Journal of Advances in Modeling Earth Systems最新文献

{"title":"Countergradient Momentum Transport in Clear Convective Atmospheric Boundary Layers","authors":"Stephan R. de Roode,&nbsp;Fredrik Jansson,&nbsp;Lydia Mak,&nbsp;Louise Nuijens","doi":"10.1029/2024MS004579","DOIUrl":"https://doi.org/10.1029/2024MS004579","url":null,"abstract":"<p>The vertical profiles of the wind speed and direction in atmospheric boundary layers are strongly controlled by turbulence. Most global weather forecast and climate models parameterize the vertical transport of horizontal momentum by turbulent eddies by means of a downgradient eddy diffusion approach, in which the same stability-dependent eddy viscosity profile is applied to both horizontal wind components. In this study we diagnose eddy viscosity profiles from large-eddy simulations of five convective boundary layers with wind shear. Each simulation was forced by the same geostrophic wind of 7.5 <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mtext>ms</mtext>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${text{ms}}^{-1}$</annotation>\u0000 </semantics></math>, but with different surface heat fluxes in the range between 0.03 and 0.18 <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mtext>mKs</mtext>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${text{mKs}}^{-1}$</annotation>\u0000 </semantics></math>. We find that the eddy viscosity profiles for the two horizontal wind components differ significantly, in particular, we diagnose negative eddy viscosities, indicating vertical turbulent transport that is counter the mean gradient. This suggests that a purely downgradient diffusion approach for turbulent momentum fluxes is inadequate. A modified solution of the Ekman spiral demonstrates that different eddy viscosity profiles for the two horizontal wind components lead to a different wind profile. To improve parameterizations that apply a downgradient diffusion approach for momentum, correction terms to allow for non-local, boundary-layer scale transport should be incorporated.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 9","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004579","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ADAF: An Artificial Intelligence Data Assimilation Framework for Weather Forecasting","authors":"Yanfei Xiang,&nbsp;Weixin Jin,&nbsp;Haiyu Dong,&nbsp;Jonathan Weyn,&nbsp;Mingliang Bai,&nbsp;Zuliang Fang,&nbsp;Pengcheng Zhao,&nbsp;Hongyu Sun,&nbsp;Kit Thambiratnam,&nbsp;Qi Zhang,&nbsp;Xiaomeng Huang","doi":"10.1029/2024MS004839","DOIUrl":"https://doi.org/10.1029/2024MS004839","url":null,"abstract":"<p>The forecasting skill of numerical weather prediction (NWP) models critically depends on the accurate initial conditions, also known as analysis, provided by data assimilation (DA). Traditional DA methods often face a trade-off between computational cost and accuracy due to complex linear algebra computations and the high dimensionality of the model, especially in non-linear systems. Moreover, processing massive data in real-time requires substantial computational resources. To address this, we introduce an artificial intelligence-based data assimilation framework (ADAF) to generate high-quality kilometer-scale analysis. This study is the pioneering work using real-world observations from varied locations and multiple sources to verify the AI method's efficacy in DA, including sparse surface weather observations and satellite imagery. We implemented ADAF for four near-surface variables in the Contiguous United States (CONUS). The results demonstrate that ADAF consistently aligns closely with actual observations, providing high-quality analysis fields capable of reconstructing extreme events, such as tropical cyclone wind fields. Sensitivity experiments reveal that ADAF can generate high-quality analysis even with low-accuracy backgrounds and extremely sparse surface observations. ADAF can assimilate multi-source observations within a three-hour window at low computational cost, taking about two seconds on an AMD MI200 graphics processing unit (GPU). ADAF-generated analysis fields improved short-term (0–6 hr) forecasts of an AI-based weather prediction model, outperforming HRRRDAS-initialized forecasts. ADAF has been shown to be efficient and effective in real-world DA, underscoring its potential role in operational weather forecasting.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 9","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004839","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Assessment of Representing Land-Ocean Heterogeneity via CAPE Relaxation Timescale in the Community Atmospheric Model 6 (CAM6)","authors":"Bidyut Bikash Goswami,&nbsp;Andrea Polesello,&nbsp;Caroline Muller","doi":"10.1029/2025MS005035","DOIUrl":"https://doi.org/10.1029/2025MS005035","url":null,"abstract":"&lt;p&gt;The time needed by deep convection to bring the atmosphere back to equilibrium is called convective adjustment timescale or simply adjustment timescale, typically denoted by &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;τ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $tau $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;. In the Community Atmospheric Model|Community Atmosphere Model (CAM), &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;τ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $tau $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; is the convective available potential energy (CAPE) relaxation timescale and is 1 hr, worldwide. Observational evidence suggests that &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;τ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $tau $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; is