A statistical approach to refining snow water equivalent climatologies in Alpine terrain

Abstract. Gridded snow water equivalent (SWE) are valuable to estimate the snow water resources and verify hydrological models and other models that consider snow as a component of the natural system. However, changing data availability represents a considerable challenge when trying to derive consistent time series for SWE products. In an attempt to improve the product consistency, we first evaluated the differences between two climatologies of SWE grids that were calculated on the basis of data from 110 and 203 stations, respectively. The "shorter" climatology (2001–2009) was produced using 203 stations (map203) and the "longer" one (1971–2009) 110 stations (map110). Relative to map203, map110 underestimated SWE, especially at higher elevations and at the end of the winter season. We tested the potential of quantile mapping to compensate for mapping errors in map110 relative to map203. During a nine-year calibration period from 2001–2009, for which both map203 and map110 were available, the method could successfully refine the spatial and temporal SWE representation in map110 by making seasonal, regional and altitude-related distinctions. Expanding the calibration to the full 39 yr showed that the general underestimation of map110 could be removed for the whole winter. The calibrated SWE maps were accurate when averaged over regions and time periods, where the mean error is approximately zero. However, deviations were observed at single grid cells and years. When we looked at three different regions in more detail, we found that the calibration had the largest effect in the region with the highest proportion of catchment areas above 2000 m a.s.l. and that the general underestimation of map110 could be removed for the entire snow season. The added value of the calibrated SWE climatology is illustrated with practical examples: the verification of a hydrological model, the estimation of snow resource anomalies and the predictability of runoff through SWE.

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Homogenisation of a gridded snow water equivalent climatology for Alpine terrain: methodology and applications

The Cryosphere ◽

10.5194/tc-8-471-2014 ◽

2014 ◽

Vol 8 (2) ◽

pp. 471-485 ◽

Cited By ~ 16

Author(s):

S. Jörg-Hess ◽

F. Fundel ◽

T. Jonas ◽

M. Zappa

Keyword(s):

Land Surface ◽

Snow Water Equivalent ◽

Winter Season ◽

Data Availability ◽

Model Systems ◽

Added Value ◽

Data Sets ◽

Atmospheric Models ◽

Catchment Areas ◽

Snow Water

Abstract. Gridded snow water equivalent (SWE) data sets are valuable for estimating the snow water resources and verify different model systems, e.g. hydrological, land surface or atmospheric models. However, changing data availability represents a considerable challenge when trying to derive consistent time series for SWE products. In an attempt to improve the product consistency, we first evaluated the differences between two climatologies of SWE grids that were calculated on the basis of data from 110 and 203 stations, respectively. The "shorter" climatology (2001–2009) was produced using 203 stations (map203) and the "longer" one (1971–2009) 110 stations (map110). Relative to map203, map110 underestimated SWE, especially at higher elevations and at the end of the winter season. We tested the potential of quantile mapping to compensate for mapping errors in map110 relative to map203. During a 9 yr calibration period from 2001 to 2009, for which both map203 and map110 were available, the method could successfully refine the spatial and temporal SWE representation in map110 by making seasonal, regional and altitude-related distinctions. Expanding the calibration to the full 39 yr showed that the general underestimation of map110 with respect to map203 could be removed for the whole winter. The calibrated SWE maps fitted the reference (map203) well when averaged over regions and time periods, where the mean error is approximately zero. However, deviations between the calibrated maps and map203 were observed at single grid cells and years. When we looked at three different regions in more detail, we found that the calibration had the largest effect in the region with the highest proportion of catchment areas above 2000 m a.s.l. and that the general underestimation of map110 compared to map203 could be removed for the entire snow season. The added value of the calibrated SWE climatology is illustrated with practical examples: the verification of a hydrological model, the estimation of snow resource anomalies and the predictability of runoff through SWE.

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Nimbus-7 SMMR Derived Global Snow Cover Parameters

Annals of Glaciology ◽

10.1017/s0260305500200736 ◽

1987 ◽

Vol 9 ◽

pp. 39-44 ◽

Cited By ~ 200

Author(s):

A.T.C. Chang ◽

J.L. Foster ◽

D.K. Hall

Keyword(s):

Snow Cover ◽

Northern Hemisphere ◽

Snow Water Equivalent ◽

Theoretical Calculations ◽

Winter Season ◽

Western China ◽

High Plains ◽

Snow Covered Area ◽

Covered Area ◽

Snow Water

Snow covers about 40 million km2of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

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Nimbus-7 SMMR Derived Global Snow Cover Parameters

Annals of Glaciology ◽

10.3189/s0260305500200736 ◽

1987 ◽

Vol 9 ◽

pp. 39-44 ◽

Cited By ~ 85

Author(s):

