontal sector under the low-level stable stratification and cross-barrier winds exceeding 2.5 standard deviations (σ) from the climatological monthly mean. The combination of strong cross-mountain winds with the stable stratification in the air mass of a frontal system, impinging on the high Andes range, appears to be the major factor in determining the flow structure that produced the pattern of precipitation enhancement, with uplift maximized near mountaintops and low-level blocking upwindleading to the formation of a low-level along-barrier jet. Additionally, only the upstream wind anomalies for the 15 heaviest events over a 10-yr (1967–76) period were investigated. They exhibited strong anomalous northwesterly winds for 14 of the 15 events, whereas for the remaining event there were no available observations to evaluate. Thus, these anomalies may also be exploited for forecasting capabilities.
