Representation Of Fluxes Research Articles

Subgrid-scale models of isotropic turbulence need not produce energy backscatter

This investigation questions the importance of inverse interscale energy fluxes, the so-called energy backscatter, for the modelling of the energy cascade in large-eddy simulations (LES) of turbulent flows. The invariance of the filtered Navier–Stokes equations to divergence-preserving transformations of the subgrid-scale (SGS) stress tensor is exploited here to explore alternative representations of the local SGS energy fluxes. Numerical optimisation procedures are applied to the SGS stress tensor – obtained by filtering isotropic turbulence flow fields – to find alternative stresses that satisfy the filtered Navier–Stokes equations, but that produce negligible backscatter. These alternative SGS stresses show that backscatter represents not a flux of energy from the subgrid to the resolved scales, but conservative spatial fluxes, and that it need not be modelled to reproduce the local energetic exchange between the resolved and the subgrid scales in LES. From the perspective of statistical mechanics, it is argued that this is a consequence of the strong statistical irreversibility of inertial-range dynamics, which precludes inverse energy cascades even in a local sense. These findings show that the energy cascade is strongly unidirectional locally, and that it can be modelled as an irreversible sink of energy, justifying the extended use of purely dissipative SGS models in LES.

Modelling high-resolution Evapotranspiration in fragmented croplands from the constellation of Sentinels

The Sentinels for Evapotranspiration (Sen-ET) developed by the European Space Agency (ESA) provides a synoptic representation of actual ET (ETa) and other land-surface energy fluxes at high spatial (20 m) and temporal (daily) resolutions by the fusion of Sentinel-2 and Sentinel-3 datasets. However, the non-availability of optical sensor enabled Sentinel-2 images during the periods of high cloud cover such as monsoon limits the perennial use of Sen-ET. Here, we propose an alternate method to estimate ETa fluxes using locally observed weather data and the polarimetric parameters derived from Sentinel-1 with an application to fragmented, heterogeneous croplands. At first, the Sen-ET modelling approach with cloud-free datasets is validated using eddy covariance (EC) flux datasets (R2 = 0.74). Sen-ET derived ETa fluxes were used to develop crop coefficient (Kc) curves by considering reference ET (ET0) obtained from the weather data (Monteith, 1965b). Functional relations were then established between Sentinel-1 derived polarimetric parameters and Kc considering cloud-free datasets, and further translated to the periods of high cloud cover. We observed a strong dependency of VH on Kc for sugarcane and vegetables, and radar vegetation index (RVI) on Kc for rice (Rveg2=0.55,Rs.c.2=0.61,Rrice.2=0.51). The performance of Sentinel-1 derived ETa estimates were further validated with EC fluxes and found to be high during non-monsoon period (R2 = 0.74, RMSE = 1.25) than in monsoon period (R2 = 0.63, RMSE = 0.82). Our results indicate the suitability of Sentinel-1 in estimating ETa fluxes during the periods of high cloud cover for effective irrigation management.

Constraining Arctic Climate Projections of Wintertime Warming With Surface Turbulent Flux Observations and Representation of Surface-Atmosphere Coupling

