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- Author or Editor: A. Verhoef x
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Abstract
Data for water vapor adsorption and evaporation are presented for a bare soil (sandy loam, clay content 15%) in a southern Spanish olive grove. Water losses and gains were measured using eight high-precision minilysimeters, placed around an olive tree, which had been irrigated until the soil reached field capacity (∼0.22 m3 m−3). They were subsequently left to dry for 10 days. A pair of lysimeters was situated at each of the main points of the compass (N, E, S, W), at a distance of 1 m (the inner set of lysimeters; ILS) and 2 m (the outer set of lysimeters; OLS), respectively, from the tree trunk.
Distinct periods of moisture loss (evaporation) and moisture gain (vapor adsorption) could be distinguished for each day. Vapor adsorption often started just after noon and generally lasted until the (early) evening. Values of up to 0.7 mm of adsorbed water per day were measured. Adsorption was generally largest for the OLS (up to 100% more on a daily basis), and increased during the dry down. This was mainly the result of lower OLS surface soil moisture contents (period-average absolute difference ∼0.005 m3 m−3), as illustrated using various analyses employing a set of micrometeorological equations describing the exchange of water vapor between bare soil and the atmosphere. These analyses also showed that the amount of water vapor adsorbed by soils is very sensitive to changes in atmospheric forcing and surface variables. The use of empirical equations to estimate vapor adsorption is therefore not recommended.
Abstract
Data for water vapor adsorption and evaporation are presented for a bare soil (sandy loam, clay content 15%) in a southern Spanish olive grove. Water losses and gains were measured using eight high-precision minilysimeters, placed around an olive tree, which had been irrigated until the soil reached field capacity (∼0.22 m3 m−3). They were subsequently left to dry for 10 days. A pair of lysimeters was situated at each of the main points of the compass (N, E, S, W), at a distance of 1 m (the inner set of lysimeters; ILS) and 2 m (the outer set of lysimeters; OLS), respectively, from the tree trunk.
Distinct periods of moisture loss (evaporation) and moisture gain (vapor adsorption) could be distinguished for each day. Vapor adsorption often started just after noon and generally lasted until the (early) evening. Values of up to 0.7 mm of adsorbed water per day were measured. Adsorption was generally largest for the OLS (up to 100% more on a daily basis), and increased during the dry down. This was mainly the result of lower OLS surface soil moisture contents (period-average absolute difference ∼0.005 m3 m−3), as illustrated using various analyses employing a set of micrometeorological equations describing the exchange of water vapor between bare soil and the atmosphere. These analyses also showed that the amount of water vapor adsorbed by soils is very sensitive to changes in atmospheric forcing and surface variables. The use of empirical equations to estimate vapor adsorption is therefore not recommended.
Abstract
This paper deals with the parameter kB−1, the logarithm of the ratio between momentum and heat roughness length, of sparsely vegetated surfaces and bare soil. The bare soil surface is included as a reference, since it is fairly homogenous and smooth, having no distinguishable roughness elements. The mean value of kB−1 is about 8 for the vineyard and 12 for the savannah. These values are significantly greater than kB−1 = 2, which is usually assumed to hold for vegetation. The mean value of kB−1 for bare soil is small and negative, which agrees with the literature. A large variation of kB−1 during the day is measured for all three surfaces. This behavior has been observed for sparse vegetation in previous studies. Some authors explained the phenomenon with a vertical movement of the source of heat through the day as solar angle varies, or with the use of an inappropriate value of effective surface temperature to calculate kB−1. For the first time, this diurnal variation is measured for a smooth surface, the bare soil, for which neither explanation is valid. A sensitivity study reveals that the calculated kB−1 is very sensitive to measuring errors in the micrometeorological variables and errors in the roughness length for momentum. This explains the large range in observed kB−1 values for one particular surface type. In addition, several semiempirical expressions for kB−1 from the literature are tested. Two well-established formulas, both based on a simple combination of Reynolds and Prandtl numbers, appear to produce the best estimates of daily averaged kB−1 values. None of the formulas are able to describe the diurnal variation. The authors conclude that the concept of kB−1 is questionable as it is based upon extrapolating a theoretical profile through a region where this profile does not hold, toward a “surface temperature” that is difficult to define and to measure. It should therefore be avoided in meteorological models, for example, by applying canopy boundary layer resistances. Unfortunately, in remote sensing, the bulk transfer equations are up to now the only option, which therefore requires the use of kB−1.
Abstract
This paper deals with the parameter kB−1, the logarithm of the ratio between momentum and heat roughness length, of sparsely vegetated surfaces and bare soil. The bare soil surface is included as a reference, since it is fairly homogenous and smooth, having no distinguishable roughness elements. The mean value of kB−1 is about 8 for the vineyard and 12 for the savannah. These values are significantly greater than kB−1 = 2, which is usually assumed to hold for vegetation. The mean value of kB−1 for bare soil is small and negative, which agrees with the literature. A large variation of kB−1 during the day is measured for all three surfaces. This behavior has been observed for sparse vegetation in previous studies. Some authors explained the phenomenon with a vertical movement of the source of heat through the day as solar angle varies, or with the use of an inappropriate value of effective surface temperature to calculate kB−1. For the first time, this diurnal variation is measured for a smooth surface, the bare soil, for which neither explanation is valid. A sensitivity study reveals that the calculated kB−1 is very sensitive to measuring errors in the micrometeorological variables and errors in the roughness length for momentum. This explains the large range in observed kB−1 values for one particular surface type. In addition, several semiempirical expressions for kB−1 from the literature are tested. Two well-established formulas, both based on a simple combination of Reynolds and Prandtl numbers, appear to produce the best estimates of daily averaged kB−1 values. None of the formulas are able to describe the diurnal variation. The authors conclude that the concept of kB−1 is questionable as it is based upon extrapolating a theoretical profile through a region where this profile does not hold, toward a “surface temperature” that is difficult to define and to measure. It should therefore be avoided in meteorological models, for example, by applying canopy boundary layer resistances. Unfortunately, in remote sensing, the bulk transfer equations are up to now the only option, which therefore requires the use of kB−1.
Abstract
6th WGNE workshop on systematic errors in weather and climate models What: Scientists, ranging from early career to highly experienced, involved in the development of weather and climate models and in the diagnosis of model errors, held an international workshop to discuss the nature, causes and remedies of systematic errors across timescales and across Earth system modeling components. When: 31 Oct - 04 Nov 2022 Where: Reading, UK and online
Abstract
6th WGNE workshop on systematic errors in weather and climate models What: Scientists, ranging from early career to highly experienced, involved in the development of weather and climate models and in the diagnosis of model errors, held an international workshop to discuss the nature, causes and remedies of systematic errors across timescales and across Earth system modeling components. When: 31 Oct - 04 Nov 2022 Where: Reading, UK and online
