Journal of Advances in Modeling Earth Systems最新文献

{"title":"Diffusion-Based Reconstruction of Western North Pacific Surface Winds From CYGNSS for Tropical Cyclone Analysis","authors":"Xinhai Han,&nbsp;Xiaohui Li,&nbsp;Jingsong Yang,&nbsp;Zeyi Niu,&nbsp;Guoqi Han,&nbsp;Naifeng Fu,&nbsp;Jiuke Wang,&nbsp;Wei Tao,&nbsp;Lotfi Aouf,&nbsp;Dake Chen","doi":"10.1029/2026MS005911","DOIUrl":"https://doi.org/10.1029/2026MS005911","url":null,"abstract":"<p>Sea surface wind retrieval under extreme weather conditions is constrained by the sparse and irregular spatiotemporal sampling of Global Navigation Satellite System Reflectometry (GNSS-R). This study presents a probabilistic wind field reconstruction framework for the Western North Pacific using Score-Based Data Assimilation (SDA). A diffusion model trained on historical wind analyses serves as a statistical prior, and sparse Cyclone Global Navigation Satellite System (CYGNSS) observations constrain the reverse diffusion process to draw samples from an approximate posterior. Track-segment withholding (80% input, 20% verification), additionally excluding verification cells containing input observations, yields a case-averaged Root Mean Square Error (RMSE) of 1.637 m/s. In Tropical Cyclone (TC) scenarios, for cases with analysis-box CYGNSS coverage above 10%, the reconstruction reduces the inner-core intensity bias of both gridded references (the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis by 78.4%, and the Cross-Calibrated Multi-Platform analysis—its own training prior—by 70.1%) with lower RMSE than the reanalysis but slightly higher RMSE than the multi-platform analysis. Furthermore, the framework provides informative pixel-level uncertainty estimates that are under-dispersed relative to withheld CYGNSS observations, with the spread correlating with the reconstruction error. These results indicate improved mean intensity estimates in the higher-coverage subset, with performance still dependent on inner-core sampling.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005911","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205627","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":"Kilometer-Scale Modeling of Atmospheric River Precipitation Using the Regionally Refined SCREAM Model","authors":"Sourav Taraphdar,&nbsp;L. Ruby Leung,&nbsp;Xiaodong Chen,&nbsp;Ning Sun","doi":"10.1029/2026MS005968","DOIUrl":"https://doi.org/10.1029/2026MS005968","url":null,"abstract":"<p>This study evaluates kilometer-scale simulations of atmospheric river (AR) precipitation using the Simple Cloud Resolving E3SM Atmosphere Model (SCREAM). Four AR events that cause flooding and impact the Puget Sound basin in the U.S. Pacific Northwest (PNW) are simulated using SCREAM with a regional refined mesh (RRM) at 3.125 km over the PNW within a global domain at 25 km resolution. Two SCREAM configurations are evaluated that differ only in their representation of ice-cloud fraction: the original version (SCREAMv0) uses a relative humidity-based formulation, whereas the revised version (SCREAMv0+) uses the cell-averaged ice mass mixing ratio. For all AR cases, SCREAMv0+ simulates stronger lower-level wind, more precipitable water, and increased moisture flux than SCREAMv0, aligning more closely with ERA5 reanalysis. With realistic large-scale circulation, SCREAMv0+ increases precipitation over the Cascades and decreases it over the Coastal Range, leading to a closer resemblance of the spatial rainfall distribution according to multiple observational products. SCREAMv0+ shows a deeper layer of cloud ice and mixed-phase hydrometeors than the SCREAMv0 simulations. It is likely that an altered latent heat release, caused by changes in the representation of ice- and mixed-phase mass ratios, causes a large-scale circulation response that eventually affects the precipitation distribution. Sensitivity experiments confirm these changes are mainly driven by how ice-cloud fraction interacts with microphysics. Results show that altering cloud macrophysics can significantly change the connection between microphysics, diabatic heating, and large-scale circulation in kilometer-scale models. These findings emphasize the importance of cloud mixed-phase processes in AR precipitation and demonstrate how regionally refined models like SCREAM can well simulate cold-season extreme rainfall in complex terrain.