The drivers of rapid Arctic climate change—record sea ice loss, warming SSTs, and a lengthening of the sea ice melt season—compel us to understand how this complex system operates and use this knowledge to enhance Arctic predictability. Changing energy flows sparked by sea ice decline, spotlight atmosphere-surface coupling processes as central to Arctic system function and its climate change response. Despite this, the representation of surface turbulent flux parameterizations in models has not kept pace with our understanding. The large uncertainty in Arctic climate change projections, the central role of atmosphere-surface coupling, and the large discrepancy in model representation of surface turbulent fluxes indicates that these processes may serve as useful observational constraints on projected Arctic climate change. This possibility requires an evaluation of surface turbulent fluxes and their sensitivity to controlling factors (surface-air temperature and moisture differences, sea ice, and winds) within contemporary climate models (here Coupled Model Intercomparison Project 6). The influence of individual controlling factors and their interactions is diagnosed using a multi-linear regression approach. This evaluation is done for four sea ice loss regimes, determined from observational sea ice loss trends, to control for the confounding effects of natural variability between models and observations. The comparisons between satellite- and model-derived surface turbulent fluxes illustrate that while models capture the general sensitivity of surface turbulent fluxes to declining sea ice and to surface-air gradients of temperature and moisture, substantial mean state biases exist. Specifically, the central Arctic is too weak of a heat sink to the winter atmosphere compared to observations, with implications to the simulated atmospheric circulation variability and thermodynamic profiles. Models were found to be about 50% more efficient at turning an air-sea temperature gradient anomaly into a sensible heat flux anomaly relative to observations. Further, the influence of sea ice concentration on the sensible heat flux is underestimated in models compared to observations. The opposite is found for the latent heat flux variability in models; where the latent heat flux is too sensitive to a sea ice concentration anomaly. Lastly, the results suggest that present-day trends in sea ice retreat regions may serve as suitable observational constraints of projected Arctic warming.

The Orinoco Low‐Level Jet and the Cross‐Equatorial Moisture Transport Over Tropical South America: Lessons From Seasonal WRF Simulations

AbstractA study of the simulation of the Orinoco Low‐Level Jet (OLLJ) and the cross‐equatorial moisture transport over tropical South America using the Weather Research and Forecasting (WRF) model is presented. The focus is on the diurnal cycle and monthly means during one December‐January‐February (DJF) season (2003–2004). The sensitivity of the OLLJ and cross‐equatorial moisture transport to the representation of surface fluxes and turbulence is explored by using two different Land Surface Models (LSM) and three Planetary Boundary Layer (PBL) schemes. Different LSMs produce large differences in the sensible heat flux over the Orinoco basin, but no substantial differences in the flow at the entrance of the OLLJ. However, these changes in surface fluxes were associated with a change in the low‐level pressure gradient between the Orinoco and Amazon basins, and with up to 10% change in the simulated cross‐equatorial moisture transport. The largest effects from different PBL schemes were found in the low‐level flow near the Andes cordillera, and on the low‐level southward cross‐equatorial flow during the daytime. One of the PBL schemes exhibited a reduced moisture transport on the eastern flank of the Andes but enhanced southward transport around the core of the cross‐equatorial moisture flux. Another PBL scheme produced a stronger net cross‐equatorial moisture transport, with enhanced precipitation over the Andes‐Amazon region by up to 30% during the afternoon and up to 13% in the daily mean. Improved observations over the region are needed to evaluate which combination best represents the flow.

Study of Induction Motor Inter-Turn Fault Part I: Development of Fault Models with Distorted Flux Representation

An inter-turn fault (ITF) is one of the most frequent induction motor faults; thus, many previous works have studied its model and diagnosis. However, previous works, simplifying the specific distorted flux distribution by the ITF, presented induction motor fault models and focused on the fault signal analysis for diagnoses. Consequently, these results are only adequate for the pretested motor and sensitive to fault signal distortion. This paper presents an induction motor ITF model in the stationary DQ frame, for a model-based diagnosis. Furthermore, to describe the distorted flux distribution along the air gap by the ITF, the rotor flux linkages are described in the independent DQ frame of every pole, and the mutual flux linkages among the rotor, stator, and ITF windings are specifically modeled. Hence, the proposed full model has many current states and mutual inductances to describe the high pole number motor. A simplified model is also proposed for easier usage in the diagnosis, with light ITF to overcome this complexity. Finally, simulation and experiments are performed to verify the presented induction motor ITF fault models.

