Physically Based Global Downscaling: Regional Evaluation

Abstract The climate simulated by a global atmosphere–land model with a physically based subgrid orography scheme is evaluated in 10 selected regions. Climate variables simulated for each of multiple elevation classes within each grid cell are mapped according to a high-resolution distribution of surface elevation in each region. Comparison of the simulated annual mean climate with gridded observations leads to the following conclusions. At low to moderate elevations the downscaling scheme correctly simulates increasing precipitation, decreasing temperature, and increasing snow with increasing elevation across distances smaller than 100 km. At high elevations the downscaling scheme correctly simulates decreasing precipitation with increasing elevation. The rain shadow of many mountain ranges is poorly resolved, with too little precipitation simulated on the windward side of mountain ranges and too much on the lee side. The simulated sensitivity of surface air temperature to surface elevation is too strong, particularly in valleys influenced by drainage circulations. Observations show little evidence of a “snow shadow,” so the neglect of the subgrid rain shadow does not produce an unrealistic simulation of the snow distribution. Summertime snow area, which is a proxy for land ice, is much larger than observed, mostly because of excessive snowfall but in some places because of a cold bias. Summertime snow water equivalent is far less than the observed thickness of glaciers because a 1-m upper bound on snow water is applied to the simulations and because snow transport by slides is neglected. The 1-m upper bound on snow water equivalent also causes an underestimate of seasonal snow water during late winter, compared with gridded station measurements. Potential solutions to these problems are discussed.

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

Hydrology and Earth System Sciences ◽

10.5194/hess-22-1593-2018 ◽

2018 ◽

Vol 22 (2) ◽

pp. 1593-1614 ◽

Cited By ~ 21

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.

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Physically based simulating long-term dynamics of diurnal variations of river runoff and snow water equivalent in the Kolyma River Basin

Water Resources ◽

10.1134/s0097807815060056 ◽

2015 ◽

Vol 42 (6) ◽

pp. 834-841 ◽

Cited By ~ 1

Author(s):

E. M. Gusev ◽

O. N. Nasonova ◽

L. Ya. Dzhogan

Keyword(s):

River Basin ◽

River Runoff ◽

Snow Water Equivalent ◽

Diurnal Variations ◽

Physically Based ◽

Snow Water ◽

Kolyma River

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

10.5194/hess-2017-309 ◽

2017 ◽

Cited By ~ 4

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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Simulation of the snowmelt runoff contributing area in a small alpine basin

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-7-971-2010 ◽

2010 ◽

Vol 7 (1) ◽

pp. 971-1003 ◽

Cited By ~ 3

Author(s):

C. M. DeBeer ◽

J. W. Pomeroy

Keyword(s):

Snow Cover ◽

Snow Water Equivalent ◽

Spatial Scales ◽

Snowmelt Runoff ◽

Point Scale ◽

Cold Regions ◽

Covered Area ◽

Basin Scale ◽

Physically Based ◽

Snow Water

Abstract. Simulation of areal snowmelt and snow-cover depletion over time can be carried out by applying point-scale melt rate computations to distributions of snow water equivalent (SWE). In alpine basins, this can be done by considering these processes separately on individual slope units. However, differences in melt timing and rates arise at smaller spatial scales due to the variability in SWE and snowpack cold content, which affects the timing of melt initiation, depletion of the snow-cover and spatial extent of the snowmelt runoff contributing area (SRCA). This study examined the effects of variability in SWE, internal energy and applied melt energy on melt rates and timing, and snow-cover depletion in a small cold regions alpine basin over various scales ranging from point to basin. Melt rate computations were performed using a physically based energy balance snowmelt routine (Snobal) in the Cold Regions Hydrological Model (CRHM) and compared with measurements at three meteorological stations over a ridge within the basin. At the point scale, a negative association between daily melt rates and SWE was observed in the early melt period, with deeper snow requiring greater energy inputs to initiate melt. SWE distributions over the basin (stratified by slope) were measured using snow surveys and repeat LiDAR depth estimates, and used together with computed melt rates to simulate the areal snow-cover depletion. Comparison with observations from georeferenced oblique photographs showed an improvement in simulated areal snow-cover depletion curves when accounting for the variability in melt rate with depth of SWE in the early melt period. Finally, the SRCA was characterized as the product of the snow-covered area and the fraction of the SWE distribution undergoing active melt on each slope unit. Results for each slope were then aggregated to give the basin scale SRCA. The SRCA is controlled by the variability of melt amongst slope units and over individual SWE distributions, the variability of SWE and the resulting snow-cover depletion patterns over the basin.

