scholarly journals Snow water equivalent along elevation gradients in the Merced and Tuolumne River basins of the Sierra Nevada

2011 ◽  
Vol 47 (8) ◽  
Author(s):  
Robert Rice ◽  
Roger C. Bales ◽  
Thomas H. Painter ◽  
Jeff Dozier
Keyword(s):  
Sierra Nevada ◽  
Snow Water Equivalent ◽  
River Basins ◽  
Elevation Gradients ◽  
Tuolumne River ◽  
Snow Water

scholarly journals Geocryological conditions triggering thermokarst processes in Central Yakutia

2020 ◽  
Vol 163 ◽  
pp. 02007
Author(s):  
Nataliia Nesterova ◽  
Olga Makarieva ◽  
Alexander Fedorov ◽  
Andrey Shikhov
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
River Basins ◽  
Soil Freezing ◽  
Abrupt Increase ◽  
Landsat Images ◽  
Thermokarst Lakes ◽  
Central Yakutia ◽  
Snow Water

The use of the Central Yakutia Landsat images revealed an increase in the area of thermokarst lakes by two times for the Suola and Taatta River basins and a quarter times in the Tanda River basin during the period 2000-2019. The abrupt increase in the lakes area is due to shortterm periods of abnormal rising in the active layer temperature, which are caused by high values of snow water equivalent and total annual precipitation. Increased soil moisture and the warming effect of snow cover led to the decrease of the intensity of soil freezing and increase of the temperature of the ground top layer. The combination of these factors triggered the activation of thermokarst processes, which led to a sharp, more than 1.5 times, increase of the thermokarst lakes area in 2007-2008.

scholarly journals Nutrient and mercury deposition and storage in an alpine snowpack of the Sierra Nevada, USA

2015 ◽  
Vol 12 (12) ◽  
pp. 3665-3680 ◽  
Author(s):  
C. Pearson ◽  
R. Schumer ◽  
B. D. Trustman ◽  
K. Rittger ◽  
D. W. Johnson ◽  
...  
Keyword(s):  
Sierra Nevada ◽  
Dry Deposition ◽  
Wet Deposition ◽  
Snow Water Equivalent ◽  
Snow Accumulation ◽  
Organic N ◽  
Lake Tahoe Basin ◽  
Inorganic N ◽  
Elevation Gradients ◽  
Tahoe Basin

Abstract. Biweekly snowpack core samples were collected at seven sites along two elevation gradients in the Tahoe Basin during two consecutive snow years to evaluate total wintertime snowpack accumulation of nutrients and pollutants in a high-elevation watershed of the Sierra Nevada. Additional sampling of wet deposition and detailed snow pit profiles were conducted the following year to compare wet deposition to snowpack storage and assess the vertical dynamics of snowpack nitrogen, phosphorus, and mercury. Results show that, on average, organic N comprised 48% of all snowpack N, while nitrate (NO3--N) and TAN (total ammonia nitrogen) made up 25 and 27%, respectively. Snowpack NO3--N concentrations were relatively uniform across sampling sites over the sampling seasons and showed little difference between seasonal wet deposition and integrated snow pit concentrations. These patterns are in agreement with previous studies that identify wet deposition as the dominant source of wintertime NO3--N deposition. However, vertical snow pit profiles showed highly variable concentrations of NO3--N within the snowpack indicative of additional deposition and in-snowpack dynamics. Unlike NO3--N, snowpack TAN doubled towards the end of winter, which we attribute to a strong dry deposition component which was particularly pronounced in late winter and spring. Organic N concentrations in the snowpack were highly variable (from 35 to 70%) and showed no clear temporal, spatial, or vertical trends throughout the season. Integrated snowpack organic N concentrations were up to 2.5 times higher than seasonal wet deposition, likely due to microbial immobilization of inorganic N as evident by coinciding increases in organic N and decreases in inorganic N in deeper, aged snow. Spatial and temporal deposition patterns of snowpack P were consistent with particulate-bound dry deposition inputs and strong impacts from in-basin sources causing up to 6 times greater enrichment at urban locations compared to remote sites. Snowpack Hg showed little temporal variability and was dominated by particulate-bound forms (78% on average). Dissolved Hg concentrations were consistently lower in snowpack than in wet deposition, which we attribute to photochemically driven gaseous re-emission. In agreement with this pattern is a significant positive relationship between snowpack Hg and elevation, attributed to a combination of increased snow accumulation at higher elevations causing limited light penetration and lower photochemical re-emission losses in deeper, higher-elevation snowpack. Finally, estimates of basin-wide loading based on spatially extrapolated concentrations and a satellite-based snow water equivalent reconstruction model identify snowpack chemical loading from atmospheric deposition as a substantial source of nutrients and pollutants to the Lake Tahoe Basin, accounting for 113 t of N, 9.3 t of P, and 1.2 kg of Hg each year.

scholarly journals Influence of snow water equivalent on droughts and their prediction in the USA

2018 ◽  
Author(s):  
Daniel Abel ◽  
Felix Pollinger ◽  
Heiko Paeth
Keyword(s):  
Sierra Nevada ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Southern Oscillation ◽  
Original Data ◽  
The United States ◽  
Early Summer ◽  
Drought Severity ◽  
Southern Us ◽  
Snow Water

