Great Basin National Park, NV air temperature and relative humidity

Hourly air temperature and relative humidity data has been collected from a network of 29 data-logging sensors installed within radiation shields ~1.5 m above ground level at discrete sites within the Great Basin National Park (GBNP), NV, USA from August 2006 to August 2023. The sensors are “embedded” – suspended in trees or atop wooden stakes – within diverse ecosystem types spanning over 2,000 m of elevation, and are maintained/downloaded during annual visitations by collaborating teams of students and staff from the Ohio State University, University of Georgia, and Sinclair Community College, assisted by GBNP staff.  This dataset can be utilized to assess the microclimates and weather patterns within the GBNP. The dataset comprises daily mean, maximum, and minimum temperature and relative humidity collected between Aug 2006 – Aug 2023. Hourly, raw data are available upon request. 

Methods

A network of temperature (°C) and relative humidity (%) sensors was established in the Great Basin National Park in the summer of 2006. The network consists of Lascar EL-USB-2 Temperature and Humidity Data Loggers with a typical temperature error of ± 0.5°C and typical relative humidity error of ± 3%. The internal resolution is 0.5°C for the temperature and 0.5% for the humidity. The data loggers are programed to record hourly data.  

The sensors are hung in trees or fastened to posts 1-2m above the ground and are covered with ventilated, solar radiation shields. Data exists for 30 locations in the National Park and nearby town of Baker, NV ranging from 1639 m – 3976 m above sea level. Annual maintenance is required to replace batteries, download the data, and test the data loggers. This dataset includes data from August 2006 to August 2023. 

The provided data are the daily mean, maximum, and minimum temperature and humidity values. Daily aggregations were processed to include days with at least 23 observations. Data were filtered to remove outliers before aggregation, but the datasets include days when sensors were covered in snow because such data may be of interest for studying snowpack and related work.