Journal of Advances in Modeling Earth Systems最新文献

{"title":"Quantitative Decoupling Analysis for Assessing the Meteorological, Emission, and Chemical Influences on Fine Particle Pollution","authors":"Junhua Wang,&nbsp;Baozhu Ge,&nbsp;Lei Kong,&nbsp;Xueshun Chen,&nbsp;Jie Li,&nbsp;Keding Lu,&nbsp;Yayuan Dong,&nbsp;Hang Su,&nbsp;Zifa Wang,&nbsp;Yuanhang Zhang","doi":"10.1029/2024MS004261","DOIUrl":"https://doi.org/10.1029/2024MS004261","url":null,"abstract":"<p>A comprehensive understanding of meteorological, emission and chemical influences on severe haze is essential for air pollution mitigation. However, the nonlinearity of the atmospheric system greatly hinders this understanding. In this study, we developed the quantitative decoupling analysis (QDA) method by applying the Factor Separation (FS) method into the model processes to quantify the effects of emissions (E), meteorology (M), chemical reactions (C), and their nonlinear interactions and impact on fine particulate matter (PM_2.5) pollution. Taking a heavy-haze episode in Beijing as an example, we show that different from the integrated process rate (IPR) and the scenario analysis approach (SAA) in previous studies, the QDA method explicitly demonstrate the nonlinear effects by decomposing the variation of PM_2.5 concentration into individual contributions of <i>E</i>, <i>M</i> and <i>C</i> terms as well as the contributions from interactions among these processes. Results showed that <i>M</i> dominated the hourly fluctuation of the PM_2.5 concentration. The <i>C</i> terms increase with increasing the level of haze, reaching maximum (0.37 μg <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>·</mo>\u0000 </mrow>\u0000 <annotation> $mathit{cdot }$</annotation>\u0000 </semantics></math> m⁻³ <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>·</mo>\u0000 </mrow>\u0000 <annotation> $mathit{cdot }$</annotation>\u0000 </semantics></math> h⁻¹) at the maintenance stage. Moreover, our method reveals that there are non-negligible non-linear effects of meteorological, emission, and chemical processes during pollution stage, with the mean accounting for 50% of the increase in PM_2.5 concentrations, which is often ignored in the current air pollution control strategies. This study highlights that the QDA approach can be used to gain insight into the formation of heavy pollution, and to identify uncertainty in numerical models.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 11","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004261","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641937","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":"Scale- and Variable-Dependent Localization for 3DEnVar Data Assimilation in the Rapid Refresh Forecast System","authors":"Sho Yokota,&nbsp;Jacob R. Carley,&nbsp;Ting Lei,&nbsp;Shun Liu,&nbsp;Daryl T. Kleist,&nbsp;Yongming Wang,&nbsp;Xuguang Wang","doi":"10.1029/2023MS004098","DOIUrl":"https://doi.org/10.1029/2023MS004098","url":null,"abstract":"<p>This study demonstrates the advantages of scale- and variable-dependent localization (SDL and VDL) on three-dimensional ensemble variational data assimilation of the hourly-updated high-resolution regional forecast system, the Rapid Refresh Forecast System (RRFS). SDL and VDL apply different localization radii for each spatial scale and variable, respectively, by extended control vectors. Single-observation assimilation tests and cycling experiments with RRFS indicated that SDL can enlarge the localization radius without increasing the sampling error caused by the small ensemble size and decreased associated imbalance of the analysis field, which was effective at decreasing the bias of temperature and humidity forecasts. Moreover, simultaneous assimilation of conventional and radar reflectivity data with VDL, where a smaller localization radius was applied only for hydrometeors and vertical wind, improved precipitation forecasts without introducing noisy analysis increments. Statistical verification showed that these impacts contributed to forecast error reduction, especially for low-level temperature and heavy precipitation.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 11","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023MS004098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641547","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":"Precipitation Extremes and Their Modulation by Convective Organization in RCEMIP","authors":"Graham L. O’Donnell,&nbsp;Allison A. Wing","doi":"10.1029/2024MS004535","DOIUrl":"https://doi.org/10.1029/2024MS004535","url":null,"abstract":"<p>We examine the influence of convective organization on extreme tropical precipitation events using model simulation data from the Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP). At a given SST, simulations with convective organization have more intense precipitation extremes than those without it at all scales, including instantaneous precipitation at the grid resolution (3 km). Across large-domain simulations with convective organization, models with explicit convection exhibit better agreement in the response of extreme precipitation rates to warming than those with parameterized convection. Among models with