Advertisement

Theoretical and Applied Climatology

, Volume 133, Issue 3–4, pp 751–762 | Cite as

Retrieving air humidity, global solar radiation, and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

  • P. Lobit
  • L. López Pérez
  • J. P. Lhomme
  • A. Gómez Tagle
Original Paper

Abstract

This study evaluates the dew point method (Allen et al. 1998) to estimate atmospheric vapor pressure from minimum temperature, and proposes an improved model to estimate it from maximum and minimum temperature. Both methods were evaluated on 786 weather stations in Mexico. The dew point method induced positive bias in dry areas but also negative bias in coastal areas, and its average root mean square error for all evaluated stations was 0.38 kPa. The improved model assumed a bi-linear relation between estimated vapor pressure deficit (difference between saturated vapor pressure at minimum and average temperature) and measured vapor pressure deficit. The parameters of these relations were estimated from historical annual median values of relative humidity. This model removed bias and allowed for a root mean square error of 0.31 kPa. When no historical measurements of relative humidity were available, empirical relations were proposed to estimate it from latitude and altitude, with only a slight degradation on the model accuracy (RMSE = 0.33 kPa, bias = −0.07 kPa). The applicability of the method to other environments is discussed.

References

  1. Allen RG (2005) Penman-Monteith equation. in Encyclopedia of soil science, pp 180–188Google Scholar
  2. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing water requirements. Irr Drain Paper 56. UN-FAO, RomeGoogle Scholar
  3. Hubbard KG, Mahmood R, Carlson C (2003) Estimating daily dew point temperature for the northern great plains using maximum and minimum temperature. Agron J 95:323–328CrossRefGoogle Scholar
  4. Jensen ME, RD Burman, Allen RG (1990) Evapotranspiration and irrigation water requirements. ASCE Manuals and Reports on Engineering Practice No. 70, Am Soc Civil Engr, New York, NY. 332 ppGoogle Scholar
  5. Kimball JS, Running SW, Nemani R (1997) An improved method for estimating surface humidity from daily minimum temperature. J Agric Forest Met 85:87–98CrossRefGoogle Scholar
  6. Majidi M, Alizadeh A, Vazifedoust M, Farid A, Ahmadi T (2015) Analysis of the effect of missing weather data on estimating daily reference evapotranspiration under different climatic conditions. Water Resour Manag 29(7):2107–2124CrossRefGoogle Scholar
  7. R Development Core Team (2012) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/
  8. Willmott CJ (1982) Some comments on the evaluation of model performance. Bull Am Meteorol Soc 63(11):1309–1313CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria 2017

Authors and Affiliations

  1. 1.Instituto de Investigaciones Agropecuarias y ForestalesUniversidad Michoacana de San Nicolás de HidalgoMoreliaMexico
  2. 2.UMR LISAHMontpellier cedex 1France
  3. 3.INIRENAUniversidad Michoacana de San Nicolás de HidalgoMoreliaMexico

Personalised recommendations