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High-Resolution Global Modeling of the Effects of Subgrid-Scale Clouds and Turbulence on Precipitating Cloud Systems
The PI’s at the National Center for Atmospheric Research (NCAR), Chin-Hoh Moeng and Peter Bogenschutz, have primarily focused their time on the implementation of the Simplified-Higher Order Turbulence Closure (SHOC; Bogenschutz and Krueger 2013) to the Multi-scale Modeling Framework (MMF) global model and testing of SHOC on deep convective cloud regimes.
Collaborative Project: High-resolution Global Modeling of the Effects of Subgrid-Scale Clouds and Turbulence on Precipitating Cloud Systems
We proposed to implement, test, and evaluate recently developed turbulence parameterizations, using a wide variety of methods and modeling frameworks together with observations including ARM data. We have successfully tested three different turbulence parameterizations in versions of the Community Atmosphere Model: CLUBB, SHOC, and IPHOC. All three produce significant improvements in the simulated climate. CLUBB will be used in CAM6, and also in ACME. SHOC is being tested in the NCEP forecast model. In addition, we have achieved a better understanding of the strengths and limitations of the PDF-based parameterizations of turbulence and convection.
Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"
The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. The chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.
AI-Automated Detection of Subgrid-scale Processes for Adaptivity Guidance
Focal Area(s) The proposed white paper focuses on focal areas 2 and 3, and intends to build a pipeline to automate the detection of unresolved processes based on model errors and assist subsequent modeling solutions.
Eigenspace Perturbations of Subgrid Stresses in Large-Eddy Simulations.
Abstract not provided.
Recovering the effects of subgrid heterogeneity in simulations of radionuclide transport through fractured media
Groundwater flow and contaminant transport through fractured media can be simulated using Discrete Fracture Network (DFN) models which provide a natural description of structural heterogeneity. However, this approach is computationally expensive, with the large number of intersecting fractures necessitated by many real-world applications requiring modeling simplifications to be made for calculations to be tractable. Upscaling methods commonly used for this purpose can result in some loss of local-scale variability in the groundwater flow velocity field, resulting in underestimation of particle travel times, transport resistance and retention in transport calculations. In this paper, a transport downscaling algorithm to recover the transport effects of heterogeneity is tested on a synthetic Brittle Fault Zone model, motivated by the problem of large safety assessment calculations for geological repositories of spent nuclear fuel. We show that the variability in the local-scale velocity field which is lost by upscaling can be recovered by sampling from a library of DFN transport paths, accurately reproducing DFN transport statistic distributions and radionuclide breakthrough curves in an upscaled model.
A reduced-order modeling approach to represent subgrid-scale hydrological dynamics for land-surface simulations: application in a polygonal tundra landscape
Existing land surface models (LSMs) describe physical and biological processes that occur over a wide range of spatial and temporal scales. For example, biogeochemical and hydrological processes responsible for carbon (CO 2 , CH 4 ) exchanges with the atmosphere range from the molecular scale (pore-scale O 2 consumption) to tens of kilometers (vegetation distribution, river networks). Additionally, many processes within LSMs are nonlinearly coupled (e.g., methane production and soil moisture dynamics), and therefore simple linear upscaling techniques can result in large prediction error. In this paper we applied a reduced-order modeling (ROM) technique known as "proper orthogonal decomposition mapping method" that reconstructs temporally resolved fine-resolution solutions based on coarse-resolution solutions. We developed four different methods and applied them to four study sites in a polygonal tundra landscape near Barrow, Alaska. Coupled surface–subsurface isothermal simulations were performed for summer months (June–September) at fine (0.25 m) and coarse (8 m) horizontal resolutions. We used simulation results from three summer seasons (1998–2000) to build ROMs of the 4-D soil moisture field for the study sites individually (single-site) and aggregated (multi-site). The results indicate that the ROM produced a significant computational speedup (> 10 3 ) with very small relative approximation error (< 0.1%) for 2 validation years not used in training the ROM. We also demonstrate that our approach: (1) efficiently corrects for coarse-resolution model bias and (2) can be used for polygonal tundra sites not included in the training data set with relatively good accuracy (< 1.7% relative error), thereby allowing for the possibility of applying these ROMs across a much larger landscape. By coupling the ROMs constructed at different scales together hierarchically, this method has the potential to efficiently increase the resolution of land models for coupled climate simulations to spatial scales consistent with mechanistic physical process representation.
Machine Learning for Explanation of Subgrid Convective Precipitation: A Case Study over CONUS Using a Convection-Allowing Model and SHAP Analysis
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Subgrid resolution of flow and force fields.
By means of spline fitting, both while converting a Lagrangian distribution of field sources onto an Eulerian grid, and while interpolating the field from its Eulerian grid to the Lagrangian positions of the responding elements, one achieves effective resolution down to about one-eight of a grid mesh unit. One also avoids discontinuities and noise due to cell boundary crossings.
Subgrid or Reynolds stress-modeling for three-dimensional turbulence computations
A review is given of recent advances in two distinct computational methods for evaluating turbulence fields, namely, statistical Reynolds stress modeling and turbulence simulation, where large eddies are followed in time. It is shown that evaluation of the mean Reynolds stresses, rather than use of a scalar eddy viscosity, permits an explanation of streamline curvature effects found in several experiments. Turbulence simulation, with a new volume averaging technique and third-order accurate finite-difference computing is shown to predict the decay of isotropic turbulence in incompressible flow with rather modest computer storage requirements, even at Reynolds numbers of aerodynamic interest.
