scholarly journals Exploring the Origins of Snow Drought in the Northern Sierra Nevada, California

2018 ◽  
Vol 22 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Benjamin J. Hatchett ◽  
Daniel J. McEvoy
Keyword(s):  
Water Resources ◽  
Sierra Nevada ◽  
Time Scales ◽  
Snow Water Equivalent ◽  
Mountain Watersheds ◽  
Snow Water ◽  
Peak Runoff ◽  
Widespread Interest ◽  
Runoff Events ◽  
Low Precipitation

Abstract The concept of snow drought is gaining widespread interest as the climate of snow-dominated mountain watersheds continues to change. Warm snow drought is defined as above- or near-average accumulated precipitation coinciding with below-average snow water equivalent at a point in time. Dry snow drought is defined as below-average accumulated precipitation and snow water equivalent at a point in time. This study contends that such point-in-time definitions might miss important components of how snow droughts originate, persist, and terminate. Using these simple definitions and a variety of observations at monthly, daily, and hourly time scales, the authors explore the hydrometeorological origins of potential snow droughts in the northern Sierra Nevada from water years 1951 to 2017. This study finds that snow droughts can result from extreme early season precipitation, frequent rain-on-snow events, and low precipitation years. Late-season snow droughts can follow persistent warm and dry periods with effects that depend upon elevation. Many snow droughts were characterized by lower snow fractions and midwinter peak runoff events. These findings can guide improved evaluations of historical and potential future snow droughts, particularly with regards to how impacts on water resources and mountain ecosystems may vary depending on how snow droughts originate and evolve in time.

scholarly journals Seasonal Estimates and Uncertainties of Snow Accumulation from CloudSat Precipitation Retrievals

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 363
Author(s):  
George Duffy ◽  
Fraser King ◽  
Ralf Bennartz ◽  
Christopher G. Fletcher
Keyword(s):  
Time Scales ◽  
Snow Water Equivalent ◽  
Spatial Scales ◽  
Snow Accumulation ◽  
High Latitudes ◽  
Percentage Points ◽  
Snow Water ◽  
Time Periods ◽  
Predicted Values ◽  
Good Agreement

CloudSat is often the only measurement of snowfall rate available at high latitudes, making it a valuable tool for understanding snow climatology. The capability of CloudSat to provide information on seasonal and subseasonal time scales, however, has yet to be explored. In this study, we use subsampled reanalysis estimates to predict the uncertainties of CloudSat snow water equivalent (SWE) accumulation measurements at various space and time resolutions. An idealized/simulated subsampling model predicts that CloudSat may provide seasonal SWE estimates with median percent errors below 50% at spatial scales as small as 2° × 2°. By converting these predictions to percent differences, we can evaluate CloudSat snowfall accumulations against a blend of gridded SWE measurements during frozen time periods. Our predictions are in good agreement with results. The 25th, 50th, and 75th percentiles of the percent differences between the two measurements all match predicted values within eight percentage points. We interpret these results to suggest that CloudSat snowfall estimates are in sufficient agreement with other, thoroughly vetted, gridded SWE products. This implies that CloudSat may provide useful estimates of snow accumulation over remote regions within seasonal time scales.

scholarly journals Spatial models of adjusted precipitation for Canada at varying time scales

2021 ◽  
Author(s):  
Heather MacDonald ◽  
Daniel W. McKenney ◽  
Xiaolan L. Wang ◽  
John Pedlar ◽  
Pia Papadopol ◽  
...  
Keyword(s):  
Time Scales ◽  
Input Data ◽  
Snow Water Equivalent ◽  
Spatial Models ◽  
Total Precipitation ◽  
Spline Surfaces ◽  
Monthly Total Precipitation ◽  
Monthly Total ◽  
Snow Water ◽  
First Time

AbstractThis study presents spatial models (i.e., thin plate spatially continuous spline surfaces) of adjusted precipitation for Canada at daily, pentad (5-day), and monthly time scales from 1900 to 2015. The input data include manual observations from 3346 stations that were adjusted previously to correct for snow water equivalent (SWE) conversion and various gauge-related issues. In addition to the 42,331 models for daily total precipitation and 1392 monthly total precipitation models 8395 pentad models were developed for the first time, depicting mean precipitation for 73 pentads annually. For much of Canada, mapped precipitation values from this study were higher than those from the corresponding unadjusted models (i.e., models fitted to the unadjusted data), reflecting predominantly the effects of the adjustments to the input data. Error estimates compared favourably to the corresponding unadjusted models. For example, Root generalized cross validation (GCV) estimate (a measure of predictive error) at the daily time scale was 3.6 mm on average for the 1960 to 2003 period as compared to 3.7 mm for the unadjusted models over the same period. There was a dry bias in the predictions relative to recorded values of between 1% and 6.7% of the average precipitations amounts for all time scales. Mean absolute predictive errors of the daily, pentad, and monthly models were 2.5 mm (52.7%), 0.9 mm (37.4%), and 11.2 mm (19.3%), respectively. In general, the model skill was closely tied to the density of the station network. The current adjusted models are available in grid form at ~2-10 km resolutions.