A.T.C. Chang ◽

J.L. Foster ◽

D.K. Hall

Keyword(s):

Snow Cover ◽

Northern Hemisphere ◽

Snow Water Equivalent ◽

Theoretical Calculations ◽

Winter Season ◽

Western China ◽

High Plains ◽

Snow Covered Area ◽

Covered Area ◽

Snow Water

Snow covers about 40 million km2 of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

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Snowpack energy balance and changes in the frequency and extremity of rain-on-snow events in the warming climate

10.5194/egusphere-egu21-73 ◽

2021 ◽

Author(s):

Ondrej Hotovy ◽

Michal Jenicek

Keyword(s):

Energy Balance ◽

Air Temperature ◽

Snow Water Equivalent ◽

Hydrological Cycle ◽

Winter Season ◽

Catchment Scale ◽

The Future ◽

Snow Water ◽

The Impact ◽

Catchment Runoff

Seasonal snowpack significantly influences the catchment runoff and thus represents an important input for the hydrological cycle. Changes in the precipitation distribution and intensity, as well as a shift from snowfall to rain is expected in the future due to climate changes. As a result, rain-on-snow events, which are considered to be one of the main causes of floods in winter and spring, may occur more frequently. Heat from liquid precipitation constitutes one of the snowpack energy balance components. Consequently, snowmelt and runoff may be strongly affected by these temperature and precipitation changes.The objective of this study is 1) to evaluate the frequency, inter-annual variability and extremity of rain-on-snow events in the past based on existing measurements together with an analysis of changes in the snowpack energy balance, and 2) to simulate the effect of predicted increase in air temperature on the occurrence of rain-on-snow events in the future. We selected 40 near-natural mountain catchments in Czechia with significant snow influence on runoff and with available long-time series (>35 years) of daily hydrological and meteorological variables. A semi-distributed conceptual model, HBV-light, was used to simulate the individual components of the water cycle at a catchment scale. The model was calibrated for each of study catchments by using 100 calibration trials which resulted in respective number of optimized parameter sets. The model performance was evaluated against observed runoff and snow water equivalent. Rain-on-snow events definition by threshold values for air temperature, snow depth, rain intensity and snow water equivalent decrease allowed us to analyze inter-annual variations and trends in rain-on-snow events during the study period 1965-2019 and to explain the role of different catchment attributes.The preliminary results show that a significant change of rain-on-snow events related to increasing air temperature is not clearly evident. Since both air temperature and elevation seem to be an important rain-on-snow drivers, there is an increasing rain-on-snow events occurrence during winter season due to a decrease in snowfall fraction. In contrast, a decrease in total number of events was observed due to the shortening of the period with existing snow cover on the ground. Modelling approach also opened further questions related to model structure and parameterization, specifically how individual model procedures and parameters represent the real natural processes. To understand potential model artefacts might be important when using HBV or similar bucket-type models for impact studies, such as modelling the impact of climate change on catchment runoff.

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Performance and reliability of multimodel hydrological ensemble simulations based on seventeen lumped models and a thousand catchments

Hydrology and Earth System Sciences ◽

10.5194/hess-14-2303-2010 ◽

2010 ◽

Vol 14 (11) ◽

pp. 2303-2317 ◽

Cited By ~ 45

Author(s):

J. A. Velázquez ◽

F. Anctil ◽

C. Perrin

Keyword(s):

Predictive Distribution ◽

Added Value ◽

Average Error ◽

Hydrological Models ◽

Relative Operating Characteristic ◽

Probability Score ◽

Ensemble Simulations ◽

Continuous Ranked Probability Score ◽

The Mean ◽

Improved Performance

Abstract. This work investigates the added value of ensembles constructed from seventeen lumped hydrological models against their simple average counterparts. It is thus hypothesized that there is more information provided by all the outputs of these models than by their single aggregated predictors. For all available 1061 catchments, results showed that the mean continuous ranked probability score of the ensemble simulations were better than the mean average error of the aggregated simulations, confirming the added value of retaining all the components of the model outputs. Reliability of the simulation ensembles is also achieved for about 30% of the catchments, as assessed by rank histograms and reliability plots. Nonetheless this imperfection, the ensemble simulations were shown to have better skills than the deterministic simulations at discriminating between events and non-events, as confirmed by relative operating characteristic scores especially for larger streamflows. From 7 to 10 models are deemed sufficient to construct ensembles with improved performance, based on a genetic algorithm search optimizing the continuous ranked probability score. In fact, many model subsets were found improving the performance of the reference ensemble. This is thus not essential to implement as much as seventeen lumped hydrological models. The gain in performance of the optimized subsets is accompanied by some improvement of the ensemble reliability in most cases. Nonetheless, a calibration of the predictive distribution is still needed for many catchments.

