A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

Bonner, Hannah M.; Smyth, E.; Raleigh, M. S.; Small, E. E.

doi:10.1029/2022wr033006

Cited by 2 publications

(3 citation statements)

References 47 publications

(55 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These stations -run by three different research groups (i.e. (Simonpietri and Carbone, 2023;Ryken, 2021;Bonner et al, 2022)) -have collected data over different periods of time and have distinct combinations of sensors. We averaged these streams to develop a daily mean temperature and humidity dataset for the hillslope to estimate the evaporative mixing lines described above (2.2.1).…”

Section: Meteorological Datamentioning

confidence: 99%

“…To do this, we simply took the daily average temperature based on all available measurements for a given day. We utilized snow depth and snow water equivalent (SWE) from a pair of adjacent forest and meadow stations based on both continuous snow height sensors and periodic snow pits (Bonner et al, 2022) to estimate canopy effects on snow inputs. We utilize daily precipitation for weighting the importance of each precipitation event into the growing season isotopic inputs for the mixing model (Sections 2.2.1 and 2.2.2).…”

Section: Meteorological Datamentioning

confidence: 99%

“…CC BY 4.0 License. measurements made on this hillslope,Bonner et al (2022) show that beginning around May 1 forested sites have higher SWE relative to open sites over a period that may last as much as 40 days during large snowpack years (FigureS5). This extended period of snowmelt input coincides with an important period of growth and water use especially for conifers which are active early in the spring.…”

mentioning

confidence: 93%

See 2 more Smart Citations

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

Berkelhammer,

Page,

Zurek

et al. 2024

Preprint

View full text Add to dashboard Cite

Abstract. Declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. However, the effect of this forcing at the species and hillslope scale are difficult to predict from remote sensing or eddy covariance. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common subalpine tree species (Picea engelmannii, Abies lasiocarpa, Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River Basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpacks but high summer rains of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to a major decline in snowpack. The trees that benefited from the large snow year were all found in dense canopy stands – irrespective of species – while trees in open canopy stands were more active during the years with modest snow and higher summer rains. This pattern reflects how persistent access to soil moisture recharged by snowmelt in topographically-mediated convergence zones shapes stand density. These locally dense canopies also experience high levels of summer rainfall interception that reduce summer precipitation inputs to the soil perpetuating their greater sensitivity to snowmelt inputs. The results illustrate that the progression towards a low snowpack future will manifest at the sub-hillslope scale in dense stands with significant rainfall interception and high water demands reflecting their historical reliance on snowmelt water.

show abstract

Section: Meteorological Datamentioning

confidence: 99%

Section: Meteorological Datamentioning

confidence: 99%

mentioning

confidence: 93%

See 1 more Smart Citation

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

Berkelhammer,

Page,

Zurek

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Reanalyzing the spatial representativeness of snow depth at automated monitoring stations using airborne lidar data

Herbert,

Raleigh,

Small

2024

The Cryosphere

View full text Add to dashboard Cite

Abstract. Automated snow station networks provide critical hydrologic data. Whether point observations represent snowpack at larger areas is an enduring question. Leveraging the recent proliferation of airborne lidar snow depth data, we revisit the question of snow station representativeness at multiple scales surrounding 111 stations in Colorado and California (USA) from 2021–2023 (n=476 total samples). In about 50 % of cases, station depths were at least 10 cm higher than areal-mean snow depth (from lidar) at 0.5 to 4 km scales. The nearest 50 m lidar pixels had lower bias and were more often representative of the areal-mean snow depth than coincident stations. The closest 3 m lidar pixel often agreed with station snow depth to within 10 cm, suggesting differences between station snow depth and the nearest 50 m lidar pixel result from highly localized conditions and not the measurement method. Representativeness decreased as scale increased up to ∼6 km, mainly explained by the elevation of a site relative to the larger area. Relative values of vegetation and southness did not have significant impacts on site representativeness. The sign of bias at individual snow stations is temporally consistent, suggesting the relationship between station depth and that of the surrounding area may be predictable. Improving understanding of snow station representativeness could allow for more accurate validation of modeled and remotely sensed data.

show abstract

A Meteorology and Snow Data Set From Adjacent Forested and Meadow Sites at Crested Butte, CO, USA

Cited by 2 publications

References 47 publications

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

Reanalyzing the spatial representativeness of snow depth at automated monitoring stations using airborne lidar data

Contact Info

Product

Resources

About