Journal of Advances in Modeling Earth Systems最新文献

{"title":"Incorporating the Acclimation of Photosynthesis and Leaf Respiration in the Noah-MP Land Surface Model: Model Development and Evaluation","authors":"Yanghang Ren,&nbsp;Han Wang,&nbsp;Sandy P. Harrison,&nbsp;I. Colin Prentice,&nbsp;Giulia Mengoli,&nbsp;Long Zhao,&nbsp;Peter B. Reich,&nbsp;Kun Yang","doi":"10.1029/2024MS004599","DOIUrl":"https://doi.org/10.1029/2024MS004599","url":null,"abstract":"<p>Realistic simulation of leaf photosynthetic and respiratory processes is needed for accurate prediction of the global carbon cycle. These two processes systematically acclimate to long-term environmental changes by adjusting photosynthetic and respiratory traits (e.g., the maximum photosynthetic capacity at 25°C (<i>V</i>_cmax,25) and the leaf respiration rate at 25°C (<i>R</i>₂₅)) following increasingly well-understood principles. While some land surface models (LSMs) now account for thermal acclimation, they do so by assigning empirical parameterizations for individual plant functional types (PFTs). Here, we have implemented an Eco-Evolutionary Optimality (EEO)-based scheme to represent the universal acclimation of photosynthesis and leaf respiration to multiple environmental effects, and that therefore requires no PFT-specific parameterizations, in a standard version of the widely used LSM, Noah MP. We evaluated model performance with plant trait data from a 5-year experiment and extensive global field measurements, and carbon flux measurements from FLUXNET2015. We show that observed <i>R</i>₂₅ and <i>V</i>_cmax,25 vary substantially both temporally and spatially within the same PFT (<i>C.V.</i> &gt;20%). Our EEO-based scheme captures 62% of the temporal and 70% of the spatial variations in <i>V</i>_cmax,25 (73% and 54% of the variations in <i>R</i>₂₅). The standard scheme underestimates gross primary production by 10% versus 2% for the EEO-based scheme and generates a larger spread in <i>r</i> (correlation coefficient) across flux sites (0.79 ± 0.16 vs. 0.84 ± 0.1, mean ± S.D.). The standard scheme greatly overestimates canopy respiration (bias: ∼200% vs. 8% for the EEO scheme), resulting in less CO₂ uptake by terrestrial ecosystems. Our approach thus simulates climate-carbon coupling more realistically, with fewer parameters.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143565199","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":"Large Eddy Simulation of Shallow Cumulus Clouds in the Southern Great Plains With an Interactive Land Surface Model","authors":"Jake J. Gristey,&nbsp;Graham Feingold,&nbsp;Wayne M. Angevine,&nbsp;Yao-Sheng Chen","doi":"10.1029/2024MS004658","DOIUrl":"https://doi.org/10.1029/2024MS004658","url":null,"abstract":"<p>Shallow cumulus clouds are ubiquitous over continental land masses in summertime. They impart complex patterns of solar heating on the surface below. These patterns are dominated by cloud shadows, which drive spatial variability in the surface latent and sensible heat fluxes via the surface energy balance. This, in-turn, generates spatial variability in buoyancy that has been suggested to modulate cloud evolution. Despite the coupling between the land surface and clouds, it is commonplace to model continental shallow cumulus clouds with large eddy simulation (LES) using spatially-uniform prescribed surface heat fluxes. Here we present new LES of shallow cumulus clouds in the Southern Great Plains that are run with an interactive land surface model (LSM). The LSM is coupled to a 1D radiation scheme and therefore provides dynamic, heterogeneous surface heat fluxes that correspond to the evolving 1D surface solar heating pattern. We use this new simulation configuration to test whether spatially-variable fluxes impact cloud field evolution, finding limited impact for a typical case study. Furthermore, we find no evidence of systematic differences in radiatively-relevant cloud field properties when applying spatially-variable fluxes across 14 simulated cases. We therefore conclude that the heterogeneity of surface fluxes due to 1D cloud shading is insufficient to influence cloud evolution. This finding agrees with previously documented length scales of static surface heterogeneities required to develop secondary circulations that can influence cloud evolution, and provides a renewed focus for mechanistic understanding of recently reported large responses in cloud evolution when invoking 3D radiation.