Geoscientific Model Development最新文献

{"title":"Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0","authors":"Minjin Lee, C. Stock, J. Dunne, E. Shevliakova","doi":"10.5194/gmd-17-5191-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-5191-2024","url":null,"abstract":"Abstract. Estimating global river solids, nitrogen (N), and phosphorus (P), in both quantity and composition, is necessary for understanding the development and persistence of many harmful algal blooms, hypoxic events, and other water quality issues in inland and coastal waters. This requires a comprehensive freshwater model that can resolve intertwined algae, solid, and nutrient dynamics, yet previous global watershed models have limited mechanistic resolution of instream biogeochemical processes. Here we develop the global, spatially explicit, and process-based Freshwater Algae, Nutrient, and Solid cycling and Yields (FANSY) model and incorporate it within the Land Model (LM3). The resulting model, LM3-FANSY v1.0, is intended as a baseline for eventual linking of global terrestrial and ocean biogeochemistry in next-generation Earth system models to project global changes that may challenge empirical approaches. LM3-FANSY explicitly resolves interactions between algae, N, P, and solid dynamics in rivers and lakes at 1° spatial and 30 min temporal resolution. Simulated suspended solids (SS), N, and P in multiple forms (particulate or dissolved, organic or inorganic) agree well with measurement-based yield (kg km−2 yr−1), load (kt yr−1), and concentration (mg L−1) estimates across a globally distributed set of large rivers, with an accuracy comparable to other global nutrient and SS models. Furthermore, simulated global river loads of SS, N, and P in different forms to the coastal ocean are consistent with published ranges, though regional biases are apparent. River N loads are estimated to contain approximately equal contributions by dissolved inorganic N (41 %) and dissolved organic N (39 %), with a lesser contribution by particulate organic N (20 %). For river P load estimates, particulate P, which includes both organic and sorbed inorganic forms, is the most abundant form (64 %), followed by dissolved inorganic and organic P (25 % and 11 %). Time series analysis of river solid and nutrient loads in large US rivers for the period ∼ 1963–2000 demonstrates that simulated SS and N loads in different N forms covary with variations of measurement-based loads. LM3-FANSY, however, has less capability to capture interannual variability of P loads, likely due to the lack of terrestrial P dynamics in LM3. Analyses of the model results and sensitivity to components, parameters, and inputs suggest that fluxes from terrestrial litter and soils, wastewater, and weathering are the most critical inputs to the fidelity of simulated river nutrient loads for observation-based estimates. Sensitivity analyses further demonstrate a critical role of algal dynamics in controlling the ratios of inorganic and organic nutrient forms in freshwaters. While the simulations are able to capture significant cross-watershed contrasts at a global scale, disagreement for individual rivers can be substantial. This limitation is shared by other global river models and could be amel","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"111 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141668141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1","authors":"Chongzhi Yin, Shin‐ichiro Shima, L. Xue, Chunsong Lu","doi":"10.5194/gmd-17-5167-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-5167-2024","url":null,"abstract":"Abstract. The super-droplet method (SDM) is a Lagrangian particle-based numerical scheme for cloud microphysics. In this work, a series of simulations based on the DYCOMS-II (RF02) setup with different horizontal and vertical resolutions are conducted to explore the grid convergence of the SDM simulations of marine stratocumulus. The results are compared with the double-moment bulk scheme (SN14) and model intercomparison project (MIP) results. In general, all SDM and SN14 variables show a good agreement with the MIP results and have similar grid size dependencies. The stratocumulus simulation is more sensitive to the vertical resolution than to the horizontal resolution. The vertical grid length DZ ≪ 2.5 m is necessary for both SDM and SN14. The horizontal grid length DX < 12.5 m is necessary for the SDM simulations. DX ≤ 25 m is sufficient for SN14. We also assess the numerical convergence with respect to the super-droplet numbers. The simulations are well converged when the super-droplet number concentration (SDNC) is larger than 16 super-droplets per cell. Our results indicate that the super-droplet number per grid cell is more critical than that per unit volume at least for the stratocumulus case investigated here. Our comprehensive analysis not only offers guidance on numerical settings essential for accurate stratocumulus cloud simulation but also underscores significant differences in liquid water content and cloud