Insights into precipitation orographic enhancement from snow-course data and their value for improved hydrologic predictions

2020 ◽  
Author(s):  
Francesco Avanzi ◽  
Giulia Ercolani ◽  
Simone Gabellani ◽  
Edoardo Cremonese ◽  
Umberto Morra di Cella ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
High Elevation ◽  
Elevation Gradients ◽  
Precipitation Distribution ◽  
Orographic Enhancement ◽  
Snow Water ◽  
Snow Model ◽  
Precipitation Gauge ◽  
Lapse Rates ◽  
High Elevations

<p>Precipitation enhancement along elevation gradients is the result of complex interactions between synoptic-circulation patterns and local topography. Since precipitation measurements at high elevation are often biased and sparse, predicting precipitation distribution in mountain regions is challenging, despite this being a key step of hydrologic-forecasting procedures and of water management in general. By acting as a natural precipitation gauge, the snowpack can provide useful information about precipitation orographic enhancement, but the information content of snow-course measurements in this regard has been generally underappreciated. We leveraged 70,000+ measurements upstream five reservoirs in Valle d’Aosta, Italy, to show how manual and radar snow courses can be used to estimate precipitation lapse rates and consequently improve predictions of hydrologic models. Snow Water Equivalent above 3000 m ASL can be more than 4-5 times cumulative seasonal precipitation below 1000 m ASL, with elevational gradients up to 1000 mm w.e. / km ASL. Enhancement factors estimated by blending precipitation-gauge and snow-course data are highly seasonal and spatially variable, with exponential or linear profiles with elevation depending on the year. Blended gauge - snow-course precipitation lapse rates can be used to infer precipitation in ungauged areas and compensate for elevation gradients in an iterative, two-step distribution procedure of precipitation based on modified Kriging. Coupling this precipitation-distribution procedure with a snow model (S3M) shows promising improvements in Snow Water Equivalent estimates at high elevations.</p>

scholarly journals Learning about precipitation orographic enhancement from snow-course data improves water-balance modeling

2020 ◽  
Author(s):  
Francesco Avanzi ◽  
Giulia Ercolani ◽  
Simone Gabellani ◽  
Edoardo Cremonese ◽  
Paolo Pogliotti ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Water Security ◽  
High Elevation ◽  
Data Sets ◽  
European Alps ◽  
Spatially Distributed ◽  
Significant Step ◽  
Orographic Enhancement ◽  
Precipitation Gauge ◽  
Lapse Rates

Abstract. Precipitation orographic enhancement depends on both synoptic circulation and topography. Since high-elevation headwaters are often sparsely instrumented, the magnitude and distribution of this enhancement remain poorly understood. Filling this knowledge gap would allow a significant step ahead for hydrologic-forecasting procedures and water management in general. Here, we hypothesized that spatially distributed, manual measurements of snow depth (courses) could provide new insights into this process. We leveraged 11,000+ snow-course data upstream two reservoirs in the Western European Alps (Aosta Valley, Italy) to estimate precipitation orographic enhancement in the form of lapse rates and consequently improve predictions of a snow-hydrologic modeling chain (Flood-PROOFS). We found that Snow Water Equivalent (SWE) above 3000 m ASL was between 2 and 8.5 times higher than recorded cumulative seasonal precipitation below 1000 m ASL, with gradients up to 1000 mm w.e. km−1. Enhancement factors estimated by blending precipitation-gauge and snow-course data were quite consistent between the two hydropower headwaters (median values above 3000 m ASL between 4.1 and 4.8). Including blended gauge-course lapse rates in an iterative precipitation-spatialization procedure allowed Flood-PROOFS to remedy underestimations of both SWE above 3000 m ASL (up to 50 %) and importantly precipitation vs. observed streamflow. Runoff coefficients based on blended lapse rates were also more consistent from year to year that those based on precipitation gauges alone (standard deviation of 0.06 and 0.19, respectively). Thus, snow courses bear a characteristic signature of orographic precipitation, which opens a window of opportunity for leveraging these data sets to improve our understanding of the mountain water budget. This is all the more important due to their essential role in supporting water security and ecosystem services worldwide.

scholarly journals Learning about precipitation lapse rates from snow course data improves water balance modeling

2021 ◽  
Vol 25 (4) ◽  
pp. 2109-2131
Author(s):  
Francesco Avanzi ◽  
Giulia Ercolani ◽  
Simone Gabellani ◽  
Edoardo Cremonese ◽  
Paolo Pogliotti ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Water Security ◽  
High Elevation ◽  
Annual Runoff ◽  
Data Sets ◽  
European Alps ◽  
Significant Step ◽  
Orographic Enhancement ◽  
Precipitation Gauge ◽  
Lapse Rates

