Extending Generalized Surface Layer Scaling to Diverse, Complex Terrain and Canopies for Improved Land-Atmosphere Exchange

For the past five decades, modelers have relied on Monin-Obukhov Similarity Theory (MOST) to model surface exchanges for application in atmospheric models for boundary layer meteorology and weather and climate prediction. During this time, studies have also illuminated some of the limitations of MOST based surface layer parameterizations, particularly when MOST’s foundational assumptions of flat and horizontally homogeneous terrain are violated. Recent work over groups of meteorological towers from Stiperski and Calaf 2023 have provided a promising method to account for these deviations from the ideal, traditional MOST using the anisotropy of turbulence to create new surface exchange relations. These modified relations may be able to capture the deviations from MOST specifically around non-homogeneous surfaces, and non-stationarity. To further assess the validity of the Stiperski relations, we examine them over 7 years of turbulence data from the 47, ecologically diverse eddy-covariance tower sites in the National Ecological Observation Network (NEON) and develop new anisotropy generalized MOST scalings for the scalar variances of moisture and carbon.

 

The relations from Stiperski and Calaf 2023 show significant improvement over traditional MOST based schemes for predicting the velocity variances as well as the variances of heat, moisture and carbon in the NEON network under both stable and unstable stratification. This extends the work of Stiperski and Calaf to vegetated canopies, where the scaling has not been previously examined. The improvement is consistent across the varied ecosystems present in NEON, including tropical, arctic, and mountainous sites. For the streamwise velocity variance, for example, we see a median improvement (measured with a skill score) of 40% at the NEON sites. Characteristics of anisotropy are also examined across the sites, with an eye towards developing model relations for turbulence anisotropy applicable in large scale schemes (i.e. numerical weather prediction and earth system models. Initial results for the scaling of the gradients of heat and momentum, which can be used to parameterize surface fluxes in the modeling context, are also shown, with promising improvement over traditional MOST despite significant scatter. The route for application of these schemes in surface layer parameterizations in ESMs is also briefly explored, with an eye towards the potential for significant improvements in modeling of surface exchange.