On the application of the analytical discrete ordinates method to the solution of nonclassical transport problems in slab geometry

In this work we investigate the use of the Analytical Discrete Ordinates (ADO) method when solving the spectral approximation of the nonclassical transport equation. The spectral approximation is a recently developed method based on the representation of the nonclassical angular flux as a series of Laguerre polynomials. This representation generates, as outcome, a system of equations that have the form of classical transport equations and can therefore be solved by current deterministic algorithms. Thus, the investigation of efficient approaches to solve the nonclassical transport equation is of interest and shall be pursued. This is the case of the ADO method which has been successfully used to solve a wide class of problems in the general area of particle transport. Numerical results are presented for two nonclassical test problems in slab geometry. These nonclassical transport problems are chosen in such way that their solution exactly reproduces the solution of the classical diffusion problem. Very accurate results are obtained for both test problems. However, the use of high precision arithmetic is sometimes required as illustrated in the second test problem. Limitations of the spectral approximation are also analyzed and discussed.

Impact of Real‐Time Satellite‐Derived Green Vegetation Fraction on National Water Model Fluxes in Humid Alabama Watersheds

AbstractVegetation is parameterized in the operational National Oceanic and Atmospheric Administration National Water Model (NWM) using climatologies of leaf area index and green vegetation fraction (GVF) which do not capture interannual variability or seasonal anomalies. This study investigates the impact of assimilating real‐time Visible Infrared Imaging Radiometer Suite (VIIRS) GVF on NWM streamflow and land surface energy and moisture fluxes. Using a subset of the NWM over three humid watersheds in Alabama, VIIRS GVF was assimilated into an experimental NWM configuration to replace the default GVF climatology to provide a more accurate representation of the land surface vegetation greenness. Although the use of real‐time VIIRS GVF in place of the climatological GVF slightly improved NWM stream‐flow prediction, results were not statistically significant. GVF assimilation also improved the interannual representation of land surface fluxes with increases in GVF resulting in increased evapotranspiration and latent heat.

Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4)

Abstract. The uptake of carbonyl sulfide (COS) by terrestrial plants is linked to photosynthetic uptake of CO2 as these gases partly share the same uptake pathway. Applying COS as a photosynthesis tracer in models requires an accurate representation of biosphere COS fluxes, but these models have not been extensively evaluated against field observations of COS fluxes. In this paper, the COS flux as simulated by the Simple Biosphere Model, version 4 (SiB4), is updated with the latest mechanistic insights and evaluated with site observations from different biomes: one evergreen needleleaf forest, two deciduous broadleaf forests, three grasslands, and two crop fields spread over Europe and North America. We improved SiB4 in several ways to improve its representation of COS. To account for the effect of atmospheric COS mole fractions on COS biosphere uptake, we replaced the fixed atmospheric COS mole fraction boundary condition originally used in SiB4 with spatially and temporally varying COS mole fraction fields. Seasonal amplitudes of COS mole fractions are ∼50–200 ppt at the investigated sites with a minimum mole fraction in the late growing season. Incorporating seasonal variability into the model reduces COS uptake rates in the late growing season, allowing better agreement with observations. We also replaced the empirical soil COS uptake model in SiB4 with a mechanistic model that represents both uptake and production of COS in soils, which improves the match with observations over agricultural fields and fertilized grassland soils. The improved version of SiB4 was capable of simulating the diurnal and seasonal variation in COS fluxes in the boreal, temperate, and Mediterranean region. Nonetheless, the daytime vegetation COS flux is underestimated on average by 8±27 %, albeit with large variability across sites. On a global scale, our model modifications decreased the modeled COS terrestrial biosphere sink from 922 Gg S yr−1 in the original SiB4 to 753 Gg S yr−1 in the updated version. The largest decrease in fluxes was driven by lower atmospheric COS mole fractions over regions with high productivity, which highlights the importance of accounting for variations in atmospheric COS mole fractions. The change to a different soil model, on the other hand, had a relatively small effect on the global biosphere COS sink. The secondary role of the modeled soil component in the global COS budget supports the use of COS as a global photosynthesis tracer. A more accurate representation of COS uptake in SiB4 should allow for improved application of atmospheric COS as a tracer of local- to global-scale terrestrial photosynthesis.