Abstract. Droughts can result in enormous impacts for environment, societies, and economy. In arid or semiarid regions with bordering high mountains, snow is the major source of water supply due to its role as natural water storage. The goal of this study is to examine the influence of snow water equivalent (SWE) on droughts in the United States and find large-scale climatic predictors for SWE and drought. For this, a Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition, is performed with snow data from the ERA–Interim reanalysis and the self-calibrating Palmer Drought Severity Index (sc–PDSI) as drought index. Furthermore, the relationship of resulting principal components and original data with atmospheric patterns is investigated. The leading mode shows the spatial connection between SWE and drought via downstream water/moisture transport. Especially the Rocky Mountains in Colorado (CR) play a key role for the central and western South, but the Sierra Nevada and even the Appalachian Mountains are relevant, too. The temperature and precipitation based sc–PDSI is able to capture this link because increased soil moisture results in higher evapotranspiration with lower sensible heat and vice versa. A time shifted MCA indicates a prediction skill for drought conditions in spring and early summer for the downstream regions of CR on the basis of SWE in March. Furthermore, the phase of the El Niño–Southern Oscillation is a good predictor for drought in the southern US and SWE around Colorado. The influence of the North Atlantic Oscillation and Pacific North American Pattern is not that clear.

scholarly journals A quantitative method to decompose SWE differences between regional climate models and reanalysis datasets

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Yun Xu ◽  
Andrew Jones ◽  
Alan Rhoades
Keyword(s):  
Sierra Nevada ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Driving Forces ◽  
Regional Climate ◽  
Model Development ◽  
Regional Climate Models ◽  
The North ◽  
Snow Water ◽  
Regional Downscaling

Abstract The simulation of snow water equivalent (SWE) remains difficult for regional climate models. Accurate SWE simulation depends on complex interacting climate processes such as the intensity and distribution of precipitation, rain-snow partitioning, and radiative fluxes. To identify the driving forces behind SWE difference between model and reanalysis datasets, and guide model improvement, we design a framework to quantitatively decompose the SWE difference contributed from precipitation distribution and magnitude, ablation, temperature and topography biases in regional climate models. We apply this framework within the California Sierra Nevada to four regional climate models from the North American Coordinated Regional Downscaling Experiment (NA-CORDEX) run at three spatial resolutions. Models generally predict less SWE compared to Landsat-Era Sierra Nevada Snow Reanalysis (SNSR) dataset. Unresolved topography associated with model resolution contribute to dry and warm biases in models. Refining resolution from 0.44° to 0.11° improves SWE simulation by 35%. To varying degrees across models, additional difference arises from spatial and elevational distribution of precipitation, cold biases revealed by topographic correction, uncertainties in the rain-snow partitioning threshold, and high ablation biases. This work reveals both positive and negative contributions to snow bias in climate models and provides guidance for future model development to enhance SWE simulation.

scholarly journals Snow water scarcity induced by record-breaking warm winter in 2020 in Japan

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Satoshi Watanabe ◽  
Shunji Kotsuki ◽  
Shinjiro Kanae ◽  
Kenji Tanaka ◽  
Atsushi Higuchi
Keyword(s):  
Water Resources ◽  
High Temperatures ◽  
Water Scarcity ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
River Basins ◽  
Reanalysis Data ◽  
Temperature And Precipitation ◽  
Snow Water ◽  
The Impact

Abstract This study highlights the severity of the low snow water equivalent (SWE) and remarkably high temperatures in 2020 in Japan, where reductions in SWE have significant impacts on society due to its importance for water resources. A continuous 60-year land surface simulation forced by reanalysis data revealed that the low SWE in many river basins in the southern snowy region of mainland Japan are the most severe on record. The impact of the remarkably high temperatures in 2020 on the low SWE was investigated by considering the relationships among SWE, temperature, and precipitation. The main difference between the 2020 case and prior periods of low SWE is the record-breaking high temperatures. Despite the fact that SWE was the lowest in 2020, precipitation was much higher than that in 2019, which was one of the lowest SWE on record pre-2020. The results indicate the possibility that even more serious low-SWE periods will be caused if lower precipitation and higher temperatures occur simultaneously.

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

2012 ◽  
Vol 13 (6) ◽  
pp. 1970-1976 ◽  
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.

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 A Landsat-Era Sierra Nevada Snow Reanalysis (1985–2015)

2016 ◽  
Vol 17 (4) ◽  
pp. 1203-1221 ◽  
Author(s):  
Steven A. Margulis ◽  
Gonzalo Cortés ◽  
Manuela Girotto ◽  
Michael Durand
Keyword(s):  
Sierra Nevada ◽  
Snow Water Equivalent ◽  
Reanalysis Dataset ◽  
In Situ Data ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water ◽  
Fully Bayesian ◽  
Mean Square Errors

Abstract A newly developed state-of-the-art snow water equivalent (SWE) reanalysis dataset over the Sierra Nevada (United States) based on the assimilation of remotely sensed fractional snow-covered area data over the Landsat 5–8 record (1985–2015) is presented. The method (fully Bayesian), resolution (daily and 90 m), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The reanalysis dataset was used to characterize the peak SWE climatology to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years. The pixel-wise peak SWE volume over the domain was found to be 20.0 km3 on average with a range of 4.0–40.6 km3. The ongoing drought in California contains the two lowest snowpack years (water years 2014 and 2015) and three of the four driest years over the examined record. It was found that the basin-average peak SWE, while underestimating the total water storage in snowpack over the year, accurately captures the interannual variability in stored snowpack water. However, the results showed that the assumption that 1 April SWE is representative of the peak SWE can lead to significant underestimation of basin-average peak SWE both on an average (21% across all basins) and on an interannual basis (up to 98% across all basin years).

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.

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