Earth and Space Science最新文献

{"title":"A Rare Tropical Cyclone Associated With Southwest Monsoon Over the Northern Part of the South China Sea—Tropical Storm Maliksi","authors":"J. Y. He,&nbsp;P. W. Chan,&nbsp;C. W. Choy,&nbsp;P. Cheung,&nbsp;C. C. Lam,&nbsp;Y. H. He,&nbsp;C. K. Pan,&nbsp;K. K. Lai,&nbsp;H. Su,&nbsp;E. Z. Zhang,&nbsp;C. J. Sun,&nbsp;C. J. Huang","doi":"10.1029/2024EA003826","DOIUrl":"https://doi.org/10.1029/2024EA003826","url":null,"abstract":"<p>This study examines the characteristics and development of Tropical Storm Maliksi, which is a special case of tropical cyclone developed in the northwestern part of the South China Sea during a southwest monsoon outbreak. Detailed analyses were conducted using observational data and forecast products. Surface observations, radar wind profilers, aircraft data, and satellite products were used to evaluate Maliksi's wind structure, revealing multiple circulation centers and gale force winds. Vertical wind profiles, warm core structure, wind waves, and the influence of sea temperatures and salinity on Maliksi's intensification were investigated. Regarding forecasting, AI-based models outperformed conventional numerical weather prediction (NWP) models in predicting Maliksi's initial development, though both struggled to capture the persistence of strong winds as the system moved inland. High-resolution NWP simulations were employed to examine terrain-induced wind variability around Hong Kong International Airport, revealing the mountain wake effect and uneven wind and turbulence distribution. These findings provide insights into the challenges of forecasting and monitoring such tropical cyclones, and highlight the need for enhanced observational platforms and forecasting tools along coastlines vulnerable to these systems.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 11","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003826","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555480","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":"Improving Interpolating Accuracy of Weighted Mean Temperature by Using a Novel Lapse Rate Model in Compact VMF1 Product","authors":"Peng Sun,&nbsp;Kefei Zhang,&nbsp;Dantong Zhu,&nbsp;Moufeng Wan,&nbsp;Ren Wang,&nbsp;Suqin Wu","doi":"10.1029/2024EA003702","DOIUrl":"https://doi.org/10.1029/2024EA003702","url":null,"abstract":"<p>In GNSS (Global Navigation Satellite Systems) meteorology, the accuracy of precipitable water vapor (PWV) retrieved from the tropospheric delay of GNSS signals is affected by the conversion factor. Compact VMF1 product (known as GGOS Atmosphere data) provides high-accuracy global grid-wise weighted mean temperature (<i>T</i>_<i>m</i>) values, which can be utilized to calculate the conversion factor. However, the <i>T</i>_<i>m</i> provided in the compact VMF1 data are solely ground surface values. To enhance the performance of compact VMF1 product, a new <i>T</i>_<i>m</i> lapse rate model for each grid point was developed for the purpose of reducing its surface <i>T</i>_<i>m</i> to the elevation of the GNSS site. Then the reduced <i>T</i>_<i>m</i> values over the neighboring grid points together with horizontal interpolation were used to obtain the interpolated <i>T</i>_<i>m</i> for the GNSS station. The sample data for the development of the new model were the <i>T</i>_<i>m</i> profiles obtained from ERA5 monthly averaged data spanning 2009–2018. To assess the model's performance, global radiosonde data at 504 radiosonde stations spanning 2019–2021 were employed. Results demonstrated that implementing the <i>T</i>_<i>m</i> lapse rate model significantly enhanced the accuracy of interpolating <i>T</i>_<i>m</i> values for GNSS stations with substantial height disparities from adjacent grid points, thereby improving PWV conversion accuracy. This indicates that employing the new <i>T</i>_<i>m</i> lapse rate model to adjust surface <i>T</i>_<i>m</i> data in the compact VMF1 product holds promise for enhancing its utility in GNSS meteorology.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 11","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003702","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555481","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":"A Scalable, Cloud-Based Workflow for Spectrally-Attributed ICESat-2 Bathymetry With Application to Benthic Habitat Mapping Using Deep Learning","authors":"Forrest Corcoran,&nbsp;Christopher E. Parrish,&nbsp;Lori A. Magruder,&nbsp;J. P. Swinski","doi":"10.1029/2024EA003735","DOIUrl":"https://doi.org/10.1029/2024EA003735","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>Since the 2018 launch of NASA's ICESat-2 satellite, numerous studies have documented the bathymetric measurement capabilities of the space-based laser altimeter. However, a commonly identified limitation of ICESat-2 bathymetric point clouds is that they lack accompanying spectral reflectance attributes, or even intensity values, which have been found useful for benthic habitat mapping with airborne bathymetric lidar. We present a novel method for extracting bathymetry from ICESat-2 data and automatically adding spectral reflectance values from Sentinel-2 imagery to each detected bathymetric point. This method, which leverages the cloud computing systems Google Earth Engine and NASA's SlideRule Earth, is ideally suited for “big data” projects with ICESat-2 data products. To demonstrate the scalability of our workflow, we collected 3,500 ICESat-2 segments containing approximately 1.4 million spectrally-attributed bathymetric points. We then used this data set to facilitate training of a deep recurrent neural network for classifying benthic habitats at the ICESat-2 photon level. We trained two identical models, one with and one without the spectral attributes, to investigate the benefits of fusing ICESat-2 photons with Sentinel-2. The results show an improvement in model performance of 18 percentage points, based on F1 score. The procedures and source code are publicly available and will enhance the value of the new ICESat-2 bathymetry data product, ATL24, which is scheduled for release in Fall 2024. These procedures may also be applicable to data from NASA's upcoming CASALS mission.