Abstract. Precipitation orographic enhancement is the result of both synoptic circulation and topography. Since high-elevation headwaters are often sparsely instrumented, the magnitude and distribution of this enhancement, as well as how they affect precipitation lapse rates, remain poorly understood. Filling this knowledge gap would allow a significant step ahead for hydrologic forecasting procedures and water management in general. Here, we hypothesized that spatially distributed, manual measurements of snow depth (courses) could provide new insights into this process. We leveraged over 11 000 snow course data upstream of two reservoirs in the western European Alps (Aosta Valley, Italy) to estimate precipitation orographic enhancement in the form of lapse rates and, consequently, improve predictions of a snow hydrologic modeling chain (Flood-PROOFS). We found that snow water equivalent (SWE) above 3000 m a.s.l. (above sea level) was between 2 and 8.5 times higher than recorded cumulative seasonal precipitation below 1000 m a.s.l., with gradients up to 1000 mm w.e. km−1. Enhancement factors, estimated by blending precipitation gauge and snow course data, were consistent between the two hydropower headwaters (median values above 3000 m a.s.l. between 4.1 and 4.8). Including blended gauge course lapse rates in an iterative precipitation spatialization procedure allowed Flood-PROOFS to remedy underestimations both of SWE above 3000 m a.s.l. (up to 50 %) and – importantly – of precipitation vs. observed streamflow. Annual runoff coefficients based on blended lapse rates were also more consistent from year to year than those based on precipitation gauges alone (standard deviation of 0.06 and 0.19, respectively). Thus, snow courses bear a characteristic signature of orographic precipitation, which opens a window of opportunity for leveraging these data sets to improve our understanding of the mountain water budget. This is all the more important due to the essential role of high-elevation headwaters in supporting water security and ecosystem services worldwide.

scholarly journals Investigating the Variability of High-Elevation Seasonal Orographic Snowfall Enhancement and Its Drivers across Sierra Nevada, California

2018 ◽  
Vol 19 (1) ◽  
pp. 47-67 ◽  
Author(s):  
Laurie S. Huning ◽  
Steven A. Margulis
Keyword(s):  
Sierra Nevada ◽  
Snow Water Equivalent ◽  
High Elevation ◽  
Mountain Range ◽  
Distributed Data ◽  
Mountainous Regions ◽  
Average Maximum ◽  
Spatially Distributed ◽  
Orographic Enhancement ◽  
Snow Water

Abstract While orographically driven snowfall is known to be important in mountainous regions, a complete understanding of orographic enhancement from the basin to the mountain range scale is often inhibited by limited distributed data and spatial and/or temporal resolutions. A novel, 90-m spatially distributed snow water equivalent (SWE) reanalysis was used to overcome these limitations. Leveraging this SWE information, the interannual variability of orographic gradients in cumulative snowfall (CS) was investigated over 14 windward (western) basins in the Sierra Nevada in California from water years 1985 to 2015. Previous studies have not provided a detailed multidecadal climatology of orographic CS gradients or compared wet-year and dry-year orographic CS patterns, distributions, and gradients across an entire mountain range. The magnitude of seasonal CS gradients range from over 15 cm SWE per 100-m elevation to under 1 cm per 100 m with a 31-yr average of 6.1 cm per 100 m below ~2500 m in the western basins. The 31-yr average CS gradients generally decrease in higher elevation zones across the western basins and become negative at the highest elevations. On average, integrated vapor transport and zonal winds at 700 hPa are larger during wet years, leading to higher orographically driven CS gradients across the Sierra Nevada than in dry years. Below ~2500 m, wet years yield greater enhancement (relative to dry years) by factors of approximately 2 and 3 in the northwestern and southwestern basins, respectively. Overall, the western Sierra Nevada experiences about twice as much orographic enhancement during wet years as in dry years below the elevation corresponding to the 31-yr average maximum CS.

scholarly journals Assessment of MERRA-2 and ERA5 to Model the Snow Water Equivalent in the High Atlas (1981–2019)