explicit convection, deviations from the Clausius-Clapeyron scaling of precipitation extremes with warming are correlated with changes in organization, especially on large spatiotemporal scales. Though the RCEMIP ensemble is nearly evenly split between CRMs which become more and less organized with warming, most of the models which show increased organization with warming also allow super-CC scaling of precipitation extremes. We also apply an established precipitation extremes scaling to understand changes in the extreme condensation events leading to extreme precipitation. Increased organization leads to greater increases in precipitation extremes by enhancing both the dynamic and implied efficiency contributions. We link these contributions to environmental variables modified by the presence of organization and suggest that increases in moisture in the aggregated region may be responsible for enhancing both convective updraft area fraction and precipitation efficiency. By leveraging a controlled intercomparison of models with both explicit and parameterized convection, this work provides strong evidence for the amplification of tropical precipitation extremes and their response to warming by convective organization.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 11","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004535","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641522","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 Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site-Level Validation, and Global Applicability","authors":"Zeli Tan,&nbsp;Huaxia Yao,&nbsp;John Melack,&nbsp;Hans-Peter Grossart,&nbsp;Joachim Jansen,&nbsp;Sivakiruthika Balathandayuthabani,&nbsp;Khachik Sargsyan,&nbsp;L. Ruby Leung","doi":"10.1029/2024MS004275","DOIUrl":"https://doi.org/10.1029/2024MS004275","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH₄) emissions; however, no earth system model (ESM) has represented lake CH₄ dynamics. To fill this gap, we refined a process-based lake biogeochemical model to simulate global lake CH₄ emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non-linear CH₄ oxidation kinetics, and the coupling of sediment carbon pools with in-lake primary production and terrigenous carbon loadings. We compiled a lake CH₄ data set for model validation. The model shows promising performance in capturing the seasonal and inter-annual variabilities of CH₄ emissions at 10 representative lakes for different lake types and the variations in mean annual CH₄ emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH₄ diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH₄ diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH₄ outgassing events in non-floodplain lakes and the seasonal variability of CH₄ ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH₄ emissions and climate-CH₄ feedback.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004275","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525422","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 Autoconversion Representation in E3SMv2 Using an Ensemble of Large-Eddy Simulations of Low-Level Warm Clouds","authors":"Mikhail Ovchinnikov,&nbsp;Po-Lun Ma,&nbsp;Colleen M. Kaul,&nbsp;Kyle G. Pressel,&nbsp;Meng Huang,&nbsp;Jacob Shpund,&nbsp;Shuaiqi Tang","doi":"10.1029/2024MS004280","DOIUrl":"https://doi.org/10.1029/2024MS004280","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;p&gt;In numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate &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;mi&gt;A&lt;/mi&gt;\u0000 &lt;mi&gt;u&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $(Au)$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;A&lt;/mi&gt;\u0000 &lt;mi&gt;u&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $Au$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; is commonly parameterized as a function of DSD moments: cloud droplet number &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mfenced&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;n&lt;/mi&gt;\u0000 &lt;mi&gt;c&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mfenced&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $left({n}_{c}right)$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and mass &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mfenced&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;q&lt;/mi&gt;\u0000 &lt;mi&gt;c&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mfenced&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $left({q}_{c}right)$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; concentrations. When applied in a large-scale model, the grid-mean &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;A&lt;/mi&gt;\u0000 &lt;mi&gt;u&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $Au$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large-eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local &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":"16 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004280","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525313","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":"Description and Evaluation of the CNRM-Cerfacs Climate Prediction System (C3PS)","authors":"E. Sanchez-Gomez,&nbsp;R. Séférian,&nbsp;L. Batté,&nbsp;S. Berthet,&nbsp;C. Cassou,&nbsp;B. Dewitte,&nbsp;M. P. Moine M,&nbsp;R. Msadek,&nbsp;C. Prodhomme,&nbsp;Y. Santana-Falcón,&nbsp;L. Terray,&nbsp;A. Voldoire","doi":"10.1029/2023MS004193","DOIUrl":"https://doi.org/10.1029/2023MS004193","url":null,"abstract":"<p>The CNRM-Cerfacs Climate Prediction System (C3PS) is a new research modeling tool for performing climate reanalyzes and seasonal-to-multiannual predictions for a wide array of Earth system variables. C3PS is based on the CNRM-ESM2-1 model including interactive aerosols and stratospheric chemistry schemes as well as terrestrial and marine biogeochemistry enabling a comprehensive representation of the global carbon cycle. C3PS operates through a seamless coupled initialization for the atmosphere, land, ocean, sea ice and biogeochemistry components that allows a continuum of predictions across seasonal to multiannual time-scales. C3PS has also contributed to the Decadal Climate Prediction Project (DCPP-A) as part of the sixth Coupled Model Intercomparison Project (CMIP6). Here we describe the main characteristics of this novel Earth system-based prediction platform, including the methodological steps for obtaining initial states to produce forecasts. We evaluate the entire C3PS initialization procedure with the most up-to-date observations and reanalyzes over 1960–2021, and we discuss the overall performance of the system in the light of the lessons learned from previous and actual prediction platforms. Regarding the forecast skill, C3PS exhibits comparable seasonal predictive skill to other systems. At the multiannual scale, C3PS shows significant predictive skill in surface temperature during the first 2 years after initialization in several regions of the world. C3PS also exhibits potential predictive skill in Net primary production (NPP) and carbon fluxes several years in advance. This expands the possibility of applications of forecasting systems, such as the possibility of performing multiannual predictions of marine ecosystems and carbon cycle.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023MS004193","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525316","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":"Generative Diffusion for Regional Surrogate Models From Sea-Ice Simulations","authors":"Tobias Sebastian Finn,&nbsp;Charlotte Durand,&nbsp;Alban Farchi,&nbsp;Marc Bocquet,&nbsp;Pierre Rampal,&nbsp;Alberto Carrassi","doi":"10.1029/2024MS004395","DOIUrl":"https://doi.org/10.1029/2024MS004395","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>We introduce deep generative diffusion for multivariate and regional surrogate modeling learned from sea-ice simulations. Given initial conditions and atmospheric forcings, the model is trained to generate forecasts for a 12-hr lead time from simulations by the state-of-the-art sea-ice model neXtSIM. For our regional model setup, the diffusion model outperforms as ensemble forecast all other tested models, including a free-drift model and a stochastic extension of a deterministic data-driven surrogate model. The diffusion model additionally retains information at all scales, resolving smoothing issues of deterministic models. Furthermore, by generating physically consistent forecasts, previously unseen for such kind of completely data-driven surrogates, the model can almost match the scaling properties of neXtSIM, as similarly deduced from sea-ice observations. With these results, we provide a strong indication that diffusion models can achieve similar results as traditional geophysical models with the significant advantage of being orders of magnitude faster and solely learned from data.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004395","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525558","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":"Contributions of Irrigation Modeling, Soil Moisture and Snow Data Assimilation to High-Resolution Water Budget Estimates Over the Po Basin: Progress Towards Digital Replicas","authors":"Gabriëlle J. M. De Lannoy,&nbsp;Michel Bechtold,&nbsp;Louise Busschaert,&nbsp;Zdenko Heyvaert,&nbsp;Sara Modanesi,&nbsp;Devon Dunmire,&nbsp;Hans Lievens,&nbsp;Augusto Getirana,&nbsp;Christian Massari","doi":"10.1029/2024MS004433","DOIUrl":"https://doi.org/10.1029/2024MS004433","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>High-resolution water budget estimates benefit from modeling of human water management and satellite data assimilation (DA) in river basins with a large human footprint. Utilizing the Noah-MP land surface model with dynamic vegetation growth and river routing, in combination with an irrigation module, Sentinel-1 backscatter and snow depth retrievals, we produce a set of 0.7-km² water budget estimates of the Po river basin (Italy) for 2015–2023. The results demonstrate that irrigation modeling improves the seasonal soil moisture variation and summer streamflow at all gauges in the valley after withdrawal of irrigation water from the streamflow in postprocessing (12% error reduction relative to observed low summer streamflow), even if the basin-wide irrigation amount is underestimated. Sentinel-1 backscatter DA