Simulation of Northeast Monsoon in a coupled regional model framework

The rainfall during Northeast Monsoon (NEM) meets most of the water demand and influences the socioeconomic condition of the population in the southern part of India. The present study focuses to identify a better, coupled land-atmosphere combination using regional downscaling experiments with RegCM4 for representing the mean characteristics of the NEM rainfall. Three suites of model integrations are made using three different land-surface schemes such as Biosphere-Atmosphere Transfer Scheme (BATS), Subgrid-BATS (SUB), and Community Land Model version 4.5 (CLM). The CLM experiment shows a better spatial representation of the rainfall due to the better representation of the moisture flux and convection, whereas the BATS and SUB experiments show strong wet bias (1–6 mm/yr) over Tamilnadu and Kerala. The spatial correlation of the climatological rainfall with respect to observation is maximum (0.5–0.6) for the CLM. However, the model experiments fail to reproduce the interannual variability of rainfall. The better representation of climatological rainfall, evaporation and turbulent fluxes (sensible and latent heat flux) leads to an improved temperature climatology in the CLM experiment. The study illustrates that the CLM land-surface scheme performs better in representing the northeast monsoon as compared to others however there is a need to explore avenues for further improvements in the performance of the coupled model framework.

Parameterizing Eddy Transport of Biogeochemical Tracers

AbstractThe distribution of oceanic biogeochemical tracers is fundamentally tied to physical dynamics at and below the mesoscale. Since global climate models rarely resolve those scales, turbulent transport is parameterized in terms of the large‐scale gradients in the mean tracer distribution and the physical fields. Here, we demonstrate that this form of the eddy flux is not necessarily appropriate for reactive tracers, such as nutrients and phytoplankton. In an idealized nutrient‐phytoplankton system, we show that the eddy flux of one tracer should depend on the gradients of itself and the other. For certain parameter regimes, incorporating cross‐diffusion can significantly improve the representation of both phytoplankton and nutrient eddy fluxes. We also show that the efficacy of eddy diffusion parameterizations requires timescale separation between the flow and reactions. This result has ramifications for parameterizing subgrid scale biogeochemistry in more complex ocean models since many biological processes have comparable timescales to submesoscale motions.

Assessment of the neutron flux stability in a high power BN-type reactor in terms of modal spatial kinetics

The article discusses the neutron flux stability in the core of a high-power sodium-cooled fast reactor (of the BN-type) without feedbacks. The importance of this problem for high-power BN-type reactors is associated with the specific features of the layout of their cores, including a large diameter and height/diameter ratio about 5. The technique used to substantiate the stability of neutron fields is based on the analysis of the spectrum of the matrix of the system of spatial kinetics equations describing the core of a high-power BN-type reactor without feedbacks. A computational model of the spatial kinetics of a high-power BN-type reactor has been developed in the modal approximation based on the representation of an unsteady flux as a sum of orthogonal functions multiplied by time-dependent amplitudes. The eigenfunctions of the conditionally critical problem are used in the diffusion approximation, which in the discrete case form a complete system. The spectrum of the matrix of the system of ordinary differential equations describing the spatial kinetics of the reactor has been calculated. It is shown that the neutron flux in the core of a high-power BN-type reactor without feedbacks is stable. Test calculations have illustrated the damping of perturbations of the power distribution for a reactor in a critical state.

Reconstructing a point source from diffusion fluxes to narrow windows in three dimensions

We develop a computational approach to locate the source of a steady-state gradient of diffusing particles from the fluxes through narrow windows distributed either on the boundary of a three-dimensional half-space or on a sphere. This approach is based on solving the mixed boundary stationary diffusion equation with Neumann–Green’s function. The method of matched asymptotic expansions enables the computation of the probability fluxes. To explore the range of validity of this expansion, we develop a fast analytical-Brownian numerical scheme. This scheme accelerates the simulation time by avoiding the explicit computation of Brownian trajectories in the infinite domain. The results obtained from our derived analytical formulae and the fast numerical simulation scheme agree on a large range of parameters. Using the analytical representation of the particle fluxes, we show how to reconstruct the location of the point source. Furthermore, we investigate the uncertainty in the source reconstruction due to additive fluctuations present in the fluxes. We also study the influence of various window configurations: clustered versus uniform distributions on recovering the source position. Finally, we discuss possible applications for cell navigation in biology.