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005968","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205969","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":"Impact of Spatially Continuous Urban Surface Properties on Summertime and Heatwave Simulations: A Multi-City Analysis","authors":"Timothy Jiang,&nbsp;TC Chakraborty,&nbsp;Yifan Cheng,&nbsp;Rohit Mukherjee,&nbsp;Lei Zhao,&nbsp;Alberto Martilli","doi":"10.1029/2026MS005775","DOIUrl":"https://doi.org/10.1029/2026MS005775","url":null,"abstract":"<p>Urban areas are unique in form, function, and fabric, and representing them in process-based models requires, among other things, prescribing facet-level morphological and radiative properties, which vary widely. Most urban canopy models (UCMs) prescribe these by density class or local climate zone (LCZ), assigning identical values across broad regions or worldwide. Global km-scale, facet-level urban property data sets have recently emerged, but are seldom applied in regional modeling. Here, we incorporate one such data set, U-Surf, into the Weather Research and Forecasting (WRF) model, modifying it for WRF's multi-layer UCM and releasing it as U-Surf-WRF. Considering 13 US cities, U-Surf-WRF parameters vary more between LCZs than default WRF parameters, with consistently lower impervious fraction. To determine the effects of using U-Surf-WRF, we conduct high-resolution WRF summertime seasonal and recent heatwave simulations for these 13 cities using default and U-Surf-WRF parameters. Either prescribed by LCZ or for each grid point, using U-Surf-WRF usually yields more accurate surface temperatures. It generally decreases modeled urban air temperature and increases modeled urban humidity, yielding lower heat and dry islands. Decomposing the impact of each U-Surf-WRF variable, we find that while albedo can impact daytime simulations, especially for air temperature, morphology and impervious fraction are most relevant, especially for surface temperature. This study demonstrates the impact of city-specific, facet-level urban properties in urban-resolving numerical weather simulations, with remaining gaps against observations demonstrating other challenges in representing cities in process-based models. Conversely, in WRF simulations with poorly constrained parameters, we suggest caution interpreting the magnitude and spatial distribution of urban signals.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005775","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205704","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 Catchment-Based Global Model of River Discharge and Flow Velocity for Earth System Models","authors":"Yujin Zeng,&nbsp;Randal D. Koster,&nbsp;Rolf H. Reichle,&nbsp;Biljana Orescanin,&nbsp;Jana Kolassa,&nbsp;P. C. D. Milly","doi":"10.1029/2025MS005234","DOIUrl":"https://doi.org/10.1029/2025MS005234","url":null,"abstract":"<p>The representation of river flows in Earth System Models (ESMs) is crucial for understanding water resources availability, contaminant transport, and the impacts of climate change on river systems. In this study, we introduce a global runoff routing model founded on hydraulic geometry principles and hydrologic catchments, specifically designed for integration with ESMs. To simulate river dynamics, the model capitalizes on (a) the river network topology defined by the Pfafstetter coding system, (b) hydraulic geometry principles that connect river discharge to flow velocity, and (c) calibration using more than 2.7 million intermittent field measurements of flow velocity in the contiguous US (CONUS). The model is shown to produce reasonably accurate natural daily river discharge over CONUS except within some arid regions and the region adjacent to the Great Lakes, where streamflow is strongly impacted by reservoir management and by the natural buffering behavior of the large lakes themselves. The average correlation coefficient for discharge (vs. in situ measurements) is 0.80 for tested major rivers over CONUS except in arid regions and the Great Lakes. A unique feature of the model is its ability to simulate flow velocity with realistic magnitudes, standing it in good stead for tracer tracking and water management applications.