generally longer than 1 hr. Further, continental and oceanic convection are different in terms of the vigor of updrafts and can have different longevities. So using &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;τ&lt;/mi&gt;\u0000 &lt;mo&gt;=&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $tau =1$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; hour worldwide in CAM has two potential caveats. A longer &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;τ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $tau $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; improves the simulation of the mean climate. However, it does not address the land-ocean heterogeneity of atmospheric deep convection. We investigate the prescription of two different CAPE relaxation timescales for land (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;τ&lt;/mi&gt;\u0000 &lt;mi&gt;L&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;=&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${tau }_{L}=1$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; hr) and ocean (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;τ&lt;/mi&gt;\u0000 &lt;mi&gt;O&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;=&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${tau }_{O}=1$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; to 4 hr). It is arguably an extremely crude parameterization of boundary layer control on atmospheric convection. We contrast a suite of 5-year-long simulations with two different &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 ","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 9","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS005035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144935166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic Parameterization: The Importance of Nonlocality and Memory","authors":"Martin T. Brolly","doi":"10.1029/2025MS005223","DOIUrl":"https://doi.org/10.1029/2025MS005223","url":null,"abstract":"<p>Stochastic parameterizations deployed in models of the Earth system frequently invoke locality assumptions such as Markovianity or spatial locality. This work highlights the impact of such assumptions on predictive performance. Both in terms of short-term forecasting and the representation of long-term statistics, we find locality assumptions to be detrimental in idealized experiments. We show, however, that judicious choice of Markovian parameterization can mitigate errors due to assuming Markovianity. We propose a simple modification to standard Markovian parameterizations, which yields significant improvements in predictive skill while reducing computational cost. We further note a divergence between configurations of a parameterization which perform best in short-term prediction and those which best represent time-invariant statistics.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 9","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS005223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Path Toward Vertical Grid Options for the Community Atmosphere Model Version 7: The Impact of Vertical Resolution on the QBO and Tropical Waves","authors":"Isla R. Simpson,&nbsp;Rolando R. Garcia,&nbsp;Julio T. Bacmeister,&nbsp;Peter H. Lauritzen,&nbsp;Cecile Hannay,&nbsp;Brian Medeiros,&nbsp;Julie Caron,&nbsp;Gokhan Danabasoglu,&nbsp;Adam Herrington,&nbsp;Christiane Jablonowski,&nbsp;Dan Marsh,&nbsp;Richard B. Neale,&nbsp;Lorenzo M. Polvani,&nbsp;Jadwiga H. Richter,&nbsp;Nan Rosenbloom,&nbsp;Simone Tilmes","doi":"10.1029/2025MS004957","DOIUrl":"https://doi.org/10.1029/2025MS004957","url":null,"abstract":"<p>The Community Earth System Model currently contains two primary atmospheric configurations: the Community Atmosphere Model 6 (CAM6, 32 levels, <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>∼</mo>\u0000 </mrow>\u0000 <annotation> ${sim} $</annotation>\u0000 </semantics></math>40-km top); and the Whole Atmosphere Community Climate Model 6 (WACCM6, 70 levels, <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>∼</mo>\u0000 </mrow>\u0000 <annotation> ${sim} $</annotation>\u0000 </semantics></math>140-km top). For CAM7, a number of factors motivate a raising of the model top and enhancement of the vertical resolution and this study documents the decision making process toward this next generation vertical grid. As vertical resolution in the troposphere/lower stratosphere is increased, the role of the resolved waves in driving the Quasi-Biennial Oscillation (QBO) is enhanced, becoming more similar in magnitude to ERA5 reanalysis. This can be traced to improved equatorial Kelvin waves and their vertical momentum fluxes. It is further shown that a model lid at <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>∼</mo>\u0000 </mrow>\u0000 <annotation> ${sim} $</annotation>\u0000 </semantics></math>80-km does not have detrimental impacts on the representation of the QBO compared to a 140-km top. Based on this analysis, the vertical grid for CAM7 will have an <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>∼</mo>\u0000 </mrow>\u0000 <annotation> ${sim} $</annotation>\u0000 </semantics></math>80-km top with 93 levels, 500-m grid spacing in the troposphere and lower stratosphere, and 10 additional levels in the boundary layer compared to CAM6. A 58-level/<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>∼</mo>\u0000 </mrow>\u0000 <annotation> ${sim} $</annotation>\u0000 </semantics></math>40-km low-top option will also be available. We further introduce new coupled simulations using CAM6 but with CAM7's vertical grid above the boundary layer and use these to demonstrate that basic features of the stratospheric circulation are similar to WACCM6, despite the lower model top. These simulations further show that despite the higher fidelity of the QBO, the observed connection between the QBO and the Madden-Julian Oscillation is absent.