Earth and Space Science最新文献

{"title":"Residence Time of Lagrangian Profiling Floats: Observational Assessment and Numerical Simulation of Station Keeping Ability","authors":"Barry B. Ma,&nbsp;Zoltan B. Szuts,&nbsp;Thomas B. Curtin","doi":"10.1029/2026EA005018","DOIUrl":"https://doi.org/10.1029/2026EA005018","url":null,"abstract":"<p>Autonomous profiling floats have revolutionized global ocean observation, yet their passive drift limits their ability to remain within desired regions. Using observations and simulations with numerical ocean models, we quantify observed and potential residence time (RT) of profiling floats and explore station-keeping strategies. Analysis of Argo float trajectories, performing fixed Argo-style sampling, reveals strong spatial variability in RT, from &lt;20 days in western boundary currents to &gt;100 days in subtropical gyre interiors and marginal seas. To quantify RT for alternate sampling behaviors, trajectories are calculated using velocity fields from an assimilative ocean reanalysis model in the dynamically complex western Pacific. A simple selection criterion of choosing to park at the depth of minimum horizontal velocity increases the mean RT by tens to several hundreds of percent, compared with fixed parking at 1,000 m. More sophisticated selection strategies lengthen RT further—such as accounting for flow direction or changing the park depth multiple times during one dive. These control methods provide upper limits on the RT by assuming perfect knowledge of the ocean's velocity profile. These results demonstrate the potential of adaptive park-depth selection for mission-specific profiling floats and regional observing applications where enhanced RT is a primary objective. Such strategies are not intended for the core Argo array, for which consistent parking-depth sampling is important for maintaining the long-term middepth velocity record.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EA005018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Schumann Resonance Frequency Increase Following Recurrent Solar Wind Stream Onsets","authors":"J. Tacza,&nbsp;G. Sátori,&nbsp;A. Neska,&nbsp;T. Raita,&nbsp;T. Bozoki","doi":"10.1029/2026EA005271","DOIUrl":"https://doi.org/10.1029/2026EA005271","url":null,"abstract":"<p>Recurrent high-speed streams and corotating interaction regions (HSS/CIRs) are common solar-wind drivers, but their influence on Schumann resonance (SR) frequencies remains poorly quantified. We analyzed 173 threshold-defined HSS/CIR proxy onsets using superposed epoch composites, bootstrap uncertainty, and a month-matched random-epoch null model. At the polar Hornsund station (corrected geomagnetic latitude 74.16°N), the apparent first-mode SR frequency exhibits a positive response on days 0 to +1 relative to onset and is unlikely under the month-matched random-epoch null. A similar positive response appears at the high-latitude Ivalo (65.14°N) and Rovaniemi (63.69°N) stations, with the same ordering under matched-support restriction. Event-level scaling with baseline-relative Kp, AE, and Vsw impulses shows the clearest organization by Kp, consistent support from AE, and a positive but less diagnostic relation with Vsw. The Kp/AE organization strengthened after excluding ICME-overlap events. Overall, HSS/CIR proxy onsets are followed by a small but repeatable first-mode SR response that is statistically supported, reproducible across high-latitude stations, and organized more clearly by geomagnetic coupling than by solar-wind speed alone.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EA005271","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Automatic GNSS Coordinate Time Series Analysis for Very Large Networks","authors":"Richard A. Bennett,&nbsp;Phillip K. McFarland,&nbsp;Amy Whetter,&nbsp;Jordan Krcmaric","doi":"10.1029/2025EA004741","DOIUrl":"https://doi.org/10.1029/2025EA004741","url":null,"abstract":"<p>We present a new algorithm, AutoCF, for automatically constructing coordinate functions (CFs) for continuously operating GNSS reference stations (CORSs). The iterative algorithm alternates between application of LASSO and Ridge Regression methods, with hyperparameters successively tightened with each iteration to more judiciously scrutinize candidate breakpoints. We developed the algorithm using data from 60 CORSs from two independent analysis centers. These CORSs experienced displacements associated with four large magnitude earthquakes. Some stations are located in the near-field of two of these earthquakes, while the other two earthquakes occurred at intermediate and far-field distances from the nearest station. We show that automatically determined CFs track the observed site motion with weighted RMS (WRMS) residual scatter less than 2–3 mm and 5–7 mm for horizontal and vertical components, respectively. We tuned the algorithm such that estimates for site velocity are as close to the estimates generated by the independent processing centers as those centers' results are to one another. We then assessed the algorithm's performance on a new, unseen data set comprising 3226 coordinate time series generated independently at NOAA's National Geodetic Survey. The median WRMS misfits of the automatic fits to the time series are 1 mm for horizontal and 4 mm for vertical components. 