Pub Date : 2024-07-25DOI: 10.1175/jtech-d-22-0148.1
Xiong Xiong, Zhongbao Jiang, Hongsheng Tang, An Ran, Liu Yuzhu, X. Ye
This article aims to improve the quality control (QC) of surface daily temperature observations over complex physical geography. A new QC method based on multi-verse optimization algorithm, variational modal decomposition and kernel extreme learning machine was employed to identify potential outliers (the MVO-VMD-KELM method). For the selected six regions with complex physical geography, the inverse distance weighting (IDW), the spatial regression test (SRT), the kernel extreme learning machine (KELM), and the empirical mode decomposition improved KELM (EMD-KELM) methods were employed to test the proposed method. The results indicate that the MVO-VMD-KELM method outperformed other methods in all the cases. The MVO-VMD-KELM method yielded better mean absolute error (MAE), root mean square error (RMSE), index of agreement (IOA) and Nash-Sutcliffe model efficiency coefficient (NSC) values than others via the analysis of evaluation metrics for different cases. The comparison results led to the recommendation that the proposed method is an effective quality control method in identifying the seeded errors for the surface daily temperature observations.
{"title":"Research on Quality Control Method of Surface Temperature Observations for Complex Physical Geography","authors":"Xiong Xiong, Zhongbao Jiang, Hongsheng Tang, An Ran, Liu Yuzhu, X. Ye","doi":"10.1175/jtech-d-22-0148.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0148.1","url":null,"abstract":"\u0000This article aims to improve the quality control (QC) of surface daily temperature observations over complex physical geography. A new QC method based on multi-verse optimization algorithm, variational modal decomposition and kernel extreme learning machine was employed to identify potential outliers (the MVO-VMD-KELM method). For the selected six regions with complex physical geography, the inverse distance weighting (IDW), the spatial regression test (SRT), the kernel extreme learning machine (KELM), and the empirical mode decomposition improved KELM (EMD-KELM) methods were employed to test the proposed method. The results indicate that the MVO-VMD-KELM method outperformed other methods in all the cases. The MVO-VMD-KELM method yielded better mean absolute error (MAE), root mean square error (RMSE), index of agreement (IOA) and Nash-Sutcliffe model efficiency coefficient (NSC) values than others via the analysis of evaluation metrics for different cases. The comparison results led to the recommendation that the proposed method is an effective quality control method in identifying the seeded errors for the surface daily temperature observations.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141804378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.1175/jtech-d-23-0159.1
E. Zaron, S. Elipot
Internal waves generated by the interaction of the surface tides with topography are known to propagate long distances and lead to observable effects such as sea level variability, ocean currents, and mixing. In an effort to describe and predict these waves, the present work is concerned with using geographically-distributed data from satellite altimeters and drifting buoys to estimate and map the baroclinic sea level associated with the M2, S2, N2, K1, and O1 tides. A new mapping methodology is developed, based on a mixed L1/L2-norm optimization, and compared with previously-developed methods for tidal estimation from altimeter data. The altimeter and drifter data are considered separately in their roles for estimating tides and for cross-validating estimates obtained with independent data. Estimates obtained from altimetry and drifter data are found to agree remarkably well in regions where the drifter trajectories are spatially dense; however, heterogeneity of the drifter trajectories is a disadvantage when they are considered alone for tidal estimation. When the different data types are combined by using geodetic-mission altimetry to cross-validate estimates obtained with either exact-repeat altimetry or drifter data, and subsequently averaging the latter estimates, the estimates significantly improve on the previously-published HRET8.1 model, as measured by their utility for predicting sea level and surface currents in the open ocean. The methodology has been applied to estimate the annual modulations of M2, which are found to have much smaller amplitudes compared to those reported in HRET8.1, and suggest that the latter estimates of these tides were not reliable.