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 890
Author(s):  
Mohamed Wassim Baba ◽  
Abdelghani Boudhar ◽  
Simon Gascoin ◽  
Lahoucine Hanich ◽  
Ahmed Marchane ◽  
...  
Keyword(s):  
River Discharge ◽  
Snow Water Equivalent ◽  
High Elevation ◽  
Water Runoff ◽  
High Atlas ◽  
Seasonal Snow ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Melt water runoff from seasonal snow in the High Atlas range is an essential water resource in Morocco. However, there are only few meteorological stations in the high elevation areas and therefore it is challenging to estimate the distribution of snow water equivalent (SWE) based only on in situ measurements. In this work we assessed the performance of ERA5 and MERRA-2 climate reanalysis to compute the spatial distribution of SWE in the High Atlas. We forced a distributed snowpack evolution model (SnowModel) with downscaled ERA5 and MERRA-2 data at 200 m spatial resolution. The model was run over the period 1981 to 2019 (37 water years). Model outputs were assessed using observations of river discharge, snow height and MODIS snow-covered area. The results show a good performance for both MERRA-2 and ERA5 in terms of reproducing the snowpack state for the majority of water years, with a lower bias using ERA5 forcing.

scholarly journals Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

2017 ◽  
Vol 11 (4) ◽  
pp. 1647-1664 ◽  
Author(s):  
Emmy E. Stigter ◽  
Niko Wanders ◽  
Tuomo M. Saloranta ◽  
Joseph M. Shea ◽  
Marc F. P. Bierkens ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Snow Cover ◽  
Climate Sensitivity ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Snowmelt Runoff ◽  
Snow Water ◽  
Snow Model

Abstract. Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE). Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of) SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF). Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May) and decreases during the late melt season (June to September) as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly) compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

scholarly journals Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach

2018 ◽  
Vol 22 (2) ◽  
pp. 1593-1614 ◽  
Author(s):  
Florian Hanzer ◽  
Kristian Förster ◽  
Johanna Nemec ◽  
Ulrich Strasser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Future Climate Change ◽  
Climate Projections ◽  
Early 21St Century ◽  
Physically Based ◽  
Snow Water ◽  
High Elevations

Abstract. A physically based hydroclimatological model (AMUNDSEN) is used to assess future climate change impacts on the cryosphere and hydrology of the Ötztal Alps (Austria) until 2100. The model is run in 100 m spatial and 3 h temporal resolution using in total 31 downscaled, bias-corrected, and temporally disaggregated EURO-CORDEX climate projections for the representative concentration pathways (RCPs) 2.6, 4.5, and 8.5 scenarios as forcing data, making this – to date – the most detailed study for this region in terms of process representation and range of considered climate projections. Changes in snow coverage, glacierization, and hydrological regimes are discussed both for a larger area encompassing the Ötztal Alps (1850 km2, 862–3770 m a.s.l.) as well as for seven catchments in the area with varying size (11–165 km2) and glacierization (24–77 %). Results show generally declining snow amounts with moderate decreases (0–20 % depending on the emission scenario) of mean annual snow water equivalent in high elevations (> 2500 m a.s.l.) until the end of the century. The largest decreases, amounting to up to 25–80 %, are projected to occur in elevations below 1500 m a.s.l. Glaciers in the region will continue to retreat strongly, leaving only 4–20 % of the initial (as of 2006) ice volume left by 2100. Total and summer (JJA) runoff will change little during the early 21st century (2011–2040) with simulated decreases (compared to 1997–2006) of up to 11 % (total) and 13 % (summer) depending on catchment and scenario, whereas runoff volumes decrease by up to 39 % (total) and 47 % (summer) towards the end of the century (2071–2100), accompanied by a shift in peak flows from July towards June.

scholarly journals Air temperature variability in a high-elevation Himalayan catchment

2016 ◽  
Vol 57 (71) ◽  
pp. 212-222 ◽  
Author(s):  
Martin Heynen ◽  
Evan Miles ◽  
Silvan Ragettli ◽  
Pascal Buri ◽  
Walter W. Immerzeel ◽  
...  
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Monsoon Season ◽  
High Elevation ◽  
Catchment Scale ◽  
Diurnal Variability ◽  
Atmosphere Interaction ◽  
Temperature Seasonality ◽  
Lapse Rates ◽  
High Elevations