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004658","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143564618","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":"Modeling the Effect of Trees on Energy Demand for Indoor Cooling and Dehumidification Across Cities and Climates","authors":"Naika Meili,&nbsp;Xing Zheng,&nbsp;Yuya Takane,&nbsp;Ko Nakajima,&nbsp;Kazuki Yamaguchi,&nbsp;Dengkai Chi,&nbsp;Yue Zhu,&nbsp;Jing Wang,&nbsp;Yeshan Qiu,&nbsp;Athanasios Paschalis,&nbsp;Gabriele Manoli,&nbsp;Paolo Burlando,&nbsp;Puay Yok Tan,&nbsp;Simone Fatichi","doi":"10.1029/2024MS004590","DOIUrl":"https://doi.org/10.1029/2024MS004590","url":null,"abstract":"<p>Increasing urban tree cover is a common strategy to lower urban temperatures and indirectly the building energy demand for air-conditioning (AC). However, urban vegetation leads to increasing humidity with potential negative effects on the AC dehumidification loads in hot-humid climates, an effect that has so far been unexplored. Here, we included a building energy model into the urban ecohydrological model Urban Tethys-Chloris (UT&amp;C-BEM) to quantify the AC energy reduction effects of trees in seven hot cities with varying background humidity. A numerical experiment was performed simulating various urban densities and tree cover scenarios in the city-climates of Riyadh, Phoenix, Dubai, New Delhi, Singapore, Lagos, and Tokyo. The relative contribution of tree shade, air temperature reduction, and humidity increase on the AC energy reduction was further quantified. We found that well-watered trees provide the largest average summer AC energy reduction of −17% in the hot-dry climate (Riyadh, Phoenix). As tree shade is the dominant factor leading to the AC energy reduction in all city-climates, humid cities also show an average summer AC energy reduction ranging from −6% to −9%. However, increasing humidity is affecting AC dehumidification loads, especially under higher ventilation rates in humid climates and in these cities, AC energy reduction is most efficient with up to 40% tree cover. Additionally, we found that trees effectively reduce peak AC energy consumption due to higher shading effects in those hours. These results can inform urban planning strategies to maximize reduction in the AC energy demand using urban trees.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004590","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554792","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":"Impacts of Predicted Liquid Fraction and Multiple Ice-Phase Categories on the Simulation of Hail in the Predicted Particle Properties (P3) Microphysics Scheme","authors":"Jason A. Milbrandt,&nbsp;Hugh Morrison,&nbsp;Mélissa Cholette","doi":"10.1029/2024MS004404","DOIUrl":"https://doi.org/10.1029/2024MS004404","url":null,"abstract":"<p>Since its inception in 2015, the Predicted Particle Properties (P3) bulk microphysics scheme has undergone several major developments. Ice is now represented by a user-specified number of freely-evolving (non-prescribed) categories; the liquid fraction of particles is predicted, thereby allowing for mixed-phase particles and improved process rates; and the scheme is triple-moment, which allows the size spectral width to vary independently. As such, P3 is now capable of representing key properties and microphysical processes that are important for hail. In this study, the impacts of some new capabilities of P3 on the simulation of hail amounts and sizes are examined in the context of idealized, high-resolution (200-m isotropic grid spacing) hailstorm simulations using a cloud-resolving model. Sensitivity tests are conducted to examine the impacts of (a) the predicted liquid fraction, and (b) the number of generic ice-phase categories (varied between one and four). Predicted liquid fraction leads to a more realistic treatment of melting and shedding, which decreases the mean ice (hail) sizes during melting compared to the original P3 scheme. In contrast, with an increasing number of ice-phase categories, the problem of property dilution is mitigated, ultimately resulting in greater quantities of hail and larger sizes reaching the surface. It is argued that the latest version of the P3 scheme is now capable of realistically representing the major microphysical processes involved in the initiation, growth, and decay of hail.