Snow Processes in Mountain Forests: Interception Modeling for Coarse-Scale Applications

Snow interception by the forest canopy controls the spatial heterogeneity of subcanopy snow accumulation leading to significant differences between forested and nonforested areas at a variety of scales. Snow intercepted by the forest canopy can also drastically change the surface albedo. As such, accurately modeling snow interception is of importance for various model applications such as hydrological, weather, and climate predictions. Due to difficulties in the direct measurements of snow interception, previous empirical snow interception models were developed at just the point scale. The lack of spatially extensive data sets has hindered the validation of snow interception models in different snow climates, forest types, and at various spatial scales and has reduced the accurate representation of snow interception in coarse-scale models. We present two novel empirical models for the spatial mean and one for the standard deviation of snow interception derived from an extensive snow interception data set collected in an evergreen coniferous forest in the Swiss Alps. Besides open-site snowfall, subgrid model input parameters include the standard deviation of the DSM (digital surface model) and/or the sky view factor, both of which can be easily precomputed. Validation of both models was performed with snow interception data sets acquired in geographically different locations under disparate weather conditions. Snow interception data sets from the Rocky Mountains, US, and the French Alps compared well to the modeled snow interception with a normalized root mean square error (NRMSE) for the spatial mean of ≤10 % for both models and NRMSE of the standard deviation of ≤13 %. Compared to a previous model for the spatial mean interception of snow water equivalent, the presented models show improved model performances. Our results indicate that the proposed snow interception models can be applied in coarse land surface model grid cells provided that a sufficiently fine-scale DSM is available to derive subgrid forest parameters

Spatio-temporal assessment of WRF, TRMM and in situ precipitation data in a tropical mountain environment (Cordillera Blanca, Peru)

The estimation of precipitation over the broad range of scales of interest for climatologists, meteorologists and hydrologists is challenging at high altitudes of tropical regions, where the spatial variability of precipitation is important while in situ measurements remain scarce largely due to operational constraints. Three different types of rainfall products - ground based (kriging interpolation), satellite derived (TRMM3B42), and atmospheric model outputs (WRF - Weather Research and Forecasting) - are compared for 1 hydrological year in order to retrieve rainfall patterns at timescales ranging from sub-daily to annual over a watershed of approximately 10 000 km(2) in Peru. An ensemble of three different spatial resolutions is considered for the comparison (27, 9 and 3 km), as long as well as a range of timescales (annual totals, daily rainfall patterns, diurnal cycle). WRF simulations largely overestimate the annual totals, especially at low spatial resolution, while reproducing correctly the diurnal cycle and locating the spots of heavy rainfall more realistically than either the ground-based KED or the Tropical Rainfall Measuring Mission (TRMM) products. The main weakness of kriged products is the production of annual rainfall maxima over the summit rather than on the slopes, mainly due to a lack of in situ data above 3800 ma.s.l. This study also confirms that one limitation of TRMM is its poor performance over ice-covered areas because ice on the ground behaves in a similar way as rain or ice drops in the atmosphere in terms of scattering the microwave energy. While all three products are able to correctly represent the spatial rainfall patterns at the annual scale, it not surprisingly turns out that none of them meets the challenge of representing both accumulated quantities of precipitation and frequency of occurrence at the short timescales (sub-daily and daily) required for glacio-hydrological studies in this region. It is concluded that new methods should be used to merge various rainfall products so as to make the most of their respective strengths

Climate reconstruction of the Little Ice Age maximum extent of the tropical Zongo Glacier using a distributed energy balance model

This study assessed the climate conditions that caused the tropical Zongo Glacier (16° S, Bolivia) to reach its Little Ice Age (LIA) maximum extent in the late 17th century. We carried out sensitivity analyses of the annual surface mass balance to different physically coherent climate scenarios constrained by information taken from paleoclimate proxies and sensitivity studies of past glacier advances. These scenarios were constrained by a 1.1 K cooling and a 20% increase in annual precipitation compared to the current climate. Seasonal precipitation changes were constructed using shuffled input data for the model: measurements of air temperature and relative humidity, precipitation, wind speed, incoming short and longwave radiation fluxes, and assessed using a distributed energy balance model. They were considered plausible if conditions close to equilibrium glacier-wide mass balance were obtained. Results suggest that on top of a 1.1 K cooling and ${\sim }$20% increase in annual precipitation, only two seasonal precipitation patterns allow LIA equilibrium: evenly distributed precipitation events across the year and an early wet season onset

Climate reconstruction of the Little Ice Age maximum extent of the tropical Zongo Glacier using a distributed energy balance model