587 stations (18%) were flagged for human assessment. A velocity solution computed with station trajectories parameterized according to the algorithm-assisted analysis agrees with similar large-scale solutions produced by three independent analysis centers at the level of 0.2 mm/yr in horizontal components.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004741","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Enhancing Tropical Cyclone Prediction Through AI Weather Model Ensemble Forecasts and Multi-Source Data Integration","authors":"Shijin Yuan,&nbsp;Guansong Wang,&nbsp;Bin Mu,&nbsp;Feifan Zhou,&nbsp;Hao Li,&nbsp;Yake Zhang","doi":"10.1029/2026EA005040","DOIUrl":"https://doi.org/10.1029/2026EA005040","url":null,"abstract":"<p>Tropical cyclone (TC) forecasting is essential for disaster preparedness, yet accurate intensity prediction remains challenging, particularly during rapid intensification. This study proposes TianXing-TC, a lightweight probabilistic post-processing framework that leverages ensemble forecasts from the AI weather prediction model TianXing and integrates multi-source TC-related information. The framework first generates perturbed TianXing ensemble forecasts and extracts TC-centered environmental trajectories along the predicted storm tracks. A TC Correction Network then fuses these environmental trajectories with geostationary satellite cloud-pattern imagery and storm-state statistical factors to predict maximum sustained wind, minimum sea-level pressure, longitude, and latitude up to 96 hr ahead. Compared with the raw TianXing ensemble, TianXing-TC substantially reduces systematic intensity underestimation and improves track forecasts, particularly at longer lead times. Homogeneous comparisons with official forecasts show that TianXing-TC consistently reduces intensity forecast errors and achieves competitive track forecast skill, with the largest long-lead track improvements in the western North Pacific basin. Stratified verification further indicates useful short-range skill during rapid-intensification events, although rapid intensity changes remain underestimated. Integrated-gradient analyses and case studies reveal physically plausible attribution patterns related to environmental flow, convective organization, and storm-state persistence. These results suggest that AI weather model generated ensemble trajectories, when combined with satellite and statistical information, can provide an efficient complementary approach for TC forecast post-processing.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EA005040","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Two Radio Occultation Constellations on Numerical Weather Prediction: Polar-Orbits Only and Mixed Polar-Equatorial Orbits","authors":"Nikki C. Privé,&nbsp;Christopher Barsoum,&nbsp;Douglas Hunt,&nbsp;Michael J. Murphy,&nbsp;Richard Anthes,&nbsp;William Gullotta,&nbsp;Natalie Laudier","doi":"10.1029/2026EA005114","DOIUrl":"https://doi.org/10.1029/2026EA005114","url":null,"abstract":"<p>This study explores the relative impact of two orbital configurations for Global Navigation Satellite System radio occultation (RO) observations in numerical weather prediction using observing system simulation experiments (OSSE). Three experiments are carried out: a Control experiment with no RO observations and two experiments with 14,000 RO profiles per day—one with only polar orbiting satellites which provides a high concentration of profiles in the extratropics but has gaps in spatial coverage every 6 hr, and a second with a mix of polar and equatorial orbits with RO profiles that are more concentrated in the tropics and a more uniform local time coverage. Both experiments with RO included show a marked increase in forecast accuracy compared to the Control. The mixed orbit case shows improvement in forecast accuracy compared to the polar-only orbit case in the tropics. The OSSE framework allows calculation of observation impacts on background and analysis errors, so that the contribution of information from retained RO information can be compared with the contribution of new information from observations ingested in the current cycle. Impacts of RO in the two sampling experiments are also explored using a forecast sensitivity observation impact tool for 24-hr forecasts, and by comparing the skill of medium-range forecasts. In stratospheric midlatitudes, the RO observational information is well retained, so that more frequent sampling is not required. However, the Tropics are found to be particularly sensitive to RO data in both the stratosphere and troposphere, and relatively uniform coverage is advantageous.