Observing Climate at High Elevations Using United States Climate Reference Network Approaches

Abstract

The U.S. Climate Reference Network (USCRN) was deployed between 2001 and 2008 for the purpose of yielding high-quality and temporally stable in situ climate observations in pristine environments over the twenty-first century. Given this mission, USCRN stations are engineered to operate largely autonomously with great reliability and accuracy. A triplicate approach is used to provide redundant measurements of temperature and precipitation at each location, allowing for observations at a specific time to be compared for quality control. This approach has proven to be robust in the most extreme environments, from extreme cold (2498C) to extreme heat (1528C), in areas of heavy precipitation (4700 mm yr 21 ), and in locations impacted by strong winds, freezing rain, and other hazards. In addition to a number of stations enduring extreme winter environments in Alaska and the northern United States, seven of the USCRN stations are located at elevations over 2000 m, including stations on Mauna Loa, Hawaii (3407 m) and on Niwot Ridge above Boulder, Colorado (2996 m). The USCRN temperature instruments and radiation shield have also been installed and run successfully at a station on the Quelccaya Ice Cap in Peru (5670 m). This paper reviews the performance of the USCRN station network during its brief lifetime and the potential utility of its triplicate temperature instrument configuration for measuring climate change at elevation.

High‐latitude dust in the Earth system

“…Unlike subtropical dust source regions, those in high latitudes often have very low winter temperatures, the presence of ice and deep, often drifting snow, and extremely high wind speeds. In order to capture year‐round in situ data quantifying meteorological conditions and sediment fluxes, it is necessary to use instruments that will function during long periods of low temperatures and polar darkness, can withstand icing, and are reliable in locations often very far from support services [ Palecki and Groisman , ; Bourassa et al , ]. The harsh conditions during high‐latitude winters can also pose serious challenges to researchers [ Kadir et al , ] making it preferable to use self‐logging instruments that can be installed at site and downloaded remotely or manually after extended intervals rather than requiring daily servicing.…”

“…Such instruments must be accurate and reliable to ensure quality and completeness of data and must also be robust enough to understand the rigors of harsh winters at high latitudes. At high latitudes, although the instruments themselves can often operate in extreme conditions (e.g.,−49°C recorded in Barrow, Alaska, in 2006), they may require custom engineering to mount and power the instruments and despite combined power systems (solar, wind, and cold weather‐tolerant batteries) there can still be considerable challenges of ensuring data continuity during long, cold, dark winters [ Palecki and Groisman , ]. Other challenges of autonomous instrument networks include drifting snow that can make year‐round observations of near‐surface measurements difficult.…”

U.S. Climate Reference Network after One Decade of Operations: Status and Assessment

“…This allows the historical record from the nineteenth century onward to be connected correctly to the modern USCRN record and for USCRN to extend the U.S. temperature record forward through the twenty-first century. A subsequent paper was published (Palecki and Groisman 2011) documenting the utility of USCRN instrumentation approaches, especially the triplicate measurement strategy, for high-elevation climate networks.…”

Testing the daily PRISM air temperature model on semiarid mountain slopes

“…Gridded products extrapolating point observations of meteorological parameters to landscape scales have advanced in recent years [ Brohan et al , ; Daly et al , ; Haylock et al , ; Thornton et al , ]. Regardless of model sophistication, the accuracy of these modeling efforts varies with density and quality of source data networks [ Hamlet and Lettenmaier , ; Daly , ; Hofstra et al , ; McEvoy et al , ; Stoklosa et al , ; Oyler et al , ], and it is in mountainous topographic regions that observational data are the most scarce [ Palecki and Groisman , ]. Source data for models are typically derived from valley‐situated ground stations and ridgetop or upper air data, leaving the category of mountain slopes poorly represented in observational data sets.…”