White water: Fifty years of snow research in <scp>WRR</scp> and the outlook for the future

Sturm, Matthew

doi:10.1002/2015wr017242

Cited by 63 publications

(66 citation statements)

References 125 publications

(159 reference statements)

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“…In the past several decades, significant changes in snowpack volume have been recorded in the Sierra Nevada Mountains [62][63][64] and are projected to continue to change in the future [65]. Snow monitoring techniques have also evolved and advanced significantly, providing more comprehensive data sources which likely revolutionize the snow sciences [66][67][68][69]. How to capitalize on these advancements to modernize our forecasting tools remains to be a challenging task for (particularly the next generation) forecasters.…”

Section: Implications Of This Studymentioning

confidence: 99%

Changes in Extremes of Temperature, Precipitation, and Runoff in California’s Central Valley During 1949–2010

He¹,

Russo²,

Anderson³

et al. 2017

Hydrology

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This study presents a comprehensive trend analysis of precipitation, temperature, and runoff extremes in the Central Valley of California from an operational perspective. California is prone to those extremes of which any changes could have long-lasting adverse impacts on the society, economy, and environment of the State. Available long-term operational datasets of 176 forecasting basins in six forecasting groups and inflow to 12 major water supply reservoirs are employed. A suite of nine precipitation indices and nine temperature indices derived from historical (water year 1949-2010) six-hourly precipitation and temperature data for these basins are investigated, along with nine indices based on daily unimpaired inflow to those 12 reservoirs in a slightly shorter period. Those indices include daily maximum precipitation, temperature, runoff, snowmelt, and others that are critical in informing decision making in water resources management. The non-parametric Mann-Kendall trend test is applied with a trend-free pre-whitening procedure in identifying trends in these indices. Changes in empirical probability distributions of individual study indices in two equal sub-periods are also investigated. The results show decreasing number of cold nights, increasing number of warm nights, increasing maximum temperature, and increasing annual mean minimum temperature at about 60% of the study area. Changes in cold extremes are generally more pronounced than their counterparts in warm extremes, contributing to decreasing diurnal temperature ranges. In general, the driest and coldest Tulare forecasting group observes the most consistent changes among all six groups. Analysis of probability distributions of temperature indices in two sub-periods yields similar results. In contrast, changes in precipitation extremes are less consistent spatially and less significant in terms of change rate. Only four indices exhibit statistically significant changes in less than 10% of the study area. On the regional scale, only the American forecasting group shows significant decreasing trends in two indices including maximum six-hourly precipitation and simple daily intensity index. On the other hand, runoff exhibits strong resilience to the changes noticed in temperature and precipitation extremes. Only the most southern reservoir (Lake Isabella) shows significant earlier peak timing of snowmelt. Additional analysis on runoff indices using different trend analysis methods and different analysis periods also indicates limited changes in these runoff indices. Overall, these findings are meaningful in guiding reservoir operations and water resources planning and management practices. IntroductionClimatic and weather-induced hazards including excessive heat, flooding, and drought are often economically, environmentally, and societally disruptive [1][2][3]. Previous studies have suggested that such hazards are typically caused by changes in the frequency and intensity rather than the mean of hydro-climatic variables including precipita...

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Section: Implications Of This Studymentioning

confidence: 99%

Changes in Extremes of Temperature, Precipitation, and Runoff in California’s Central Valley During 1949–2010

He¹,

Russo²,

Anderson³

et al. 2017

Hydrology

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“…3.1. during snowfall and also by repeat freezing and melting cycles, which are more common to under maritime conditions. These climatic differences in turn affect the thermal properties of snow and ice because the thermal conductivity of snow is primarily a function of density and water content, and the snowpack properties impact the surface heat flux of glaciers when and where they are snow covered (Sturm et al, 1997;DeWalle and Rango, 2008). O'Neel et al (2014) find that Gulkana's glacier mass balance is primarily a function of summer temperatures and Wolverine glacier's mass balance is a function of both summer temperatures and winter precipitation.…”

Section: Cryosphere Energy Balance Representationsmentioning

confidence: 99%

“…The USGS has been measuring glacier and snow accumulation and ablation at three locations on Gulkana glacier from 1974 through the present (with an additional stake from 1990 through the present) and three locations on Wolverine from 1965 through the present (Van Beusekom et al, 2010). Glacier stakes measure changes in depth of snow and ice at one location between two observation dates.…”

