样式: 排序: IF: - GO 导出 标记为已读
-
The GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-15 Meiyun Lin, Larry W. Horowitz, Ming Zhao, Lucas Harris, Paul Ginoux, John Dunne, Sergey Malyshev, Elena Shevliakova, Hamza Ahsan, Steve Garner, Fabien Paulot, Arman Pouyaei, Steven J. Smith, Yuanyu Xie, Niki Zadeh, Linjiong Zhou
We present a variable-resolution global chemistry-climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban-to-rural chemical regimes, mesoscale convective systems, and land-surface heterogeneity. With the resolution gradually
-
Recreating Observed Convection-Generated Gravity Waves From Weather Radar Observations via a Neural Network and a Dynamical Atmospheric Model J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-16 C. G. Kruse, M. J. Alexander, M. Bramberger, A. Chattopadhyay, P. Hassanzadeh, B. Green, A. Grimsdell, L. Hoffmann
Convection-generated gravity waves (CGWs) transport momentum and energy, and this momentum is a dominant driver of global features of Earth's atmosphere's general circulation (e.g., the quasi-biennial oscillation, the pole-to-pole mesospheric circulation). As CGWs are not generally resolved by global weather and climate models, their effects on the circulation need to be parameterized. However, quality
-
Bayesian History Matching Applied to the Calibration of a Gravity Wave Parameterization J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-14 Robert C. King, Laura A. Mansfield, Aditi Sheshadri
Breaking atmospheric gravity waves (GWs) in the tropical stratosphere are essential in driving the roughly 2-year oscillation of zonal winds in this region known as the Quasi-Biennial Oscillation (QBO). As Global Climate Models (GCM)s are not typically able to directly resolve the spectrum of waves required to drive the QBO, parameterizations are necessary. Such parameterizations often require knowledge
-
Advancing Eddy Parameterizations: Dynamic Energy Backscatter and the Role of Subgrid Energy Advection and Stochastic Forcing J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-15 Ekaterina Bagaeva, Sergey Danilov, Marcel Oliver, Stephan Juricke
Viscosity in the momentum equation is needed for numerical stability, as well as to arrest the direct cascade of enstrophy at grid scales. However, a viscous momentum closure tends to over-dissipate eddy kinetic energy. To return excessively dissipated energy to the system, the viscous closure is equipped with what is called dynamic kinetic energy backscatter. The amplitude of backscatter is based
-
Changes in Stratospheric Dynamics Simulated by the EC-Earth Model From CMIP5 to CMIP6 J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-12 F. Serva, B. Christiansen, P. Davini, J. von Hardenberg, G. van den Oord, T. J. Reerink, K. Wyser, S. Yang
The simulated stratospheric dynamics have been improved compared to previous generations in many climate models taking part in the Coupled Model Intercomparison Project Phase 6 (CMIP6). This was achieved by going from low to high-top configurations, that is, increasing the atmospheric vertical resolution, raising the model lid height and including parameterization schemes, such as non-orographic gravity
-
Explicit Habit-Prediction in the Lagrangian Super-Particle Ice Microphysics Model McSnow J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-12 Jan-Niklas Welss, C. Siewert, A. Seifert
The Monte-Carlo ice microphysics model McSnow is extended by an explicit habit prediction scheme, combined with the hydrodynamic theory of Böhm. Böhm's original cylindrical shape assumption for prolates is compared against recent lab results, showing that interpolation between cylinder and prolate yields the best agreement. For constant temperature and supersaturation, the predicted mass, size, and
-
Spatial Dispersion and Statistical Description of Organized Cumulus Cloud Ensembles in Radiative Convective Equilibrium J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-12 J. Savre
Descriptions of cloud ensembles in radiative convective equilibrium (RCE) rely mostly on the assumption that clouds are randomly distributed in space, a hypothesis that obviously fails in presence of strong organization. In this work, idealized RCE simulations at horizontal grid spacings ranging from 2 km to 125 m are analyzed, displaying a transition between complete randomness at coarse resolution