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS005234","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205381","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 Online Moisture Tagging Framework for Detrainment of Convective Hydrometeors and Associated Precipitation in Convection-Permitting Models","authors":"Guoqing Dai,&nbsp;Ben Yang,&nbsp;Xin Xu,&nbsp;Yuanzhe Zhang,&nbsp;Lianglu Qu,&nbsp;Yuncheng Yang,&nbsp;Yun Qian,&nbsp;Yaocun Zhang,&nbsp;Danqing Huang","doi":"10.1029/2026MS005900","DOIUrl":"https://doi.org/10.1029/2026MS005900","url":null,"abstract":"<p>Convective detrainment is an important process in mesoscale convective systems (MCSs) that strongly influence adjacent stratiform clouds and precipitation. However, it remains difficult to quantify convective detrainment in numerical models. In this study, we develop an online convection identification and water vapor tracer (WVT) framework based on the Eulerian WVTs coupled with Weather Research and Forecasting convection-permitting model. Convection is identified using radar reflectivity, and two types of tracers are introduced to track water species and precipitation within convective regions and those detrained from them, which can be distinguished from those newly generated in the stratiform areas. The framework is applied to both an idealized case and a real case. In the idealized simulation, the framework captures the convective detrainment and its associated precipitation during the lifecycle of convective systems featured by rapid evolution in location and structure. In the real case, the framework demonstrates distinct temporal variations in the intensity and area coverage of stratiform precipitation produced by convective detrainment. Both the ice- and liquid-phase detrainments decrease dramatically at the moment when convective precipitation starts to increase, suggesting intensified conversion from cloud to precipitating hydrometeors. After that, the conversion efficiency weakens, which is favorable for the formation of stratiform clouds and precipitation. Overall, this framework provides a useful tool for quantifying the characteristics and impacts of convective detrainment and for evaluating convective parameterization schemes.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005900","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205545","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":"Convectively Coupled Equatorial Waves in a Global Storm-Resolving Model","authors":"Sebastián Ortega,&nbsp;Hans Segura,&nbsp;Víctor C. Mayta,&nbsp;Romain Fiévet,&nbsp;Angel Peinado,&nbsp;Junhong Lee,&nbsp;Marco A. Giorgetta,&nbsp;Bjorn Stevens","doi":"10.1029/2026MS005799","DOIUrl":"https://doi.org/10.1029/2026MS005799","url":null,"abstract":"<p>We show how reducing the fall speeds of rain and ice leads to reduced biases of Convectively Coupled Equatorial Waves (CCEWs) in convection-resolving configurations of the Icosahedral Non-hydrostatic Model (ICON). In particular, reducing the fall speeds of rain and ice leads to stronger activity over the wavenumbers and frequencies associated with convectively coupled Kelvin waves, inertio-gravity waves, mixed Rossby-gravity waves, equatorial Rossby waves, and the Madden-Julian oscillation, and to weaker activity of tropical depressions. The changes in CCEW activity are mediated by changes in the frequency of mesoscale convection profiles. Reducing the fall speeds increases the frequency of bottom-heavy and top-heavy mesoscale convection profiles and decreases the frequency of mid-heavy mesoscale convection profiles. In turn, changes to the mesoscale convective profiles are reflected in the ability of the model to develop the tilt and top-heaviness of CCEWs. Reductions in the fall speeds also increase precipitation over the warm pool region, possibly allowing for a stronger equatorial forcing of convectively coupled Kelvin waves. Our findings suggest that the representation of CCEWs within ICON agrees with their observed multiscale structure.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005799","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146326","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":"Reduced Order Modeling for Tsunami Forecasting With Bayesian Hierarchical Pooling","authors":"Shane X. Coffing,&nbsp;John Tipton,&nbsp;Arvind T. Mohan,&nbsp;Darren Engwirda","doi":"10.1029/2025MS005663","DOIUrl":"https://doi.org/10.1029/2025MS005663","url":null,"abstract":"<p>Reduced-order models (ROMs) can represent spatiotemporal processes in significantly fewer dimensions and can often be solved many orders of magnitude faster than their governing partial differential equations (PDEs). For example, proper orthogonal decomposition yields a ROM in which the state is represented as a low-dimensional linear combination of fixed spatial modes and time-dependent coefficients, but this representation remains constrained by the process used to construct the basis. In this work, we explore a new type of ROM that is not restricted to a single fixed coefficient trajectory. Specifically, we