Reviews

Chen, J,Chen, BZ,Black, TA,Innes, JL,Wang, GY,Kiely, G,Hirano, T,Wohlfahrt, G

2013

December

Comparison of terrestrial evapotranspiration estimates using the mass transfer and Penman-Monteith equations in land surface models

Validated

1

WOS: 34 ()

evapotranspiration the mass transfer equation the Penman-Monteith equation land surface model model comparison eddy covariance NET ECOSYSTEM PRODUCTIVITY CARBON-DIOXIDE EXCHANGE ATMOSPHERE CO2 EXCHANGE ENERGY-BALANCE CLOSURE ENSEMBLE KALMAN FILTER LEAF-AREA INDEX STOMATAL CONDUCTANCE BOREAL FOREST SOIL-MOISTURE INTERANNUAL VARIABILITY

The mass transfer (MT) equation and the Penman-Monteith (PM) equation are two common approaches used in various land surface models for simulating evapotranspiration (ET). Yet assessments are rarely conducted to determine how well these structurally differing equations simulate ET across various biomes and climatic environments with different canopy upscaling strategies. We evaluated the capacity of models to estimate ET using the MT equation with the one-leaf strategy in the Community Land Model version 4 and the PM equation in the Dynamic Land Model using the one-leaf and two-leaf upscaling approaches for 22 selected eddy covariance flux towers representing 10 typical plant functional types. Overall, across half-hourly, daily, monthly, and seasonal scales, the MT equation performed less robust than the PM equation in forests. The former had 8-15% higher root-mean-square error and 1-4% lower index of agreement and a large uncertainty in warm and wet seasons for several sites. It leaves a doubt about its application of estimating ET across regional to global scales. Considering the net radiation available on the surface of leaf/soil and adopting the two-leaf approach made the PM equation closer to the EC measurements on average but still could not capture the variation during the cold season. We suggest that further improvements in simulation of ET require seasonal variation of some key parameters and quantification of spatial heterogeneity.

1715

1731

10.1002/2013JG002446