-
Turbulence Closure With Small, Local Neural Networks: Forced Two-Dimensional and β-Plane Flows J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-12 Kaushik Srinivasan, Mickaël D. Chekroun, James C. McWilliams
We parameterize sub-grid scale (SGS) fluxes in sinusoidally forced two-dimensional turbulence on the β-plane at high Reynolds numbers (Re ∼25,000) using simple 2-layer convolutional neural networks (CNN) having only O(1000) parameters, two orders of magnitude smaller than recent studies employing deeper CNNs with 8–10 layers; we obtain stable, accurate, and long-term online or a posteriori solutions
-
Enhancing Urban Climate-Energy Modeling in the Community Earth System Model (CESM) Through Explicit Representation of Urban Air-Conditioning Adoption J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-12 Xinchang “Cathy” Li, Lei Zhao, Keith Oleson, Yuyu Zhou, Yue Qin, Keer Zhang, Bowen Fang
Improved representation of urban processes in Earth System Models (ESMs) is a pressing need for climate modeling and climate-driven urban energy studies. Despite recent improvements to its fully coupled Building Energy Model (BEM), the current Community Land Model Urban (CLMU) in the Community Earth System Model (CESM) lacks the infrastructure to model air-conditioning (AC) adoption explicitly. This
-
A Verification Suite of Test Cases for the Barotropic Solver of Ocean Models J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-10 Siddhartha Bishnu, Mark R. Petersen, Bryan Quaife, Joseph Schoonover
The development of any atmosphere or ocean model warrants a suite of test cases (TCs) to verify its spatial and temporal discretizations, order of accuracy, stability, reproducibility, portability, scalability, etc. In this paper, we present a suite of shallow water TCs designed to verify the barotropic solver of atmosphere and ocean models. These include the non-dispersive coastal Kelvin wave; the
-
Toward More Accurate Modeling of Canopy Radiative Transfer and Leaf Electron Transport in Land Surface Modeling J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-06 Yujie Wang, Christian Frankenberg
Modeling leaf photosynthesis is essential for quantifying the carbon, water, and energy fluxes of the terrestrial biosphere. However, due to the lack of simultaneous measurements of leaf light absorption and gas exchange, canopy radiative transfer (RT) and photosynthesis modeling often rely on simplified assumptions about light absorption and electron transport. These assumptions ignore variations
-
Inferring Tracer Diffusivity From Coherent Mesoscale Eddies J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-04-06 Wenda Zhang, Christopher L. P. Wolfe
Mixing along isopycnals plays an important role in the transport and uptake of oceanic tracers. Isopycnal mixing is commonly quantified by a tracer diffusivity. Previous studies have estimated the tracer diffusivity using the rate of dispersion of surface drifters, subsurface floats, or numerical particles advected by satellite-derived velocity fields. This study shows that the diffusivity can be more
-
Baroclinic Sea Level J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-30 James C. McWilliams, M. Jeroen Molemaker, Pierre Damien
Sea level and its horizontal gradient are an expression of oceanic volume, heat content, and currents. Large-scale currents have historically been viewed as mostly “baroclinic,” and tides as “barotropic,” respectively, in the loose sense of being strongly related to the oceanic density distribution or not. In particular, the evolution of the barotropic velocity is influenced by a horizontal pressure-gradient
-
Emulation of Cloud Microphysics in a Climate Model J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-28 W. Andre Perkins, Noah D. Brenowitz, Christopher S. Bretherton, Jacqueline M. Nugent
We present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao-Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in predicting condensate and precipitation amounts and maintains low global-average bias (≤4%) for 1 year of continuous simulation when replacing
-
Issue Information J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-29
No abstract is available for this article.