consider a corrected Galerkin-projection ROM, formulated as an initial value problem that encodes the physics of the governing PDEs and is calibrated through operator corrections to more accurately reproduce the coefficient dynamics. By combining this corrected reduced model with a Bayesian hierarchical pooling framework over the initial reduced coefficients, we obtain new, statistically interpretable and physically grounded coefficient trajectories that generalize across related scenarios. When recombined with the spatial modes, these trajectories define a complete probabilistic physics surrogate, called a randPROM, for generating simulations that are distributionally consistent with a neighborhood of initial conditions near those used to construct the ROM. We apply the randPROM framework to tsunami modeling, a setting involving unpredictable, catastrophic, and strongly nonlinear dynamics, using both a synthetic case study near Fiji and the real-world 2011 Tohoku tsunami. We demonstrate that randPROMs can substantially reduce the number of full simulations required while providing statistically calibrated and physically defensible predictions of tsunami wave arrival times and heights.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS005663","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145854","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":"Two Localization Strategies for Sequential MCMC Data Assimilation With Applications to Nonlinear Non-Gaussian Geophysical Models","authors":"Hamza Ruzayqat,&nbsp;Hristo G. Chipilski,&nbsp;Omar Knio","doi":"10.1029/2026MS005908","DOIUrl":"https://doi.org/10.1029/2026MS005908","url":null,"abstract":"<p>We present a localized data assimilation (DA) scheme based on sequential Markov Chain Monte Carlo (SMCMC) (Ruzayqat et al., 2024, https://doi.org/10.1002/qj.4710), a provably convergent method for filtering high-dimensional, nonlinear, and potentially non-Gaussian state-space models (SSMs). Unlike particle filters, which are exact for such models, SMCMC does not assign weights to samples, avoiding weight degeneracy in small-ensemble regimes. We design two localization approaches within the SMCMC framework that exploit observation sparsity to reduce effective degrees of freedom. The first variant collects observed blocks into a single reduced domain and runs parallel MCMC chains over this combined region. The second further reduces per-chain state dimension by decomposing the observed region into independent blocks with compact halos, applying Gaspari–Cohn tapering to down-weight distant observations. When the observation model is linear Gaussian, the approximate filtering density reduces to a Gaussian mixture from which independent samples can be drawn exactly; otherwise, we employ an MCMC kernel. We test on high-dimensional <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <mi>d</mi>\u0000 <mo>∼</mo>\u0000 <mn>1</mn>\u0000 <msup>\u0000 <mn>0</mn>\u0000 <mn>4</mn>\u0000 </msup>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 <msup>\u0000 <mn>0</mn>\u0000 <mn>5</mn>\u0000 </msup>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow>\u0000 <annotation> $left(dsim 1{0}^{4}-1{0}^{5}right)$</annotation>\u0000 </semantics></math> SSMs, including a linear Gaussian model and a nonlinear multilayer shallow water equation with linear and nonlinear observation operators. We consider Gaussian and Student-<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>t</mi>\u0000 </mrow>\u0000 <annotation> $t$</annotation>\u0000 </semantics></math> observation noise, showing that LSMCMC handles heavy-tailed errors that cause ensemble Kalman methods to diverge. Observations include synthetic and real SWOT (NASA) and ocean drifter (NOAA) data. We compare the two variants against each other and the local ensemble transform Kalman filter.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005908","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145855","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":"Evaluation of Timing and Amplitude Biases in the Controls of Simulated Southern Ocean pCO2","authors":"Seth M. Bushinsky,&nbsp;Lionel A. Arteaga,&nbsp;Andrea J. Fassbender,&nbsp;Judith Hauck,&nbsp;Matthew R. Mazloff,&nbsp;Ivana Cerovečki,&nbsp;Peter Landschützer,&nbsp;Christopher Danek,&nbsp;Anastasia Romanou,&nbsp;Paul Lerner,&nbsp;Alison R. Gray,&nbsp;Sarah Schlunegger","doi":"10.1029/2026MS005774","DOIUrl":"https://doi.org/10.1029/2026MS005774","url":null,"abstract":"&lt;p&gt;The Southern Ocean is a major sink for atmospheric carbon dioxide and