{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T21:37:24Z","timestamp":1777066644000,"version":"3.51.4"},"reference-count":84,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T00:00:00Z","timestamp":1600128000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Land surface temperature (LST) is a key variable in the determination of land surface energy exchange processes from local to global scales. Accurate ground measurements of LST are necessary for a number of applications including validation of satellite LST products or improvement of both climate and numerical weather prediction models. With the objective of assessing the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based LST measurements, intensive field experiments were conducted at NOAA\u2019s Air Resources Laboratory (ARL)\u2019s Atmospheric Turbulence and Diffusion Division (ATDD) in Oak Ridge, Tennessee, USA, from October 2015 to January 2016. The results of the comparison of LSTs retrieved by three narrow angle broadband infrared temperature sensors (IRT), hemispherical longwave radiation (LWR) measurements by pyrgeometers, forward looking infrared camera with direct LSTs by multiple thermocouples (TC), and near surface air temperature (AT) are presented here. The brightness temperature (BT) measurements by the IRTs agreed well with a bias of &lt;0.23 \u00b0C, and root mean square error (RMSE) of &lt;0.36 \u00b0C. The daytime LST(TC) and LST(IRT) showed better agreement (bias = 0.26 \u00b0C and RMSE = 0.67 \u00b0C) than with LST(LWR) (bias &gt; 1.1 and RMSE &gt; 1.46 \u00b0C). In contrast, the difference between nighttime LSTs by IRTs, TCs, and LWR were &lt;0.47 \u00b0C, whereas nighttime AT explained &gt;81% of the variance in LST(IRT) with a bias of 2.64 \u00b0C and RMSE of 3.6 \u00b0C. To evaluate the annual and seasonal differences in LST(IRT), LST(LWR) and AT, the analysis was extended to four grassland sites in the USA. For the annual dataset of LST, the bias between LST (IRT) and LST (LWR) was &lt;0.7 \u00b0C, except at the semiarid grassland (1.5 \u00b0C), whereas the absolute bias between AT and LST at the four sites were &lt;2 \u00b0C. The monthly difference between LST (IRT) and LST (LWR) (or AT) reached up to 2 \u00b0C (5 \u00b0C), whereas half-hourly differences between LSTs and AT were several degrees in magnitude depending on the site characteristics, time of the day and the season.<\/jats:p>","DOI":"10.3390\/s20185268","type":"journal-article","created":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T10:24:09Z","timestamp":1600165449000},"page":"5268","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Intercomparison of In Situ Sensors for Ground-Based Land Surface Temperature Measurements"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5760-3254","authenticated-orcid":false,"given":"Praveena","family":"Krishnan","sequence":"first","affiliation":[{"name":"NOAA ARL Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN 37830, USA"},{"name":"Oak Ridge Associated Universities, Oak Ridge, TN 37830, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tilden P.","family":"Meyers","sequence":"additional","affiliation":[{"name":"NOAA ARL Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN 37830, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon J.","family":"Hook","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory California Institute of Technology, Pasadena, CA 91109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark","family":"Heuer","sequence":"additional","affiliation":[{"name":"NOAA ARL Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN 37830, USA"},{"name":"Oak Ridge Associated Universities, Oak Ridge, TN 37830, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Senn","sequence":"additional","affiliation":[{"name":"NOAA ARL Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN 37830, USA"},{"name":"Oak Ridge Associated Universities, Oak Ridge, TN 37830, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edward J.","family":"Dumas","sequence":"additional","affiliation":[{"name":"NOAA ARL Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN 37830, USA"},{"name":"Oak Ridge Associated Universities, Oak Ridge, TN 37830, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,15]]},"reference":[{"key":"ref_1","unstructured":"Global Climate Observing System (GCOS) (2016). 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