{"title":"Estimates of Baroclinic Tidal Sea Level and Currents from Lagrangian Drifters and Satellite Altimetry","authors":"E. Zaron, S. Elipot","doi":"10.1175/jtech-d-23-0159.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0159.1","url":null,"abstract":"\u0000Internal waves generated by the interaction of the surface tides with topography are known to propagate long distances and lead to observable effects such as sea level variability, ocean currents, and mixing. In an effort to describe and predict these waves, the present work is concerned with using geographically-distributed data from satellite altimeters and drifting buoys to estimate and map the baroclinic sea level associated with the M2, S2, N2, K1, and O1 tides. A new mapping methodology is developed, based on a mixed L1/L2-norm optimization, and compared with previously-developed methods for tidal estimation from altimeter data. The altimeter and drifter data are considered separately in their roles for estimating tides and for cross-validating estimates obtained with independent data. Estimates obtained from altimetry and drifter data are found to agree remarkably well in regions where the drifter trajectories are spatially dense; however, heterogeneity of the drifter trajectories is a disadvantage when they are considered alone for tidal estimation. When the different data types are combined by using geodetic-mission altimetry to cross-validate estimates obtained with either exact-repeat altimetry or drifter data, and subsequently averaging the latter estimates, the estimates significantly improve on the previously-published HRET8.1 model, as measured by their utility for predicting sea level and surface currents in the open ocean. The methodology has been applied to estimate the annual modulations of M2, which are found to have much smaller amplitudes compared to those reported in HRET8.1, and suggest that the latter estimates of these tides were not reliable.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141652235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Generally, sea ice prediction skills can be improved by assimilating available observations of the sea ice concentration (SIC) and sea ice thickness (SIT) into a numerical forecast model to update the initial conditions. However, due to inadequate daily SIT satellite observations in the Arctic melting season, the SIC fields in forecast models are usually directly updated, which causes mismatch of SIC and SIT in dynamics and affects the model prediction accuracy. In this study, a statistically based bivariate regression model of SIT (BRMT) is tentatively established based on the grid reanalysis data of SIC and SIT to reconstruct daily Arctic SIT data. The results show that the BRMT can reproduce the spatial and temporal changes in the SIT in the melting season and capture the variation trend of SIT in some periods. Compared with the SIT observations from buoy and satellite, the reconstructed SIT shows better performance in the central Arctic than other datasets. Furthermore, when the reconstructed SIT is added to the forecast model with only assimilated SIC, the forecast accuracy of SIC, sea ice extent, and SIT in the Arctic melting season is improved and does not weaken with the increase in the forecast time. Especially in the central Arctic, the average absolute deviation between 24-h SIT forecast results and observations is only 0.16 m. The results indicate great potential for applying the reconstructed SIT to the operational forecast of Arctic sea ice during the melting season in the future. To improve the prediction skills of Arctic sea ice, it is necessary to assimilate the sea ice observation into the dynamic model to generate a more realistic initial prediction field. At present, the observation data of daily sea ice thickness (SIT) during the Arctic melting season are few, which cannot well meet the demand of operational SIT forecast. In this study, a bivariate regression model is put forward to construct SIT using the sea ice concentration (SIC) observation. Benefitting from the joint assimilation of the observed SIC and the reconstructed SIT, the forecast accuracy of sea ice variables is greatly improved. The reconstructed SIT is expected to provide an available dataset for further research on the Arctic sea ice forecast.