Impact of surface roughness parameterizations on tropical cyclone simulations over the Bay of Bengal using WRF-OML model

The impact of different surface roughness schemes in air-sea coupling on simulating tropical cyclones (TCs) over the Bay of Bengal is analyzed using Weather Research and Forecasting-Ocean Mixed layer (WRF-OML) modeling system. The sensitivity of three surface roughness schemes is tested by conducting three experiments for seven TCs namely Phailin (2013), Lehar (2013), Hudhud (2014), Vardah (2016), Gaja (2018), Fani (2019) and Amphan (2020). The first experiment (Opt0) is configured with surface drag and moist enthalpy from Garratt formulations, the second (Opt1) uses surface drag from Donelan and constant moist enthalpy formulations and the third experiment (Opt2) employs the modified moist enthalpy from Garratt formulations along with Donelan drag. Results of predicted track, intensities, precipitation and structure of the cyclones are highly sensitive to the surface exchange coefficients formulated through the roughness parameterization. The Opt2 followed by Opt1 experiments captured the deepening and mature phases of the storm close to the observed estimates for both pre- and post-monsoon TCs, by improving the ocean-atmosphere feedback of surface energy fluxes. Comparison of simulated moisture convergence, transport and precipitation with observations for all cyclones suggest that the Opt2 provides an improved representation of surface enthalpy fluxes playing a crucial role in the moisture transport and cloud microphysical processes. The improved simulation of TCs with Opt1 and Opt2 over Opt0 is attributed to the realistic simulation of mixed layer deepening and sea surface temperature cooling effects in the model. An interesting result found from the WRF-OML simulations with three roughness schemes is the maximum moisture transport is mainly concentrated on the right sectors while the moisture convergence and precipitation are distributed on the left sectors of the cyclones.

A unifying model framework for soil erosion, river bedload and chemical transport

A unified framework for simulating various transport processes in the environment is presented. It consists in a single set of partial differential equations. The main feature of this model framework is its exchange layer, which allows to treat several types of transfer between the soil and the surface water.The model framework equations, termed transfer equations, is shown to reproduce three independently-published models developed for soil erosion, river bedload, and chemical transport respectively. By allowing the different processes to be represented within a single model framework, the transfer equations are therefore unifying the representation of particles and chemical fluxes in the environment. The transfer equations are implemented into the open-source software FullSWOF_1D. The code is verified against the approximation of an exact solution, assuring its proper functioning. A good adequacy is found between our numerical results and those published in the literature, attesting the capability of the transfer equations to unify modeling of soil erosion, river bedload, and chemical transport. Hence, the transfer equations can decrease the number of models to be used for simulating transfer of materials in the environment, and limit the number of computer codes to be developed and maintained. The transfer equations could also help in drawing parallels between different fields of hydrology.

On eddy transport in the ocean. Part I: The diffusion tensor

This study provides an interpretation of isopycnal eddy transport for mass and passive tracers in double-gyre eddy-resolving oceanic circulation. This paper focuses on a transport/diffusion tensor representation of the eddy tracer flux, and a companion paper will focus on advective eddy-induced tracer and mass transports. We use a spatial filter to separate the large and small scales, which leads to results distinct from those obtained via a temporal Reynolds eddy decomposition. To work towards a parameterisation, we relate the eddy tracer flux to the large-scale tracer gradient via the transport tensor K. The symmetric part of K is the diffusion tensor, S, which parameterises diffusive fluxes and whose mixing properties are determined by the signs of its eigenvalues. The eigenvalues of S are robustly of opposite sign (polar) and thus quantify filamentation of the tracer via both up- and down-gradient fluxes. Given the prevalence of polar eigenvalues – which are also obtained for Reynolds eddy fluxes – representing their associated effects should be a target of future eddy tracer transport closures. Given the inherent inhomogeneity and anisotropy of the eddy-induced transport, we argue that a full transport tensor is better suited to this task than scalar coefficients or diagonal tensors. The diffusion axis, which represents the direction of preferential mixing, tends to align with the large-scale velocity vector and contours of large-scale relative vorticity and layer thickness. Strong shears can inhibit this alignment. We show that the large-scale velocity gradient matrix may be suitable for parameterising the transport tensor, in particular at depth. Furthermore, since entries of K and S exhibit probabilistic distributions when conditioned on certain large-scale flow features, we suggest that a stochastic closure for the eddy transport would be most suitable.

