Rain or snow: hydrologic processes, observations, prediction, and research needs

Abstract

Abstract. The phase of precipitation when it reaches the ground is a first-order driver of hydrologic processes in a watershed. The presence of snow, rain, or mixed-phase precipitation affects the initial and boundary conditions that drive hydrological models. Despite their foundational importance to terrestrial hydrology, typical phase partitioning methods (PPMs) specify the phase based on near-surface air temperature only. Our review conveys the diversity of tools available for PPMs in hydrological modeling and the advancements needed to improve predictions in complex terrain with large spatiotemporal variations in precipitation phase. Initially, we review the processes and physics that control precipitation phase as relevant to hydrologists, focusing on the importance of processes occurring aloft. There is a wide range of options for field observations of precipitation phase, but there is a lack of a robust observation networks in complex terrain. New remote sensing observations have the potential to increase PPM fidelity, but generally require assumptions typical of other PPMs and field validation before they are operational. We review common PPMs and find that accuracy is generally increased at finer measurement intervals and by including humidity information. One important tool for PPM development is atmospheric modeling, which includes microphysical schemes that have not been effectively linked to hydrological models or validated against near-surface precipitation-phase observations. The review concludes by describing key research gaps and recommendations to improve PPMs, including better incorporation of atmospheric information, improved validation datasets, and regional-scale gridded data products. Two key points emerge from this synthesis for the hydrologic community: (1) current PPMs are too simple to capture important processes and are not well validated for most locations, (2) lack of sophisticated PPMs increases the uncertainty in estimation of hydrological sensitivity to changes in precipitation phase at local to regional scales. The advancement of PPMs is a critical research frontier in hydrology that requires scientific cooperation between hydrological and atmospheric modelers and field scientists.

Modeling Winter Precipitation Over the Juneau Icefield, Alaska, Using a Linear Model of Orographic Precipitation

“…We used a simple linear transition precipitation partitioning scheme. Harpold et al (2017) outlines a range of more sophisticated methods and these could be employed in future work. Additional uncertainties are the neglect of processes other than melt.…”

Lessons learned from monitoring the stable water isotopic variability in precipitation and streamflow across a snow-dominated subarctic catchment

“…For example, precipitation shifts from snow to rain are anticipated to occur across several regions, such as the North American Rockies, where snowpacks have traditionally dominated water resources (Bales et al 2006;Barnett, Adam, and Lettenmaier 2005). Harpold et al (2017) recently highlighted how these changes in precipitation phases could alter streamflow timing and amounts (Berghuijs, Woods, and Hrachowitz 2014;Jepsen et al 2016;Luce and Holden 2009), increase rain-on-snow flooding (McCabe, Clark, and Hay 2007), and impact the ability to accurately forecast water supplies (Milly et al 2008). Our understanding of how shifts in precipitation phases and how variability in frozen-ground patterns (Campbell et al 2010) impact not only streamflow amounts but also stream-water chemistry and its sources is, unfortunately, still rather limited .…”

Snow observations in Mount Lebanon (2011–2016)

“…For this study, we set z 0 = 0.01 for the time period between December and March and z 0 = 0.03 for the rest. Different approaches for precipitation phase determination have been summarized in Harpold et al (2017). Most common methods rely on the use of mean air temperature (T a ) thresholds (e.g., Marks et al, 2013).…”