-
Irrigation Quantification Through Backscatter Data Assimilation With a Buddy Check Approach J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-22 L. Busschaert, M. Bechtold, S. Modanesi, C. Massari, L. Brocca, G. J. M. De Lannoy
Irrigation is an important component of the terrestrial water cycle, but it is often poorly accounted for in models. Recent studies have attempted to integrate satellite data and land surface models via data assimilation (DA) to (a) detect and quantify irrigation, and (b) better estimate the related land surface variables such as soil moisture, vegetation, and evapotranspiration. In this study, different
-
Interpretable Structural Model Error Discovery From Sparse Assimilation Increments Using Spectral Bias-Reduced Neural Networks: A Quasi-Geostrophic Turbulence Test Case J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-23 Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh
Earth system models suffer from various structural and parametric errors in their representation of nonlinear, multi-scale processes, leading to uncertainties in their long-term projections. The effects of many of these errors (particularly those due to fast physics) can be quantified in short-term simulations, for example, as differences between the predicted and observed states (analysis increments)
-
Rains and Showers in OTREC; Weak Temperature Gradient Modeling J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-20 D. J. Raymond, Ž. Stone, S. Sentić
Rainfall in the tropics has been shown to be produced either by isolated but intense convective systems (showers regime) or widespread but weaker systems (rains regime). We examine significant rainfall systems observed in the OTREC project (Organization of Tropical East Pacific Convection) in order to tease out the physical mechanisms differentiating these two regimes. We find that rains occur in very
-
Assessment of Global Ocean Biogeochemistry Models for Ocean Carbon Sink Estimates in RECCAP2 and Recommendations for Future Studies J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-14 Jens Terhaar, Nadine Goris, Jens D. Müller, Tim DeVries, Nicolas Gruber, Judith Hauck, Fiz F. Perez, Roland Séférian
The ocean is a major carbon sink and takes up 25%–30% of the anthropogenically emitted CO2. A state-of-the-art method to quantify this sink are global ocean biogeochemistry models (GOBMs), but their simulated CO2 uptake differs between models and is systematically lower than estimates based on statistical methods using surface ocean pCO2 and interior ocean measurements. Here, we provide an in-depth
-
A New Eulerian Iceberg Module for Climate Studies J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-17 Olga Erokhina, Uwe Mikolajewicz
Icebergs modulate the effective location of freshwater input from ice sheets into the ocean and therefore play an important role for the climate, especially during times of increased ice discharge (e.g., Heinrich events). None of the models participating in the Paleo Modeling Intercomparison Project simulations of the Last Glacial Maximum or the last deglaciation included icebergs. Here, we present
-
Hyper-Local Temperature Prediction Using Detailed Urban Climate Informatics J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-12 Peiyuan Li, Ashish Sharma
The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical-based models to fully utilize the high-resolution data under the constraints
-
A Potential Vorticity Diagnosis of Tropical Cyclone Track Forecast Errors J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-12 Tyler W. Barbero, Michael M. Bell, Jan-Huey Chen, Philip J. Klotzbach
Tropical cyclone (TC) track forecasting provides essential guidance for coastal communities. However, track forecast errors still occur, highlighting the need for continued research into error sources. Piecewise potential vorticity (PV) inversion is used systematically to quantitatively diagnose errors in track forecasts in four models during the 2017 Atlantic hurricane season. The deep layer mean
-
Improving Simulation of Gas-Particle Partitioning of Atmospheric Mercury Using CMAQ-newHg-Br v2 J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-10 L. Wu, H. Mao, Z. Ye, T. S. Dibble, A. Saiz-Lopez, Y. Zhang
Mercury (Hg) is a global pollutant whose atmospheric deposition is a major input to the terrestrial and oceanic ecosystems. Gas-particle partitioning (GPP) of gaseous oxidized mercury (GOM) redistributes speciated Hg between gas and particulate phase and can subsequently alter Hg deposition flux. Most 3-dimensional chemical transport models either neglected the Hg GPP process or parameterized it with