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EA005114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Clear-Air Turbulence Upstream of a Hydraulic Jump Leading to a Helicopter Accident—A Large Eddy Simulation","authors":"J. Ito,&nbsp;H. Niino,&nbsp;K. Saito,&nbsp;K. Okuyama","doi":"10.1029/2025EA004721","DOIUrl":"https://doi.org/10.1029/2025EA004721","url":null,"abstract":"<p>This study investigates clear-air turbulence that triggered a helicopter accident in the lee of a mountain range near Koriyama, Japan, on 1 February 2020. Using numerical weather prediction models with horizontal resolutions of 1 km and 100 m, we examined the environmental conditions and mechanisms responsible for the turbulence. The models successfully reproduced a downslope windstorm with a hydraulic jump. The finer-resolution model (100 m), which is regarded as a large eddy simulation, revealed intense turbulence induced by Kelvin–Helmholtz instability at the boundary between the downslope wind and the overlying stagnant layer upstream of the hydraulic jump. Vertical wind speeds exceeding 10 m <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mi>s</mi>\u0000 <mrow>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${mathrm{s}}^{-1}$</annotation>\u0000 </semantics></math> are associated with the turbulence at the flight level. These results highlight the importance of high-resolution simulations for capturing hazardous clear-air turbulence in mountainous regions.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004721","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Deep Learning Segmentation Models for Mapping Landslides From LiDAR-Based Elevation Data","authors":"Hudson J. Koch,&nbsp;Junfeng Zhu,&nbsp;Shashank Bhatt,&nbsp;Nathan Jacobs,&nbsp;Jason M. Dortch","doi":"10.1029/2025EA004937","DOIUrl":"https://doi.org/10.1029/2025EA004937","url":null,"abstract":"<p>Robust landslide inventories are critical for characterizing landslide hazard and helping reduce societal vulnerability. For this study, LiDAR-derived digital elevation models (DEMs), their derivatives, and a landslide inventory were used to train different deep learning segmentation models to assess the functionality of automatic segmentation for high-resolution, non-event specific landslide inventories. Three deep learning segmentation approaches (U-Net, MA-Net, and FPN) were trained with a variety of hyperparameters, with some consideration of input modalities. Models were assessed with a spatial test holdout and then further evaluated against a proximal holdout landslide inventory. In total, 90 model scenarios were trained. Model performance metrics and visual assessment suggested that in general, model performances varied only slightly during hyperparameter tuning. U-Net trained on DEM gradients performed the best, with a feature IoU (intersection over union) of 0.407 among all scenarios. MA-Net trained on DEM gradients had the best performance against the proximal holdout inventory, with an IoU of 0.398, however these performances are within random variability of the models indicating no clear best model. A comparison of the proximal holdout inference results from various trained models suggested that deep learning segmentation models are effective in mapping landslides from LiDAR-derived DEMs. A well-trained landslide segmentation model could potentially be used to aid manual mapping by improving efficiency and accuracy. The direct inference result could also be used as an approximate inventory for use in data-driven models, such as landslide susceptibility models, to significantly reduce the time and resources required for traditional landslide mapping.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004937","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Construction of a Global Atmospheric Refractivity Model for Optical Wavelengths Based on Temporal Evolution Characteristics","authors":"Zhiyan Ding,&nbsp;Pengfei Wu,&nbsp;Wenyue Zhu","doi":"10.1029/2026EA005286","DOIUrl":"https://doi.org/10.1029/2026EA005286","url":null,"abstract":"<p>Atmospheric refractivity model accuracy is important for refraction correction, starlight refraction navigation, and related optoelectronic applications. To address the insufficient understanding of refractivity temporal evolution and the lack of clear criteria for selecting model temporal resolution, this study constructs a global four-dimensional gridded atmospheric refractivity data set from ERA5 reanalysis data for 2015–2024, with a spatial resolution of 0.25° × 0.25° and an hourly temporal resolution. Using this data set, we analyze the global latitudinal and longitudinal distributions, seasonal variability, and temporal evolution of refractivity at hourly, daily, and interannual scales. We further evaluate the effects of temporal span and statistical period on refractivity stability. Considering both model accuracy and data complexity, we construct the model using the 2015–2024 data set after applying monthly ±2σ outlier screening to the hourly refractivity samples at each grid point and height level, and adopt a 5-day × 12-hr temporal resolution for the global atmospheric refractivity model. Radiosonde observations from eight high-latitude stations in both hemispheres are used to compare the proposed model with four commonly used atmospheric models. At the selected high-latitude validation stations, the proposed model achieves lower RMSE values than the existing representative atmospheric models in several altitude ranges, particularly below 15 km and during Northern Hemisphere winter, while maintaining comparable performance at 20 and 25 km. The proposed temporal-resolution selection scheme provides a useful reference for optimizing high-precision global atmospheric refractivity models.