一般来说，将现有的海冰浓度（SIC）和海冰厚度（SIT）观测资料同化到数值预报模式中更新初始条件，可以提高海冰预报能力。然而，由于北极融化季每日海冰厚度卫星观测数据不足，预报模式中的海冰浓度场通常直接更新，这就造成了海冰浓度和海冰厚度在动力学上的不匹配，影响了模式的预报精度。本研究基于 SIC 和 SIT 的网格再分析数据，初步建立了基于统计的 SIT 双变量回归模型（BRMT），用于重建北极 SIT 日数据。结果表明，BRMT能够再现融化季SIT的时空变化，并能捕捉到某些时段SIT的变化趋势。与浮标和卫星观测到的 SIT 相比，重建的 SIT 在北极中部的表现优于其他数据集。此外，当将重建的 SIT 加入到仅同化 SIC 的预报模式中时，北极融化季的 SIC、海冰范围和 SIT 的预报精度都得到了提高，并且不会随着预报时间的延长而减弱。特别是在北极中部地区，24 h SIT 预报结果与观测结果的平均绝对偏差仅为 0.16 m。结果表明，未来将重建的 SIT 应用于北极融化季海冰业务预报的潜力巨大。目前，北极融化季的日海冰厚度（SIT）观测数据较少，不能很好地满足业务化 SIT 预报的需求。本研究提出了一种利用海冰浓度（SIC）观测数据构建 SIT 的双变量回归模型。得益于观测到的 SIC 和重建的 SIT 的联合同化，海冰变量的预报精度大大提高。重建的 SIT 可望为北极海冰预报的进一步研究提供可用数据集。
{"title":"Reconstruction of Arctic Sea Ice Thickness and Its Impact on Sea Ice Forecasting in the Melting Season","authors":"Lu-feng Yang, Hongli Fu, Xiaofan Luo, Xuefeng Zhang","doi":"10.1175/jtech-d-23-0049.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0049.1","url":null,"abstract":"\u0000Generally, sea ice prediction skills can be improved by assimilating available observations of the sea ice concentration (SIC) and sea ice thickness (SIT) into a numerical forecast model to update the initial conditions. However, due to inadequate daily SIT satellite observations in the Arctic melting season, the SIC fields in forecast models are usually directly updated, which causes mismatch of SIC and SIT in dynamics and affects the model prediction accuracy. In this study, a statistically based bivariate regression model of SIT (BRMT) is tentatively established based on the grid reanalysis data of SIC and SIT to reconstruct daily Arctic SIT data. The results show that the BRMT can reproduce the spatial and temporal changes in the SIT in the melting season and capture the variation trend of SIT in some periods. Compared with the SIT observations from buoy and satellite, the reconstructed SIT shows better performance in the central Arctic than other datasets. Furthermore, when the reconstructed SIT is added to the forecast model with only assimilated SIC, the forecast accuracy of SIC, sea ice extent, and SIT in the Arctic melting season is improved and does not weaken with the increase in the forecast time. Especially in the central Arctic, the average absolute deviation between 24-h SIT forecast results and observations is only 0.16 m. The results indicate great potential for applying the reconstructed SIT to the operational forecast of Arctic sea ice during the melting season in the future.\u0000\u0000\u0000To improve the prediction skills of Arctic sea ice, it is necessary to assimilate the sea ice observation into the dynamic model to generate a more realistic initial prediction field. At present, the observation data of daily sea ice thickness (SIT) during the Arctic melting season are few, which cannot well meet the demand of operational SIT forecast. In this study, a bivariate regression model is put forward to construct SIT using the sea ice concentration (SIC) observation. Benefitting from the joint assimilation of the observed SIC and the reconstructed SIT, the forecast accuracy of sea ice variables is greatly improved. The reconstructed SIT is expected to provide an available dataset for further research on the Arctic sea ice forecast.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141838729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-17DOI: 10.1175/jtech-d-23-0124.1
Pieter B. Smit, Galen Egan, Isabel Houghton
Peak periods estimated from finite resolution frequency spectra are necessarily discrete. For wind generated surface gravity waves, conflicting considerations of robust (quasi)-stationary statistics, and high spectral resolution, combined with the inverse relation between frequency and period, this typically implies that swell periods (above 10 s) are resolved at best at 𝒪(1) s intervals. Here we consider a method to improve peak period estimates for finite resolution spectra. Specifically, we propose to define the peak period based on continuous spectra derived from a spline-based interpolation of the discretely sampled monotone cumulative distribution function. The method may directly be applied to existing discrete spectra—the original time-domain data (which may not be available) are not required. We compare reconstructed spectra and derived peak periods to parametric shapes and field data. Peak estimates are markedly improved, allowing for better tracking of e.g., swells. The proposed method also marginally improves spectral levels and shape for a given discretely sampled estimate.
