The climatology of small‐scale patterns of mountain precipitation is poorly constrained, yet important for applications ranging from natural hazard assessment to understanding the geologic evolution of mountain ranges. Synthesizing four rainy seasons of high‐resolution precipitation observations and mesoscale model output (from the Penn State/NCAR MM5), reveals a persistent small‐scale pattern of precipitation over the ∼10 km wide, ∼800 m high ridges and valleys of the western Olympic Mountains, Washington State, USA. This pattern is characterized by a 50–70% excess accumulation over the ridge crests relative to the adjacent valleys in the annual mean. While the model shows excellent skill in simulating these patterns at seasonal time‐scales, major errors exist for individual storms.Investigation of a range of storm events has revealed the following mechanism for the climatological pattern. Regions of enhanced condensation of cloud water are produced by ascent in stable flow over the windward slopes of major ridges. Synoptically generated precipitation grows by collection within these clouds, leading to enhanced precipitation which is advected by the prevailing winds.Instances of atypical patterns of precipitation suggest that under certain conditions (during periods with a low freezing level, or convective cells) fundamental changes in small‐scale patterns may occur. However, case‐studies and composite analysis suggest that departures from the pattern of ridge‐top enhancement are rare; the basic patterns and processes appear robust to changes in temperature, winds, and background rainfall rates. Copyright © 2008 Royal Meteorological Society

The rate of precipitation increase with elevation, termed the orographic precipitation gradient (OPG), is critically important for hydrologic forecasting in mountain basins that receive both rain and snow. Here, the following are examined to see how well they are able to predict the OPG and how it changes between storms and years: 1) a linear model of orographic precipitation forced by upstream radiosonde data, 2) monthly Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data, and 3) seven years of hourly wind profiler data used to identify characteristics of the Sierra barrier jet (SBJ). These are compared against 124 daily resolution (four of which also had quality controlled, hourly resolution) precipitation gauge records in the northern Sierra Nevada. All methods represent the OPG well in the mean and during a year when less than 30% of the precipitation occurred on days with SBJs. However, the linear model and PRISM do not adequately capture annual variations in the OPG during years when more than 70% of the precipitation occurred on days with SBJs. Throughout all of the years, wind profiler data indicating the height of the SBJ provided additional, and necessary, information. The OPG is negatively correlated with the height of the SBJ. The SBJ height is lower, and hence, the OPG greater when the westerly winds are stronger, with more vertical wind shear. These westerly storms result in greater increases of precipitation with elevation, which act to increase snow storage in most storms but also to increase storm runoff during warmer-than-average storms.

Observations show that on a mountainside the boundary between snow and rain, the snow line, is often located at an elevation hundreds of meters below its elevation in the free air upwind. The processes responsible for this mesoscale lowering of the snow line are examined in semi-idealized simulations with a mesoscale numerical model and in simpler theoretical models. Spatial variations in latent cooling from melting precipitation, in adiabatic cooling from vertical motion, and in the melting distance of frozen hydrometeors are all shown to make important contributions. The magnitude of the snow line drop, and the relative importance of the responsible processes, depends on properties of the incoming flow and terrain geometry. Results suggest that the depression of the snow line increases with increasing temperature, a relationship that, if present in nature, could act to buffer mountain hydroclimates against the impacts of climate warming. The simulated melting distance, and hence the snow line, depends substantially on the choice of microphysical parameterization, pointing to an important source of uncertainty in simulations of mountain snowfall.

The Dominica Experiment (DOMEX) took place in the eastern Caribbean from 4 April to 10 May 2011 with 21 research flights of the Wyoming King Air and several other observing systems. The goal was an improved understanding of the physics of convective orographic precipitation in the tropics. Two types of convection were found. During a period of weak trade winds, diurnal thermal convection was seen over Dominica. This convection caused little precipitation but carried aloft air with island-derived aerosol and depleted CO2. During periods of strong trades, mechanically forced convection over the windward slopes brought heavy rain to the high terrain. This convection was “seeded” by trade-wind cumuli or neutrally buoyant cool wet patches of air. In this mechanically forced convection, air parcels did not touch the island surface to gain buoyancy so no island-derived tracers were lofted. With fewer aerosols, the mean cloud droplet diameter increased from 15 to 25 μm. Plunging airflow and a wake were found in the lee of Dominica. The DOMEX dataset will advance our understanding and test our theories of cumulus triggering and aerosol influence on precipitation.

The snow‐albedo feedback (SAF) strongly influences climate over midlatitude mountainous regions. However, over these regions the skill of regional climate models (RCMs) at simulating properties such as snow cover and surface albedo is poorly characterized. These properties are evaluated in a pair of 7 year long high‐resolution RCM simulations with the Weather Research and Forecasting model over the central Rocky Mountains. Key differences between the simulations include the computational domain (regional versus continental) and land surface model used (Noah versus Noah‐MP). Simulations are evaluated against high‐resolution satellite estimates of snow cover and albedo from the Moderate Resolution Imaging Spectroradiometer. Both simulations generally reproduce the observed seasonal and spatial variability of snow cover and also exhibit important biases. One simulation substantially overpredicts subpixel fractional snow cover over snowy pixels (by up to 0.4) causing large positive biases in surface albedo, likely due in part to inadequate representation of canopy effects. The other simulation exhibits a negative bias in areal snow extent (as much as 19% of the analysis domain). Surface measurements reveal large positive biases in snow albedo (exceeding 0.2) during late spring caused by neglecting radiative effects of impurities deposited onto snow. Semi‐idealized climate change experiments show substantially different magnitudes of SAF‐enhanced warming in the two simulations that can be tied to the differences in snow cover in their control climates. More confident projections of regional climate change over mountains will require further work to evaluate and improve representation of snow cover and albedo in RCMs.