macrostructure between SDM and SN14. These differences are attributed to the inherent modeling strategies of the two schemes. SDM's dynamic representation of aerosol size distribution through wet deposition markedly contrasts with SN14's static approach, influencing cloud structure and behavior over a 6 h simulation. Findings reveal sedimentation's crucial role in altering aerosol distributions near cloud tops, affecting the vertical profile of cloud fraction (CF). Additionally, the study briefly addresses numerical diffusion's potential effects, suggesting further investigation is needed. The results underscore the importance of accurate aerosol modeling and its interactions with cloud processes in marine stratocumulus simulations, pointing to future research directions for enhancing stratocumulus modeling accuracy and predictive capabilities.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":" 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141677164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth","authors":"V. de Toma, D. Ciani, Yassmin Hesham Essa, Chunxue Yang, V. Artale, A. Pisano, Davide Cavaliere, R. Santoleri, A. Storto","doi":"10.5194/gmd-17-5145-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-5145-2024","url":null,"abstract":"Abstract. In this paper, we explore different prognostic methods to account for skin sea surface temperature diurnal variations in a coupled ocean–atmosphere regional model of the Mediterranean Sea. Our aim is to characterise the sensitivity of the considered methods with respect to the underlying assumption of how the solar radiation shapes the warm layer of the ocean. All existing prognostic methods truncate solar transmission coefficient at a warm-layer reference depth that is constant in space and time; instead, we implement a new scheme where this latter is estimated from a chlorophyll dataset as the e-folding depth of solar transmission, which thus allows it to vary in space and time depending on seawater's transparency conditions. Comparison against satellite data shows that our new scheme, compared to the one already implemented within the ocean model, improves the spatially averaged diurnal signal, especially during winter, and the seasonally averaged one in spring and autumn, while showing a monthly basin-wide averaged bias smaller than 0.1 K year-round. In April, when most of the drifters' measurements are available, the new scheme mitigates the bias during nighttime, keeping it positive but smaller than 0.12 K during the rest of the monthly averaged day. The new scheme implemented within the ocean model improves the old one by about 0.1 K, particularly during June. All the methods considered here showed differences with respect to objectively analysed profiles confined between 0.5 K during winter and 1 K in summer for both the eastern and the western Mediterranean regions, especially over the uppermost 60 m. The new scheme reduces the RMSE on the top 15 m in the central Mediterranean for summertime months compared to the scheme already implemented within the ocean model. Overall, the surface net total heat flux shows that the use of a skin sea surface temperature (SST) parameterisation brings the budget about 1.5 W m−2 closer to zero on an annual basis, despite all simulations showing an annual net heat loss from the ocean to the atmosphere. Our “chlorophyll-interactive” method proved to be an effective enhancement of existing methods, its strength relying on an improved physical consistency with the solar extinction implemented in the ocean component.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":" 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) – towards an improved representation of mountain water resources in global assessments","authors":"Sarah Hanus, Lilian Schuster, P. Burek, F. Maussion, Y. Wada, D. Viviroli","doi":"10.5194/gmd-17-5123-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-5123-2024","url":null,"abstract":"Abstract. Glaciers are present in many large river basins, and due to climate change, they are undergoing considerable changes in terms of area, volume, magnitude and seasonality of runoff. Although the spatial extent of glaciers is very limited in most large river basins, their role in hydrology can be substantial because glaciers store large amounts of water at varying timescales. Large-scale hydrological models are an important tool to assess climate change impacts on water resources in large river basins worldwide. Nevertheless, glaciers remain poorly represented in large-scale hydrological models. Here we present a coupling between the large-scale glacier model Open Global Glacier Model (OGGM) v1.5.3 and the large-scale hydrological model Community Water Model (CWatM) V1.08. We evaluated the improved glacier representation in the coupled model against the baseline hydrological model for four selected river basins at 5 arcmin resolution and globally at 30 arcmin resolution, focusing on future discharge projections under low- and high-emission scenarios. We find that increases