{"title":"Continuous peak period estimates from discrete surface-wave spectra","authors":"Pieter B. Smit, Galen Egan, Isabel Houghton","doi":"10.1175/jtech-d-23-0124.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0124.1","url":null,"abstract":"\u0000Peak periods estimated from finite resolution frequency spectra are necessarily discrete. For wind generated surface gravity waves, conflicting considerations of robust (quasi)-stationary statistics, and high spectral resolution, combined with the inverse relation between frequency and period, this typically implies that swell periods (above 10 s) are resolved at best at 𝒪(1) s intervals. Here we consider a method to improve peak period estimates for finite resolution spectra. Specifically, we propose to define the peak period based on continuous spectra derived from a spline-based interpolation of the discretely sampled monotone cumulative distribution function. The method may directly be applied to existing discrete spectra—the original time-domain data (which may not be available) are not required. We compare reconstructed spectra and derived peak periods to parametric shapes and field data. Peak estimates are markedly improved, allowing for better tracking of e.g., swells. The proposed method also marginally improves spectral levels and shape for a given discretely sampled estimate.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140692563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-09DOI: 10.1175/jtech-d-22-0147.1
Xiaoyan Chen, G. Quartly, Ge Chen
Argo floats are widely used to characterize vertical structures of ocean eddies, yet their capability to invert sea-surface features of eddies, especially those overlooked by available altimeters, has not been explored. In this paper, we propose an “interior-to-surface” inversion algorithm to effectively expand the capacity of eddy detection by estimating altimeter-missed eddies’ surface attributes from their Argo-derived potential density anomaly profiles, given that interior property and surface signature of eddies are highly correlated. An altimeter-calibrated machine learning ensemble is employed for the inversion training based on the joint altimeter-Argo eddy data and shows promising performance with mean absolute errors of 5.4 km, 0.5 cm, and 14.3 cm2/s2 for eddy radius, amplitude, and kinetic energy. Then, the trained ensemble model is applied to independently invert the properties of eddies captured by an Argo-alone detection scheme, which yields a high spatiotemporal consistency with their altimeter-captured counterparts. In particular, a portion of Argo-alone eddies is ~25% smaller than altimeter-derived ones, indicating Argo’s unique capability of profiling weaker submesoscale eddies. Sea surface temperature and chlorophyll data are further applied to validate the reliability of eddies identified and characterized by the Argo-only algorithm. This new methodology effectively complements that of altimetry in eddy detecting and can be expanded to estimate other physical/biochemical eddy variables from a variety of in-situ observations.
{"title":"Eddy detection inverted from Argo profiles to surface altimetry","authors":"Xiaoyan Chen, G. Quartly, Ge Chen","doi":"10.1175/jtech-d-22-0147.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0147.1","url":null,"abstract":"\u0000Argo floats are widely used to characterize vertical structures of ocean eddies, yet their capability to invert sea-surface features of eddies, especially those overlooked by available altimeters, has not been explored. In this paper, we propose an “interior-to-surface” inversion algorithm to effectively expand the capacity of eddy detection by estimating altimeter-missed eddies’ surface attributes from their Argo-derived potential density anomaly profiles, given that interior property and surface signature of eddies are highly correlated. An altimeter-calibrated machine learning ensemble is employed for the inversion training based on the joint altimeter-Argo eddy data and shows promising performance with mean absolute errors of 5.4 km, 0.5 cm, and 14.3 cm2/s2 for eddy radius, amplitude, and kinetic energy. Then, the trained ensemble model is applied to independently invert the properties of eddies captured by an Argo-alone detection scheme, which yields a high spatiotemporal consistency with their altimeter-captured counterparts. In particular, a portion of Argo-alone eddies is ~25% smaller than altimeter-derived ones, indicating Argo’s unique capability of profiling weaker submesoscale eddies. Sea surface temperature and chlorophyll data are further applied to validate the reliability of eddies identified and characterized by the Argo-only algorithm. This new methodology effectively complements that of altimetry in eddy detecting and can be expanded to estimate other physical/biochemical eddy variables from a variety of in-situ observations.