scholarly journals Subseasonal Forecast Skill of Snow Water Equivalent and Its Link with Temperature in Selected SubX Models

2020 ◽  
Vol 35 (1) ◽  
pp. 273-284 ◽  
Author(s):  
G. T. Diro ◽  
H. Lin
Keyword(s):  
Snow Water Equivalent ◽  
The Other ◽  
Prediction Skill ◽  
Temperature Relationship ◽  
Contributing Factors ◽  
Strong Negative Correlation ◽  
Near Surface ◽  
Apparent Lack ◽  
Snow Water ◽  
Snow Temperature

AbstractAccurate and skillful subseasonal forecasts have tremendous potential for sectors that are sensitive to hazardous weather and climate events. Analysis of prediction skill for snow water equivalent (SWE) and near-surface air temperature (T2m) is carried out for three (GEPS, GEFS, and FIM) global models from the subseasonal experiment (SubX) project for the 2000–14 period. The prediction skill of SWE is higher than the skill of T2m at week-3 and week-4 lead times in all models. The GEPS forecast tends to yield higher (lower) prediction skill of SWE (T2m) compared to the other two systems in terms of correlation skill score. The snow–temperature relationship in reanalysis is characterized by a strong negative correlation over most of the midlatitude regions and a weak positive correlation over high-latitude Arctic regions. All forecast systems reproduced well these observed features; however, the snow–temperature relationship is slightly weaker in the GEPS model. Despite the apparent lack of skill in temperature forecasts at week 4, all three models are able to predict the sign of temperature anomalies associated with extreme SWE conditions albeit with reduced intensity. The strength of the predicted temperature anomaly associated with extreme snow conditions is slightly weaker in the GEPS forecast compared to reanalysis and the other two models, despite having better skill in predicting SWE. These apparent disparities suggest that weak snow–temperature coupling strength in the model is one of the contributing factors for the lower temperature skill.

scholarly journals Analysis of the Snow Water Equivalent at the AEMet-Formigal Field Laboratory (Spanish Pyrenees) During the 2019/2020 Winter Season Using a Stepped-Frequency Continuous Wave Radar (SFCW)

2021 ◽  
Vol 13 (4) ◽  
pp. 616
Author(s):  
Rafael Alonso ◽  
José María García del Pozo ◽  
Samuel T. Buisán ◽  
José Adolfo Álvarez
Keyword(s):  
Software Defined Radio ◽  
Continuous Wave ◽  
Snow Water Equivalent ◽  
Cosmic Ray ◽  
Relative Dielectric Permittivity ◽  
Near Surface ◽  
Wave Radar ◽  
Spanish Pyrenees ◽  
Snow Water ◽  
Stepped Frequency

Snow makes a great contribution to the hydrological cycle in cold regions. The parameter to characterize available the water from the snow cover is the well-known snow water equivalent (SWE). This paper presents a near-surface-based radar for determining the SWE from the measured complex spectral reflectance of the snowpack. The method is based in a stepped-frequency continuous wave radar (SFCW), implemented in a coherent software defined radio (SDR), in the range from 150 MHz to 6 GHz. An electromagnetic model to solve the electromagnetic reflectance of a snowpack, including the frequency and wetness dependence of the complex relative dielectric permittivity of snow layers, is shown. Using the previous model, an approximated method to calculate the SWE is proposed. The results are presented and compared with those provided by a cosmic-ray neutron SWE gauge over the 2019–2020 winter in the experimental AEMet Formigal-Sarrios test site. This experimental field is located in the Spanish Pyrenees at an elevation of 1800 m a.s.l. The results suggest the viability of the approximate method. Finally, the feasibility of an auxiliary snow height measurement sensor based on a 120 GHz frequency modulated continuous wave (FMCW) radar sensor, is shown.

scholarly journals Microwave Snow-Water Equivalent Mapping of the Upper Colorado River Basin, U.S.A. (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 244-245
Author(s):  
W.J. Campbell ◽  
E.G. Josberger ◽  
P. Gloersen ◽  
A.T.C. Chang
Keyword(s):  
Real Time ◽  
River Basin ◽  
Crystal Size ◽  
Colorado River ◽  
Snow Water Equivalent ◽  
The Other ◽  
Colorado River Basin ◽  
Snow Pack ◽  
Upper Colorado River Basin ◽  
Snow Water