critical to the current and future carbon cycle. This net annual &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; flux reflects the balance of strong seasonal variability characterized by opposing periods of winter outgassing and summer uptake. Using a simple framework, we evaluate how model biases in both the amplitude and timing of dissolved inorganic carbon (DIC) and total alkalinity (TA) and the amplitude of sea surface temperature (SST) impact simulated &lt;i&gt;p&lt;/i&gt;&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;. We examine seasonal &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; fluxes and &lt;i&gt;p&lt;/i&gt;&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; south of the Subantarctic Front in 42 Earth System Model and three state estimate simulations. Only 11 of the 45 simulations have a seasonal &lt;i&gt;p&lt;/i&gt;&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; cycle correlation of &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;≥&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${ge} $&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;0.7 to observed &lt;i&gt;p&lt;/i&gt;&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;CO&lt;/mtext&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{CO}}_{2}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, while 25 have a correlation of &lt;0. Four of the well-correlated models accurately re","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005774","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145856","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":"Assessing JULES Across Bioclimatic Domains Through a Pan-African Flux Tower Evaluation: Insights Into Controls on Gross Primary Productivity, Ecosystem Respiration, and Evapotranspiration Biases","authors":"Enimhien F. Akhabue,&nbsp;Andrew M. Cunliffe,&nbsp;Karina Bett-Williams,&nbsp;Anna B. Harper,&nbsp;Songyan Zhu,&nbsp;Petra Holden,&nbsp;Jonas Ardö,&nbsp;Mika Aurela,&nbsp;Jerome Demarty,&nbsp;Frederic C. Do,&nbsp;Jordi Etchanchu,&nbsp;Mangaliso Gondwe,&nbsp;Carole Helfter,&nbsp;Laurent Kergoat,&nbsp;Giacomo Nicolini,&nbsp;Yann Nouvellon,&nbsp;Maria Carolina Duran Rojas,&nbsp;Olivier Roupsard,&nbsp;Torbern Tagesson,&nbsp;Ville Vakkari,&nbsp;Pieter VanZyl,&nbsp;Aleksander Wieckowski","doi":"10.1029/2026MS005888","DOIUrl":"https://doi.org/10.1029/2026MS005888","url":null,"abstract":"<p>Land surface models are fundamental for simulating coupled carbon, water and energy exchanges in Earth system models, yet their performance remains poorly constrained across Africa's diverse hydroclimatic gradients. We evaluate the Joint UK Land Environment Simulator (JULES) using eddy covariance observations from 16 flux towers spanning major African ecosystem types. Model skill is assessed for gross primary productivity (GPP), ecosystem respiration (Reco), and evapotranspiration, and we examine how model bias and error vary along gradients of mean annual temperature, aridity index, and precipitation anomalies. JULES reproduced broad seasonal dynamics of carbon and water fluxes across several ecosystems but showed systematic limitations in simulating Reco and interannual variability of GPP. Model performance differed among ecosystem types, with wetlands exhibiting large model-observation mismatches and cropland sites showing GPP overestimation linked to excessive simulated leaf area index. To isolate environmental controls on performance, we applied linear mixed-effects modeling to partition site-level variability from climate-driven effects. Aridity and precipitation anomalies emerged as dominant predictors of model bias and error, with wetter and anomalously humid conditions associated with larger deviations from observations, indicating limitations in representing soil hydrology and vegetation water stress processes. By integrating an expanded African flux tower network, this study provides a comprehensive regional evaluation of JULES. The results identify hydroclimatic regimes where model development should be prioritized and emphasize the importance of strengthening benchmarking across underrepresented African ecosystems to improve model transferability and support reliable climate and land management decision support under environmental change.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"18 10","pages":""},"PeriodicalIF":4.6,"publicationDate":"2026-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026MS005888","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145717","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}