USGS ScienceSearch

USGS · tm2E3

USGS Polar Temperature Logging System, Description and Measurement Uncertainties

Abstract

This paper provides an updated technical description of the USGS Polar Temperature Logging System (PTLS) and a complete assessment of the measurement uncertainties. This measurement system is used to acquire subsurface temperature data for climate-change detection in the polar regions and for reconstructing past climate changes using the 'borehole paleothermometry' inverse method. Specifically designed for polar conditions, the PTLS can measure temperatures as low as -60 degrees Celsius with a sensitivity ranging from 0.02 to 0.19 millikelvin (mK). A modular design allows the PTLS to reach depths as great as 4.5 kilometers with a skid-mounted winch unit or 650 meters with a small helicopter-transportable unit. The standard uncertainty (uT) of the ITS-90 temperature measurements obtained with the current PTLS range from 3.0 mK at -60 degrees Celsius to 3.3 mK at 0 degrees Celsius. Relative temperature measurements used for borehole paleothermometry have a standard uncertainty (urT) whose upper limit ranges from 1.6 mK at -60 degrees Celsius to 2.0 mK at 0 degrees Celsius. The uncertainty of a temperature sensor's depth during a log depends on specific borehole conditions and the temperature near the winch and thus must be treated on a case-by-case basis. However, recent experience indicates that when logging conditions are favorable, the 4.5-kilometer system is capable of producing depths with a standard uncertainty (uZ) on the order of 200-250 parts per million.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gary D. Clow. 2008. USGS Polar Temperature Logging System, Description and Measurement Uncertainties. https://doi.org/10.3133/tm2e3

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

dMODELS, a MATLAB software package for modeling crustal deformation near volcanic centers and active faults using Global Navigation Satellite System data—User guide

dMODELS is a MATLAB software package that implements the most common analytical models used to interpret deformation measurements near faults and active volcanic centers. This manual focuses on inversion of deformation data from the Global Navigation Satellite System (GNSS). The included case studies emphasize the GNSS inversion component of the software. Source models include pressurized spherical, spheroidal, and horizontal sill (penny-crack) magma reservoirs in a homogeneous, elastic, isotropic, flat half-space. A topography correction is available for the spherical source. Dikes and faults are described following the mathematical notation for the rectangular dislocations in a homogeneous, elastic, flat half-space. Equations have been reviewed for typographical errors present in the original literature and verified against finite-element method numerical models. GNSS data from the 2006 eruption at Augustine Volcano, Alaska; the 1998–2000 unrest at Taal Volcano, Philippines; and the 2009 earthquake in L’Aquila, Italy, are used to demonstrate the application of the software package.

Techniques and Methods

Aspergillosis (Avian) case definition for wildlife

Diagnostic laboratories receive carcasses and samples for diagnostic evaluation and pathogen/toxin detection. Case definitions bring clarity and consistency to the evaluation process. Their use within and between organizations allows more uniform reporting of diseases and etiologic agents. The intent of a case definition is to provide scientifically based criteria for determining: (a) if an individual carcass has a specific disease and degree of confidence in that diagnosis and (b) if there is evidence of a pathogen or toxin in a carcass or sample (for example, swab, tissue sample, skin scraping, blood/serum sample, environmental sample, or other). This case definition is specific to aspergillosis and applies to all avian species.

Techniques and Methods

Field sampling guidelines for developing and verifying satellite remote sensing chlorophyll a concentration and fluorescence models in inland waters

Harmful algal blooms are increasing in frequency in inland waters across the United States, resulting in a need to monitor phytoplankton bloom events to track ecosystem health and productivity. Remote sensing of chlorophyll a values offers a cost-effective and powerful method for early detection and characterization of bloom events and serves as an overall indicator of water quality and trophic state, with regular, repeated sampling of landscape-wide, high spatial resolution measurements. Field measurements are necessary for developing and verifying chlorophyll a retrieval models. For model verification, chlorophyll a concentration or fluorescence and light attenuation measurements are needed; for model development, turbidity and colored dissolved organic matter concentration measurements are additionally needed; and for model development and verification, radiometric measurements, taxonomic identification of phytoplankton, inherent optical properties, and cyanotoxin concentration are further measurements that can provide context. This report outlines detailed methods and priority considerations for collecting high-quality field data in inland waters (defined as rivers, lakes, reservoirs, estuaries, streams, and wetlands). The described methods include best practices for collecting and preparing discretely collected water samples and for calibration, maintenance, and quality assurance and quality control of field sensors. Whereas the priorities will vary between applications, some general guidelines are to collect field samples (1) as close in time to a satellite overpass as possible, (2) from representative areas of the waterbody to capture the range of spatial variability, and (3) near the surface to match remote sensing reflectance data.

Techniques and Methods