The UCD Advanced Canopy‐Atmosphere‐Soil Algorithm: Comparisons with observations from different climate and vegetation regimes

Abstract

AbstractThe University of California, Davis (UCD), Advanced Canopy‐Atmosphere‐Soil Algorithm (ACASA) is presented and its output is compared with a comprehensive set of observations at six diverse sites. ACASA is a multi‐layer canopy‐surface‐layer model that solves the steady‐slate Reynolds‐averaged fluid flow equations to the third‐order. These equations include an explicit representation of the steady‐state, horizontally homogeneous, diabatic set of vector and scalar fluxes and flux transports. ACASA includes a fourth‐order, near‐exact technique to calculate leaf, stem, and soil surface temperatures and surface energy fluxes at various levels within the canopy. Plan! physiological response to micro‐environmental conditions is also included using Ball‐Berry/von Caemmerer‐Farquhar formulations. Observed energy fluxes and microenvironmental conditions from a grass field in the Netherlands, deciduous and coniferous forests in Canada, tropical pasture and forest in Brazil, and an ancient temperate rainforest in the USA are compared with simulated values.Results indicate that simulated and observed estimates of monthly to annual means of all surface fluxes agree within 95% confidence thresholds for all six sites. Observed and simulated hourly estimates of net radiation are also in excellent agreement for all sites considered. Observed and simulated hourly sensible‐ and latent‐heat flux estimates are in very good statistical agreement in most cases. Differences that exist between ACASA and observed sensible‐and latent‐heat flux estimates are of the same magnitudes as observational uncertainties. Estimates of observed and simulated hourly values of canopy and ground heal storage are within 95% statistical confidence limits of agreement with observations in most cases. Simulated and measured values of daytime intra‐canopy mean wind speed, temperature, and specific humidity agree with 95% confidence within both a tropical and temperate rainforest at all levels. Results also indicate that, in general, ACASA produces flux estimates closer to observations with significantly less scatter than does the Biosphere‐Atmosphere Transfer Scheme. Sensitivity tests show that reducing the vertical resolution, linearizing surface temperature calculations, and/or simplifying the treatment of surface‐layer turbulence each altered mean sensible‐ and latent‐heat flux estimates by amounts that are statistically significant in many cases. Results show that simplifying the model alters flux predictions in manners not simply related to vegetation character, and that using ACASA at its full complexity for all vegetation regimes is warranted. Increasing the vertical resolution beyond 20 layers improved flux predictions at tropical locations but had little impact elsewhere.