Long-term (1900-2100) Hydrometeorological and Snow Water Equivalent reconstructions in the French Southern Alps (Mercantour Natural Parc).

2021 ◽  
Author(s):  
Thibault Mathevet ◽  
Cyril Thébault ◽  
Jérôme Mansons ◽  
Matthieu Le Lay ◽  
Audrey Valery ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Water Resources ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Hydrological Regime ◽  
Southern Alps ◽  
Snow Line ◽  
Snow Water

<p>The aim of this communication is to present a study on climate variability and change on snow water equivalent (SWE) and streamflow over the 1900-2100 period in a mediteranean and moutainuous area.  It is based on SWE and streamflow observations, past reconstructions (1900-2018) and future GIEC scenarii (up to 2100) of some snow courses and hydrological stations situated within the French Southern Alps (Mercantour Natural Parc). This has been conducted by EDF (French hydropower company) and Mercantour Natural Parc.</p><p>This issue became particularly important since a decade, especially in regions where snow variability had a large impact on water resources availability, poor snow conditions in ski resorts and artificial snow production or impacts on mountainous ecosystems (fauna and flora). As a water resources manager in French mountainuous regions, EDF developed and managed a large hydrometeorological network since 1950. A recent data rescue research allowed to digitize long term SWE manual measurements of a hundred of snow courses within the French Alps. EDF have been operating an automatic SWE sensors network, complementary to historical snow course network. Based on numerous SWE observations time-series and snow modelization (Garavaglia et al., 2017), continuous daily historical SWE time-series have been reconstructed within the 1950-2018 period. These reconstructions have been extented to 1900 using 20 CR (20<sup>th</sup> century reanalyses by NOAA) reanalyses (ANATEM method, Kuentz et al., 2015) and up to 2100 using GIEC Climate Change scenarii (+4.5 W/m² and + 8.5 W/m² hypotheses). In the scope of this study, Mercantour Natural Parc is particularly interested by snow scenarii in the future and its impacts on their local flora and fauna.</p><p>Considering observations within Durance watershed and Mercantour region, this communication focuses on: (1) long term (1900-2018) analyses of variability and trend of hydrometeorological and snow variables (total precipitation, air temperature, snow water equivalent, snow line altitude, snow season length, streamflow regimes) , (2) long term variability of snow and hydrological regime of snow dominated watersheds and (3) future trends (2020 -2100) using GIEC Climate Change scenarii.</p><p>Comparing old period (1950-1984) to recent period (1984-2018), quantitative results within these regions roughly shows an increase of air temperature by 1.2 °C, an increase of snow line height by 200m, a reduction of SWE by 200 mm/year and a reduction of snow season duration by 15 days. Characterization of the increase of snow line height and SWE reduction are particularly important at a local and watershed scale. Then, this communication focuses on impacts on long-term time scales (2050, 2100). This long term change of snow dynamics within moutainuous regions both impacts (1) water resources management, (2) snow resorts and artificial snow production developments or (3) ecosystems dynamics.Connected to the evolution of snow seasonality, the impacts on hydrological regime and some streamflow signatures allow to characterize the possible evolution of water resources in this mediteranean and moutianuous region This study allowed to provide some local quantitative scenarii.</p>

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.

scholarly journals Future snow? A spatial-probabilistic assessment of the extraordinarily low snowpacks of 2014 and 2015 in the Oregon Cascades

2017 ◽  
Vol 11 (1) ◽  
pp. 331-341 ◽  
Author(s):  
Eric A. Sproles ◽  
Travis R. Roth ◽  
Anne W. Nolin
Keyword(s):  
Water Resources ◽  
Pacific Northwest ◽  
Snow Water Equivalent ◽  
Probabilistic Approach ◽  
Water Storage ◽  
Climate Change Impacts ◽  
Willamette River ◽  
Climate Conditions ◽  
Snow Water ◽  
Social Environmental

Abstract. In the Pacific Northwest, USA, the extraordinarily low snowpacks of winters 2013–2014 and 2014–2015 stressed regional water resources and the social-environmental system. We introduce two new approaches to better understand how seasonal snow water storage during these two winters would compare to snow water storage under warmer climate conditions. The first approach calculates a spatial-probabilistic metric representing the likelihood that the snow water storage of 2013–2014 and 2014–2015 would occur under +2 °C perturbed climate conditions. We computed snow water storage (basin-wide and across elevations) and the ratio of snow water equivalent to cumulative precipitation (across elevations) for the McKenzie River basin (3041 km2), a major tributary to the Willamette River in Oregon, USA. We applied these computations to calculate the occurrence probability for similarly low snow water storage under climate warming. Results suggest that, relative to +2 °C conditions, basin-wide snow water storage during winter 2013–2014 would be above average, while that of winter 2014–2015 would be far below average. Snow water storage on 1 April corresponds to a 42 % (2013–2014) and 92 % (2014–2015) probability of being met or exceeded in any given year. The second approach introduces the concept of snow analogs to improve the anticipatory capacity of climate change impacts on snow-derived water resources. The use of a spatial-probabilistic approach and snow analogs provide new methods of assessing basin-wide snow water storage in a non-stationary climate and are readily applicable in other snow-dominated watersheds.

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