Mountain Temperature Changes From Embedded Sensors Spanning 2000 m in Great Basin National Park, 2006–2018

Abstract

Mountains of the arid Great Basin region of Nevada are home to critical water resources and numerous species of plants and animals. Understanding the nature of climatic variability in these environments, especially in the face of unfolding climate change, is a challenge for resource planning and adaptation. Here, we utilize an Embedded Sensor Network (ESN) to investigate landscape-scale temperature variability in Great Basin National Park (GBNP). The ESN was installed in 2006 and has been maintained during uninterrupted annual student research training expeditions. The ESN is comprised of 29 Lascar sensors that record hourly near-surface air temperature and relative humidity at locations spanning 2000 m and multiple ecoregions within the park. From a maximum elevation near 4000 m a.s.l. atop Wheeler Peak, the sensor locations are distributed: (1) along a multi-mountain ridgeline to the valley floor, located ∼2000 m lower; (2) along two streams in adjoining eastern-draining watersheds; and (3) within multiple ecological zones including sub-alpine forests, alpine lakes, sagebrush meadows, and a rock glacier. After quality checking all available hourly observations, we analyze a 12-year distributed temperature record for GBNP and report on key patterns of variability. From 2006 to 2018, there were significantly increasing trends in daily maximum, minimum and mean temperatures for all elevations. The average daily minimum temperature increased by 2.1°C. The trend in daily maximum temperatures above 3500 m was significantly greater than the increasing trends at lower elevations, suggesting that daytime forcings may be driving enhanced warming at GBNP’s highest elevations. These results indicate that existing weather stations, such as the Wheeler Peak SNOTEL site, alone cannot account for small-scale variability found in GBNP. This study offers an alternative, low-cost methodology for sustaining long-term, distributed observations of conditions in heterogeneous mountainous environments at finer spatial resolutions. In arid mountainous regions with vulnerable water resources and fragile ecosystems, it is imperative to maintain and extend existing networks and observations as climate change continues to alter conditions.