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Spatiotemporal Characteristics of Snowpack Density in the Mountainous Regions of the Western United States

Journal of Hydrometeorology ◽

10.1175/2008jhm981.1 ◽

2008 ◽

Vol 9 (6) ◽

pp. 1416-1426 ◽

Cited By ~ 45

Author(s):

Naoki Mizukami ◽

Sanja Perica

Keyword(s):

United States ◽

Snow Depth ◽

Snow Water Equivalent ◽

Winter Season ◽

Western United States ◽

Densification Rate ◽

Snow Density ◽

Mountainous Regions ◽

Spatiotemporal Characteristics ◽

Snow Water

Abstract Snow density is calculated as a ratio of snow water equivalent to snow depth. Until the late 1990s, there were no continuous simultaneous measurements of snow water equivalent and snow depth covering large areas. Because of that, spatiotemporal characteristics of snowpack density could not be well described. Since then, the Natural Resources Conservation Service (NRCS) has been collecting both types of data daily throughout the winter season at snowpack telemetry (SNOTEL) sites located in the mountainous areas of the western United States. This new dataset provided an opportunity to examine the spatiotemporal characteristics of snowpack density. The analysis of approximately seven years of data showed that at a given location and throughout the winter season, year-to-year snowpack density changes are significantly smaller than corresponding snow depth and snow water equivalent changes. As a result, reliable climatological estimates of snow density could be obtained from relatively short records. Snow density magnitudes and densification rates (i.e., rates at which snow densities change in time) were found to be location dependent. During early and midwinter, the densification rate is correlated with density. Starting in early or mid-March, however, snowpack density increases by approximately 2.0 kg m−3 day−1 regardless of location. Cluster analysis was used to obtain qualitative information on spatial patterns of snowpack density and densification rates. Four clusters were identified, each with a distinct density magnitude and densification rate. The most significant physiographic factor that discriminates between clusters was proximity to a large water body. Within individual mountain ranges, snowpack density characteristics were primarily dependent on elevation.

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Utility of late summer transient snowline migration rate on Taku Glacier, Alaska

The Cryosphere ◽

10.5194/tc-5-1127-2011 ◽

2011 ◽

Vol 5 (4) ◽

pp. 1127-1133 ◽

Cited By ~ 30

Author(s):

M. Pelto

Keyword(s):

Mass Balance ◽

Migration Rate ◽

Satellite Images ◽

Snow Water Equivalent ◽

Late Summer ◽

Ablation Rate ◽

Field Observations ◽

Balance Assessment ◽

Snow Water ◽

The Mean

Abstract. On Taku Glacier, Alaska a combination of field observations of snow water equivalent (SWE) from snowpits and probing in the vicinity of the transient snowline (TSL) are used to quantify the mass balance gradient. The balance gradient derived from the TSL and SWE measured in snowpits at 1000 m from 1998–2010 ranges from 2.6–3.8 mm m−1. Probing transects from 950 m–1100 m directly measure SWE and yield a slightly higher balance gradient of 3.3–3.8 mm m−1. The TSL on Taku Glacier is identified in MODIS and Landsat 4 and 7 Thematic Mapper images for 31 dates during the 2004–2010 period to assess the consistency of its rate of rise and reliability in assessing ablation for mass balance assessment. For example, in 2010, the TSL was 750 m on 28 July, 800 m on 5 August, 875 m on 14 August, 925 m on 30 August, and 975 m on 20 September. The mean observed probing balance gradient was 3.3 mm m−1, combined with the TSL rise of 3.7 m day−1 yields an ablation rate of 12.2 mm day−1 from mid-July to mid-Sept, 2010. The TSL rise in the region from 750–1100 m on Taku Glacier during eleven periods each covering more than 14 days during the ablation season indicates a mean TSL rise of 3.7 m day−1, the rate of rise is relatively consistent ranging from 3.1 to 4.4 m day−1. This rate is useful for ascertaining the final ELA if images or observations are not available near the end of the ablation season. The mean ablation from 750–1100 m during the July–September period determined from the TSL rise and the observed balance gradient is 11–13 mm day−1 on Taku Glacier during the 2004–2010 period. The potential for providing an estimate of bn from TSL observations late in the melt season from satellite images combined with the frequent availability of such images provides a means for efficient mass balance assessment in many years and on many glaciers.

