Snowpack Change From 1982 to 2016 Over Conterminous United States

Zeng, Xubin; Broxton, P. D.; Dawson, Nicholas

doi:10.1029/2018gl079621

Cited by 128 publications

(153 citation statements)

References 34 publications

(63 reference statements)

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“…Following previous studies (Mote, 2006;Zeng et al, 2018), we partitioned the entire CONUS into two geographic units (Western and Eastern CONUS) using the 100°W longitude line for discussion. We resized this data set from 4-km to 0.125°spatial resolution to match the model grids using the nearest neighbor interpolation.…”

Section: Resultsmentioning

confidence: 99%

“…We resized this data set from 4-km to 0.125°spatial resolution to match the model grids using the nearest neighbor interpolation. Following previous studies (Mote, 2006;Zeng et al, 2018), we partitioned the entire CONUS into two geographic units (Western and Eastern CONUS) using the 100°W longitude line for discussion. While we are aware that more detailed data analyses through aggregation by latitude may generate some extra insights on the climatic impacts (e.g., Saavedra et al, 2018), in this study, we aggregate the data by relative humidity and elevation (related to humidity) to focus on the effects of humidity on precipitation phase prediction.…”

Section: Resultsmentioning

confidence: 99%

“…Snowmelt is the primary source of streamflow and groundwater recharge in alpine and cold regions (Bales et al, 2006;Mote et al, 2005) and accounts for more than 70% of freshwater runoff in the mountainous and semiarid Western United States (Cayan et al, 2001;Knowles et al, 2006;Li et al, 2017). The snow water equivalent (SWE), snow cover extent, and snow depth in the Western United States have been declining (Knowles, 2015;Zeng et al, 2018) due to a shift from snowfall to rainfall and earlier snowmelt, as evidenced by earlier streamflow peaks and earlier blooming and leafing out of plants (Cayan et al, 2001;Mote et al, 2005). Less snowfall is also expected by the middle of the 21st century over most of the Western United States due to global warming (Klos et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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A Wet‐Bulb Temperature‐Based Rain‐Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States

Wang

Broxton

Fang

et al. 2019

Geophysical Research Letters

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Accumulation of snowfall during winter and snowmelt in the subsequent spring or earlier summer provides a dominant water source in alpine regions. Most land surface and hydrological models use near-surface air temperature (T a ) thresholds to partition precipitation into snow and rain, underestimating snowfall over drier regions. We developed a snow-rain partitioning scheme using the wet-bulb temperature (T w ), which is closer to the surface temperature of a falling hydrometeor than T a . T w becomes more depressed in drier environments as derived from T w depression equation using T a and surface air humidity, resulting in a greater fraction of snowfall. We implemented this new T w scheme in the Noah-MP land surface model and evaluated the model against a high-quality ground-based snow product over the contiguous United States. The results suggest that the new T w scheme substantially improves the model skill in simulating snow depth and snow water equivalent over most snow-covered grids, especially the higher and drier continental mountain ranges in the Western United States, while it retains the modeling accuracy over the more humid Eastern United States.Plain Language Summary The partitioning between rainfall and snowfall is important for understanding the impacts of climate change and water resource availability. Most land surface and hydrological models use surface air temperature to partition precipitation into rain and snow and thus underestimate snowfall and snow mass accumulated on the ground in the drier Western United States. A falling hydrometeor evaporates or sublimates at its surface depending on the humidity of the surrounding air and cools off, resulting in a surface temperature that is cooler than the air temperature. The depressed surface temperature is close to the wet-bulb temperature. We developed a scheme using the wet-bulb temperature and tested it with a physically based snow model over the contiguous United States. The testing results strongly support the use of wet-bulb temperature, which enhances snowfall and the snow mass on the ground more significantly over the higher and drier mountains in the Western United States, while it retains the modeling accuracy in the more humid Eastern United States.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Wet‐Bulb Temperature‐Based Rain‐Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States

Wang

Broxton

Fang

et al. 2019

Geophysical Research Letters

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“…In addition to real‐time snow observations, a long‐term record of SWE is important for identifying climate variability and trends and for developing a climatology of the snowpack. As changes in seasonal snow have recently accelerated across the United States in the last few decades (Ashfaq et al, ; Georgakakos et al, ), reliable long‐term SWE measurements are further needed for effective water management and flood risk assessments (Zeng et al, ). Point‐based long‐term SWE records from snow station networks (e.g., NRCS Snowpack Telemetry [SNOTEL]) have provided high‐quality measurements.…”

Section: Introductionmentioning

confidence: 99%

The Value of Long‐Term (40 years) Airborne Gamma Radiation SWE Record for Evaluating Three Observation‐Based Gridded SWE Data Sets by Seasonal Snow and Land Cover Classifications

