estimate_vpd_from_dew: Estimate VPD from assuming dewpoint at daily minimum...

In REddyProc: Post Processing of (Half-)Hourly Eddy-Covariance Measurements

Estimate VPD from assuming dewpoint at daily minimum temperature

Description

VPD is required for daytime NEE flux partitioning. Hence, it is necessary to estimate VPD also for long gaps in data. With two assumptions, VPD can be estimated from temperature 1). The change of water mass in air is negligible during the day. VPD is the difference of actual vapour pressure to saturation vapour pressure. 2.) At morning minimum temperature, vapour pressure is at minimum in many cases at saturation. Hence

VPD = Esat(Tair) - E \approx Esat(Tair) - Esat_{daymin} \approx Esat(Tair) - Esat(Tair_{min})

Usage

estimate_vpd_from_dew(df, pNonMissing = 0.1)

Arguments

df	data.frame with columns DateTime, VPD, Tair, and Tair_f
pNonMissing	numeric scalar of the necessary fraction of finite VPD and Tair. If fraction is lower then a warning is thrown.

Details

Since sometimes Esat_daymin is lower than Esat(Tair_min) the estimated VPDfromDew is underestimated. This function applies a linear model of the existing VPD and estimated VPD to correct for this bias: VPD ~ 0 + VPDfromDew * Tair_f * hourOfDay * TminOftheDay * TRangeDay

Value

numeric vector of length(nrow(data)) of estimated VPD

REddyProc documentation built on March 18, 2022, 5:41 p.m.