An official website of the United States government
The data files in this data set contain climate information from sites on the North Slope of Alaska in or near the Kuparuk River basin. The data was collected for a hydrologic study of rivers in the North Slope region between 1985-present. Hydro-meteorological stations were established at various locations throughout the Kuparuk, but also in the Putuligayuk and Sagavanirktok watersheds. The variables collected at most stations were air temperature, humidity, wind speed and direction, soil temperature, snow temperature, precipitation, snow depth, and radiation. In the Imnavait Creek watershed (headwaters of the Kuparuk River), the Imnavait B site (IB) meteorological station operated from 1986 to present. This data package contains meteorological data from the Imnavait B site (IB) station and snow depth from the nearby station in the valley bottom (Imnavait Creek weir [IH]) collected from 2017 to 2023. Variables in this data package include air temperature, relative humidity, wind speed and direction, rainfall, and radiation at the Imnavait B site (IB) (2018-2023) and winter snow depth at Imnavait Weir (IH) (2017-2023). IMPORTANT NOTE: This dataset contains Imnavait B site (IB) meteorological data for 2018-2023. Updates and corrections to Imnavait B site (IB) (and others) were made in 2021 to the original datasets by the investigators, and all of the previously published data files (prior to 2008) should be replaced with the updated dataset (1985-2018) available at https://arcticdata.io/catalog/view/doi%3A10.18739%2FA2TQ5RF72. The following corrections were made to the datasets originally published in 2008 and 2010 (for data collected 1985-2008): 1) data from annual .csv files were merged into one .csv file (for each station) containing all years of data, 2) appended new data collected from 2008 to 2018 into the .csv file 3) standardized file headers, 4) standardized variable names, units, and sensor installation height above ground surface 5) reviewed all data for quality assurance and added qualifiers to erroneous data, 6) added a data qualifier to wind data during periods of extensive riming on wind sensors, 7) added a qualifier when air temperatures are below -39 degrees Celsius (C) (minimum reporting temperature of some air temperature sensors), and 8) removed duplicative data and fixed timestamp issues. See https://arcticdata.io/catalog/view/urn%3Auuid%3Ad5fa4cfa-b84b-4970-926a-8dd10b418e6d for additional climate data from other nearby stations in our studies.
more »
« less
alex-pk-sir/Siren---White-Mountains-Snowpack-Data: Siren---White-Mountains-Snowpack-Data
Snow depth and penetrability data from the northern White Mountains of New Hampshire (winter 2011-2012). -Overview of data and code - Data and associated code for modeling and plotting data from snowpack stations (n = 30) used for evaluating the influence of dormant season canopy cover (DSCC) on snow depth and penetrability during the 2011-2012 season. Stations were surveyed on 6 occasions over the course of the winter as part of a study to evaluate carnivore habitat use (Siren et al. 2017). -Response variables include snow depth and snow penetrability found in the depth.csv and penetrability.csv files. -Snow depth and penetrability measurements were taken 5 times at each site during each survey using a "research grade" avalanche probe and penetrometer, respectively. -There were 30 snow stations, 8 in open DSCC sites (Open), 4 in low DSCC sites (Low), 8 in medium DSCC sites (Medium), and 10 in high DSCC sites (High). These classifications were made using proprietary stand data provided by the landowners. For more information, please seen Siren et al. (2017). -The code was written using R Statistical software. Base R functions were used for linear modeling (lm) and the lubridate and ggplot2 packages were used for converting dates and plotting model predictions, respectively. -Structure of files - The nomenclature of the .csv files are the same for both .csv files. They are as follows: -site: name of the snow station -date: date of the snow survey -elevation: elevation of the snow station -canopy_density: DSCC classification of the site -elevation_s: scaled and centered elevation -date_f: categorical variable (created in R) -Structure of code - See R code. -Description of data collection and original use - Data were collected by Alexej Siren and originally used for evaluating the influence of snow on carnivores: Sirén, A. P. K., P. J. Pekins, J. R. Kilborn, J. J. Kanter, and C. S. Sutherland. 2017. Potential influence of high-elevation wind farms on carnivore mobility. Journal of Wildlife Management 81:1–8. https://doi.org/10.1002/jwmg.21317