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004404","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143530202","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":"Sensitivity to Sea Ice Thickness Parameters in a Coupled Ice-Ocean Data Assimilation System","authors":"Carmen Nab,&nbsp;Davi Mignac,&nbsp;Jack Landy,&nbsp;Matthew Martin,&nbsp;Julienne Stroeve,&nbsp;Michel Tsamados","doi":"10.1029/2024MS004276","DOIUrl":"https://doi.org/10.1029/2024MS004276","url":null,"abstract":"<p>Sea ice thickness (SIT) estimates derived from CryoSat-2 radar freeboard measurements are assimilated into the Met Office's Forecast Ocean Assimilation Model. We test the sensitivity of winter simulations to the snow depth, radar freeboard product and assumed radar penetration through the snowpack in the freeboard-to-thickness conversion. We find that modifying the snow depth has the biggest impact on the modeled SIT, changing it by up to 0.88 m (48%), compared to 0.65 m (33%) when modifying the assumed radar penetration through the snowpack and 0.55 m (30%) when modifying the freeboard product. We find a doubling in the thermodynamic volume change over the winter season when assimilating SIT data, with the largest changes seen in the congelation ice growth. Next, we determine that the method used to calculate the observation uncertainties of the assimilated data products can change the mean daily model SIT by up to 36%. Compared to measurements collected at upward-looking sonar moorings and during the Operation IceBridge campaign, we find an improvement in the SIT simulations' variability representation when assuming partial radar penetration through the snowpack and when improving the method used to calculate the CryoSat-2 observation uncertainties. This paper highlights a concern for future SIT data assimilation and forecasting, with the chosen parameterization of the freeboard-to-thickness conversion having a substantial impact on model results.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004276","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489837","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":"Diagnosing Nonlocal Vertical Acceleration in Moist Convection Using a Large-Eddy Simulation","authors":"Fu-Sheng Kao,&nbsp;Yi-Hung Kuo,&nbsp;Chien-Ming Wu","doi":"10.1029/2024MS004636","DOIUrl":"https://doi.org/10.1029/2024MS004636","url":null,"abstract":"<p>The anelastic theory of effective buoyancy has been generalized to include effects of momentum flux convergence, and has suggested that the dynamics—mediated by the nonlocal perturbation pressure—tends to average over forcing details, yielding vertical acceleration robust to small-scale variations of the flow. Here we aim to substantiate this theoretical assertion through examining a large-eddy simulation (LES) with a 100-m horizontal grid spacing. Specifically, instances of convection in the LES are identified. For these, the buoyancy and dynamic contributions to the vertical momentum tendency are separately diagnosed, and their sensitivity resulting from averaging over sub-cloud-scale features quantified. In the absence of a background shear or vorticity, both buoyancy and vertical momentum flux convergence are the leading effect in the vertical acceleration while the influence of the horizontal momentum flux convergence on the vertical motion appears to be substantially weaker. For deep-convective cases, these contributions at the cloud scale (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>∼</mo>\u0000 <mn>8</mn>\u0000 </mrow>\u0000 <annotation> ${sim} 8$</annotation>\u0000 </semantics></math> km) exhibit a robustness, as measured in a root-mean-square sense, to horizontally smoothing out turbulent features of scales <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>≲</mo>\u0000 <mn>3</mn>\u0000 </mrow>\u0000 <annotation> $lesssim 3$</annotation>\u0000 </semantics></math> km. As expected, such scales depend on the size of the convective element of interest, while dynamic contributions tend to be more susceptible to horizontal smoothing than does the buoyancy contribution. We thus argue that including the anelastic nonlocal dynamics can help capture the evolution of convective-cloud-scale flows without fully resolving the finer-scale turbulent features embedded in the flow. Results here lend support to simplifying the subgrid-scale representation of moist convection for global climate models and storm-resolving simulations.