AbstractAir temperature is a key control of processes affecting snow and glaciers in high-elevation catchments, including melt, snowfall and sublimation. It is therefore a key input variable to models of land–surface–atmosphere interaction. Despite this importance, its spatial variability is poorly understood and simple assumptions are made to extrapolate it from point observations to the catchment scale. We use a dataset of 2.75 years of air temperature measurements (from May 2012 to November 2014) at a network of up to 27 locations in the Langtang River, Nepal, catchment to investigate air temperature seasonality and consistency between years. We use observations from high elevations and from the easternmost section of the basin to corroborate previous findings of shallow lapse rates. Seasonal variability is strong, with shallowest lapse rates during the monsoon season. Diurnal variability is also strong and should be taken into account since processes such as melt have a pronounced diurnal variability. Use of seasonal lapse rates seems crucial for glacio-hydrological modelling, but seasonal lapse rates seem stable over the 2–3 years investigated. Lateral variability at transects across valley is high and dominated by aspect, with south-facing sites being warmer than north-facing sites and deviations from the fitted lapse rates of up to several degrees. Local factors (e.g. topographic shading) can reduce or enhance this effect. The interplay of radiation, aspect and elevation should be further investigated with high-elevation transects.

scholarly journals Evaluation of CLASS Snow Simulation over Eastern Canada

2017 ◽  
Vol 18 (5) ◽  
pp. 1205-1225 ◽  
Author(s):  
Diana Verseghy ◽  
Ross Brown ◽  
Libo Wang
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern Canada ◽  
Fractional Snow Cover ◽  
Forest Regions ◽  
Snow Water ◽  
Snow Model

Abstract The Canadian Land Surface Scheme (CLASS), version 3.6.1, was run offline for the period 1990–2011 over a domain centered on eastern Canada, driven by atmospheric forcing data dynamically downscaled from ERA-Interim using the Canadian Regional Climate Model. The precipitation inputs were adjusted to replicate the monthly average precipitation reported in the CRU observational database. The simulated fractional snow cover and the surface albedo were evaluated using NOAA Interactive Multisensor Snow and Ice Mapping System and MODIS data, and the snow water equivalent was evaluated using CMC, Global Snow Monitoring for Climate Research (GlobSnow), and Hydro-Québec products. The modeled fractional snow cover agreed well with the observational estimates. The albedo of snow-covered areas showed a bias of up to −0.15 in boreal forest regions, owing to neglect of subgrid-scale lakes in the simulation. In June, conversely, there was a positive albedo bias in the remaining snow-covered areas, likely caused by neglect of impurities in the snow. The validation of the snow water equivalent was complicated by the fact that the three observation-based datasets differed widely. Also, the downward adjustment of the forcing precipitation clearly resulted in a low snow bias in some regions. However, where the density of the observations was high, the CLASS snow model was deemed to have performed well. Sensitivity tests confirmed the satisfactory behavior of the current parameterizations of snow thermal conductivity, snow albedo refreshment threshold, and limiting snow depth and underlined the importance of snow interception by vegetation. Overall, the study demonstrated the necessity of using a wide variety of observation-based datasets for model validation.

scholarly journals Projected cryospheric and hydrological impacts of 21st century climate change in the Ötztal Alps (Austria) simulated using a physically based approach

2017 ◽  
Author(s):  
Florian Hanzer ◽  
Kristian Förster ◽  
Johanna Nemec ◽  
Ulrich Strasser
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Future Climate Change ◽  
Climate Projections ◽  
Early 21St Century ◽  
Physically Based ◽  
Snow Water ◽  
High Elevations

Abstract. A physically based hydroclimatological model (AMUNDSEN) is used to assess future climate change impacts on the cryosphere and hydrology of the Ötztal Alps (Austria) until 2100. The model is run in 100 m spatial and 3 h temporal resolution using in total 31 downscaled, bias-corrected, and temporally disaggregated EURO-CORDEX climate projections for the RCP2.6, RCP4.5, and RCP8.5 scenarios as forcing data. Changes in snow coverage, glacierization, and hydrological regimes are discussed both for a larger area encompassing the Ötztal Alps (1850 km2, 862–3770 m a.s.l.) as well as for seven catchments in the area with varying size (11–16 km2) and glacierization (24–77 %). Results show generally declining snow amounts with moderate decreases (0–20 % depending on the emission scenario) of mean annual snow water equivalent in high elevations (> 2500 m a.s.l.) until the end of the century, however decreases of 25–80 % in elevations below 1500 m a.s.l. Glaciers in the region will continue to retreat strongly, leaving only 4–20 % of the initial (as of 2006) ice volume left by 2100. Total and summer (JJA) runoff will change little during the early 21st century (2011–2040) with simulated decreases (compared to 1997–2006) of up to 11 % (total) and 13 % (summer) depending on catchment and scenario, whereas runoff volumes decrease by up to 39 % (total) and 47 % (summer) towards the end of the century (2071–2100), accompanied by a shift in peak flows from July towards June.

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