Evaluation of Turbulence Stability Schemes of Land Models for Stable Conditions

Abstract

During stable conditions, simulated sensible heat fluxes, Qh, in land models exhibit a wide range of behavior, with some models decoupling the atmosphere and land surface, while others continue turbulent exchange. This behavior is dictated by the representation of stability within the model. We explicitly test the representation of Qh during stable conditions using observed surface temperature, air temperature, and wind speed at the Shallow Cold Pool (SCP) Experiment site in Colorado, USA. This site is characterized by frequent stable conditions and weak‐wind conditions, which are known to be difficult to represent in turbulence schemes. We test the log‐linear, Louis, Holtslag and de Bruin, Beljaar and Holtslag, and Cheng and Brutsaert stability schemes against the observations at the SCP site. We also evaluate the minimum conductance assumption commonly implemented in land models. Simulated Qh biases are generally small, due largely to compensating errors. Parameterizations could represent Qh in strong‐wind conditions and during the transition from a weak‐ to strong‐wind regime. The behavior of simulated Qh during strong winds was controlled by the aerodynamic surface roughness, z0. All models, except those that maintain a minimum conductance, were unable to represent turbulence in the weak‐wind regime. We discuss the interacting roles of countergradient fluxes, intermittent turbulence, and decoupled turbulence during this regime. Finally, we list the characteristics that a turbulence parameterization should include and recommend that land models should include a minimum conductance to simulate Qh in the weak‐wind regime.

Multi-physics ensemble snow modelling in the western Himalaya

“…There is also further evidence here that turbulent heat fluxes can be overly suppressed under stable atmospheric conditions when using a stability adjustment based on the bulk Richardson number (e.g. Andreas, 2002;Collier et al, 2015;Slater et al, 2001), such that testing additional approaches would be valuable (Andreadis et al, 2009;Lapo et al, 2019). The results reflect the consensus from site-based inter-comparisons that no single model configuration performs best in all conditions, but that subsets of typically better-performing models are identifiable (Essery et al, 2013;Lafaysse et al, 2017;Magnusson et al, 2015).…”

“…However, there is evidence that turbulent fluxes are overly suppressed in some conditions by applying the adjustment based on the bulk Richardson number implemented in FSM. Correctly simulating these fluxes is a major ongoing challenge in land surface modelling (Lapo et al, 2019).…”

Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities

“…In CRHM, SnowModel, and AMUDSEN, sublimation is calculated based on laboratory experiments (Thorpe & Mason, 1966), which related the sublimation rate of individual ice spheres to relative humidity and wind speed. This is then modified to include the additional influence of solar radiation absorbed by the particle as developed for a blowing snow model (Schmidt, 1972), and scaled based on studying snow on an artificial tree (Schmidt, 1991) and a fractal analysis of photographs of snow on boreal forest branches (Pomeroy & Schmidt, 1993 Lapo et al (2019) for review, sublimation scales with wind speed and with vapour pressure gradients in all but the rare representations of stable conditions shutting down turbulence completely. We leave a full analysis of canopy wind speed variations and stability corrections as a subject for future research.…”

Thermal Submeso Motions in the Nocturnal Stable Boundary Layer. Part 2: Generating Mechanisms and Implications

“…10). The relationship between dynamic stability and Q H is commonly used for prescribing turbulent exchange in land models (Lapo et al 2019) or other studies (Brotzge and Crawford 2000). Within the transition area of TSFs, the air layers converged and created strong static stability as well as a low wind shear leading to high Ri B , hence a strong dynamic stability (Fig.…”