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EA005286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149145749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Determination of Earth's Static Gravity Field Using Quantum Gravity Satellites at Very Low Earth Orbit","authors":"Wenming Chen,&nbsp;Hao Zhou,&nbsp;Yanbin Zhao,&nbsp;Zhu Zhu,&nbsp;Shuyun Zheng,&nbsp;Zhicai Luo,&nbsp;Zebing Zhou","doi":"10.1029/2026EA005368","DOIUrl":"https://doi.org/10.1029/2026EA005368","url":null,"abstract":"&lt;p&gt;Very Low Earth Orbit (VLEO) satellite platforms and quantum-optical sensing technologies may provide new observation approaches for improving Earth's static gravity field models. This study conceptually assesses their potential contribution through a two-tier closed-loop simulation framework. Under idealized conditions considering only instrumental observation noise, with the cold atom interferometry (CAI) gradiometer modeled using joint three-axis observations of &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;V&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;x&lt;/mi&gt;\u0000 &lt;mi&gt;x&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${V}_{xx}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, &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;V&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;y&lt;/mi&gt;\u0000 &lt;mi&gt;y&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${V}_{yy}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and &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;V&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;z&lt;/mi&gt;\u0000 &lt;mi&gt;z&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${V}_{zz}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; at 180 km altitude and a noise level of &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;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mtext&gt;mE&lt;/mtext&gt;\u0000 &lt;mo&gt;/&lt;/mo&gt;\u0000 &lt;msqrt&gt;\u0000 &lt;mtext&gt;Hz&lt;/mtext&gt;\u0000 &lt;/msqrt&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; $1 text{mE}/sqrt{text{Hz}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, the VLEO-borne CAI gradiometer concept yields overall recovery errors lower than those of the selected GOCE-derived reference models. For the GRACE-like scheme based on space-to-space optical-clock observations of gravitational potential differences, a frequency accuracy of 10&lt;sup&gt;−20&lt;/sup&gt; or better is required to outperform the GRACE-derived reference model. In addition, the idealized simulations indicate that lowering the orbital altitude and adopting a Bender-like dual-orbit configuration can reduce recovery errors. When attitude errors (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;0.8&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mtext&gt;mE&lt;/mtext&gt;\u0000 &lt;mo&gt;/&lt;/mo&gt;\u0000 ","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2026EA005368","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149072654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 of Nocturnal Low-Level Jet Representation to Model Resolution and Boundary Layer Schemes: Implications for Wind Energy Assessment Over Saudi Arabia","authors":"Andrew Janiszeski,&nbsp;Cian Gross,&nbsp;Giacomo Moraglia,&nbsp;Paola Crippa","doi":"10.1029/2025EA004588","DOIUrl":"https://doi.org/10.1029/2025EA004588","url":null,"abstract":"<p>Sensitivity tests on low-level wind speeds and stability associated with the diurnal cycle of convective boundary layer (CBL) are performed using five Weather Research and Forecasting (WRF) Model simulations over the Riyadh, Saudi Arabia region. Multiscale WRF domain configurations with domain grid-spacings ranging from 12,150–450 m are coupled with different planetary boundary layer schemes with one simulation having two inner-domains of 150 and 50 m using a large-eddy simulation (LES) turbulence model. Low-level wind speed and stability from these simulations indicate a deep, well-mixed daytime CBL extending to 3 km, with winds that are nearly uniform with height. Following sunset, the surface layer rapidly stabilizes, and a nocturnal low-level jet (NLLJ) forms between 100 and 800 m altitude, with a core near 500 m and wind speeds of 7.5–12.5 m s⁻¹. Model PBL scheme choice and changes in horizontal and vertical resolution affect the stability and wind speed output little in this study. Additionally, low-level winds in this region are important for wind energy production. Sensitivity of wind energy production to WRF model configuration, wind turbine height, and model resolution indicates that wind energy output is highest during nighttime, associated with the NLLJ and predicted best by the WRF simulation employing the MYNN scheme in this study. Higher hub heights produce greater wind output while the greatest sensitivity to model resolution for wind energy occurs at the transition from daytime to nighttime with the subsequent CBL evolution and NLLJ formation.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"13 10","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025EA004588","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149072655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}