</p>\u0000 </section>\u0000 </div>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 11","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003735","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540826","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":"How to Find Accurate Terrain and Canopy Height GEDI Footprints in Temperate Forests and Grasslands?","authors":"Vítězslav Moudrý,&nbsp;Jiří Prošek,&nbsp;Suzanne Marselis,&nbsp;Jana Marešová,&nbsp;Eliška Šárovcová,&nbsp;Kateřina Gdulová,&nbsp;Giorgi Kozhoridze,&nbsp;Michele Torresani,&nbsp;Duccio Rocchini,&nbsp;Anette Eltner,&nbsp;Xiao Liu,&nbsp;Markéta Potůčková,&nbsp;Adéla Šedová,&nbsp;Pablo Crespo-Peremarch,&nbsp;Jesús Torralba,&nbsp;Luis A. Ruiz,&nbsp;Michela Perrone,&nbsp;Olga Špatenková,&nbsp;Jan Wild","doi":"10.1029/2024EA003709","DOIUrl":"https://doi.org/10.1029/2024EA003709","url":null,"abstract":"<p>Filtering approaches on Global Ecosystem Dynamics Investigation (GEDI) data differ considerably across existing studies and it is yet unclear which method is the most effective. We conducted an in-depth analysis of GEDI's vertical accuracy in mapping terrain and canopy heights across three study sites in temperate forests and grasslands in Spain, California, and New Zealand. We started with unfiltered data (2,081,108 footprints) and describe a workflow for data filtering using Level 2A parameters and for geolocation error mitigation. We found that retaining observations with at least one detected mode eliminates noise more effectively than sensitivity. The accuracy of terrain and canopy height observations depended considerably on the number of modes, beam sensitivity, landcover, and terrain slope. In dense forests, a minimum sensitivity of 0.9 was required, while in areas with sparse vegetation, sensitivity of 0.5 sufficed. Sensitivity greater than 0.9 resulted in an overestimation of canopy height in grasslands, especially on steep slopes, where high sensitivity led to the detection of multiple modes. We suggest excluding observations with more than five modes in grasslands. We found that the most effective strategy for filtering low-quality observations was to combine the quality flag and difference from TanDEM-X, striking an optimal balance between eliminating poor-quality data and preserving a maximum number of high-quality observations. Positional shifts improved the accuracy of GEDI terrain estimates but not of vegetation height estimates. Our findings guide users to an easy way of processing of GEDI footprints, enabling the use of the most accurate data and leading to more reliable applications.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003709","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525123","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":"Illuminating the Hierarchical Segmentation of Faults Through an Unsupervised Learning Approach Applied to Clouds of Earthquake Hypocenters","authors":"E. Piegari,&nbsp;G. Camanni,&nbsp;M. Mercurio,&nbsp;W. Marzocchi","doi":"10.1029/2023EA003267","DOIUrl":"https://doi.org/10.1029/2023EA003267","url":null,"abstract":"<p>We propose a workflow for the recognition of the hierarchical segmentation of faults through earthquake hypocenter clustering without prior information. Our approach combines density-based clustering algorithms (DBSCAN and OPTICS), and principal component analysis (PCA). Given a spatial distribution of earthquake hypocenters, DBSCAN identifies first-order clusters, representing regions with the highest density of connected seismic events. Within each first-order cluster, OPTICS further identifies nested higher-order clusters, providing information on their number and size. PCA analysis is applied to first- and higher-order clusters to evaluate eigenvalues, allowing discrimination between seismicity associated with planar features and distributed seismicity that remains uncategorized. The identified planes are then geometrically characterized in terms of their location and orientation in the space, length, and height. This automated procedure operates within two spatial scales: the largest scale corresponds to the longest pattern of approximately equally dense earthquake clouds, while the smallest scale relates to earthquake location errors. By applying PCA analysis, a planar feature outputted from a first-order cluster can be interpreted as a fault surface while planes outputted after OPTICS can be interpreted as fault segments comprised within the fault surface. The evenness between the orientation of illuminated fault surfaces and fault segments, and that of the nodal planes of earthquake focal mechanisms calculated along the same faults, corroborates this interpretation. Our workflow has been successfully applied to earthquake hypocenter distributions from various seismically active areas (Italy, Taiwan, and California) associated with faults exhibiting diverse kinematics.