Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures
At thousands of stations worldwide, the mean daily surface air temperature is estimated as a mean of the daily maximum (T _{max}) and minimum (T _{min}) temperatures. In this paper, we use the NOAA Surface Radiation Budget Network (SURFRAD) of seven US stations with surface air temperature recorded each minute to assess the accuracy of the mean daily temperature estimate as an average of the daily maximum and minimum temperatures and to investigate how the accuracy of the estimate increases with an increasing number of daily temperature observations. We find the average difference between the estimate based on an average of the maximum and minimum temperatures and the average of 1440 1min daily observations to be  0.05 ± 1.56 °C, based on analyses of a sample of 238 days of temperature observations. Considering determination of the daily mean temperature based on 3, 4, 6, 12, or 24 daily temperature observations, we find that 2, 4, or 6 daily observations do not reduce significantly the uncertainty of the daily mean temperature. The bias reduction in a statistically significant manner (95% confidence level) occurs only with 12 or 24 daily observations. The daily mean temperature determination based on 24 hourly observationsmore »
 Authors:

^{[1]};
^{[2]};
^{[3]};
^{[4]};
^{[1]}
 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab. Global Monitoring Division
 New Mexico State Univ., Las Cruces, NM (United States)
 Dalhousie Univ., Halifax, NS (Canada)
 Publication Date:
 Report Number(s):
 LAUR1721392
Journal ID: ISSN 0177798X
 Grant/Contract Number:
 AC5206NA25396
 Type:
 Accepted Manuscript
 Journal Name:
 Theoretical and Applied Climatology
 Additional Journal Information:
 Journal Volume: 134; Journal Issue: 12; Journal ID: ISSN 0177798X
 Publisher:
 Springer Nature
 Research Org:
 Los Alamos National Lab. (LANL), Los Alamos, NM (United States); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
 Sponsoring Org:
 USDOE
 Country of Publication:
 United States
 Language:
 English
 Subject:
 54 ENVIRONMENTAL SCIENCES
 OSTI Identifier:
 1402626
Chylek, Petr, Augustine, John A., Klett, James D., Lesins, Glen, and Dubey, Manvendra K.. Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures. United States: N. p.,
Web. doi:10.1007/s0070401722774.
Chylek, Petr, Augustine, John A., Klett, James D., Lesins, Glen, & Dubey, Manvendra K.. Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures. United States. doi:10.1007/s0070401722774.
Chylek, Petr, Augustine, John A., Klett, James D., Lesins, Glen, and Dubey, Manvendra K.. 2017.
"Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures". United States.
doi:10.1007/s0070401722774. https://www.osti.gov/servlets/purl/1402626.
@article{osti_1402626,
title = {Daily mean temperature estimate at the US SUFRAD stations as an average of the maximum and minimum temperatures},
author = {Chylek, Petr and Augustine, John A. and Klett, James D. and Lesins, Glen and Dubey, Manvendra K.},
abstractNote = {At thousands of stations worldwide, the mean daily surface air temperature is estimated as a mean of the daily maximum (Tmax) and minimum (Tmin) temperatures. In this paper, we use the NOAA Surface Radiation Budget Network (SURFRAD) of seven US stations with surface air temperature recorded each minute to assess the accuracy of the mean daily temperature estimate as an average of the daily maximum and minimum temperatures and to investigate how the accuracy of the estimate increases with an increasing number of daily temperature observations. We find the average difference between the estimate based on an average of the maximum and minimum temperatures and the average of 1440 1min daily observations to be  0.05 ± 1.56 °C, based on analyses of a sample of 238 days of temperature observations. Considering determination of the daily mean temperature based on 3, 4, 6, 12, or 24 daily temperature observations, we find that 2, 4, or 6 daily observations do not reduce significantly the uncertainty of the daily mean temperature. The bias reduction in a statistically significant manner (95% confidence level) occurs only with 12 or 24 daily observations. The daily mean temperature determination based on 24 hourly observations reduces the sample daily temperature uncertainty to  0.01 ± 0.20 °C. Finally, estimating the parameters of population of all SURFRAD observations, the 95% confidence intervals based on 24 hourly measurements is from  0.025 to 0.004 °C, compared to a confidence interval from  0.15 to 0.05 °C based on the mean of Tmax and Tmin.},
doi = {10.1007/s0070401722774},
journal = {Theoretical and Applied Climatology},
number = 12,
volume = 134,
place = {United States},
year = {2017},
month = {9}
}