During spring 1984, a joint agency research effort was made to explore the use of satellite passive microwave techniques to measure snow-water equivalents in the upper Colorado River basin. This study involved the near real-time acquisition of microwave radiances from the Scanning Multichannel Microwave Radiometer (SMMR) aboard the Nimbus-7 satellite, coupled with quasi-simultaneous surface measurements of snow-pack depth and profiles of temperature, density, and crystal size within the basin. A key idea in this study was to compare, for the same space and time-scales, the SMMR synoptic physics data taken in the basin. Such a snow-measurement program was logistically difficult, but two field teams took detailed snow-pit measurements at 18 sites in Colorado, Utah, and Wyoming during the last 2 weeks of March, when the snow-pack is normally at its maximum extent and depth. These observations were coupled with snow-water-equivalent measurements from Soil Conservation Service SNOTEL sites. Microwave- gradient ratio, Gr (Gr is the difference of the vertically polarized radiances at 8 mm and 17 mm divided by the sum), maps of the basin were derived in a near real-time mode every 6 days from SMMR observations. The sequential Gr maps showed anomalously low values in the Wyoming snow-pack when compared to the other states. This near real-time information then directed the field teams to Wyoming to carry out an extensive survey, which showed that these values were due to the presence of depth hoar; the average crystal sizes were more than twice as large as in the other areas. SMMR can be used to monitor the spatial distribution and temporal evolution of crystal size in snow-packs. Also, scatter diagrams of snow-water equivalents from the combined snow-pit and SNOTEL observations versus Gr from the Wyoming part, and the Colorado and Utah part, of the basin can be used to estimate snow-water equivalents for various parts of the basin.

scholarly journals The Impact of a Low Bias in Snow Water Equivalent Initialization on CFS Seasonal Forecasts

2017 ◽  
Vol 30 (21) ◽  
pp. 8657-8671 ◽  
Author(s):  
Patrick D. Broxton ◽  
Xubin Zeng ◽  
Nicholas Dawson
Keyword(s):  
Lead Time ◽  
Snow Water Equivalent ◽  
Seasonal Prediction ◽  
Seasonal Forecasts ◽  
Near Surface ◽  
Air Temperatures ◽  
Forecast Lead Time ◽  
Snow Water ◽  
The Impact

Across much of the Northern Hemisphere, Climate Forecast System forecasts made earlier in the winter (e.g., on 1 January) are found to have more snow water equivalent (SWE) in April–June than forecasts made later (e.g., on 1 April); furthermore, later forecasts tend to predict earlier snowmelt than earlier forecasts. As a result, other forecasted model quantities (e.g., soil moisture in April–June) show systematic differences dependent on the forecast lead time. Notably, earlier forecasts predict much colder near-surface air temperatures in April–June than later forecasts. Although the later forecasts of temperature are more accurate, earlier forecasts of SWE are more realistic, suggesting that the improvement in temperature forecasts occurs for the wrong reasons. Thus, this study highlights the need to improve atmospheric processes in the model (e.g., radiative transfer, turbulence) that would cause cold biases when a more realistic amount of snow is on the ground. Furthermore, SWE differences in earlier versus later forecasts are found to much more strongly affect April–June temperature forecasts than the sea surface temperature differences over different regions, suggesting the major role of snowpack in seasonal prediction during the spring–summer transition over snowy regions.

scholarly journals Microwave Snow-Water Equivalent Mapping of the Upper Colorado River Basin, U.S.A. (Abstract)

1987 ◽  
Vol 9 ◽  
pp. 244-245
Author(s):  
W.J. Campbell ◽  
E.G. Josberger ◽  
P. Gloersen ◽  
A.T.C. Chang
Keyword(s):  
Real Time ◽  
River Basin ◽  
Crystal Size ◽  
Colorado River ◽  
Snow Water Equivalent ◽  
The Other ◽  
Colorado River Basin ◽  
Snow Pack ◽  
Upper Colorado River Basin ◽  
Snow Water

During spring 1984, a joint agency research effort was made to explore the use of satellite passive microwave techniques to measure snow-water equivalents in the upper Colorado River basin. This study involved the near real-time acquisition of microwave radiances from the Scanning Multichannel Microwave Radiometer (SMMR) aboard the Nimbus-7 satellite, coupled with quasi-simultaneous surface measurements of snow-pack depth and profiles of temperature, density, and crystal size within the basin. A key idea in this study was to compare, for the same space and time-scales, the SMMR synoptic physics data taken in the basin. Such a snow-measurement program was logistically difficult, but two field teams took detailed snow-pit measurements at 18 sites in Colorado, Utah, and Wyoming during the last 2 weeks of March, when the snow-pack is normally at its maximum extent and depth. These observations were coupled with snow-water-equivalent measurements from Soil Conservation Service SNOTEL sites. Microwave- gradient ratio, Gr (Gr is the difference of the vertically polarized radiances at 8 mm and 17 mm divided by the sum), maps of the basin were derived in a near real-time mode every 6 days from SMMR observations. The sequential Gr maps showed anomalously low values in the Wyoming snow-pack when compared to the other states. This near real-time information then directed the field teams to Wyoming to carry out an extensive survey, which showed that these values were due to the presence of depth hoar; the average crystal sizes were more than twice as large as in the other areas. SMMR can be used to monitor the spatial distribution and temporal evolution of crystal size in snow-packs. Also, scatter diagrams of snow-water equivalents from the combined snow-pit and SNOTEL observations versus Gr from the Wyoming part, and the Colorado and Utah part, of the basin can be used to estimate snow-water equivalents for various parts of the basin.

