Recent Advances in Mountain Hydrology: Has our Ability to Model Mountain Rain and Snow Exceeded the Skill of Our Observational Precipitation Networks?

Mountain precipitation volumes, phase, and timing govern streamflow, and accurate spatial precipitation estimates are critical for flood forecasting, snow mapping, and runoff prediction for water resources. Unfortunately, mountain precipitation, particularly in regions receiving both liquid and solid precipitation, is notoriously difficult to measure, and interpolating or extrapolating values between sparse measurements leads to further problems. Even distinguishing the phase of precipitation through time is a challenge for most measurement systems. While surface observational systems have remained static over the past few decades, the computational power for models has dramatically increased. Models at resolutions of 4 km or finer (e.g., WRF, HRRR) are now run routinely over mountain regions and resolve not only the topography but most of the physics controlling precipitation rates and phase. Extensive snow and streamflow observations indicate that gridded precipitation datasets based on observations and statistics are often less accurate than numerical weather model simulations. Evaluating further improvements in modeling orographic precipitation will require carefully designed observation networks and close collaborations between hydrologists and atmospheric scientists.