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140722608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-25DOI: 10.1175/jtech-d-23-0129.1
Falk Feddersen, Olavo B. Marques, James H. MacMahan, Robert L. Grenzeback
Wave spectra and directional moment measurements are of scientific and engineering interest and are routinely estimated with wave buoys. Recently, both fixed-location and Uncrewed Aircraft System (UAS)-mounted lidar have estimated surfzone wave spectra. However, nearshore wave statistics seaward of the surfzone have not been measured with lidar due to low return number and nearshore directional moments have not been measured at all. We use a multi-beam scanning lidar mounted on a gasoline-powered UAS to estimate wave spectra, wave slope spectra, and directional moments on the inner shelf in ≈ 10 m water depth from an 11-min hover and compare to a co-located wave buoy. Lidar returns within circular sampling regions with varying radius R are fit to a plane and a 2D parabola, providing sea-surface and slope timeseries. Wave spectra across the sea-swell (0.04–0.4 Hz) are robustly estimated for R ≥ 0.8 m. Estimating slope spectra is more challenging. Large R works well in the swell band and smaller R work well at higher frequencies, in good agreement with a wave buoy inferred slope spectrum. Directional Fourier coefficients, estimated from wave and slope spectra and cross-spectra, are compared to a wave buoy in the sea-swell band. Larger R and the 2D parabola-fit yield better comparison to the wave buoy. Mean wave angles and directional spreads, functions of the directional Fourier coefficients, are well reproduced at R = 2.4 m and the 2D parabola-fit, within the uncertainties of the wave buoy. The internal consistency of the UAS-lidar-derived results and their good comparison to the Spotter wave buoy demonstrate the effectiveness of this tool for estimating wave statistics.
波谱和方向力矩测量具有科学和工程学意义，通常使用波浪浮标进行估算。最近，安装在固定地点和无人驾驶飞机系统（UAS）上的激光雷达估算了冲浪区的波谱。然而，由于回波数较低，激光雷达还没有测量过冲浪区海面的近岸波浪统计量，也没有测量过近岸方向力矩。我们使用安装在以汽油为动力的无人机系统上的多波束扫描激光雷达，通过 11 分钟的悬停，估算了水深≈ 10 米的内陆架的波谱、波坡谱和方向矩，并与同位波浪浮标进行了比较。半径 R 不同的圆形采样区域内的激光雷达回波与平面和二维抛物线拟合，提供海面和斜坡时间序列。当 R ≥ 0.8 米时，可以稳健地估算出海面波谱（0.04-0.4 赫兹）。大 R 在涌浪波段效果好，小 R 在较高频率效果好，与波浪浮标推断的斜率谱很一致。根据波谱、坡谱和横谱估算出的方向傅里叶系数与海涌波段的波浪浮标进行了比较。较大的 R 和二维抛物线拟合与波浪浮标的比较结果更好。在 R = 2.4 米和二维抛物线拟合条件下，在波浪浮标的不确定性范围内，平均波浪角和方向展宽（方向傅里叶系数的函数）得到了很好的再现。无人机系统激光雷达衍生结果的内部一致性及其与 Spotter 波浪浮标的良好对比证明了该工具在估算波浪统计数据方面的有效性。
{"title":"Estimating Directional Wave Spectra Properties in Non-Breaking Waves from a UAS-Mounted Multi-beam Lidar","authors":"Falk Feddersen, Olavo B. Marques, James H. MacMahan, Robert L. Grenzeback","doi":"10.1175/jtech-d-23-0129.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0129.1","url":null,"abstract":"\u0000Wave spectra and directional moment measurements are of scientific and engineering interest and are routinely estimated with wave buoys. Recently, both fixed-location and Uncrewed Aircraft System (UAS)-mounted lidar have estimated surfzone wave spectra. However, nearshore wave statistics seaward of the surfzone have not been measured with lidar due to low return number and nearshore directional moments have not been measured at all. We use a multi-beam scanning lidar mounted on a gasoline-powered UAS to estimate wave spectra, wave slope spectra, and directional moments on the inner shelf in ≈ 10 m water depth from an 11-min hover and compare to a co-located wave buoy. Lidar returns within circular sampling regions with varying radius R are fit to a plane and a 2D parabola, providing sea-surface and slope timeseries. Wave spectra across the sea-swell (0.04–0.4 Hz) are robustly estimated for R ≥ 0.8 m. Estimating