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 9","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS004957","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144915226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Impact of Internal Variability on Benchmarking Deep Learning Climate Emulators","authors":"Björn Lütjens,&nbsp;Raffaele Ferrari,&nbsp;Duncan Watson-Parris,&nbsp;Noelle E. Selin","doi":"10.1029/2024MS004619","DOIUrl":"https://doi.org/10.1029/2024MS004619","url":null,"abstract":"<p>Full-complexity Earth system models (ESMs) are computationally very expensive, limiting their use in exploring the climate outcomes of multiple emission pathways. More efficient emulators that approximate ESMs can directly map emissions onto climate outcomes, and benchmarks are being used to evaluate their accuracy on standardized tasks and data sets. We investigate a popular benchmark in data-driven climate emulation, ClimateBench, on which deep learning-based emulators are currently achieving the best performance. We compare these deep learning emulators with a linear regression-based emulator, akin to pattern scaling, and show that it outperforms the incumbent 100M-parameter deep learning foundation model, ClimaX, on 3 out of 4 regionally resolved climate variables, notably surface temperature and precipitation. While emulating surface temperature is expected to be predominantly linear, this result is surprising for emulating precipitation. Precipitation is a much more noisy variable, and we show that deep learning emulators can overfit to internal variability noise at low frequencies, degrading their performance in comparison to a linear emulator. We address the issue of overfitting by increasing the number of climate simulations per emission pathway (from 3 to 50) and updating the benchmark targets with the respective ensemble averages from the MPI-ESM1.2-LR model. Using the new targets, we show that linear pattern scaling continues to be more accurate on temperature, but can be outperformed by a deep learning-based technique for emulating precipitation. We publish our code and data at https://github.com/blutjens/climate-emulator.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 8","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004619","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144897778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Particle-in-Cell Wave Model for Efficient Sea-State Estimates in Earth System Models—PiCLES","authors":"Momme Hell,&nbsp;Baylor Fox-Kemper,&nbsp;Bertrand Chapron","doi":"10.1029/2025MS005221","DOIUrl":"https://doi.org/10.1029/2025MS005221","url":null,"abstract":"<p>Ocean surface waves have been demonstrated to be an important component of coupled Earth System Models (ESMs), influencing atmosphere-ocean momentum transfer; ice floe breakage; CFC, carbon, and energy uptake; and mixed-layer depth. Modest errors in sea state properties do not strongly affect the impacts of these parameterizations. The modest data and accuracy needed contrast sharply with the high computational costs of spectral wave models in next-generation ESMs, which can very easily exceed the cost of the ocean model component. We establish an alternative, cost-efficient prototype wave modeling framework for air-sea and ice-ocean interactions, enabling the routine use of sea state-dependent air-sea coupling in future ESMs. In contrast to spectral models, the Particle-in-Cell for Efficient Swell (PiCLES) wave model is customized for coupled atmosphere-ocean-sea ice modeling. Combining Lagrangian wave growth solutions with the Particle-In-Cell method leads to a model that periodically projects wave information onto any convenient grid and scales in an embarrassingly parallel manner. The set of equations solves for the growth and propagation of a parametric wave spectrum's peak wavenumber vector and total wave energy, which reduces the state vector size by a factor of 50–200 compared to the standard resolution of spectral models. PiCLES's current computational costs in idealized wind-sea simulations are about one order of magnitude faster than established wave models used in ESMs, with sufficient accuracy in bulk sea-state variables relevant for coupling. PiCLES is compared to WAVEWATCH III in efficiency and accuracy in idealized cases.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 8","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS005221","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144905557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parameter Optimization for Global Soil Carbon Simulations: Not a Simple Problem","authors":"Charles B. Gauthier,&nbsp;Joe R. Melton,&nbsp;Gesa Meyer,&nbsp;S. N. Raj Deepak,&nbsp;Oliver Sonnentag","doi":"10.1029/2024MS004577","DOIUrl":"https://doi.org/10.1029/2024MS004577","url":null,"abstract":"<p>Accurate simulation of soil organic carbon (SOC) dynamics by terrestrial biosphere models is hampered by poorly constrained parameters and parameter equifinality, amongst other issues. To address this, we use Bayesian optimization to constrain the 16 SOC-related parameters in the Canadian Land Surface Scheme Including biogeochemical Cycles (CLASSIC). We employed a global sensitivity analysis (Sobol’) to develop four parameter sets based upon different sensitivity criteria. We then optimized each set against observed SOC (World Soil Information Service; WoSIS) and soil respiration (Soil Respiration Database; SRDB). Using two different loss functions; one focused on reproducing the observational mean value, and the other explicitly