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Changes in Snow Storage in the Upper Hron River Basin (Slovakia)

Acta Silvatica et Lignaria Hungarica ◽

10.2478/aslh-2014-0011 ◽

2014 ◽

Vol 10 (2) ◽

pp. 145-160

Author(s):

Katarína Kotríková ◽

Kamila Hlavčová ◽

Róbert Fencík

Keyword(s):

Snow Cover ◽

Snow Depth ◽

Satellite Images ◽

Snow Water Equivalent ◽

Winter Season ◽

Kendall Test ◽

Measured Data ◽

Time Step ◽

Snow Storage ◽

Snow Water

Abstract An evaluation of changes in the snow cover in mountainous basins in Slovakia and a validation of MODIS satellite images are provided in this paper. An analysis of the changes in snow cover was given by evaluating changes in the snow depth, the duration of the snow cover, and the simulated snow water equivalent in a daily time step using a conceptual hydrological rainfall-runoff model with lumped parameters. These values were compared with the available measured data at climate stations. The changes in the snow cover and the simulated snow water equivalent were estimated by trend analysis; its significance was tested using the Mann-Kendall test. Also, the satellite images were compared with the available measured data. From the results, it is possible to see a decrease in the snow depth and the snow water equivalent from 1961-2010 in all the months of the winter season, and significant decreasing trends were indicated in the months of December, January and February

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Modeling Snow Ablation over the Western United States Mountains: Patterns and Controlling Factors

Journal of Hydrometeorology ◽

10.1175/jhm-d-19-0198.1 ◽

2020 ◽

Author(s):

Mu Xiao ◽

Sarith P. Mahanama ◽

Yongkang Xue ◽

Fei Chen ◽

Dennis P. Lettenmaier

Keyword(s):

Surface Albedo ◽

Snow Water Equivalent ◽

Bare Soil ◽

Snow Accumulation ◽

Hydrological Models ◽

Net Radiation ◽

Energy Inputs ◽

Model Predictions ◽

Snow Water ◽

Canopy Removal

AbstractCompared to differences in snow accumulation predicted by widely-used hydrological models, there is a much greater divergence among otherwise “good” models in their simulation of snow ablation process. Here, we explore differences in the performance of VIC, Noah-MP, Catchment and SSiB3 in their ability to reproduce observed snow water equivalent (SWE) during the ablation season at ten SNOTEL stations over 1992-2012. During the ablation period net radiation generally has stronger correlations with observed melt rates than does air temperature. Average ablation rates tend to be higher (in both model predictions and observations) at stations with large accumulated SWE. The differences in the dates of last snow between models and observations range from several days to approximately a month (on average 5.1 days earlier than in observations). If the surface cover in the models is changed from observed vegetation to bare soil in all the models, only the melt rate of the VIC model increases.The differences in responses of models to canopy removal are directly related to snowpack energy inputs, which are further affected by different algorithms for surface albedo and energy allocation across the models. Finally, we find that the melt rates become higher in VIC and lower in Noah-MP if the shrub/grass present at the observation sites is switched to trees.

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Numerical experiments in calculating snow water equivalent and estimating their impact on the formation of spring floods

E3S Web of Conferences ◽

10.1051/e3sconf/202016306003 ◽

2020 ◽

Vol 163 ◽

pp. 06003

Author(s):

Evgenii Churiulin ◽

Vladimir Kopeykin ◽

Natalia Frolova ◽

Inna Krylenko

Keyword(s):

Snow Cover ◽

Snow Water Equivalent ◽

Weather Prediction ◽

Hydrological Models ◽

In Situ Data ◽

Use Of Data ◽

Complex Approach ◽

Snow Water ◽

Seasonal Snow Cover

Seasonal snow cover has a significant impact on forming spring floods. Sparse snow course-measuring network does not meet the requirements of modern tasks related to the technologies of numerical weather prediction (NWP) systems and runoff formation models. Moreover, insufficient volume of hydrometeorological data creates a need to improve spring floods forecasting methods by means of available modern hydrometeorological information related to snow cover. To work out an efficient solution to the issue of initial snow data preparation we need a complex approach including the use of data from satellite, atmospheric models, physical-mathematical models of snow cover and insitu information. This approach will provide modern NWP and hydrological models with reliable initial data on snow cover (snow water equivalent – SWE, snow density – SD). The main purpose of our investigation is related to approbation of satellite data and development of snow cover calculation methods for NWP and hydrological models. Numerous SWE and SD experiments have been performed in order to achieve this aim. A regional snow data assimilation system for COSMORu was implemented during the research. Moreover, a new method of hydrological modelling of spring floods based on ECOMAG model with initial information from COSMO-Ru, SnoWE and in-situ data has been proposed and tested.

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