Section: Observation Datamentioning

confidence: 99%

“…The reason that energy balance models are theoretically more robust than conceptual models is that the relative balance of heat fluxes changes over time and between locations (Kustas et al, 1994;Sicart et al, 2008;Huss et al, 2009). Several of the energy balance inputs are even more sparsely measured in mountain environments than precipitation and temperature and often vary significantly over short spatial and temporal scales (see discussion on the surface energy balance in Sturm, 2015). As an example, wind speed linearly scales each convective heat flux (i.e., sensible and latent) and is therefore necessary for energy balance models.…”

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confidence: 99%

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How much cryosphere model complexity is just right? Exploration using the conceptual cryosphere hydrology framework

2016

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Abstract. Making meaningful projections of the impacts that possible future climates would have on water resources in mountain regions requires understanding how cryosphere hydrology model performance changes under altered climate conditions and when the model is applied to ungaged catchments. Further, if we are to develop better models, we must understand which specific process representations limit model performance. This article presents a modeling tool, named the Conceptual Cryosphere Hydrology Framework (CCHF), that enables implementing and evaluating a wide range of cryosphere modeling hypotheses. The CCHF represents cryosphere hydrology systems using a set of coupled process modules that allows easily interchanging individual module representations and includes analysis tools to evaluate model outputs. CCHF version 1 (Mosier, 2016) implements model formulations that require only precipitation and temperature as climate inputs -for example variations on simple degree-index (SDI) or enhanced temperature index (ETI) formulations -because these model structures are often applied in data-sparse mountain regions, and perform relatively well over short periods, but their calibration is known to change based on climate and geography. Using CCHF, we implement seven existing and novel models, including one existing SDI model, two existing ETI models, and four novel models that utilize a combination of existing and novel module representations. The novel module representations include a heat transfer formulation with net longwave radiation and a snowpack internal energy formulation that uses an approximation of the cold content. We assess the models for the Gulkana and Wolverine glaciated watersheds in Alaska, which have markedly different climates and contain long-term US Geological Survey benchmark glaciers. Overall we find that the best performing models are those that are more physically consistent and representative, but no single model performs best for all of our model evaluation criteria.

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“…Remote sensing captures the spatial and temporal patterns of snow and thus overcomes the potential undersampling of point measurements and the long surveys needed for snow courses [16,17]. Existing methods include Terrestrial Laser Scanner (TLS, [7,13,[18][19][20][21][22]), digital photogrammetry [23,24], tachymetry [20], Ground Penetrating Radar (GPR) [25], time-lapse photography [26,27], or satellite-based sensors [16].…”

Section: Introductionmentioning

confidence: 99%

Centimetric Accuracy in Snow Depth Using Unmanned Aerial System Photogrammetry and a MultiStation

et al. 2018

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Performing two independent surveys in 2016 and 2017 over a flat sample plot (6700 m 2 ), we compare snow-depth measurements from Unmanned-Aerial-System (UAS) photogrammetry and from a new high-resolution laser-scanning device (MultiStation) with manual probing, the standard technique used by operational services around the world. While previous comparisons already used laser scanners, we tested for the first time a MultiStation, which has a different measurement principle and is thus capable of millimetric accuracy. Both remote-sensing techniques measured point clouds with centimetric resolution, while we manually collected a relatively dense amount of manual data (135 pt in 2016 and 115 pt in 2017). UAS photogrammetry and the MultiStation showed repeatable, centimetric agreement in measuring the spatial distribution of seasonal, dense snowpack under optimal illumination and topographic conditions (maximum RMSE of 0.036 m between point clouds on snow). A large fraction of this difference could be due to simultaneous snowmelt, as the RMSE between UAS photogrammetry and the MultiStation on bare soil is equal to 0.02 m. The RMSE between UAS data and manual probing is in the order of 0.20-0.30 m, but decreases to 0.06-0.17 m when areas of potential outliers like vegetation or river beds are excluded. Compact and portable remote-sensing devices like UASs or a MultiStation can thus be successfully deployed during operational manual snow courses to capture spatial snapshots of snow-depth distribution with a repeatable, vertical centimetric accuracy.

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White water: Fifty years of snow research in WRR and the outlook for the future

Cited by 63 publications

References 125 publications

Changes in Extremes of Temperature, Precipitation, and Runoff in California’s Central Valley During 1949–2010

Changes in Extremes of Temperature, Precipitation, and Runoff in California’s Central Valley During 1949–2010

How much cryosphere model complexity is just right? Exploration using the conceptual cryosphere hydrology framework

Centimetric Accuracy in Snow Depth Using Unmanned Aerial System Photogrammetry and a MultiStation

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