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004636","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143490004","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":"Toward Transparency and Consistency: An Open-Source Optics Parameterization for Clouds and Precipitation","authors":"Jing Feng,&nbsp;Raymond Menzel,&nbsp;David Paynter","doi":"10.1029/2024MS004478","DOIUrl":"https://doi.org/10.1029/2024MS004478","url":null,"abstract":"<p>In this study, a new open-source package for cloud and precipitation modeling is introduced. Based on Mie theory and existing ice crystal data sets, the scheme generates optical properties for user-defined gas bands, particle size distribution, and crystal habits, ensuring continuity across wide spectral bands and from small particles (clouds) to large particles (precipitation). Compared with existing schemes in GFDL's AM4-MG2, it reduces shortwave reflection of liquid clouds at the top of the atmosphere (TOA) by 1.50 Wm⁻² and increases that of ice clouds by 1.62 Wm⁻², based on offline radiative calculations. Using the new scheme, we find that cloud radiative effects are sensitive to microphysics variables such as particle size and habit, which affect the effective radius. Systematic flux biases may arise if the effective radius is not fully predicted in microphysics due to predefined size and habit distributions. We show that assuming spherical ice crystals underestimates ice-cloud radiative effects by 3.20 Wm⁻² in the longwave TOA and 2.76 Wm⁻² in the shortwave TOA. These biases can be addressed by improving the effective radius approximation with a volume-to-radius ratio derived from in-situ measurements. Combining these findings, we propose that climate models use a set of optics parameterizations for each hydrometeor type while adequently accounting for radiation effects caused by size and habit distributions. Uncertainties due to this simplification are evaluated. This study offers a consistent and physically based representation of radiative processes of clouds and precipitation in weather and climate simulations.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143490003","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":"Characterizing How Meteorological Forcing Selection and Parameter Uncertainty Influence Community Land Model Version 5 Hydrological Applications in the United States","authors":"Hisham Eldardiry,&nbsp;Ning Sun,&nbsp;Hongxiang Yan,&nbsp;Patrick Reed,&nbsp;Travis Thurber,&nbsp;Jennie Rice","doi":"10.1029/2024MS004222","DOIUrl":"https://doi.org/10.1029/2024MS004222","url":null,"abstract":"<p>Despite the increasing use of large-scale Land Surface Models (LSMs) in predicting hydrological responses in extreme conditions, there's a critical gap in understanding the uncertainties in these predictions. This study addresses this gap through a detailed diagnostic evaluation of the uncertainties arising from meteorological forcing selection and model parametrization in hydrological simulations of the Community Land Model version 5 (CLM5). CLM5 is configured at a spatial scale of about 12-km to simulate runoff processes for 464 headwater watersheds, selected from the Catchment Attributes for Large-Sample Studies (CAMELS) data set to be representative of physiographic and climatic gradients across the conterminous United States. For each watershed, CLM5 is driven by five commonly used gridded forcing data sets in combination with a large ensemble (&gt;1,200) of key CLM5 hydrologic parameters. Our results suggest that uncertainty in CLM5 runoff simulations resulting from both forcing and parametric sources is markedly higher in arid regions, for example, Great Plains and Midwest regions. Uncertainty in low flow is dominated by parametric uncertainty, while the selection of meteorological forcing contributes more dominantly to high flow and seasonal flows during fall and spring. Our analysis also demonstrates that the selection of forcing data sets and the metrics used to calibrate CLM5 significantly impact the model's predictive accuracy in extreme event severity for both floods and droughts. Overall, the results from this study highlight the need to understand and account for forcing and parametric uncertainties in CLM5 simulations, particularly for hazard and risk assessments addressing hydrologic extremes.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 3","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143490005","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":"Insights on Tropical High-Cloud Radiative Effect From a New Conceptual Model","authors":"Jakob Deutloff,&nbsp;Stefan A. Buehler,&nbsp;Manfreth Brath,&nbsp;Ann Kristin Naumann","doi":"10.1029/2024MS004615","DOIUrl":"https://doi.org/10.1029/2024MS004615","url":null,"abstract":"&lt;p&gt;The new capabilities of global storm-resolving models to resolve individual clouds allow for a more physical perspective on the tropical high-cloud radiative effect and how it might change with warming. In this study, we develop a conceptual model of the high-cloud radiative effect as a function of cloud thickness measured by ice water path. We use atmospheric profiles from a global ICON simulation with &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;5&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;mi&gt;m&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $5hspace*{.5em}mathrm{k}mathrm{m}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; horizontal grid spacing to calculate the radiation offline with the ARTS line-by-line radiative transfer model. The conceptual model of the high-cloud radiative effect reveals that it is sufficient to approximate high clouds as a single layer characterized by an albedo, emissivity and temperature, which vary with ice water path. The increase of the short-wave high-cloud radiative effect with ice water path is solely explained by the high-cloud albedo. The increase of the long-wave high-cloud radiative effect with ice water path is governed by an increase of emissivity for ice water path below &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;msup&gt;\u0000 &lt;mn&gt;0&lt;/mn&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;1&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msup&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mi&gt;k&lt;/mi&gt;\u0000 &lt;mi&gt;g&lt;/mi&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;m&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $1{0}^{-1}hspace*{.5em}mathrm{k}mathrm{g}hspace*{.5em}{mathrm{m}}^{-mathrm{2}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, and by a decrease of high-cloud temperature with increasing ice water path above this threshold. The mean high-cloud radiative effect from the ARTS simulations for the chosen day of this ICON model run is &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;1.25&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mi&gt;W&lt;/mi&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;msup&gt;\u0000 &lt;mi&gt;m&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;2&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msup&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $1.25hspace*{.5em}mathrm{W}hspace*{.5em","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 2","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004615","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489764","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 Novel Ensemble-Based Parameter Estimation for Improving Ocean Biogeochemistry in an Earth System Model","authors":"Tarkeshwar Singh,&nbsp;François Counillon,&nbsp;Jerry Tjiputra,&nbsp;Yiguo Wang","doi":"10.1029/2024MS004237","DOIUrl":"https://doi.org/10.1029/2024MS004237","url":null,"abstract":"<p>Estimating ocean biogeochemistry (BGC) parameters in Earth System Models is challenging due to multiple error sources and interlinked parameter sensitivities. Reducing the temperature and salinity bias in the ocean physical component of the Norwegian Earth System Model (NorESM) diminishes the BGC state bias at intermediate depth but leads to a greater bias increase near the surface. This suggests that BGC parameters are tuned to compensate for the physical ocean model biases. We successfully apply the iterative ensemble smoother data assimilation technique to estimate BGC parameters in NorESM with reduced bias in its physical ocean component. We estimate BGC parameters based on the monthly climatological error of nitrate, phosphate, and oxygen in a coupled reanalysis of NorESM that assimilates observed monthly climatology of temperature and salinity. First, we compare the performance of globally uniform and spatially varying parameter estimations. Both approaches reduce BGC bias obtained with default parameters, even for variables not assimilated in the parameter estimation (e.g., <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mtext>CO</mtext>\u0000 <mn>2</mn>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${text{CO}}_{2}$</annotation>\u0000 </semantics></math> fluxes and primary production). While spatial parameter estimation performs locally best, it also increases biases in areas with few observations, and overall performs poorer than global parameter estimation. A second iteration further reduces the bias in the near-surface BGC with global parameter estimation. Finally, we assess the performance of global estimated parameters in a 30-year coupled reanalysis produced by assimilating time-varying temperature and salinity observations. This reanalysis reduces error by 10%–20% for phosphate, nitrate, oxygen, and dissolved inorganic carbon compared to a reanalysis done with default parameters.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 2","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481602","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}