-
Parameterizing Mesoscale Eddy Buoyancy Transport Over Sloping Topography J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-07 Aleksi Nummelin, Pål Erik Isachsen
Most of the ocean's kinetic energy is contained within the mesoscale eddy field. Models that do not resolve these eddies tend to parameterize their impacts such that the parameterized transport of buoyancy and tracers reduces the large-scale available potential energy and spreads tracers. However, the parameterizations used in the ocean components of current generation Earth System Models rely on an
-
UQAM-TCW: A Global Hybrid Tropical Cyclone Wind Model Based Upon Statistical and Coupled Climate Models J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-07 David A. Carozza, Mathieu Boudreault, Manuel Grenier, Louis-Philippe Caron
Tropical cyclones (TCs) are among the most destructive natural hazards and yet, quantifying their financial impacts remains a significant methodological challenge. It is therefore of high societal value to synthetically simulate TC tracks and winds to assess potential impacts along with their probability distributions for example, land use planning and financial risk management. A common approach to
-
Improving Stratocumulus Cloud Amounts in a 200-m Resolution Multi-Scale Modeling Framework Through Tuning of Its Interior Physics J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-06 Liran Peng, Peter N. Blossey, Walter M. Hannah, Christopher S. Bretherton, Christopher R. Terai, Andrea M. Jenney, Michael Pritchard
High-Resolution Multi-scale Modeling Frameworks (HR)—global climate models that embed separate, convection-resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered
-
A Coordinated Sea-Ice Assimilation Scheme Jointly Using Sea-Ice Concentration and Thickness Observations With a Coupled Climate Model J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-03 X. Liu, J. Yao, S. Zhang, T. Wu, Z. Chen, Y. Fang, M. Chu, J. Yan, W. Jie
For jointly assimilating sea-ice concentration (SIC) and sea-ice thickness (SIT) observations into a global coupled climate system model consisting of sea-ice component with multiple sea-ice categories, we propose a new sea-ice analysis update scheme in an ensemble assimilation framework and compare it with some previously used schemes. Different from the conventional scheme that often assigns SIC/SIT
-
A Machine Learning Parameterization of Clouds in a Coarse-Resolution Climate Model for Unbiased Radiation J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-04 Brian Henn, Yakelyn R. Jauregui, Spencer K. Clark, Noah D. Brenowitz, Jeremy McGibbon, Oliver Watt-Meyer, Andrew G. Pauling, Christopher S. Bretherton
Coarse-grid weather and climate models rely particularly on parameterizations of cloud fields, and coarse-grained cloud fields from a fine-grid reference model are a natural target for a machine-learned parameterization. We machine-learn the coarsened-fine cloud properties as a function of coarse-grid model state in each grid cell of NOAA's FV3GFS global atmosphere model with 200 km grid spacing, trained
-
Nutrient Dynamics in a Coupled Terrestrial Biosphere and Land Model (ELM-FATES-CNP) J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-03-02 Ryan G. Knox, Charles D. Koven, William J. Riley, Anthony P. Walker, S. Joseph Wright, Jennifer A. Holm, Xinyuan Wei, Rosie A. Fisher, Qing Zhu, Jinyun Tang, Daniel M. Ricciuto, Jacquelyn K. Shuman, Xiaojuan Yang, Lara M. Kueppers, Jeffrey Q. Chambers
We present a representation of nitrogen and phosphorus cycling in the Functionally Assembled Terrestrial Ecosystem Simulator, a demographic vegetation model within the Energy Exascale Earth System land model. This representation is modular, and designed to allow testing of multiple hypothetical approaches for carbon-nutrient coupling in plants. Novel model hypotheses introduced in this work include
-
Localized General Vertical Coordinates for Quasi-Eulerian Ocean Models: The Nordic Overflows Test-Case J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-29 Diego Bruciaferri, Catherine Guiavarc'h, Helene T. Hewitt, James Harle, Mattia Almansi, Pierre Mathiot, Pedro Colombo
A generalized methodology to deploy different types of vertical coordinate system in arbitrarily defined time-invariant local areas of quasi-Eulerian numerical ocean models is presented. After detailing its characteristics, we show how the general localization method can be used to improve the representation of the Nordic Seas overflows in the UK Met Office NEMO-based eddy-permitting global ocean configuration
