Estimating dew duration. I. Utilizing micrometeorological data

Pedro, M.J.; Gillespie, T. J.

doi:10.1016/0002-1571(81)90081-9

Cited by 112 publications

(53 citation statements)

References 13 publications

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“…we followed the approach presented by Pedro and Gillespie (1982) and Nikolayev et al (1996), which has been found to agree reasonably well with empirical measurements of dew collection (e.g. Nilsson, 1996;Beysens et al, 2005;Jacobs et al, 2008;Richards, 2009;Maestre-Valero et al, 2011).…”

Section: Parameter Valuesupporting

confidence: 56%

Estimates of global dew collection potential on artificial surfaces

Vuollekoski

Vogt

Sinclair

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. The global potential for collecting usable water from dew on an artificial collector sheet was investigated by utilizing 34 years of meteorological reanalysis data as input to a dew formation model. Continental dew formation was found to be frequent and common, but daily yields were mostly below 0.1 mm. Nevertheless, some water-stressed areas such as parts of the coastal regions of northern Africa and the Arabian Peninsula show potential for large-scale dew harvesting, as the yearly yield may reach up to 100 L m −2 for a commonly used polyethylene foil. Statistically significant trends were found in the data, indicating overall changes in dew yields of between ±10 % over the investigated time period.

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Section: Parameter Valuesupporting

confidence: 56%

Estimates of global dew collection potential on artificial surfaces

Vuollekoski

Vogt

Sinclair

et al. 2015

Hydrol. Earth Syst. Sci.

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“…The energy balance approach allows a greater degree of sophistication when estimating duration of plant wetness (Goudriaan 1977;Pedro and Gillespie 1982a). The deposition rate of dew and the evaporation rate of dew or intercepted rain are affected by many environmental and biological variables, which can be integrated into an energy budget for a plant part:…”

Section: Physical Modelsmentioning

confidence: 99%

“…All symbols are listed, with units, in Appendix A. For a maize ear, following Pedro and Gillespie (1982a), the net radiation was estimated as:…”

Section: Physical Modelsmentioning

confidence: 99%

“…If the solar radiation, air temperature, wind speed and water vapor pressure near the ear are known, the above energy balance and heat transfer Eqs. 1 to 4 can be combined with the function relating saturation vapor pressure of water to temperature, and with the following expression to iteratively solve for the "micro-scale latent heat flux" (LE m ) (Kreith and Sellers 1975;Pedro and Gillespie 1982a):…”

Section: Physical Modelsmentioning

confidence: 99%

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Estimating wetness duration on maize ears from meteorological observations

Rao¹,

Gillespie²,

Schaafsma³

1998

Can. J. Soil. Sci.

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Estimating wetness duration on maize ears from meteorological observations. Can. J. Soil Sci. 78: 149-154. The onset and cessation of surface wetness on maize ears were simulated with six models, using hourly meteorological data, to examine the linkage between wetness duration and possible forecasting of fungal infections that produce mycotoxins. Two threshold models (using relative humidity and dew point temperature), one regression model (using humidity and wind speed), and three physical models based on the energy balance approach, were compared. Also, spatial and temporal variability in wetness duration was measured and simulated at three sites located at distances up to 29 km from a central weather station. The estimated wetness values were compared with observations from cylindrical wetness sensors placed near ear level in maize canopies. The results relate to potential mycotoxin warning systems and indicate that threshold models can provide reasonable estimates of ear wetness duration in this region, that a comprehensive physical model can give superior estimates, and that wetness estimates made from a central weather station data can be extended to nearby crop fields with a moderate degree of confidence.Key words: epidemiology, mycotoxins, surface wetness models Rao, P. S., Gillespie, T. J. et Schaafsma, A. W. 1998. Estimation de la durée d'humectation des épis de maïs à partir des observations météorologiques. Can. J. Soil Sci. 78: 149-154. Étant donné le lien observé entre la durée d'humectation et l'apparition éventuelle des infections fongiques mycotoxinogènes, nous avons simulé au moyen de 6 modèles, à partir des données météorologiques horaires, le début et la fin de l'humectation superficielle des épis de maïs. Deux modèles à seuils (utilisant l'humidité relative et la température au point de rosée), un modèle de régression utilisant l'humidité et la vitesse du vent et 3 modèles physiques basés sur le bilan énergétique étaient comparés. En outre, la variabilité dans le temps et dans l'espace de la durée d'humectation était mesurée et simulée à 3 emplacements situés à des distances allant jusqu'à 29 km d'une station météorologique centrale. Les valeurs d'humectation estimées étaient comparées à des observations enregistrées par des capteurs d'humectation cylindriques posés à la hauteur approximative des épis dans une culture de maïs. Les résultats sont intéressants pour les futurs systèmes d'avertissement de production de mycotoxines. Ils montrent aussi que les modèles à seuils peuvent fournir des valeurs raisonnables de la durée d'humectation des épis dans cette région. Ces valeurs peuvent encore être améliorées par l'utilisation d'un modèle physique intégré. On a enfin constaté que les valeurs de durée d'humectation provenant d'une station météorologique centrale peuvent être étendues aux cultures avoisinantes avec un degré de confiance modéré.

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“…Since dewfall represents a latent heat flux at a surface, it can be estimated from the energy balance of an atmosphere-canopy system, if the other components of the EB are available either from measurement or calculation [17][18][19][20][21]. Dewfall estimated with the EB equation is generally in good agreement with measurements.…”

Section: Introductionmentioning

confidence: 94%

Agreement of Four Equations for Computing Dewfall in Northern Germany

Xiao

Meißner

Borg

et al. 2017

Water

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Abstract:The energy balance (EB), turbulent vapour transport (TVT), Penman-Monteith (PM) and Bowen ratio energy balance (BREB) equation were used to estimate dewfall based on meteorological data. Initially there were big disagreements between the estimates from these four equations. However, after multiplying the heat and vapour conductance terms by 0.33 the agreement was much better. This implies that the disagreements derived from improper conductance values. Initially we did not consider the effect of atmospheric stability on the conductances. With stability correction the conductances were on average 0.5 times the values without stability correction. To arrive at the aforementioned 0.33, the conductances with stability correction still need to be lower by a factor of 0.66. The value of the von Karman constant and the relationships for the zero plane displacement and the roughness length we used in our conductance computations are widely used, but not the only possible ones. With different values and relationships also suggested in the literature one can reach this factor. However, it is also possible that our wind speed data contributed to the fact that the conductances we computed were too high. Their computation for a given canopy-atmosphere system requires wind speeds from a wind profile in equilibrium with the vegetation. This in turn requires an adequate fetch around the investigated surface. The highly varied vegetation in and around the site where the study was conducted makes adequate fetch rather doubtful. To obtain valid conductance values the atmospheric stability conditions must be considered, the appropriate values for the von Karman constant, the zero plane displacement and roughness length must be used, and there must be adequate fetch. The BREB equation does not contain a conductance term and therefore does not suffer from the problems just stated. The other three equations do. However, the BREB, like the EB and TVT equations, need the surface temperature which is not routinely measured. This then leaves the PM equation from which this temperature has been eliminated as the only option. Hence, in a future study dewfall estimates from the PM equation should be compared with direct measurements with a high precision weighing lysimeter.

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Estimating dew duration. I. Utilizing micrometeorological data

Cited by 112 publications

References 13 publications

Estimates of global dew collection potential on artificial surfaces

Estimates of global dew collection potential on artificial surfaces

Estimating wetness duration on maize ears from meteorological observations

Agreement of Four Equations for Computing Dewfall in Northern Germany

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