Mass flux of dispersed particles in turbulence: Representations and the influence of correlation structure in gravitational settling.

Different integral representations for the mass flux of inertial particles transported by turbulent gas flows have been proposed. These are discussed and analyzed. Each formulation provides its own insights into the underlying physical processes governing the resulting flux. However, none of the representations, as it stands, provides an explicit closed-form expression in terms of known statistical properties of the flow and parameters governing particle dynamics. We consider the representations in terms of their potential for reduction to closed-form models. To enable an analysis uncomplicated by the presence of many coupled interactions, we confine our attention to the classic test case of monodisperse particles in homogeneous, isotropic turbulent flows, and subject to a uniform gravitational field. The modification of the mean particle settling velocity resulting from their preferential sampling of fluid velocities is captured by the flux representations. A distribution-based symmetry analysis coupled with a correlation splitting technique is used to reduce and simplify the terms appearing in the flux integrals. This prompts a strategy for closure modeling of the resulting expressions in terms of correlations between the sampled fluid velocity and fluid strain-rate fields. Results from particle-trajectory-based simulations are presented to assess the potential of this closure strategy.

An Urban Scheme for the ECMWF Integrated Forecasting System: Single‐Column and Global Offline Application

AbstractThe societal benefits of numerical weather prediction (NWP) forecasts are most evident in populated areas. An urban representation within NWP models should provide improved forecast accuracy. Here, we present the preliminary implementation of an urban scheme within the Integrated Forecasting System (IFS) using a simplified single‐layer urban canopy model. The scheme makes assumptions of canyon geometry and considers fluxes from roads, walls, and roofs. Temperature observations were used to optimize single‐column model (SCM) parameters using the Gauss‐Newton method. Observation comparisons over six European cities, show a 2‐m temperature root‐mean‐squared error reduction from 1.85 to 1.75 K with the urban scheme. Optimized parameters were used globally at kilometric scale in a land surface model. A sensitivity experiment assuming a 100% urban world showed spatially averaged northern hemisphere 2‐m temperatures increased by 0.54 K (January) and 0.42 K (July) at night caused by changes in the albedo, emissivity, roughness, and thermal and hydrological properties. Global ∼1‐km resolution simulations using ancillary urban mapping information produce an urban heat island effect over major and minor conurbations. Only major conurbations were well represented at ∼9‐km resolution. Results from SCM simulations show a heightening of the planetary boundary layer over city sites, with the largest enhancements occurring at night in July (84 ± 48 m) caused by an increased sensible heat flux. These initial developments show the importance of a high‐resolution urban representation within NWP models. Improved parameterization and mapping will enable an online representation of energy, water, and trace gas fluxes over residential areas.

A multiscale mixed finite element method applied to the simulation of two-phase flows