-
The Role of the Intraspecific Variability of Hydraulic Traits for Modeling the Plant Water Use in Different European Forest Ecosystems J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-29 C. D. Jiménez-Rodríguez, M. Sulis, S. Schymanski
The drought resilience of forest ecosystems is generally believed to depend on the dominant tree species' hydraulic traits. These traits define the maximum water transport capacity and the degree of vulnerability to hydraulic failure of a tree species. This work evaluates the effect of the intraspecific variability of hydraulic traits on the simulated tree water use in the Community Land Model (CLM
-
Data-Driven Equation Discovery of a Cloud Cover Parameterization J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-29 Arthur Grundner, Tom Beucler, Pierre Gentine, Veronika Eyring
A promising method for improving the representation of clouds in climate models, and hence climate projections, is to develop machine learning-based parameterizations using output from global storm-resolving models. While neural networks (NNs) can achieve state-of-the-art performance within their training distribution, they can make unreliable predictions outside of it. Additionally, they often require
-
Strongly Versus Weakly Coupled Data Assimilation in Coupled Systems With Various Inter-Compartment Interactions J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-28 Norihiro Miwa, Yohei Sawada
Coupled data assimilation (CDA) has been attracting researchers' interests to improve Earth system modeling. The CDA methods are classified into two: weakly coupled data assimilation (wCDA), which considers cross-compartment interaction only in a forecast phase, and strongly coupled data assimilation (sCDA), which additionally uses other compartment's information in an analysis phase. Although sCDA
-
A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus Clouds Based on Three-Dimensional Path-Tracing J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-27 Yannick Burchart, Christoph Beekmans, Roel Neggers
The complex spatial and temporal structure of cumulus clouds complicates their representation in weather and climate models. Classic meteorological instrumentation struggles to fully capture these features. Networks of multiple high-resolution hemispheric cameras are increasingly used to fill this data gap, and provide information on this missing multi-dimensional spatial information. In this study
-
Response of the Current Climate to Land-Ocean Contrasts in Parameterized Cumulus Entrainment J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-27 M. Meera, T. M. Merlis, D. J. Kirshbaum
Cumulus entrainment substantially regulates the earth's climate but remains poorly constrained in global climate models. Recent studies have shown that cumulus bulk entrainment (or dilution) is particularly sensitive to continentality, with the entrainment rate in simulated maritime cumuli nearly double that of continental cumuli. This study examines the impacts of such land–ocean entrainment contrasts
-
Assessing the Atmospheric Response to Subgrid Surface Heterogeneity in the Single-Column Community Earth System Model, Version 2 (CESM2) J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-26 Megan D. Fowler, Richard B. Neale, Tyler Waterman, David M. Lawrence, Paul A. Dirmeyer, Vincent E. Larson, Meng Huang, Jason S. Simon, John Truesdale, Nathaniel W. Chaney
Land-atmosphere interactions are central to the evolution of the atmospheric boundary layer and the subsequent formation of clouds and precipitation. Existing global climate models represent these connections with bulk approximations on coarse spatial scales, but observations suggest that small-scale variations in surface characteristics and co-located turbulent and momentum fluxes can significantly
-
Machine Learning Emulation of Subgrid-Scale Orographic Gravity Wave Drag in a General Circulation Model With Middle Atmosphere Extension J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-26 Yixiong Lu, Xin Xu, Lin Wang, Yiming Liu, Tongwen Wu, Weihua Jie, Jian Sun
Gravity wave parameterizations contribute to uncertainties in middle atmosphere modeling. To investigate the potential for using machine learning to represent atmospheric gravity waves and the impact of implementing such schemes in a general circulation model (GCM), we train a random forest (RF) emulator on outputs from an existing complex parameterization scheme for orographic gravity wave drag (GWD)
-
Issue Information J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-27
No abstract is available for this article.
