A cautionary note on the computation of daily mean temperatures and their trends
There are different methodologies to compute daily mean temperatures (DMT), including averaging the 24-hourly temperature values, readings at specific times throughout the day or simply averaging the minimum and maximum daily temperatures. This study provides an intercomparison of some of such metho...
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John Wiley and Sons Ltd
2017
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| Acceso en línea: | Registro en Scopus DOI Handle Registro en la Biblioteca Digital |
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| 024 | 7 | |2 scopus |a 2-s2.0-85007223612 | |
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| 100 | 1 | |a Saurral, R.I. | |
| 245 | 1 | 2 | |a A cautionary note on the computation of daily mean temperatures and their trends |
| 260 | |b John Wiley and Sons Ltd |c 2017 | ||
| 270 | 1 | 0 | |m Saurral, R.I.; Centro de Investigaciones del Mar y la Atmósfera (CIMA), UMI-IFAECI/CNRS, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and Universidad de Buenos AiresArgentina; email: saurral@cima.fcen.uba.ar |
| 506 | |2 openaire |e Política editorial | ||
| 504 | |a Arguez, A., Durre, I., Applequist, S., Vose, R.S., Squires, M.F., Yin, X., Heim, R.R., Jr., Owen, T.W., NOAA's 1981–2010 U.S. Climate Normals: An overview (2012) Bull. Am. Meteorol. Soc., 93, pp. 1687-1697 | ||
| 504 | |a Baker, D.G., Effect of observation time on mean temperature estimation (1975) J. Appl. Meteorol., 14, pp. 471-476 | ||
| 504 | |a Dall'Amico, M., Hornsteiner, M., A simple method for estimating daily and monthly mean temperatures from daily minima and maxima (2006) Int. J. Climatol., 26, pp. 1929-1936 | ||
| 504 | |a Harris, S.A., Pedersen, J.H., Comparison of three methods of calculating air temperature from electronic measurements (1995) Z. Geomorph., 39, pp. 203-210 | ||
| 504 | |a Kalma, J.D., A comparison of methods for computing daily mean air temperature and humidity (1968) Weather, 23, pp. 248-254 | ||
| 504 | |a Karl, T.R., Williams, C.N., Young, P.J., Wendland, W.M., A model to estimate the time of observation bias associated with monthly mean maximum, minimum and mean temperatures for the United States (1986) J. Clim. Appl. Meteorol., 25, pp. 145-160 | ||
| 504 | |a Kendall, M., (1955) Rank Correlation Methods, p. 260. , 5th edn, Kendall M, Gibbons J (eds)., Oxford University Press, New York, NY | ||
| 504 | |a Leathers, D.J., Palecki, M.A., Robinson, D.A., Dewey, K.F., Climatology of the daily temperature range annual cycle in the United States (1998) Clim. Res., 9, pp. 197-211 | ||
| 504 | |a Ma, Y., Guttorp, P., Estimating daily mean temperature from synoptic climate observations (2013) Int. J. Climatol., 33, pp. 1264-1269 | ||
| 504 | |a Mann, Nonparametric tests against trends (1945) Econometrica, 13, pp. 245-259 | ||
| 504 | |a Reicosky, D.C., Winkelman, L.J., Baker, J.M., Baker, D.G., Accuracy of hourly air temperatures calculated from daily minima and maxima (1989) Agric. For. Meteorol., 46, pp. 193-209 | ||
| 504 | |a Schwerdtfeger, W., Climates of Central and South America (1976) World Survey of Climatology, 12, p. 532. , In, Elsevier, Amsterdam | ||
| 504 | |a Weiss, A., Hays, C.J., Calculating daily mean air temperatures by different methods: implications from a non-linear algorithm (2005) Agric. For. Meteorol., 128, pp. 57-69 | ||
| 504 | |a Wilks, D.S., (2006) Statistical Methods in the Atmospheric Sciences, p. 141. , 2nd edn., Academic Press, Waltham | ||
| 520 | 3 | |a There are different methodologies to compute daily mean temperatures (DMT), including averaging the 24-hourly temperature values, readings at specific times throughout the day or simply averaging the minimum and maximum daily temperatures. This study provides an intercomparison of some of such methods applied to six meteorological stations in Argentina with continuous hourly measurements for a period of more than 24 years. Results show that differences arising from the various methodologies are largely dependent on the local weather conditions, particularly those related to cloud cover and wind intensity, while the role of air moisture is less important. Furthermore, trends derived from DMT estimates using different methodologies are found to be highly sensitive to the chosen method. In fact, statistically insignificant trends could be significant should other methodologies to calculate DMT had been used. This result could be of importance for diverse scientific areas such as agriculture or climate warming studies. © 2016 Royal Meteorological Society |l eng | |
| 536 | |a Detalles de la financiación: UBACyT-20020100100803 | ||
| 536 | |a Detalles de la financiación: Universidad de Buenos Aires, PIP-11220120100586 | ||
| 536 | |a Detalles de la financiación: Consejo Nacional de Investigaciones Científicas y Técnicas | ||
| 536 | |a Detalles de la financiación: The author would like to thank the two anonymous reviewers for critically reading this work and providing suggestions that helped improve and clarify the paper. Thanks are due to the National Weather Service (Servicio Meteorol?gico Nacional) of Argentina for providing the hourly and daily meteorological data used in this manuscript. Also acknowledged is the Data Bank at the Departamento de Ciencias de la Atm?sfera y los Oc?anos (DCAO; FCEN-UBA) for compiling the information. This work was partially funded by Grants UBACyT-20020100100803 from Universidad de Buenos Aires and PIP-11220120100586 from CONICET. | ||
| 593 | |a Centro de Investigaciones del Mar y la Atmósfera (CIMA), UMI-IFAECI/CNRS, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and Universidad de Buenos Aires, Buenos Aires, Argentina | ||
| 593 | |a Departamento de Ciencias de la Atmósfera y los Océanos (DCAO), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina | ||
| 690 | 1 | 0 | |a CLOUD COVER |
| 690 | 1 | 0 | |a DAILY MEAN TEMPERATURE |
| 690 | 1 | 0 | |a GLOBAL WARMING |
| 690 | 1 | 0 | |a TEMPERATURE TRENDS |
| 690 | 1 | 0 | |a WIND INTENSITY |
| 690 | 1 | 0 | |a GLOBAL WARMING |
| 690 | 1 | 0 | |a CLOUD COVER |
| 690 | 1 | 0 | |a DAILY TEMPERATURES |
| 690 | 1 | 0 | |a LOCAL WEATHER CONDITIONS |
| 690 | 1 | 0 | |a MEAN TEMPERATURE |
| 690 | 1 | 0 | |a METEOROLOGICAL STATION |
| 690 | 1 | 0 | |a TEMPERATURE TRENDS |
| 690 | 1 | 0 | |a TEMPERATURE VALUES |
| 690 | 1 | 0 | |a WIND INTENSITY |
| 690 | 1 | 0 | |a METEOROLOGY |
| 690 | 1 | 0 | |a CLOUD COVER |
| 690 | 1 | 0 | |a DIURNAL VARIATION |
| 690 | 1 | 0 | |a GLOBAL WARMING |
| 690 | 1 | 0 | |a TEMPERATURE GRADIENT |
| 690 | 1 | 0 | |a TREND ANALYSIS |
| 690 | 1 | 0 | |a WARMING |
| 690 | 1 | 0 | |a WIND VELOCITY |
| 651 | 4 | |a ARGENTINA | |
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