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Tyler Waterman

and 6 more

Tyler Waterman

and 3 more

Earth system models (ESMs) and mesoscale models have come to employ increasingly complex parameterization schemes for the atmospheric boundary layer (ABL), requiring surface boundary conditions for numerous higher order turbulence statistics. Of particular interest is the potential temperature variance (PTV), which is used not only as a boundary condition itself but also to close boundary conditions of other statistics. The existing schemes in ESMs largely rely on the assumptions of Monin-Obukhov similarity theory (MOST), and are not necessarily applicable over complex and heterogeneous surfaces where large scale circulations and roughness sub-layer effects may cause deviations from MOST. The National Ecological Network (NEON) is used here to evaluate existing parameterizations for the surface boundary of PTV, note key deficiencies, and explore possible remedies. The results indicate that existing schemes are acceptable over a variety of surface conditions provided the analysis of a priori filters out low frequency variability not associated with turbulent time scales. There was, however, significant inter-site variability in observed similarity constants and a significant bias when compared to the textbook values of these parameters. Existing models displayed the poorest performance over heterogeneous sites, and rough landscapes. Attempts to use canopy structure and surface roughness characteristics to improve the results confirmed a relation between these variables and PTV, but failed to significantly improve the predictive power of the models. The results did not find strong evidence indicating that large scale circulations caused substantial deviations from textbook models, although additional analysis is required to assess their full impacts.

Jason Scot Simon

and 3 more

Contemporary Earth system models mostly ignore the sub-grid scale (SGS) heterogeneous coupling between the land surface and atmosphere. To aid in the development of coupled land and atmosphere SGS parameterizations for global models, we present a study of different aspects of highly-realistic sub-100 km scale land-surface heterogeneity. The primary experiment is a set of simulations of September 24, 2017 over the Southern Great Plains (SGP) site using the Weather Research and Forecasting (WRF) model with 100-m horizontal resolution. The overall impact of land-surface heterogeneity is evaluated by comparing cloud and turbulent kinetic energy (TKE) production in large-eddy simulations (LESs) using heterogeneous and homogeneous surface fields (namely sensible and latent heat fluxes) specified by an offline field-scale resolving land-surface model (LSM). The heterogeneous land surface leads to significantly more cloud and TKE production. We then isolate specific sources of heterogeneity by using selectively domain-wide averaged fields in the LSM. It is found that heterogeneity in the land surface created by precipitation is effectively responsible for the increases in cloud and TKE production, while rivers and soil type have a negligible impact and land cover has only a small impact. Additional experiments modify the Bowen ratio in the surface fields and the initial wind profile of the heterogeneous case to clarify the results seen. Finally two additional days at the SGP site are simulated showing a similar increase in cloud production in heterogeneous cases.

Tyler Waterman

and 3 more

Earth System Models (ESMs) traditionally operate at large horizontal resolutions, on the order of 100 km, which can obscure the effects of smaller scale heterogeneity. When examining land surface states and fluxes in ESMs, one common approach to mitigate this issue is to divide the sub-grid land surface into distinct homogeneous clusters and then resolve the water, energy, and biogeochemical processes on each cluster or tile. The literature, as well as work in the Coupling of Land and Atmospheric Subgrid Parameterizations (CLASP) project, indicates that surface heterogeneity has important implications for atmospheric processes as well. Previous work using large-eddy simulation (LES) shows that spatial variability in surface heating can produce significant secondary circulations closely related to the type and scale of heterogeneity that are not captured by single column models. This presentation aims to address this persistent weakness by using a clustering or tiling approach, similar to that used with land surface processes, for the atmosphere. To accomplish this task, we run the Cloud Layers Unified By Binomials (CLUBB) single column model, a sub-grid turbulence and cloud parameterization scheme, over a 100 km box centered at the Southern Great Plains site in Oklahoma for a variety of surface and atmospheric conditions. The model is run independently over multiple surface clusters defined by surface sensible heat fluxes in the given domain. Results indicate that significant differences exist for some cases between the single column and multicolumn cases for liquid water path (LWP) as well as the turbulent kinetic energy (TKE) budget, and that results converge on consistent results with a fairly low number of clusters (i.e., atmospheric columns). We follow this up with a connected multicolumn setup where each column is dynamically connected with the other columns throughout the run to qualitatively capture the circulations observed in the LES output. The existing results show promise for capturing the effects of subgrid scale surface flux heterogeneity on the lower atmosphere in ESMs with the application of a multicolumn CLUBB setup.