This study assessed the climate conditions that caused the tropical Zongo Glacier (16° S, Bolivia) to reach its Little Ice Age (LIA) maximum extent in the late 17th century. We carried out sensitivity analyses of the annual surface mass balance to different physically coherent climate scenarios constrained by information taken from paleoclimate proxies and sensitivity studies of past glacier advances. These scenarios were constrained by a 1.1 K cooling and a 20% increase in annual precipitation compared to the current climate. Seasonal precipitation changes were constructed using shuffled input data for the model: measurements of air temperature and relative humidity, precipitation, wind speed, incoming short and longwave radiation fluxes, and assessed using a distributed energy balance model. They were considered plausible if conditions close to equilibrium glacier-wide mass balance were obtained. Results suggest that on top of a 1.1 K cooling and ${\sim }$20% increase in annual precipitation, only two seasonal precipitation patterns allow LIA equilibrium: evenly distributed precipitation events across the year and an early wet season onset

Spatial Variability of Shortwave Irradiance for Snowmelt in Forests

The spatial variation of melt energy can influence snow cover depletion rates and in turn be influenced by the spatial variability of shortwave irradiance to snow. The spatial variability of shortwave irradiance during melt under uniform and discontinuous evergreen canopies at a U. S. Rocky Mountains site was measured, analyzed, and then compared to observations from mountain and boreal forests in Canada. All observations used arrays of pyranometers randomly spaced under evergreen canopies of varying structure and latitude. The spatial variability of irradiance for both overcast and clear conditions declined dramatically, as the sample averaging interval increased from minutes to 1 day. At daily averaging intervals, there was little influence of cloudiness on the variability of subcanopy irradiance; instead, it was dominated by stand structure. The spatial variability of irradiance on daily intervals was higher for the discontinuous canopies, but it did not scale reliably with canopy sky view. The spatial variation in irradiance resulted in a coefficient of variation of melt energy of 0.23 for the set of U. S. and Canadian stands. This variability in melt energy smoothed the snow-covered area depletion curve in a distributed melt simulation, thereby lengthening the duration of melt by 20%. This is consistent with observed natural snow cover depletion curves and shows that variations in melt energy and snow accumulation can influence snow-covered area depletion under forest canopies

Rapid decline of snow and ice in the tropical Andes – Impacts, uncertainties and challenges ahead

Glaciers in the tropical Andes have been retreating for the past several decades, leading to a temporary increase in dry season water supply downstream. Projected future glacier shrinkage, however, will lead to a long-term reduction in dry season river discharge from glacierized catchments. This glacier retreat is closely related to the observed increase in high-elevation, surface air temperature in the region. Future projections using a simple freezing level height- equilibrium-line altitude scaling approach suggest that glaciers in the inner tropics, such as Antizana in Ecuador, may be most vulnerable to future warming while glaciers in the more arid outer tropics, such as Zongo in Bolivia, may persist, albeit in a smaller size, throughout the 21st century regardless of emission scenario. Nonetheless many uncertainties persist, most notably problems with accurate snowfall measurements in the glacier accumulation zone, uncertainties in establishing accurate thickness measurements on glaciers, unknown future changes associated with local-scale circulation and cloud cover affecting glacier energy balance, the role of aerosols and in particular black carbon deposition on Andean glaciers, and the role of groundwater and aquifers interacting with glacier meltwater.The reduction in water supply for export-oriented agriculture, mining, hydropower production and human consumption are the most commonly discussed concerns associated with glacier retreat, but many other aspects including glacial hazards, tourism and recreation, and ecosystem integrity are also affected by glacier retreat. Social and political problems surrounding water allocation for subsistence farming have led to conflicts due to lack of adequate water governance. Local water management practices in many regions reflect cultural belief systems, perceptions and spiritual values and glacier retreat in some places is seen as a threat to these local livelihoods.Comprehensive adaptation strategies, if they are to be successful, therefore need to consider science, policy, culture and practice, and involve local populations. Planning needs to be based not only on future scenarios derived from physically-based numerical models, but must also consider societal needs, economic agendas, political conflicts, socioeconomic inequality and cultural values. This review elaborates on the need for adaptation as well as the challenges and constraints many adaptation projects are faced with, and lays out future directions where opportunities exist to develop successful, culturally acceptable and sustainable adaptation strategies

Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set

Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Recently, snow routines in hydrological and land surface models were improved to incorporate more accurate representations of forest snow processes, but model intercomparison projects have identified deficiencies, partly due to incomplete knowledge of the processes controlling snow cover in forests. The Snow Under Forest (SnoUF) project was initiated to enhance knowledge of the complex interactions between snow and vegetation. Two field campaigns, during the winters 2016–2017 and 2017–2018, were conducted in a coniferous forest bordering the snow study at Col de Porte (1325 m a.s.l., French Alps) to document the snow accumulation and ablation processes. This paper presents the field site, the instrumentation and the collection and postprocessing methods. The observations include distributed forest characteristics (tree inventory, lidar measurements of forest structure, subcanopy hemispherical photographs), meteorology (automatic weather station and an array of radiometers), snow cover and depth (snow pole transect and laser scan) and snow interception by the canopy during precipitation events. The weather station installed under dense canopy during the first campaign has been maintained since then and has provided continuous measurements throughout the year since 2018. Data are publicly available from the repository of the Observatoire des Sciences de l'Univers de Grenoble (OSUG) data center at https://doi.org/10.17178/SNOUF.2022 (Sicart et al., 2022).</p