An algorithm for selecting a radiation transport subgrid for ablation and radiation coupled hypersonic viscous shock-layer problems
An algorithm is described for selecting a grid subset for calculating radiative transport. The subset spacing is determined by using the variation in aerothermal properties across the full grid of the shock layer. Results show that a radiation grid subset of 15 to 20 points can be used for viscous-shock layer calculations where approximately 50 grid points are required to define the aerothermal profiles. Results are presented for various planetary entry conditions with and without mass injection to demonstrate both the validity and utility of the algorithm.
Evaluation of subgrid-scale turbulence models using a fully simulated turbulent flow
An exact turbulent flow field was calculated on a three-dimensional grid with 64 points on a side. The flow simulates grid-generated turbulence from wind tunnel experiments. In this simulation, the grid spacing is small enough to include essentially all of the viscous energy dissipation, and the box is large enough to contain the largest eddy in the flow. The method is limited to low-turbulence Reynolds numbers, in our case R sub lambda = 36.6. To complete the calculation using a reasonable amount of computer time with reasonable accuracy, a third-order time-integration scheme was developed which runs at about the same speed as a simple first-order scheme. It obtains this accuracy by saving the velocity field and its first-time derivative at each time step. Fourth-order accurate space-differencing is used.
Tests of subgrid-scale models in strained turbulence
Strained and sheared turbulence is computed by direct simulation and it is shown that the results are in good qualitative agreement with experiments. It is found that after large amounts of strain have been applied to turbulence, the energy flow to the small scales is reduced and, in some cases, reversed. Eddy viscosity models are shown to be very poor in strained turbulence and, when they are used, the mean strain should not be included in them. Finally, new models proposed by Bardina et al. have been tested and found to offer considerable promise for the future.
Tracer water transport and subgrid precipitation variation within atmospheric general circulation models
A capability is developed for monitoring tracer water movement in the three-dimensional Goddard Institute for Space Science Atmospheric General Circulation Model (GCM). A typical experiment with the tracer water model follows water evaporating from selected grid squares and determines where this water first returns to the Earth's surface as precipitation or condensate, thereby providing information on the lateral scales of hydrological transport in the GCM. Through a comparison of model results with observations in nature, inferences can be drawn concerning real world water transport. Tests of the tracer water model include a comparison of simulated and observed vertically-integrated vapor flux fields and simulations of atomic tritium transport from the stratosphere to the oceans. The inter-annual variability of the tracer water model results is also examined.
Renormalization-group theory for the eddy viscosity in subgrid modeling
Renormalization-group theory is applied to incompressible three-dimensional Navier-Stokes turbulence so as to eliminate unresolvable small scales. The renormalized Navier-Stokes equation now includes a triple nonlinearity with the eddy viscosity exhibiting a mild cusp behavior, in qualitative agreement with the test-field model results of Kraichnan. For the cusp behavior to arise, not only is the triple nonlinearity necessary but the effects of pressure must be incorporated in the triple term. The renormalized eddy viscosity will not exhibit a cusp behavior if it is assumed that a spectral gap exists between the large and small scales.
On the Subgrid-Scale Modeling of Compressible Turbulence
A new sub-grid scale model is presented for the large-eddy simulation of compressible turbulence. In the proposed model, compressibility contributions have been incorporated in the sub-grid scale eddy viscosity which, in the incompressible limit, reduce to a form originally proposed by Smagorinsky (1963). The model has been tested against a simple extension of the traditional Smagorinsky eddy viscosity model using simulations of decaying, compressible homogeneous turbulence. Simulation results show that the proposed model provides greater dissipation of the compressive modes of the resolved-scale velocity field than does the Smagorinsky eddy viscosity model. For an initial r.m.s. turbulence Mach number of 1.0, simulations performed using the Smagorinsky model become physically unrealizable (i.e., negative energies) because of the inability of the model to sufficiently dissipate fluctuations due to resolved scale velocity dilations. The proposed model is able to provide the necessary dissipation of this energy and maintain the realizability of the flow. Following Zeman (1990), turbulent shocklets are considered to dissipate energy independent of the Kolmogorov energy cascade. A possible parameterization of dissipation by turbulent shocklets for Large-Eddy Simulation is also presented.
Conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models
A parameterization of land surfaces based on a statistical-dynamical approach is presented. With this approach, the most important characteristics of the soil-plant-atmosphere system that affect the partition of energy (e.g., plant stomatal conductance, soil humidity, and surface roughness) are represented by a pdf rather than by a single 'representative' value. A primary simplified version of this parameterization is used to estimate the land-surface energy fluxes that are produced at the grid scale by various distributions of stomatal conductance under a broad range of environmental conditions. To demonstrate the approach's potential, results are compared with the same fluxes calculated with a big leaf model using the mean stomatal conductance that corresponds to the distributions. Large absolute and relative differences are obtained between the two schemes for many combinations of stomatal conductance pdfs and environmental conditions.