accounting for an estimated observational uncertainty. The best optimized parameter sets for each loss function had an average relative difference of 61%. Thus, the choice of loss function impacts what parameter values are deemed optimal and should be considered carefully. The final set of selected optimal parameters saw a 12% improvement against WoSIS and SRDB, had global SOC totals in line with literature estimates, and better simulated high-latitude SOC stocks evaluated against the Northern Circumpolar Soil Carbon Database (RMSD: 16.39 vs. 17.61; bias: −5.57 vs. −10.78 kg C <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mrow>\u0000 <msup>\u0000 <mi>m</mi>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 <mn>2</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 </mrow>\u0000 <annotation> ${mathrm{m}}^{-2}$</annotation>\u0000 </semantics></math>) compared to the default CLASSIC parameters. However, some parameters were not well constrained, in particular those of needle-leaf deciduous trees that dominate the Siberian boreal forests, a region relatively poorly observed in WoSIS and SRDB. Future work should apply further constraints on the optimization framework and address observational gaps.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 8","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004577","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144869245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diapycnal Mixing and Tracer Dispersion in a Terrain-Following Coordinate Model","authors":"Noémie Schifano,&nbsp;Clément Vic,&nbsp;Jonathan Gula,&nbsp;M. Jeroen Molemaker,&nbsp;James C. McWilliams","doi":"10.1029/2024MS004768","DOIUrl":"https://doi.org/10.1029/2024MS004768","url":null,"abstract":"<p>Diapycnal mixing, driven by small-scale turbulence, is crucial for the global ocean circulation, particularly for the upwelling of deep water masses. However, accurately representing diapycnal mixing in ocean models is challenging because numerical errors can introduce significant numerical mixing. In this study, we explore the diapycnal mixing in a high-resolution regional model of the North Atlantic subpolar gyre using the Coastal and Regional Ocean Community model (CROCO). CROCO uses terrain-following vertical coordinates that do not align with isopycnals. As such, tracer advection schemes produce spurious diapycnal mixing, which can nonetheless be reduced using rotated advection schemes. We focus on how different advection schemes and vertical resolutions affect numerical diapycnal mixing. Our approach includes online diagnostics of buoyancy fluxes and tracer release experiments to quantify the effective mixing, which combines parameterized and numerical diapycnal mixing. Our main results show that in flat-bottom regions, the effective diapycnal mixing is close to the parameterized mixing. However, in regions with steep topography, numerical mixing can locally significantly exceed parameterized mixing due to grid slope constraints imposed by the rotated mixing operator. While topography smoothing can mitigate this excessive mixing, it can also alter flow-topography interactions. In addition, while a higher vertical resolution reduces the numerical mixing induced by the vertical tracer advection, it can also increase numerical mixing in steep regions by introducing a stronger constraint on the grid slope. These results underscore that diapycnal mixing representation in a numerical model requires balancing high resolution and topographic smoothing with the control of numerical errors.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 8","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004768","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144861868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Global Representative Hillslope Data Set for Use in Earth System Models","authors":"Sean C. Swenson,&nbsp;David M. Lawrence","doi":"10.1029/2024MS004410","DOIUrl":"https://doi.org/10.1029/2024MS004410","url":null,"abstract":"<p>The development of a global data set consisting of a distributed set of geomorphic parameters suitable for use in a representative hillslope parameterization within an Earth System model (ESM) is described. An element of a representative hillslope is defined by six geomorphic properties: height above the stream channel, distance to the stream channel, width, slope, aspect, and area. The methodology employs spectral analysis to identify an appropriate spatial scale at which to resolve the stream network and catchments in an ESM gridcell. This objective method is applied to an ESM grid using a global high-resolution digital elevation model (DEM) as input. The resulting spatially varying length scales then determine the stream order used to delineate catchments from the DEM. The geomorphic parameters describing the representative hillslopes are obtained by discretizing the catchments into elements based on elevation and aspect, and then averaging the geomorphic properties within each element, resulting in a statistical representation of the hillslopes within the domain. The method is applied to a DEM having a spatial resolution of 3 arcseconds (about 90 <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>m</mi>\u0000 </mrow>\u0000 <annotation> $mathrm{m}$</annotation>\u0000 </semantics></math> at the equator) on a grid having approximately <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>1</mn>\u0000 <mo>°</mo>\u0000 </mrow>\u0000 <annotation> $1{}^{circ}$</annotation>\u0000 </semantics></math> spatial resolution.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 8","pages":""},"PeriodicalIF":4.6,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144833153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}