-
Evaluating and Enhancing Snow Compaction Process in the Noah-MP Land Surface Model J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-24 Ronnie Abolafia-Rosenzweig, Cenlin He, Fei Chen, Michael Barlage
The accuracy of snow density in land surface model (LSM) simulations impacts the accuracy of simulated terrestrial water and energy budgets. However, there has been little research that has focused on enhancing snow compaction in operationally used LSMs. A baseline snow simulation with the widely used Noah-MP LSM systematically overestimates snow depth by 55 mm even after removing daily snow water
-
A Hybrid Data-Driven and Data Assimilation Method for Spatiotemporal Forecasting: PM2.5 Forecasting in China J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-24 Shengjuan Cai, Fangxin Fang, Xiao Tang, Jiang Zhu, Yanghua Wang
Spatiotemporal forecasting involves generating temporal forecasts for system state variables across spatial regions. Data-driven methods such as Convolutional Long Short-Term Memory (ConvLSTM) are effective in capturing both spatial and temporal correlations, but they suffer from error accumulation and accuracy loss as forecasting time increases due to the nonlinearity and uncertainty in physical processes
-
Integrating Thermodynamic and Dynamic Views on the Control of the Top-Heaviness of Convection in the Pacific ITCZ With Weak Temperature Gradient Simulations J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-24 Miguel Bernardez, Larissa Back
Understanding what controls vertical motion profile shape is fundamental to understanding tropical precipitation patterns. Two controls have been previously studied: the thermodynamic profiles of the environment and the dynamics imposed by sea surface temperature (SST) patterns. To fit these two perspectives together, we focus on two regions with distinctly top and bottom-heavy vertical motion: The
-
Retaining Short-Term Variability Reduces Mean State Biases in Wind Stress Overriding Simulations J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-21 Matthew T. Luongo, Noel G. Brizuela, Ian Eisenman, Shang-Ping Xie
Positive feedbacks in climate processes can make it difficult to identify the primary drivers of climate phenomena. Some recent global climate model (GCM) studies address this issue by controlling the wind stress felt by the surface ocean such that the atmosphere and ocean become mechanically decoupled. Most mechanical decoupling studies have chosen to override wind stress with an annual climatology
-
Impact of Momentum Perturbation on Convective Boundary Layer Turbulence J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-21 Mukesh Kumar, Alex Jonko, William Lassman, Jeffrey D. Mirocha, Branko Kosović, Tirtha Banerjee
Mesoscale-to-microscale coupling is an important tool for conducting turbulence-resolving multiscale simulations of realistic atmospheric flows, which are crucial for applications ranging from wind energy to wildfire spread studies. Different techniques are used to facilitate the development of realistic turbulence in the large-eddy simulation (LES) domain while minimizing computational cost. Here
-
Submesoscale-Permitting Physical/Biogeochemical Future Projections for the Main Hawaiian Islands J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-21 T. Friedrich, B. S. Powell, J. L. Gunnarson, G. Liu, S. F. Giardina, M. F. Stuecker, L. Hošeková, K. Feloy, C. A. Stock
Global climate models provide useful tools to forecast large-scale anthropogenic trends and the impacts on ocean physics and marine biology and chemistry. Due to coarse spatial resolution, they typically lack the ability to represent important regional processes while underestimating mesoscale variability and vertical mixing. This means they provide limited value when it comes to regional climate projections
-
Time Variability Correction of CMIP6 Climate Change Projections J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-17 Y. Shao, C. H. Bishop, S. Hobeichi, N. Nishant, G. Abramowitz, S. Sherwood
Accurate projections of climate change and associated extreme events under differing emission scenarios are linked to realistic representations of the temporal variability of the atmosphere at a variety of time scales, for example, annual, seasonal, synoptic, and daily. Here a new method is employed to explicitly quantify a model's ability to accurately represent covariance at and between differing
-