in future discharge are attenuated, whereas decreases are exacerbated when glaciers are represented explicitly in the large-scale hydrological model simulations. This is explained by a projected decrease in glacier-sourced runoff in almost all basins. Calibration can compensate for lacking glacier representation in large-scale hydrological models in the past. Nevertheless, only an improved glacier representation can prevent underestimating future discharge changes, even far downstream at the outlets of large glacierized river basins. Therefore, incorporating a glacier representation into large-scale hydrological models is important for climate change impact studies, particularly when focusing on summer months or extreme years. The uncertainties in glacier-sourced runoff associated with inaccurate precipitation inputs require the continued attention and collaboration of glacier and hydrological modelling communities.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"21 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141837605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption","authors":"Hunter Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, Lin Lin","doi":"10.5194/gmd-17-5087-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-5087-2024","url":null,"abstract":"Abstract. This paper describes the addition of a stratospheric prognostic aerosol (SPA) capability – developed with the goal of accurately simulating sulfate aerosol formation and evolution in the stratosphere – in the Department of Energy (DOE) Energy Exascale Earth System Model, version 2 (E3SMv2). The implementation includes changes to the four-mode Modal Aerosol Module microphysics in the stratosphere to allow for larger particle growth and more accurate stratospheric aerosol lifetime following the Pinatubo eruption. E3SMv2-SPA reasonably reproduces stratospheric aerosol lifetime, burden, aerosol optical depth, and top-of-atmosphere flux when compared to remote sensing observations. E3SMv2-SPA also has close agreement with the interactive chemistry–climate model CESM2-WACCM (Community Earth System Model version 2–Whole Atmosphere Community Climate Model) – which has a more complete chemical treatment – and the observationally constrained, prescribed volcanic aerosol treatment in E3SMv2. Global stratospheric aerosol size distributions identify the nucleation and growth of sulfate aerosol from volcanically injected SO2 from both major and minor volcanic eruptions from 1991 to 1993. The modeled aerosol effective radius is consistently lower than satellite and in situ measurements (max differences of ∼ 30 %). Comparisons with in situ size distribution samples indicate that this simulated underestimation in both E3SMv2-SPA and CESM2-WACCM is due to overly small accumulation and coarse-mode aerosols 6–18 months post-eruption, with E3SMv2-SPA simulating ∼ 50 % of the coarse-mode geometric mean diameters of observations 11 months post-eruption. Effective radii from the models and observations are used to calculate offline scattering and absorption efficiencies to explore the implications of smaller simulated aerosol size for the Pinatubo climate impacts. Scattering efficiencies at wavelengths of peak solar irradiance (∼ 0.5 µm) are 10 %–80 % higher for daily samples in models relative to observations through 1993, suggesting higher diffuse radiation at the surface and a larger cooling effect in the models due to the smaller simulated aerosol; absorption efficiencies at the peak wavelengths of outgoing terrestrial radiation (∼ 10 µm) are 15 %–40 % lower for daily samples in models relative to observations, suggesting an underestimation in stratospheric heating in the models due to the smaller simulated aerosol. These potential biases are based on aerosol size alone and do not take into account differences in the aerosol number. The overall agreement of E3SMv2-SPA with observations and its similar performance to the well-validated CESM2-WACCM makes E3SMv2-SPA a viable alternative to simulating climate impacts from stratospheric sulfate aerosols.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic adjoint-based inversion schemes for geodynamics: reconstructing the evolution of Earth's mantle in space and time","authors":"Sia Ghelichkhan, A. Gibson, D. R. Davies, Stephan C. Kramer, David A. Ham","doi":"10.5194/gmd-17-5057-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-5057-2024","url":null,"abstract":"Abstract. Reconstructing the thermo-chemical evolution of Earth's mantle and its diverse surface manifestations is a widely recognised grand challenge for the geosciences. It requires the creation of a digital twin: a digital representation of Earth's mantle across space and time that is compatible with available observational constraints on the mantle's structure, dynamics and evolution. This has led geodynamicists to explore adjoint-based approaches that reformulate mantle convection modelling as an inverse problem, in which unknown model parameters can be optimised to fit available observational data. Whilst