scholarly journals Hydrologic Flowpath Development Varies by Aspect during Spring Snowmelt in Complex Subalpine Terrain

2017 ◽  
Author(s):  
Ryan W. Webb ◽  
Steven R. Fassnacht ◽  
Michael N. Gooseff
Keyword(s):  
Soil Moisture ◽  
Snow Water Equivalent ◽  
Surface Soil ◽  
Slope Aspect ◽  
Surface Soil Moisture ◽  
Near Surface ◽  
Mountainous Regions ◽  
Snow Water ◽  
Spring Snowmelt ◽  
Preferential Flowpaths

Abstract. In many mountainous regions around the world, snow and soil moisture are key components of the hydrologic cycle. Preferential flowpaths of snowmelt water through snow have been known to occur for years with few studies observing the effect on soil moisture. In this study, statistical analysis of the topographical and hydrological controls on the spatio-temporal variability of snow water equivalent and soil moisture during snowmelt was undertaken at a subalpine forested setting with north, south, and flat aspects as a seasonally persistent snowpack melts. We investigated if preferential flowpaths in snow can be observed and the effect on soil moisture through measurements of snow water equivalent and near surface soil moisture in addition to observing how SWE and near surface soil moisture vary on hillslopes relative to the toes of hillslopes and flat areas. We then compared snowmelt infiltration beyond the near surface soil between flat and sloping terrain during the entire snowmelt season using soil moisture sensor profiles. This study was conducted during varying snowmelt seasons representing above normal, relatively normal, and below normal snow seasons in northern Colorado. Evidence is presented of preferential meltwater flowpaths at the snow-soil interface on the north facing slope with the effects observed in changes in SWE and infiltration into the soil at 20 cm depth; less association is observed in the near surface soil moisture (top 7 cm). We present a conceptualization of the meltwater flowpaths that develop based on slope aspect and soil properties. The resulting flowpaths are shown to increase the snow water equivalent by as much as 170 % at the base of a north facing hillslope. Results from this study show that snow acts as an extension of the vadose zone during spring snowmelt and future hydrologic investigations will benefit from studying the snow and soil together.

scholarly journals A 7-year dataset for driving and evaluating snow models at an arctic site (Sodankylä, Finland)

2016 ◽  
Author(s):  
R. Essery ◽  
A. Kontu ◽  
J. Lemmetyinen ◽  
M. Dumon ◽  
C. B. Ménard
Keyword(s):  
Wind Speed ◽  
Atmospheric Pressure ◽  
Snow Water Equivalent ◽  
Longwave Radiation ◽  
Snow Density ◽  
Evaluation Data ◽  
Physically Based ◽  
Snow Water ◽  
Snow Model ◽  
Snow Temperature

Abstract. Datasets derived from measurements at Sodankylä in the Finnish Arctic that can be used for driving and evaluating snow models are presented. The driving datasets comprise all of the meteorological variables required as inputs for physically-based snow models at hourly intervals: incoming solar and longwave radiation, snowfall and rainfall rates, air temperature, humidity, wind speed and atmospheric pressure. Two versions of the driving data are provided: one using radiation and wind speed measurements made above the height of the trees around the clearing where the evaluation data were measured and one with adjustments for the influence of the trees on conditions close to the ground. The available evaluation data include automatic and manual measurements of bulk snow depth and snow water equivalent, and profiles of snow temperature, snow density and soil temperature. A physically-based snow model is driven and evaluated with the datasets to illustrate their utility. Shading by trees extends the duration of snow cover on the ground by several days a year.

scholarly journals Comparison of manual snow water equivalent measurements: questioning the reference for the true SWE value

2021 ◽  
Author(s):  
Maxime Beaudoin-Galaise ◽  
Sylvain Jutras
Keyword(s):  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Large Diameter ◽  
Mean Bias Error ◽  
Bias Error ◽  
Apparent Lack ◽  
Lack Of Information ◽  
Different Types ◽  
Snow Water ◽  
Lower Uncertainty