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A multiphysical ensemble system of numerical snow modelling

10.5194/tc-2016-287 ◽

2017 ◽

Cited By ~ 1

Author(s):

Matthieu Lafaysse ◽

Bertrand Cluzet ◽

Marie Dumont ◽

Yves Lejeune ◽

Vincent Vionnet ◽

...

Keyword(s):

Surface Temperature ◽

Snow Depth ◽

Snow Water Equivalent ◽

Ensemble Forecasting ◽

Physical Processes ◽

High Quality ◽

Physically Based ◽

Snow Water ◽

Performance Results ◽

Simulation Errors

Abstract. Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multi-physical ensemble system ESCROC (Ensemble System Crocus) by implementing new representations of different physical processes in the deterministic coupled multi-layer ground/snowpack model SURFEX/ISBA/Crocus. This ensemble was driven and evaluated at Col de Porte (1325 m a.s.l., French alps) over 18 years with a high quality meteorological and snow dataset. 7776 simulations were evaluated separately accounting for the uncertainties of evaluation data. The ability of the ensemble to capture the uncertainty associated to modelling errors is assessed for snow depth, snow water equivalent, bulk density, albedo and surface temperature. Different sub-ensembles of the ESCROC system were studied with probabilistic tools to compare their performance. Results show that optimal members of the ESCROC system are able to explain more than half of the total simulation errors. Integrating members with biases exceeding the range corresponding to observations uncertainties is necessary to obtain an optimal dispersion, but this issue can also be a consequence of the fact that meterorological forcing uncertainties were not accounted for. ESCROC is a promising system to integrate numerical snow modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack modelling applications.

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Systematic Patterns of the Inconsistency between Snow Water Equivalent and Accumulated Precipitation as Reported by the Snowpack Telemetry Network

Journal of Hydrometeorology ◽

10.1175/jhm-d-12-066.1 ◽

2012 ◽

Vol 13 (6) ◽

pp. 1970-1976 ◽

Cited By ~ 19

Author(s):

Jonathan D. D. Meyer ◽

Jiming Jin ◽

Shih-Yu Wang

Keyword(s):

Sierra Nevada ◽

Rocky Mountains ◽

Snow Water Equivalent ◽

Systematic Bias ◽

Mountain Ranges ◽

Wind Speeds ◽

Drifting Snow ◽

Snow Water ◽

Interior West ◽

One Year

Abstract The authors investigated the accuracy of snow water equivalent (SWE) observations compiled by 748 Snowpack Telemetry stations and attributed the systematic bias introduced to SWE measurements to drifting snow. Often observed, SWE outpaces accumulated precipitation (AP), which can be statistically and physically explained through 1) precipitation undercatchment and/or 2) drifting snow. Forty-four percent of the 748 stations reported at least one year where the maximum SWE was greater than AP, while 16% of the stations showed this inconsistency for at least 20% of the observed years. Regions with a higher likelihood of inconsistency contained drier snow and are exposed to higher winds speeds, both of which are positively correlated to drifting snow potential as well as gauge undercatch. Differentiating between gauge undercatch and potential drifting scenarios, days when SWE increased but AP remained zero were used. These drift days occurred on an average of 13.3 days per year for all stations, with 31% greater wind speeds at 10 m for such days (using reanalysis winds). Findings suggest marked consistency between SWE and AP throughout the Cascade Mountains and lower elevations of the interior west while indicating notable inconsistency between these two variables throughout the higher elevations of the Rocky Mountains, Utah mountain ranges, and the Sierra Nevada.

