Mechanisms and prediction of precipitation over complex terrain
Zusammenfassung der Projektergebnisse
Mountain barriers and evolving dynamic processes, such as upslope ascent, downslope descent, or gravity waves, strongly modify the amount and spatial distribution of precipitation. If orographically induced ascent dominates synoptic-scale lifting, precipitation upstream and over a mountain can be significantly enhanced, which may trigger floods or landslides. Accurate assessment of orographic precipitation therefore is a prerequisite for water and risk management purposes. Furthermore, advancing our knowledge about precipitation response to mountain-induced disturbances may help to improve quantitative precipitation forecasts. Within the DFG project “Mechanisms and prediction of precipitation over complex terrain”, the process of orographic rain enhancement is investigated both for idealized and real conditions using two linear precipitation models and the non-hydrostatic weather prediction model of the Consortium for Small-scale Modeling (COSMO). Simulations of orographic precipitation over the low mountain ranges of southwestern Germany and eastern France with two different physics-based linear models based on linear theory for 3D airflow from show that the amount and spatial distribution of orographic precipitation is strongly controlled by characteristic time scales for cloud and hydrometeor advection in combination with background precipitation. These free parameters are estimated by adjusting the simulation results to observed precipitation patterns for a sample of 40 representative stratiform rainfall events during a calibration period (1971-1980). The best results in terms of lowest root-mean-square error (RMSE) and bias are obtained for characteristic time scales of 1600 s and background precipitation of 0.4 mm/h. Model simulations of 84 events during an application period (1981–2000) with fixed parameters demonstrate that both models are able to reproduce quantitatively precipitation patterns obtained from observations and high-resolution reanalyzes (ERA-40, downscaled by COSMO in climate mode, CCLM). Combining model results with observation data reveal that heavy precipitations over mountains are restricted to situations with strong atmospheric forcings in terms of synoptic-scale lifting, horizontal wind speed, and moisture content. Furthermore, idealized COSMO simulations were conducted to scrutinize the relation between ambient conditions, flow characteristics, and orographic precipitation. By changing model input parameters in terms of wind speed, static stability, temperature, and relative humidity, different flow effects from conditionally unstable flow to upstream stagnation are considered. It is shown that latent heat release significantly delays the onset of flow stagnation, which can be understood by considering the moist stability concept. Both the drying ratio, defined as the fraction of the impinging water mass removed as precipitation, and the location of the precipitation maxima can be described by the saturated non-dimensional mountain height M (inverse to the Froude number). In the flow stagnation regime, the maxima are associated with the extended gravity wave and occur downstream. With increasing direct mountain overflow (decreasing M), they are shifted upstream of the crest. The transition from stable ascent to convective-like precipitation patterns occurs quite abrupt when M becomes imaginary, indicating conditionally instability. The finding of the relation between precipitation characteristics and M reveals that the two inflow parameters, moist static stability (saturated Brunt-Väisälä frequency) and wind speed, scale with the same magnitude, but inversely.
Projektbezogene Publikationen (Auswahl)
- Characteristics of Large-scale Orographic Precipitation in a Linear Perspective. Journal of Hydrometeorology, Vol. 12. 2011, pp. 27-44.
Kunz, M.
(Siehe online unter https://dx.doi.org/10.1175/2010JHM1231.1) - Sensitivity of flow dynamics and orographic precipitation to changing ambient conditions in idealised model simulations. Meteorologische Zeitschrift, Vol. 20. 2011, No. 2, pp. 199 - 215.
Kunz, M, S. Wassermann
(Siehe online unter https://dx.doi.org/10.1127/0941-2948/2011/0221)