Emulator of PR-DNS: Accelerating Dynamical Fields With Neural Operators in Particle-Resolved Direct Numerical Simulation J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-18 Tao Zhang, Lingda Li, Vanessa López-Marrero, Meifeng Lin, Yangang Liu, Fan Yang, Kwangmin Yu, Mohammad Atif
Particle-resolved direct numerical simulations (PR-DNS) play an increasing role in investigating aerosol-cloud-turbulence interactions at the most fundamental level of processes. However, the high computational cost associated with high resolution simulations poses considerable challenges for large domain or long duration simulation using PR-DNS. To address these issues, here we present an emulator
-
New Features and Enhancements in Community Land Model (CLM5) Snow Albedo Modeling: Description, Sensitivity, and Evaluation J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-17 Cenlin He, Mark Flanner, David M. Lawrence, Yu Gu
We enhance the Community Land Model (CLM) snow albedo modeling by implementing several new features with more realistic and physical representations of snow-aerosol-radiation interactions. Specifically, we incorporate the following model enhancements: (a) updating ice and aerosol optical properties with more realistic and accurate data sets, (b) adding multiple dust types, (c) adding multiple surface
-
Implementation and Evaluation of Wet Bulb Globe Temperature Within Non-Urban Environments in the Community Land Model Version 5 J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-08 Jonathan R. Buzan
Global heat stress is a phenomenon that impacts the livelihood of humans worldwide. Due to climate change, heatwaves are already increasing negatively impact outdoor laborers and activities. However, calculating heat stress on a global scale is disparaged due to the interplay and treatment of temperature, humidity, and radiation. To help resolve this issue, the Wet Bulb Globe Temperature (WBGT), a
-
Neural Network Parameterization of Subgrid-Scale Physics From a Realistic Geography Global Storm-Resolving Simulation J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-04 Oliver Watt-Meyer, Noah D. Brenowitz, Spencer K. Clark, Brian Henn, Anna Kwa, Jeremy McGibbon, W. Andre Perkins, Lucas Harris, Christopher S. Bretherton
Parameterization of subgrid-scale processes is a major source of uncertainty in global atmospheric model simulations. Global storm-resolving simulations use a finer grid (less than 5 km) to reduce this uncertainty by explicitly resolving deep convection and details of orography. This study uses machine learning to replace the physical parameterizations of heating and moistening rates, but not wind
-
Issue Information J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-30
No abstract is available for this article.
-
How Can We Improve the Seamless Representation of Climatological Statistics and Weather Toward Reliable Global K-Scale Climate Simulations? J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-02-02 Daisuke Takasuka, Chihiro Kodama, Tamaki Suematsu, Tomoki Ohno, Yohei Yamada, Tatsuya Seiki, Hisashi Yashiro, Masuo Nakano, Hiroaki Miura, Akira T. Noda, Tomoe Nasuno, Tomoki Miyakawa, Ryusuke Masunaga
Toward the achievement of reliable global kilometer-scale (k-scale) climate simulations, we improve the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) by focusing on moist physical processes. A goal of the model improvement is to establish a configuration that can simulate realistic fields seamlessly from the daily-scale variability to the climatological statistics. Referring to the two representative
-
The Impact of Radiative Transfer at Reduced Spectral Resolution in Large-Eddy Simulations of Convective Clouds J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-30 M. A. Veerman, R. Pincus, E. J. Mlawer, C. C. van Heerwaarden
Many radiative transfer schemes approximate the spectral integration over ∼105 to ∼106 wavelengths with correlated k-distributions methods that typically require only 101–102 spectral integration points (g-points). The exact number of g-points is then chosen as an optimal balance between computational costs and accuracy, normally assessed in terms of a number of radiative quantities. How this radiative
-
Detecting Cold Pool Family Trees in Convection Resolving Simulations J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-27 Jannik Hoeller, Romain Fiévet, Jan O. Haerter