there has been a notable increase in the use of adjoint-based methods in geodynamics, the theoretical and practical challenges of deriving, implementing and validating adjoint systems for large-scale, non-linear, time-dependent problems, such as global mantle flow, has hindered their broader use. Here, we present the Geoscientific ADjoint Optimisation PlaTform (G-ADOPT), an advanced computational modelling framework that overcomes these challenges for coupled, non-linear, time-dependent systems by integrating three main components: (i) Firedrake, an automated system for the solution of partial differential equations using the finite-element method; (ii) Dolfin-Adjoint, which automatically generates discrete adjoint models in a form compatible with Firedrake; and (iii) the Rapid Optimisation Library, ROL, an efficient large-scale optimisation toolkit; G-ADOPT enables the application of adjoint methods across geophysical continua, showcased herein for geodynamics. Through two sets of synthetic experiments, we demonstrate the application of this framework to the initial condition problem of mantle convection, in both square and annular geometries, for both isoviscous and non-linear rheologies. We confirm the validity of the gradient computations underpinning the adjoint approach, for all cases, through second-order Taylor remainder convergence tests and subsequently demonstrate excellent recovery of the unknown initial conditions. Moreover, we show that the framework achieves theoretical computational efficiency. Taken together, this confirms the suitability of G-ADOPT for reconstructing the evolution of Earth's mantle in space and time. The framework overcomes the significant theoretical and practical challenges of generating adjoint models and will allow the community to move from idealised forward models to data-driven simulations that rigorously account for observational constraints and their uncertainties using an inverse approach.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"78 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141682768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4","authors":"Franciscus Liqui Lung, Christian Jakob, A. P. Siebesma, F. Jansson","doi":"10.5194/gmd-17-4053-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-4053-2024","url":null,"abstract":"Abstract. Open boundary conditions were developed for atmospheric large-eddy simulation (LES) models and implemented into the Dutch Atmospheric Large-Eddy Simulation model. The implementation was tested in a “Big Brother”-like setup, in which the simulation with open boundary conditions was forced by an identical control simulation with periodic boundary conditions. The results show that the open boundary implementation has minimal influence on the solution. Both the mean state and the turbulent structures are close to the control simulation, and disturbances at the in- and outflow boundaries are negligible. To emulate a setup in which the LES is coupled to a coarser model, the influence of coarse boundary input was tested by smoothing the output of the periodic control simulation both temporally and spatially before feeding it as input to the simulation with open boundary conditions. When smoothing is applied over larger spatial and longer temporal scales, disturbances start to form at the inflow boundary and an area exists where turbulence needs to develop. Adding synthetic turbulence to the smoothed input reduces the size of this area and the magnitude of the disturbances.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"7 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140962134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of Massive-Parallel Trajectory Calculations (MPTRAC) v2.6","authors":"Lars Hoffmann, Kaveh Haghighi Mood, A. Herten, M. Hrywniak, Jiri Kraus, J. Clemens, Mingzhao Liu","doi":"10.5194/gmd-17-4077-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-4077-2024","url":null,"abstract":"Abstract. Lagrangian particle dispersion models are indispensable tools for the study of atmospheric transport processes. However, Lagrangian transport simulations can become numerically expensive when large numbers of air parcels are involved. To accelerate these simulations, we made considerable efforts to port the Massive-Parallel Trajectory Calculations (MPTRAC) model to graphics processing units (GPUs). Here we discuss performance optimizations of the major bottleneck of the GPU code of MPTRAC, the advection kernel. Timeline, roofline, and memory analyses of the baseline GPU code revealed that the application is memory-bound, and performance suffers from near-random memory access patterns. By changing the data structure of the horizontal wind and vertical velocity fields of the global meteorological data driving the simulations from structure of arrays (SoAs) to array of structures (AoSs) and by introducing a sorting method for better memory alignment of the particle data, performance was greatly improved. We evaluated the performance on NVIDIA A100 GPUs of the Jülich Wizard