The multiscale hybrid mixed finite element method (MHM-H(div)), previously developed for Darcy’s problems, is extended for coupled flow/pressure and transport system of two-phase flow equations on heterogeneous media under the effect of gravitational segregation. It is combined with an implicit transport solver in a sequential fully implicit (SFI) manner. The MHM-H(div) method is designed to cope with the complex geometry and inherent multiscale nature of the phenomena. The discretizations are based on a general domain partition formed by polyhedral subregions, where a hierarchy of meshes and approximation spaces are considered. The multiscale approach is applied to the flux/pressure kernel making use of coarse scale normal fluxes between subregions (trace variable). The fine-scale features inside each subregion are determined by resolving completely independent local Neumann problems, the boundary conditions being set by the trace variable, by the mixed finite element method using fine flux and pressure representations. These properties imply that the MHM-H(div) can be interpreted as a classical mixed formulation of the model problem in the whole domain, based on a H(div)-conforming space with normal components over the macro-partition interfaces constrained by the trace space, and showing divergence compatibility with the pressure space. Consequently, local mass conservation is observed at the micro-scale elements inside the subregions, an essential property for flows in heterogeneous media, and divergence-free constraint strongly enforced for incompressible flows. The efficient use of static condensation leads to a global system to be solved only in terms of primary degrees of freedom associated with the trace variable and of a piecewise constant pressure for each subregion. This procedure allows a substantial reduction of the dominant computational costs associated with the flux/pressure kernel embedded in the numerical model. An iterative coupling technique is adopted to solve the two-phase flow equations using a shared integration point memory implementation model. At each SFI time step, the efficiency iterative method for the transport equations is improved using a Quasi-Newton method with a simple but effective nonlinear acceleration. The numerical examples show that the proposed scheme is able to solve challenging coupled flow and transport problems.

Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model

Abstract. Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in many global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to present the technical developments of a computationally efficient approach for representing age-class dynamics within a global ecosystem model, the Lund–Potsdam–Jena – Wald, Schnee, Landschaft version 2.0 (LPJ-wsl v2.0) dynamic global vegetation model and to determine if explicit representation of demography influenced ecosystem stocks and fluxes at global scales or at the level of a grid cell. The modeled age classes are initially created by simulated fire and prescribed wood harvesting or abandonment of managed land, otherwise aging naturally until an additional disturbance is simulated or prescribed. In this paper, we show that the age module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that simulated patterns of ecosystem function follow classic responses with age. We also present two scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a 45- to 60-year difference in ages between older boreal (50–90∘ N) and younger tropical (23∘ S–23∘ N) ecosystems. Between simulation years 1860 and 2016, land-use change and land management were responsible for a decrease in zonal age by −6 years in boreal and by −21 years in both temperate (23–50∘ N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped to reduce LPJ-wsl v2.0 complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature, and age class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C m−2 yr−1 but as high as 0.60 kg C m−2 yr−1 where the effect was greatest. In the eastern forests of North America, the simulated demographic effect was of similar magnitude, or greater than, the effects of climate; simulated demographic effects were similarly important in large regions of every vegetated continent. Simulated spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40 Pg C increase in biomass turnover when including age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. The LPJ-wsl v2.0 age module represents another step forward towards understanding the role of demography in global ecosystems.

Deep Learned Process Parameterizations Provide Better Representations of Turbulent Heat Fluxes in Hydrologic Models

AbstractDeep learning (DL) methods have shown great promise for accurately predicting hydrologic processes but have not yet reached the complexity of traditional process‐based hydrologic models (PBHM) in terms of representing the entire hydrologic cycle. The ability of PBHMs to simulate the hydrologic cycle makes them useful for a wide range of modeling and simulation tasks, for which DL methods have not yet been adapted. We argue that we can take advantage of each of these approaches by embedding DL methods into PBHMs to represent individual processes. We demonstrate that this is viable by developing DL‐based representations of turbulent heat fluxes and coupling them into the Structure for Unifying Multiple Modeling Alternatives (SUMMA), a modular PBHM modeling framework. We developed two DL parameterizations and integrated them into SUMMA, resulting in a one‐way coupled implementation which relies only on model inputs and a two‐way coupled implementation, which also incorporates SUMMA‐derived model states. Our results demonstrate that the DL parameterizations are able to outperform calibrated standalone SUMMA benchmark simulations. Further we demonstrate that the two‐way coupling can simulate the long‐term latent heat flux better than the standalone benchmark and one‐way coupled configuration. This shows that DL methods can benefit from PBHM information, and the synergy between these modeling approaches is superior to either approach individually.