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EA003267","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525124","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":"A Simple and Robust CryoSat-2 Radar Freeboard Correction Method Dedicated to TFMRA50 for the Arctic Winter Snow Depth and Sea Ice Thickness Retrieval","authors":"Hoyeon Shi,&nbsp;Rasmus Tonboe,&nbsp;Sang-Moo Lee,&nbsp;Gorm Dybkjær,&nbsp;Byung-Ju Sohn,&nbsp;Suman Singha,&nbsp;Fabrizio Baordo","doi":"10.1029/2024EA003715","DOIUrl":"https://doi.org/10.1029/2024EA003715","url":null,"abstract":"<p>CryoSat-2 has been successful in observing sea ice thickness from space by providing ice freeboard information. The initial estimate of the ice freeboard, called radar freeboard, is obtained by analyzing the observed waveform using a retracker. A series of corrections are needed to convert the radar freeboard to the ice freeboard. Those are the physical effects (e.g., changes in wave propagation speed and the distribution of scattering at snow and ice surfaces, etc.) and the bias of the retracker; however, traditionally, only the wave speed correction has been applied due to lack of enough information to perform the complete correction. Here, an alternative correction method for the CryoSat-2 radar freeboard derived using the Threshold First-Maximum Retracker Algorithm with a 50% threshold (TFMRA50) is proposed. Snow depth was used as a predictor for the correction, similar to the traditional wave speed correction, but the coefficients were empirically determined by performing a direct comparison of the radar freeboard from CryoSat-2 and the ice freeboard from airborne observations. Consequently, this new empirical correction treats the physical effects and the retracker bias as a whole, which have been difficult to separate in the retrieval process. In this paper, we demonstrate that the retrieval accuracy of snow and ice variables and the consistency of the two independent retrieval methods are improved when the new correction is applied. The result of this study emphasizes the importance of compatibility between the retracker and the freeboard correction method.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003715","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525130","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":"Planetary Wave Signature in Low Latitude Sporadic E Layer Obtained From Multi-Mission Radio Occultation Observations","authors":"S. Sobhkhiz-Miandehi,&nbsp;Y. Yamazaki,&nbsp;C. Arras,&nbsp;Y. Miyoshi,&nbsp;H. Shinagawa,&nbsp;A. P. Jadhav","doi":"10.1029/2024EA003757","DOIUrl":"https://doi.org/10.1029/2024EA003757","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>The Sporadic E layer or Es is an ionospheric phenomenon characterized by enhancements in electron density within 90–120 km above the Earth's surface. Based on the wind shear theory, the formation of Es layers is associated with vertical shears in the horizontal wind, in the presence of the Earth's magnetic field. This study explores the role of planetary waves on inducing these vertical shears and subsequently shaping Es layers. Our investigations benefit from a large amount of data facilitated by the FORMOSAT-7/COSMIC2 and Spire missions, which offer extensive global coverage. A wave analysis is applied to the Es intensity as represented by the S4 index derived from radio occultation measurements, in search of potential planetary wave signatures. Additionally, measurements from Aura/MLS are used to analyze corresponding spectra for the geopotential height, enabling a comparative examination of planetary wave signatures in the Es layer and geopotential height variations. The findings reveal westward and eastward wave components with specific wavenumbers and periods, suggesting the involvement of westward propagating quasi 6-day, quasi 4-day planetary waves, and eastward propagating Kelvin waves with a period of around 3 days in Es layer formation at low latitudes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003757","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525529","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":"TANAGER: Design and Validation of an Automated Spectrogoniometer for Bidirectional Reflectance Studies of Natural Rock Surfaces","authors":"Melissa Rice,&nbsp;Kristiana Lapo,&nbsp;Kathleen Hoza,&nbsp;Ed Cloutis,&nbsp;Mike Kraft,&nbsp;Sean Mulcahy,&nbsp;Dan Applin,&nbsp;Samantha Theuer","doi":"10.1029/2024EA003686","DOIUrl":"https://doi.org/10.1029/2024EA003686","url":null,"abstract":"<p>Laboratory measurements of reflectance spectra of rocks and minerals at multiple viewing geometries are important for interpreting spacecraft data of planetary surfaces. However, efficiently acquiring such measurements is challenging, as it requires a custom goniometer that can accommodate multiple, bulky samples beneath a movable light source and detector. Most spectrogoniometric laboratory work to date has focused on mineral mixtures and particulates, yet it is also critical to characterize natural rock surfaces to understand the influence of texture and alteration. We designed the Three-Axis N-sample Automated Goniometer for Evaluating Reflectance (TANAGER) specifically to rapidly acquire spectra of natural rock surfaces across the full scattering hemisphere. TANAGER has its light source and the spectrometer's fiber optic mounted on rotating and tilting arcs, with a rotating azimuth stage and six-position sample tray, all of which are fully motorized and integrated with a Malvern PanAnalytical ASD FieldSpec4 Hi-Res reflectance spectrometer. Using well-characterized color calibration targets, we have validated the accuracy and repeatability of TANAGER spectra. We also confirm that the system introduces no discernible noise or artifacts. All design schematics and control software for TANAGER are open-source and available for use and modification by the larger scientific community.