for European Leadership Science (JUWELS) Booster module at the Jülich Supercomputing Center, Germany. For our largest test case, transport simulations with 108 particles driven by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis, we found that the runtime for the full set of physics computations was reduced by 75 %, including a reduction of 85 % for the advection kernel. In addition to demonstrating the benefits of code optimization for GPUs, we show that the runtime of central processing unit (CPU-)only simulations is also improved. For our largest test case, we found a runtime reduction of 34 % for the physics computations, including a reduction of 65 % for the advection kernel. The code optimizations discussed here bring the MPTRAC model closer to applications on upcoming exascale high-performance computing systems and will also be of interest for optimizing the performance of other models using particle methods.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"55 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140965630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)","authors":"Caroline Arnold, Shivani Sharma, Tobias Weigel, David Greenberg","doi":"10.5194/gmd-17-4017-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-4017-2024","url":null,"abstract":"Abstract. Machine learning (ML) algorithms can be used in Earth system models (ESMs) to emulate sub-grid-scale processes. Due to the statistical nature of ML algorithms and the high complexity of ESMs, these hybrid ML ESMs require careful validation. Simulation stability needs to be monitored in fully coupled simulations, and the plausibility of results needs to be evaluated in suitable experiments. We present the coupling of SuperdropNet, a machine learning model for emulating warm-rain processes in cloud microphysics, with ICON (Icosahedral Nonhydrostatic) model v2.6.5. SuperdropNet is trained on computationally expensive droplet-based simulations and can serve as an inexpensive proxy within weather prediction models. SuperdropNet emulates the collision–coalescence of rain and cloud droplets in a warm-rain scenario and replaces the collision–coalescence process in the two-moment cloud microphysics scheme. We address the technical challenge of integrating SuperdropNet, developed in Python and PyTorch, into ICON, written in Fortran, by implementing three different coupling strategies: embedded Python via the C foreign function interface (CFFI), pipes, and coupling of program components via Yet Another Coupler (YAC). We validate the emulator in the warm-bubble scenario and find that SuperdropNet runs stably within the experiment. By comparing experiment outcomes of the two-moment bulk scheme with SuperdropNet, we find that the results are physically consistent and discuss differences that are observed in several diagnostic variables. In addition, we provide a quantitative and qualitative computational benchmark for three different coupling strategies – embedded Python, coupler YAC, and pipes – and find that embedded Python is a useful software tool for validating hybrid ML ESMs.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"40 26","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140970665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A global behavioural model of human fire use and management: WHAM! v1.0","authors":"Oliver Perkins, M. Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, James D.A. Millington","doi":"10.5194/gmd-17-3993-2024","DOIUrl":"https://doi.org/10.5194/gmd-17-3993-2024","url":null,"abstract":"Abstract. Fire is an integral ecosystem process and a major natural source of vegetation disturbance globally. Yet at the same time, humans use and manage fire in diverse ways and for a huge range of purposes. Therefore, it is perhaps unsurprising that a central finding of the first Fire Model Intercomparison Project was simplistic representation of humans is a substantial shortcoming in the fire modules of dynamic global vegetation models (DGVMs). In response to this challenge, we present a novel, global geospatial model that seeks to capture the diversity of human–fire interactions. Empirically grounded with a global database of anthropogenic fire impacts, WHAM! (the Wildfire Human Agency Model) represents the underlying behavioural and land system drivers of human approaches to fire management and their impact on fire regimes. WHAM! is designed to be coupled with DGVMs (JULES-INFERNO in the current instance), such that human and biophysical drivers of fire on Earth, and their interactions, can be captured in process-based models for the first time. Initial outputs from WHAM! presented here are in line with previous evidence suggesting managed anthropogenic fire use is decreasing globally and point to land use intensification as the underlying reason for this phenomenon.\u0000","PeriodicalId":509138,"journal":{"name":"Geoscientific Model Development","volume":"102 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140968330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}