more »
« less
- Award ID(s):
- 2224545
- PAR ID:
- 10660189
- Publisher / Repository:
- Zenodo
- Date Published:
- Edition / Version:
- Siren-WM-SnowData
- Format(s):
- Medium: X
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract: In the arid Southwest, snowpack in mountains plays an essential role in supplying surface waterresources. Water managers from the Navajo Nation monitor snowpack at nine snow survey stations located in the Chuska Mountains and Defiance Plateau in northern Arizona and New Mexico. We characterize these snowpack data for the period 1985-2014 and evaluate the efficacy of snowpack data collection efforts. Peak snow water equivalent occurs in early to mid-March depending on elevation. Variability in snowpack levels correlates highly among all sites (r > 0.64), but higher elevation sites in the Chuska Mountains correlate more strongly with one another compared to lower elevation sites and vice versa. Northern sites also correlate well with each other. A principal component analysis is used to create a weighted average time series of year-to-year peak snowpack variability. The first principal component showed no trend in increasing or decreasing Navajo Nation snowpack. Results from this research will provide the Navajo Nation Department of Water Resources information to help determine if any snow survey sites in the Chuska Mountains are redundant and can be discontinued to save time and money, while still providing snowpack information needed by the Navajo Nation. This summary of snowpack patterns, variability, and trends in the Chuska Mountains and Defiance Plateau will help the Navajo Nation to understand how snowpack and water resources respond to climate change and climate variability.more » « less
-
Abstract We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open‐forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap‐filled. These data are available to download from Bonner, Smyth, et al. (2022) athttps://doi.org/10.5281/zenodo.6618553, at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process‐based snow model. We demonstrate the utility of these data with a modeling experiment that explores open‐forest differences and identifies opportunities for improvements in model representation.more » « less
-
This dataset contains meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains during water years 2019-2021. Data collection had an emphasis on paired open-forest sites and included three forested elevations. In total, we present 270 snow pit observations, 4,019 snow depth measurements, and three years of meteorological forcing from two weather stations (one in a meadow, the other in an adjacent forest). The dataset is described in a forthcoming publication of the same name: A meteorology and snow dataset from adjacent forested and meadow sites at Crested Butte, CO, USA</em> (Bonner et al., 2022).</p> All snow observation and meteorological forcing data are available as both .nc and .mat files. Additionally, original digitized copies of snow pit observations are provided as .gsheet/.xlxs files.</p> This dataset will continue to be updated, via this repository, as additional years of data are collected.</p>more » « less
-
This resource includes Jupyter Notebooks that combine (merge) model results with observations. There are four folders: - NWM_SnowAssessment: This folder includes codes required for combining model results with observations. It also has an output folder that contains outputs of running five Jupyter Notebooks within the code folder. The order to run the Jupyter Notebooks is as follows. First run Combine_obs_mod_[*].ipynb where [*] is P (precipitation), SWE (snow water equivalent), TAir (air temperature), and FSNO (snow covered area fraction). This combines the model outputs and observations for each variable. Then, run Combine_obs_mod_P_SWE_TAir_FSNO.ipynb. - NWM_Reanalysis: This folder contains the National Water Model version 2 retrospective simulations that were retrieved and pre-processed at SNOTEL sites using https://doi.org/10.4211/hs.3d4976bf6eb84dfbbe11446ab0e31a0a and https://doi.org/10.4211/hs.1b66a752b0cc467eb0f46bda5fdc4b34. - SNOTEL: This folder contains preprocessed SNOTEL observations that were created using https://doi.org/10.4211/hs.d1fe0668734e4892b066f198c4015b06. - GEE: This folder contains MODIS observations that we downloaded using https://doi.org/10.4211/hs.d287f010b2dd48edb0573415a56d47f8. Note that the existing CSV file is the merged file of the downloaded CSV files.more » « less