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003686","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525125","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":"Deep-Learning Based Causal Inference: A Feasibility Study Based on Three Years of Tectonic-Climate Data From Moxa Geodynamic Observatory","authors":"Wasim Ahmad,&nbsp;Valentin Kasburg,&nbsp;Nina Kukowski,&nbsp;Maha Shadaydeh,&nbsp;Joachim Denzler","doi":"10.1029/2023EA003430","DOIUrl":"https://doi.org/10.1029/2023EA003430","url":null,"abstract":"<p>Highly sensitive laser strainmeters at Moxa Geodynamic Observatory (MGO) measure motions of the upper Earth's crust. Since the mountain overburden of the laser strainmeters installed in the gallery of the observatory is relatively low, the recorded time series are strongly influenced by local meteorological phenomena. To estimate the nonlinear effect of the meteorological variables on strain measurements in a non-stationary environment, advanced methods capable of learning the nonlinearity and discovering causal relationships in the non-stationary multivariate tectonic-climate time series are needed. Methods for causal inference generally perform well in identifying linear causal relationships but often struggle to retrieve complex nonlinear causal structures prevalent in real-world systems. This work presents a novel <i>model invariance-based causal discovery</i> (CDMI) method that utilizes deep networks to model nonlinearity in a multivariate time series system. We propose to use the theoretically well-established Knockoffs framework to generate in-distribution, uncorrelated copies of the original data as interventional variables and test the model invariance for causal discovery. To deal with the non-stationary behavior of the tectonic-climate time series recorded at the MGO, we propose a regime identification approach that we apply before causal analysis to generate segments of time series that possess locally consistent statistical properties. First, we evaluate our method on synthetically generated time series by comparing it to other causal analysis methods. We then investigate the hypothesized effect of meteorological variables on strain measurements. Our approach outperforms other causality methods and provides meaningful insights into tectonic-climate causal interactions.</p>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2023EA003430","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525128","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":"Observing System Simulation Experiments Exploring Potential Spaceborne Deployment Options for a Differential Absorption Radar Measuring Marine Surface Pressures","authors":"N. C. Privé,&nbsp;Matthew McLinden,&nbsp;Bing Lin,&nbsp;G. M. Heymsfield,&nbsp;Xia Cai,&nbsp;Steven Harrah","doi":"10.1029/2024EA003791","DOIUrl":"https://doi.org/10.1029/2024EA003791","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <p>A new technology for remote measurements of marine surface pressure has been proposed, employing a V-band differential absorption radar and a radiometric temperature sounder to calculate the total column atmospheric mass. Observing System Simulation Experiments (OSSEs) are performed to evaluate the potential impact of Spaceborne Marine Surface Pressure (SMSP) on Numerical Weather Prediction. These experiments build on prior efforts (Privé, McLinden, et al., 2023, https://doi.org/10.16993/tellusa.3254), but with an updated version of the OSSE framework and with more sophisticated simulation of the SMSP observations and a longer experiment period. Several different instrument configurations are compared, including both scanning and non-scanning orbits. SMSP impacts are calculated for analysis quality and forecast skill, and a forecast sensitivity observation impact tool is employed to place SMSP observations in context with the global observing network. The effects of rain contamination on observation quality are explored. Different magnitudes of simulated SMSP observation error are tested in the context of data assimilation to show the range of potential behaviors. Overall, SMSP observations are found to be most beneficial in the southern hemisphere extratropics, with statistically significant forecast improvements for the first 72 hr of the forecast. A constellation of four non-scanning SMSP satellites is found to outperform a single scanning instrument with a 250 km wide swath.</p>\u0000 </section>\u0000 </div>","PeriodicalId":54286,"journal":{"name":"Earth and Space Science","volume":"11 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EA003791","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525126","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}