Abstract. Manual measurement of snow water equivalent (SWE) is still important today for several applications such as hydrological model validation. This measurement can be performed with different types of snow tube sampler or by a snow pit. Although these methods have been performed for several decades, there is an apparent lack of information required to have a consensus regarding the best reference for “true” SWE. We define and estimate the uncertainty and measurement error of different methods of snow pits and snow samplers. Analysis was based upon measurements taken over five consecutive winters (2016–2020) from the same flat and open area. This study compares two snow pit methods and three snow samplers. In addition to including the Standard Federal sampler (SFS), this study documents the first use of two new large diameter samplers, the Hydro-Québec sampler (HQS) and Université Laval sampler (ULS). Large diameter samplers had lowest uncertainty (2.6 to 4.0 %). Snow pit methods had higher uncertainty due to instruments (7.1 to 11.4 %), close to that of the SFS (mean = 10.4 %). Given its larger collected snow volume for estimating SWE and its lower uncertainty, we posit that ULS represents the most appropriate method of reference for “true” SWE. By considering ULS as the reference in calculating mean bias error (MBE), different snow pit methods overestimated SWE by 16.6 to 26.2 %, which was much higher than SFS (8.4 %). This study suggests that large diameter samplers are the best method for estimating “true” SWE.

scholarly journals Cryosphere Applications

2020 ◽  
pp. 179-213
Author(s):  
I. Hajnsek ◽  
G. Parrella ◽  
A. Marino ◽  
T. Eltoft ◽  
M. Necsoiu ◽  
...  
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Snow Water Equivalent ◽  
Real Data ◽  
Near Surface ◽  
Ice Volume ◽  
Snow Water ◽  
Surface Ice

AbstractSynthetic aperture radar (SAR) provides large coverage and high resolution, and it has been proven to be sensitive to both surface and near-surface features related to accumulation, ablation, and metamorphism of snow and firn. Exploiting this sensitivity, SAR polarimetry and polarimetric interferometry found application to land ice for instance for the estimation of wave extinction (which relates to sub surface ice volume structure) and for the estimation of snow water equivalent (which relates to snow density and depth). After presenting these applications, the Chapter proceeds by reviewing applications of SAR polarimetry to sea ice for the classification of different ice types, the estimation of thickness, and the characterisation of its surface. Finally, an application to the characterisation of permafrost regions is considered. For each application, the used (model-based) decomposition and polarimetric parameters are critically described, and real data results from relevant airborne campaigns and space borne acquisitions are reported.

scholarly journals Hydrologic flow path development varies by aspect during spring snowmelt in complex subalpine terrain

2018 ◽  
Vol 12 (1) ◽  
pp. 287-300 ◽  
Author(s):  
Ryan W. Webb ◽  
Steven R. Fassnacht ◽  
Michael N. Gooseff
Keyword(s):  
Soil Moisture ◽  
Preferential Flow ◽  
Snow Water Equivalent ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Flow Paths ◽  
Near Surface ◽  
Preferential Flow Paths ◽  
Snow Water ◽  
Spring Snowmelt

Abstract. In many mountainous regions around the world, snow and soil moisture are key components of the hydrologic cycle. Preferential flow paths of snowmelt water through snow have been known to occur for years with few studies observing the effect on soil moisture. In this study, statistical analysis of the topographical and hydrological controls on the spatiotemporal variability of snow water equivalent (SWE) and soil moisture during snowmelt was undertaken at a subalpine forested setting with north, south, and flat aspects as a seasonally persistent snowpack melts. We investigated if evidence of preferential flow paths in snow can be observed and the effect on soil moisture through measurements of snow water equivalent and near-surface soil moisture, observing how SWE and near-surface soil moisture vary on hillslopes relative to the toes of hillslopes and flat areas. We then compared snowmelt infiltration beyond the near-surface soil between flat and sloping terrain during the entire snowmelt season using soil moisture sensor profiles. This study was conducted during varying snowmelt seasons representing above-normal, relatively normal, and below-normal snow seasons in northern Colorado. Evidence is presented of preferential meltwater flow paths at the snow–soil interface on the north-facing slope causing increases in SWE downslope and less infiltration into the soil at 20 cm depth; less association is observed in the near-surface soil moisture (top 7 cm). We present a conceptualization of the meltwater flow paths that develop based on slope aspect and soil properties. The resulting flow paths are shown to divert at least 4 % of snowmelt laterally, accumulating along the length of the slope, to increase the snow water equivalent by as much as 170 % at the base of a north-facing hillslope. Results from this study show that snow acts as an extension of the vadose zone during spring snowmelt and future hydrologic investigations will benefit from studying the snow and soil together.

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