Recent observations and modeling increasingly reveal the key role of cold pools in organizing the convective cloud field. Several methods for detecting cold pools in simulations exist, but are usually based on buoyancy fields and fall short of reliably identifying the active gust front. The current cold pool (CP) detection and tracking algorithm (CoolDeTA), aims to identify cold pools and follow them
-
Designing a Convection-Cloud Chamber for Collision-Coalescence Using Large-Eddy Simulation With Bin Microphysics J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-27 Aaron Wang, Mikhail Ovchinnikov, Fan Yang, Silvio Schmalfuss, Raymond A. Shaw
Collisional growth of cloud droplets is an essential yet uncertain process for drizzle and precipitation formation. To improve the quantitative understanding of this key component of cloud-aerosol-turbulence interactions, observational studies of collision-coalescence in a controlled laboratory environment are needed. In an existing convection-cloud chamber (the Pi Chamber), collisional growth is limited
-
A Quantile Generalized Additive Approach for Compound Climate Extremes: Pan-Atlantic Extremes as a Case Study J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-24 Leonardo Olivetti, Gabriele Messori, Shaobo Jin
We present an application of quantile generalized additive models (QGAMs) to study spatially compounding climate extremes, namely extremes that occur (near-) simultaneously in geographically remote regions. We take as an example wintertime cold spells in North America and co-occurring wet or windy extremes in Western Europe, which we collectively term Pan-Atlantic compound extremes. QGAMS are largely
-
Improving BC Mixing State and CCN Activity Representation With Machine Learning in the Community Atmosphere Model Version 6 (CAM6) J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-23 Wenxiang Shen, Minghuai Wang, Nicole Riemer, Zhonghua Zheng, Yawen Liu, Xinyi Dong
Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four-mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non-BC species and large mass ratio of coating
-
A Four-Dimensional Variational Constrained Neural Network-Based Data Assimilation Method J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-19 Wuxin Wang, Kaijun Ren, Boheng Duan, Junxing Zhu, Xiaoyong Li, Weicheng Ni, Jingze Lu, Taikang Yuan
Advances in data assimilation (DA) methods and the increasing amount of observations have continuously improved the accuracy of initial fields in numerical weather prediction during the last decades. Meanwhile, in order to effectively utilize the rapidly increasing data, Earth scientists must further improve DA methods. Recent studies have introduced machine learning (ML) methods to assist the DA process
-
The Impact of Climate Forcing Biases and the Nitrogen Cycle on Land Carbon Balance Projections J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-16 Christian Seiler, Sian Kou-Giesbrecht, Vivek K. Arora, Joe R. Melton
Earth System Models (ESMs) project that the terrestrial carbon sink will continue to grow as atmospheric CO2 increases, but this projection is uncertain due to biases in the simulated climate and how ESMs represent ecosystem processes. In particular, the strength of the CO2-fertilization effect, which is modulated by nutrient cycles, varies substantially across models. This study evaluates land carbon
-
A Parameterization for Cloud Organization and Propagation by Evaporation-Driven Cold Pool Edges J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-16 Saulo R. Freitas, Georg A. Grell, Angel D. Chovert, Maria Assunção F. Silva Dias, Ernani de Lima Nascimento
When the negatively buoyant air in the cloud downdrafts reaches the surface, it spreads out horizontally, producing cold pools. A cold pool can trigger new convective cells. However, when combined with the ambient vertical wind shear, it can also connect and upscale them into large mesoscale convective systems (MCS). Given the broad spectrum of scales of the atmospheric phenomenon involving the interaction
-
A Machine Learning Augmented Data Assimilation Method for High-Resolution Observations J. Adv. Model. Earth Syst. (IF 6.8) Pub Date : 2024-01-15 Lucas J. Howard, Aneesh Subramanian, Ibrahim Hoteit
The accuracy of initial conditions is an important driver of the forecast skill of numerical weather prediction models. Increases in the quantity of available measurements, particularly high-resolution remote sensing observational data products from satellites, are valuable inputs for improving those initial condition estimates. However, the traditional data assimilation methods for integrating observations