Nooksack Temperature Lapse Rate Study 2016-2018
|Authors:||Jezra Beaulieu Christina Bandaragoda Claire Beveridge Nicoleta Cristea|
|Resource type:||Composite Resource|
|Storage:||The size of this resource is 183.1 MB|
|Created:||Nov 10, 2017 at 1:52 a.m.|
|Last updated:|| Sep 18, 2019 at 9:51 p.m.
|Citation:||See how to cite this resource|
|Content types:||Geographic Feature Content Geographic Raster Content|
Air temperature, ground temperature and relative humidity data was collected in a longitudinal transect of the Nooksack watershed at varying elevations from 500 - 1800 m above sea level. Data was collected by anchoring sensors from trees above winter snow levels and shaded from direct solar radiation. Paired sensors were also buried 3 cm under ground near each air temperature sensor to determine snow absence or presence. Selected sites included relative humidity sensors to indicate whether precipitation was occuring. Data was collected every 3-4 hours from May 2015 to Sept 2018 (with ongoing collection). Code for processing daily mean, minimum, maximum, and rates of temperature changes with elevation is available on Github (https://doi.org/10.5281/zenodo.3239539). The sensor download and intermediate data products are available on HydroShare with publicly accessible visualization available from the Nooksack Observatory at data.cuahsi.org.
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Code for processing sub-daily temperature sensor data for analysis of elevation distributed micro-climatology processes in a coastal glaciated watershed. Code allows for visualization and publication of daily data in multiple formats (1) daily data in python dictionaries for analysis (2) daily data for visualization and download on HydroServer at data.cuahsi.org (ODM format), and (3) archive publication on the HydroShare repository (ODM2 format)).
Air temperature and relative humidity were collected on a longitudinal transect in the North Fork Nooksack River Watershed in Whatcom County, Washington using methods described in (Hubbart et al., 2005; Lundquist & Cayan, 2007; Lundquist & Lott, 2008). This code is useful for assessment of observations, especially lapse rates with increasing elevation and microclimatic influences. Every hydrologic model that we know of (circa 2019) uses a linear annual lapse rate (e.g. -6.5 C/km clear sky assumption; - 4.5 C/km North Cascades Mountain Range (Minder et al., 2010) to represent the change in temperature with elevation. We are collecting empirical evidence to test the hypothesis that high elevation temperature lapse rates in glaciated mountain peaks, especially in maritime climates, are linear. They may be curvy.
Preliminary data analysis from the North Fork Nooksack (northern flank of Mt. Baker) shows a consistent annual average (-4.4 C/km) to previous work (Minder et al., 2010). However, at the lowest elevations (~664m -1056m) the annual average lapse rate is ~ 2.3 C/km; at mid elevations (1056m- 1575m) the annual average lapse rate is ~ 5.4 C/km; at higher elevations (1575m-1743m) the annual average lapse rate is ~ -7.2 C/km. If mountain lapse rates are significantly different from modeled rates, this is expected to have significant implications for high elevation snow, glacier, and hydrologic model predictions.
Curvy is something to be proud of. -Paloma Faith
Data Publication: Bandaragoda, C., J. Beaulieu, N. Cristea, C. Beveridge, (2019). elevation distributed micro-climatology data in a coastal glaciated watershed, Data in Brief, (in preparation).
Data Resource: J. Beaulieu, Bandaragoda, C., C. Beveridge, N. Cristea (2019). Nooksack Temperature Lapse Rate Study, HydroShare, http://www.hydroshare.org/resource/2d9787bf36d04c9383e595d179f9298b
Code: C. Beveridge, N. Cristea, Bandaragoda, C., J. Beaulieu. (2019, June 5). nooksack-indian-tribe/CurvyLapseRate: Alpha release to create DOI for Nooksack Indian Tribe (Version v0.0.1-alpha). Zenodo. http://doi.org/10.5281/zenodo.3239539
Hubbart, J., Link, T., Campbell, C., & Cobos, D. (2005). Evaluation of a low‐cost temperature measurement system for environmental applications. Hydrological Processes: An International Journal, 19(7), 1517-1523.
Lundquist, J. D., & Cayan, D. R. (2007). Surface temperature patterns in complex terrain: Daily variations and long‐term change in the central Sierra Nevada, California. Journal of Geophysical Research: Atmospheres, 112(D11).
Lundquist, J.D. and Lott, F. 2008. Using inexpensive temperature sensors to monitor the duration and heterogeneity of snow-covered areas. Water Resour. Res., 44, W00D16, doi: 10.1029/2008WR007035.
Minder, J.R., Mote, P.W., Lundquist, J.D. 2010. Surface temperature lapse rates over complex terrains: Lessons from the Cascade Mountains. J. Geophys. Res. 115, D14122, doi:10.1029/2009JD013493.
|Derived From:||Sara Damiano, Anthony Aufdenkampe, Jeff Horsburgh, David Valentine, Amber Jones, Jacob Meline, … David Tarboton. (2019, May 13). ODM2/YODA-File: v0.1-alpha: Initial alpha release for testing (Version v0.1-alpha). Zenodo. http://doi.org/10.5281/zenodo.2796960|
|The content of this resource serves as the data for:||https://doi.org/10.5281/zenodo.3239539|
|The content of this resource serves as the data for:||Data in Brief publication|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|Bureau of Indian Affairs||Tribal Resilience Program|
|Bureau of Indian Affairs||Rights Protection Implementation|
|National Science Foundation||PREEVENTS TRACK 2: Integrated Modeling of Hydro-Geomorphic Hazards: Floods, Landslides and Sediment||1663859|
|National Science Foundation||Collaborative Research: SI2-SSI: Cyberinfrastructure for AdvancinHydrologic Knowledge through Collaborative Integration of Data Science, Modeling and Analysis||1664061|
People that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
|Susan Dickerson-Lange||Natural Systems Design|
|Jessica Lundquist||University of Washington||WA, US||2066857594|
|Oliver Grah||Nooksack Indian Tribe||5016 Deming Rd.||3605925140|
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