Estimating snow evaporation with GPS derived precipitable water vapour

Valeo, Caterina; Skone, S.; Ho, Carrie Lee Ing; Poon, Samantha Ka Man; Shrestha, S.M.

doi:10.1016/j.jhydrol.2004.10.009

Cited by 13 publications

(9 citation statements)

References 14 publications

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“…However, in a high latitude area like Canada, Valeo et al (2005) recorded maximum values of sublimation equal to 6.3 mm in 8 h (0.8 mm h −1 on average) in Alberta (51 • N), while Jackson and Prowse (2009) (Jordan, 1991). The latter also simulated maximum melting rates of 40.5 mm d −1 , similar to the values found in this study.…”

Section: Discussionmentioning

confidence: 99%

“…This snow "ablameter" device has an exposed surface of 1260 (29.1 × 43.3) cm 2 and a depth of approximately 8 cm. Kaser (1982) and Valeo et al (2005) used a similar device with only one pan, made of acrylic glass and aluminium with small surface areas of 400 and 260 cm 2 , respectively, but they encountered some limitations due to this reduced size and the accumulation of meltwater in the pan. Froyland et al (2010) also used just one transparent container made of acrylic glass with an exposure area of 700 cm 2 , with which they could not measure the melting snow.…”

Section: Snow Field Surveysmentioning

confidence: 99%

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Evaposublimation from the snow in the Mediterranean mountains of Sierra Nevada (Spain)

Herrero

Polo

2016

The Cryosphere

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Abstract. In this study we quantify the evaposublimation and the energy balance of the seasonal snowpack in the Mediterranean semiarid region of Sierra Nevada, Spain (37 • N). In these kinds of regions, the incidence of this return of water to the atmosphere is particularly important to the hydrology and water availability. The analysis of the evaposublimation from snow allows us to deduct the losses of water expected in the short and medium term and is critical for the efficient planning of this basic and scarce resource. To achieve this, we performed 10 field campaigns from 2009 to 2015, during which detailed measurements of mass fluxes of a controlled volume of snow were recorded using a modified version of an evaporation pan with lysimeter. Meteorological data at the site of the snow control volume were extensively monitored during the tests. With these data, a point energy balance snowmelt model was validated for the area. This model, fed with the complete meteorological data set available at the Refugio Poqueira Station (2500 m a.s.l.), let us estimate that evaposublimation losses for this site can range from 24 to 33 % of total annual ablation. This ratio is very variable throughout the year and between years, depending on the particular occurrence of snowfall and mild weather events, which is generally quite erratic in this semiarid region. Evaposublimation proceeds at maximum rates of up to 0.49 mm h −1 , an order of magnitude less than maximum melt rates. However, evaposublimation occurs during 60 % of the time that snow lies, while snowmelt only takes up 10 % of this time. Hence, both processes remain close in magnitude on the annual scale.

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Section: Discussionmentioning

confidence: 99%

Section: Snow Field Surveysmentioning

confidence: 99%

Evaposublimation from the snow in the Mediterranean mountains of Sierra Nevada (Spain)

Herrero

Polo

2016

The Cryosphere

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“…However, for many engineering hydrologists, simple data reduced expressions are desirable (Valeo et al . ). The Priestley and Taylor () (PT) model within a parameter α , radiation based, is a simplification of the Penman–Monteith (PM) equation (Agam et al .…”

Section: Introductionmentioning

confidence: 97%

“…Several models of snow evaporation exist, ranging from simple equations resembling Dalton's Law of diffusivity to very sophisticated schemes that can require considerable data input (Lundberg, 1993;Lundberg and Halldin, 2001). However, for many engineering hydrologists, simple data reduced expressions are desirable (Valeo et al 2005). The Priestley and Taylor (1972) (PT) model within a parameter α, radiation based, is a simplification of the Penman-Monteith (PM) equation (Agam et al 2010;Ding et al 2013), and it is a commonly used method to estimate evaporation.…”

Section: Introductionmentioning

confidence: 99%

Performance of Priestley–Taylor model for estimating evaporation with and without snow coverage over a temperate meadow in Inner Mongolia, China

Chen

Zhang

Jin

et al. 2018

Water & Environment J

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To promote the awareness of Priestley–Taylor (PT) model and extend the knowledge of hydrological model under snow, performance of PT model was illustrated by comparing with eddy covariance (EC) measurements over a temperate meadow. The results showed that the mean half‐hourly averages and directly calculated daily value of PT parameter α is 0.47 ± 0.27 and 0.51 ± 0.32, respectively. Vapour pressure deficit VPD is the mainly factor influences α in the snow‐covered period, while soil moisture in the snow‐free period. PT method underestimated evaporation in the whole study period and showed remarkable difference in different phases. It performed best in the snow‐melting phase, better in the presnow phase, worse in the fresh snow phase and worst in the snow‐melted phase. These studies indicated that PT model could be used to estimate evaporation over temperate meadow in dormant season, but utility of a variable PT parameter α during different phases should be considered.

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“…They utilized the time series data of GPS zenith tropospheric delays (ZTD), derived continuously from 28 permanent GPS sites from 2002 to 2004, to analyze the change of precipitable water vapor on the Chinese mainland. Valeo et al (2005) performed studies on PWV estimation -derived from GPS zenith wet delay measurements -in conjunction with a basic snow evaporation model to verify observations of snow evaporation in an open urban area. Kumar et al (2005) developed a simple theoretical model for computing global insolation on a horizontal surface.…”

Section: Introductionmentioning

confidence: 99%

An Analytical Formula for Potential Water Vapor in an Atmosphere of Constant Lapse Rate

Varmaghani¹

2012

Terr. Atmos. Ocean. Sci.

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Accurate calculation of precipitable water vapor (PWV) in the atmosphere has always been a matter of importance for meteorologists. Potential water vapor (POWV) or maximum precipitable water vapor can be an appropriate base for estimation of probable maximum precipitation (PMP) in an area, leading to probable maximum flood (PMF) and flash flood management systems. PWV and POWV have miscellaneously been estimated by means of either discrete solutions such as tables, diagrams or empirical methods; however, there is no analytical formula for POWV even in a particular atmospherical condition. In this article, fundamental governing equations required for analytical calculation of POWV are first introduced. Then, it will be shown that this POWV calculation relies on a Riemann integral solution over a range of altitude whose integrand is merely a function of altitude. The solution of the integral gives rise to a series function which is bypassed by approximation of saturation vapor pressure in the range of -55 to 55 degrees Celsius, and an analytical formula for POWV in an atmosphere of constant lapse rate is proposed. In order to evaluate the accuracy of the suggested equation, exact calculations of saturated adiabatic lapse rate (SALR) at different surface temperatures were performed. The formula was compared with both the diagrams from the US Weather Bureau and SALR. The results demonstrated unquestionable capability of analytical solutions and also equivalent functions.

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Estimating snow evaporation with GPS derived precipitable water vapour

Cited by 13 publications

References 14 publications

Evaposublimation from the snow in the Mediterranean mountains of Sierra Nevada (Spain)

Evaposublimation from the snow in the Mediterranean mountains of Sierra Nevada (Spain)

Performance of Priestley–Taylor model for estimating evaporation with and without snow coverage over a temperate meadow in Inner Mongolia, China

An Analytical Formula for Potential Water Vapor in an Atmosphere of Constant Lapse Rate

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