for soil moisture updating strongly interacts with irrigation modeling: when both are activated, the soil moisture updates are limited, and the simulated irrigation amounts are reduced. Backscatter DA systematically reduces soil moisture in the spring, which improves downstream spring streamflow. Assimilating Sentinel-1 snow depth retrievals over the surrounding Alps and Apennines further improves spring streamflow in a complementary way (2% error reduction relative to observed high spring streamflow). Despite the seasonal improvements, irrigation modeling and Sentinel-1 backscatter DA cannot significantly improve short-term or interannual variations in soil moisture, irrigation modeling causes a systematically prolonged high vegetation productivity, and snow depth DA only impacts the deep snowpacks. This study helps advancing the design of digital water budget replicas for river basins.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004433","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525014","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":"Structural Uncertainty in the Sensitivity of Urban Temperatures to Anthropogenic Heat Flux","authors":"Dan Li,&nbsp;Ting Sun,&nbsp;Jiachuan Yang,&nbsp;Ning Zhang,&nbsp;Pouya Vahmani,&nbsp;Andrew Jones","doi":"10.1029/2024MS004431","DOIUrl":"https://doi.org/10.1029/2024MS004431","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>One key source of uncertainty for weather and climate models is structural uncertainty arising from the fact that these models must simplify or approximate complex physical, chemical, and biological processes that occur in the real world. However, structural uncertainty is rarely examined in the context of simulated effects of anthropogenic heat flux in cities. Using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model, it is found that the sensitivity of urban canopy air temperature to anthropogenic heat flux can differ by an order of magnitude depending on how anthropogenic heat flux is released to the urban environment. Moreover, varying model structures through changing the treatment of roof-air interaction and the parameterization of convective heat transfer between the canopy air and the atmosphere can affect the sensitivity of urban canopy air temperature by a factor of 4. Urban surface temperature and 2-m air temperature are less sensitive to the methods of anthropogenic heat flux release and the examined model structural variants than urban canopy air temperature, but their sensitivities to anthropogenic heat flux can still vary by as much as a factor of 4 for surface temperature and 2 for 2-m air temperature. Our study recommends using temperature sensitivity instead of temperature response to understand how various physical processes (and their representations in numerical models) modulate the simulated effects of anthropogenic heat flux.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024MS004431","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524716","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 Stable Implementation of a Data-Driven Scale-Aware Mesoscale Parameterization","authors":"Pavel Perezhogin,&nbsp;Cheng Zhang,&nbsp;Alistair Adcroft,&nbsp;Carlos Fernandez-Granda,&nbsp;Laure Zanna","doi":"10.1029/2023MS004104","DOIUrl":"https://doi.org/10.1029/2023MS004104","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Ocean mesoscale eddies are often poorly represented in climate models, and therefore, their effects on the large scale circulation must be parameterized. Traditional parameterizations, which represent the bulk effect of the unresolved eddies, can be improved with new subgrid models learned directly from data. Zanna and Bolton (2020), https://doi.org/10.1029/2020gl088376 (ZB20) applied an equation-discovery algorithm to reveal an interpretable expression parameterizing the subgrid momentum fluxes by mesoscale eddies through the components of the velocity-gradient tensor. In this work, we implement the ZB20 parameterization into the primitive-equation GFDL MOM6 ocean model and test it in two idealized configurations with significantly different dynamical regimes and topography. The original parameterization was found to generate excessive numerical noise near the grid scale. We propose two filtering approaches to avoid the numerical issues and additionally enhance the strength of large-scale energy backscatter. The filtered ZB20 parameterizations led to improved climatological mean state and energy distributions, compared to the current state-of-the-art energy backscatter parameterizations. The filtered ZB20 parameterizations are scale-aware and, consequently, can be used with a single value of the non-dimensional scaling coefficient for a range of resolutions. The successful application of the filtered ZB20 parameterizations to parameterize mesoscale eddies in two idealized configurations offers a promising opportunity to reduce long-standing biases in global ocean simulations in future studies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"16 10","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023MS004104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524718","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}