Cho

Jacobs

Vuyovich

2020

Water Resources Research

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Observation-based long-term gridded snow water equivalent (SWE) products are important assets for hydrological and climate research. However, an evaluation of the currently available SWE products has been limited due to the lack of independent SWE data that extend over a large range of environmental conditions. In this study, three daily long-term SWE products (Special Sensor Microwave Imager and Sounder [SSMI/S] SWE, GlobSnow-2 SWE, and University of Arizona [UA] SWE) were evaluated by seasonal snow cover and land cover classifications over the conterminous United States from 1982 to 2017, using the historical airborne gamma radiation SWE observations (20,738 measurements). We found that there are similar patterns in SSMI/S and GlobSnow-2 SWE when compared against the gamma SWE. However, GlobSnow-2 SWE had better agreement with gamma SWE than SSMI/S SWE in some forested-type classes and maritime and prairie snow classes. As compared to SSMI/S and GlobSnow-2 SWE, UA SWE has much better agreement with gamma SWE in all land cover types and snow classes. Tree cover and topographic heterogeneity affect the agreement between the gamma and gridded SWE and accuracy of gamma SWE itself with the largest differences typically occurring when the percent tree cover was 80% or higher, the terrain slope was steeper than 2.5°, and the elevation range exceeded 100 m. The results demonstrate the reliability of the UA SWE products and the benefits of the gamma radiation approach to measure SWE, especially in forested regions.Plain Language Summary Long-term gridded snowpack data are essential for effective water resource management and flood risk assessments under a changing climate in the United States. However, the currently available snowpack data have large uncertainties, and the evaluations have been limited due to the lack of reliable independent data sets. Here, we evaluate three daily long-term (>30 years) snow water equivalent (SWE) products-empirically based SWE from passive microwave, GlobSnow-2 SWE, and University of Arizona SWE from 1982 to 2017 over the conterminous United States-using the historical airborne gamma SWE observations collected by the National Oceanic and Atmospheric Administration. Two key findings are that (1) the UA SWE product is the most reliable and (2) the long-term airborne SWE record is of great value, especially in forested regions.Special Section: Advances in remote sensing, measurement, and simulation of seasonal snow Key Points: • Long-term airborne gamma radiation observations provide reliable SWE observations even over forest regions • University of Arizona (UA) SWE has the strongest agreement with gamma SWE regardless of seasonal snow and land cover class • Large differences occur when the tree cover is 80% or higher, the slope is steeper than 2.5°, and the elevation range exceeds 100 m Supporting Information: • Supporting Information Correspondence to: E. Cho, ec1072@wildcats.unh.edu Citation: Cho, E., Jacobs, J. M., & Vuyovich, C. M. (2020). The value of long-term (40 years) airborne g...

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“…Over 60 million people in the western United States are reliant on snowmelt runoff for consumption, electrical power, and agriculture (Bales et al, 2006). Declines in mountain snowpack storage (Mote, 2003(Mote, , 2006Mote et al, 2005Mote et al, , 2018Zeng et al, 2018), earlier spring snowmelt (Clow, 2010;Harpold et al, 2012;McCabe & Clark, 2005;Regonda et al, 2005;Stewart et al, 2005), and slower snowmelt rates (Harpold & Kohler, 2017;Wu et al, 2018) have been reported in the western United States, all of which are related to a warming climate (Barnett et al, 2005;Hamlet et al, 2005;Kapnick & Hall, 2012;Mote et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Observed Spatiotemporal Changes in the Mechanisms of Extreme Water Available for Runoff in the Western United States

Yan

Sun

Wigmosta

et al. 2019

Geophysical Research Letters

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This paper presents the first study to identity, in historical records, regional changes in the mechanisms of extreme water available for runoff (W). We used a quality‐controlled Snowpack Telemetry data set (1979–2017) combined with the nonparametric regional Kendall test to examine changes in annual maximum W under four hydrometeorological conditions (melt only/rain‐on‐snow/all melt/all melt plus rainfall) over the mountainous regions of the western United States. Under a warming climate, our analyses indicated significant declining trends in annual maximum W at regional scale under all four conditions. The annual maximum of all melt plus rainfall decreased significantly by 15% in the southwestern United States, while the frequency of rain‐on‐snow events increased significantly by 32% in the northwestern United States. The annual maximum snowmelt only decreased significantly by 21% across the entire western United States. Our results confirmed that interaction between regional humidity and solar radiation with warming temperature helps drive these changes.

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Snowpack Change From 1982 to 2016 Over Conterminous United States

Cited by 128 publications

References 34 publications

A Wet‐Bulb Temperature‐Based Rain‐Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States

A Wet‐Bulb Temperature‐Based Rain‐Snow Partitioning Scheme Improves Snowpack Prediction Over the Drier Western United States

The Value of Long‐Term (40 years) Airborne Gamma Radiation SWE Record for Evaluating Three Observation‐Based Gridded SWE Data Sets by Seasonal Snow and Land Cover Classifications

Observed Spatiotemporal Changes in the Mechanisms of Extreme Water Available for Runoff in the Western United States

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