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Assessment of a multiresolution snow reanalysis framework: a multidecadal reanalysis case over the upper Yampa River basin, Colorado

Hydrology and Earth System Sciences ◽

10.5194/hess-22-3575-2018 ◽

2018 ◽

Vol 22 (7) ◽

pp. 3575-3587 ◽

Cited By ~ 4

Author(s):

Elisabeth Baldo ◽

Steven A. Margulis

Keyword(s):

Data Assimilation ◽

River Basin ◽

Large Scale ◽

Snow Water Equivalent ◽

Low Complexity ◽

Snow Accumulation ◽

Computationally Efficient ◽

Snow Cover Area ◽

Mountain Ranges ◽

Snow Water

Abstract. A multiresolution (MR) approach was successfully implemented in the context of a data assimilation (DA) framework to efficiently estimate snow water equivalent (SWE) over a large head water catchment in the Colorado River basin (CRB), while decreasing computational constraints by 60 %. A total of 31 years of fractional snow cover area (fSCA) images derived from Landsat TM, ETM+, and OLI sensor measurements were assimilated to generate two SWE reanalysis datasets, a baseline case at a uniform 90 m spatial resolution and another using the MR approach. A comparison of the two showed negligible differences in terms of snow accumulation, melt, and timing for the posterior estimates (in terms of both ensemble median and coefficient of variation). The MR approach underestimated the baseline peak SWE by less than 2 % and underestimated day of peak and duration of the accumulation season by a day on average. The largest differences were, by construct, limited primarily to areas of low complexity, where shallow snowpacks tend to exist. The MR approach should allow for more computationally efficient implementations of snow data assimilation applications over large-scale mountain ranges, with accuracies similar to those that would be obtained using ∼ 100 m simulations. Such uniform resolution applications are generally infeasible due to the computationally expensive nature of ensemble-based DA frameworks.

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Snow Wetness Influence on Impulse Radar Snow Surveys Theoretical and Laboratory Study

Hydrology Research ◽

10.2166/nh.2000.0007 ◽

2000 ◽

Vol 31 (2) ◽

pp. 89-106 ◽

Cited By ~ 23

Author(s):

A. Lundberg ◽

H. Thunehed

Keyword(s):

Water Content ◽

Liquid Water ◽

Snow Water Equivalent ◽

Liquid Water Content ◽

Late Winter ◽

Propagation Time ◽

Reservoir Water ◽

A Value ◽

Wet Snow ◽

Snow Water

The snow-water equivalent of late-winter snowpack is of utmost importance for hydropower production in areas where a large proportion of the reservoir water emanates from snowmelt. Impulse radar can be used to estimate the snow-water equivalent of the snowpack and thus the expected snowmelt discharge. Impulse radar is now in operational use in some Scandinavian basins. With radar technology the radar wave propagation time in the snowpack is converted into snow-water equivalent with help of a parameter usually termed the a-value. Use of radar technology during late winter brings about risk for measurements on wet snow. The a-value for dry snow cannot be used directly for wet snow. We have found that a liquid-water content of 5% (by volume) reduces the a-value by approximately 20%. In this paper an equation, based on snow density and snow liquid water content, for calculation of wet-snow a-value is presented.

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The Response of Areal Snow Cover to Climate Change in a Snowmelt—Runoff Model

Annals of Glaciology ◽

10.1017/s0260305500014099 ◽

1997 ◽

Vol 25 ◽

pp. 232-236 ◽

Cited By ~ 4

Author(s):

A. Rango

Keyword(s):

Climate Change ◽

Snow Cover ◽

Snow Water Equivalent ◽

Major Influence ◽

Snowmelt Runoff ◽

Snow Cover Extent ◽

Physically Based ◽

Depletion Rate ◽

Snow Water ◽

Runoff Model

The cryosphere is represented in some hydrological models by the arcal extent of snow cover, a variable that has been operationally available in recent years through remote sensing. In particular, the snowmelt runoff model (SRM) requires the remotely sensed snow-cover extent as a major input variable. The SRM is well-suited for simulating the hydrological response of a basin to hypothetical climate change because it is a non-calibrated model. In order to run the SRM in a climate-change mode, the response of the areal snow cover to a change in climate is critical, and must be calculated as a function of elevation, precipitation, temperature, and snow-water equivalent. For the snowmelt-runoff season, the effect of climate change on conditions in the winter months has a major influence. In a warmer climate, winter may experience more rain vs snow events, and more periods of winter snowmelt that reduce the snow water equivalent present in the basin at the beginning of spring snow melt. As a result, the spring snowmelt runoff under conditions of climate warming will be affected not only by different temperatures and precipitation, but also by a different snow cover with a changed depletion rate. A new radiation-based version of the SRM is under development that will also take changes in cloudiness and humidity into account, making climate-change studies of the cryosphere even more physically based.

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