slope spectra is more challenging. Large R works well in the swell band and smaller R work well at higher frequencies, in good agreement with a wave buoy inferred slope spectrum. Directional Fourier coefficients, estimated from wave and slope spectra and cross-spectra, are compared to a wave buoy in the sea-swell band. Larger R and the 2D parabola-fit yield better comparison to the wave buoy. Mean wave angles and directional spreads, functions of the directional Fourier coefficients, are well reproduced at R = 2.4 m and the 2D parabola-fit, within the uncertainties of the wave buoy. The internal consistency of the UAS-lidar-derived results and their good comparison to the Spotter wave buoy demonstrate the effectiveness of this tool for estimating wave statistics.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140382579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-05DOI: 10.1175/jtech-d-23-0091.1
T. Swaim, E. Hough, Z. Yap, J. Jacob, S. Krishnamoorthy, Daniel C. Bowman, L. Martire, A. Komjathy, B. Elbing
Heliotropes are passive solar hot air balloons that are capable of achieving nearly level flight within the lower stratosphere for several hours. These inexpensive flight platforms enable stratospheric sensing with high-cadence enabled by the low cost to manufacture, but their performance has not yet been assessed systematically. During July to September of 2021, 29 heliotropes were successfully launched from Oklahoma and achieved float altitude as part of the Balloon-based Acoustic Seismology Study (BASS). All of the heliotrope envelopes were nearly identical with only minor variations to the flight line throughout the campaign. Flight data collected during this campaign comprise a large sample to characterize the typical heliotrope flight behavior during launch, ascent, float, and descent. Each flight stage is characterized, dependence on various parameters is quantified, and a discussion of nominal and anomalous flights is provided.
{"title":"Performance Characterization of Heliotrope Solar Hot-Air Balloons during Multihour Stratospheric Flights","authors":"T. Swaim, E. Hough, Z. Yap, J. Jacob, S. Krishnamoorthy, Daniel C. Bowman, L. Martire, A. Komjathy, B. Elbing","doi":"10.1175/jtech-d-23-0091.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0091.1","url":null,"abstract":"\u0000Heliotropes are passive solar hot air balloons that are capable of achieving nearly level flight within the lower stratosphere for several hours. These inexpensive flight platforms enable stratospheric sensing with high-cadence enabled by the low cost to manufacture, but their performance has not yet been assessed systematically. During July to September of 2021, 29 heliotropes were successfully launched from Oklahoma and achieved float altitude as part of the Balloon-based Acoustic Seismology Study (BASS). All of the heliotrope envelopes were nearly identical with only minor variations to the flight line throughout the campaign. Flight data collected during this campaign comprise a large sample to characterize the typical heliotrope flight behavior during launch, ascent, float, and descent. Each flight stage is characterized, dependence on various parameters is quantified, and a discussion of nominal and anomalous flights is provided.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140264690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-01DOI: 10.1175/jtech-d-23-0037.1
Elizabeth M. Berg, Louis Urtecho, S. Krishnamoorthy, Elizabeth Silber, Andrew Sparks, D. C. Bowman
Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation. Convective vortices, or “dust devils,” contribute to regional dust loading in Earth’s atmosphere. However, long-duration convective vortex activity records are rare. We came up with a way to autonomously detect the pressure signatures left by convective vortices striking low-frequency sound, or “infrasound,” sensors. Since permanent infrasound stations have been active for decades, our method has the potential to add orders-of-magnitude more events than previously catalogued.
{"title":"An Accurate and Automated Convective Vortex Detection Method for Long-Duration Infrasound Microbarometer Data","authors":"Elizabeth M. Berg, Louis Urtecho, S. Krishnamoorthy, Elizabeth Silber, Andrew Sparks, D. C. Bowman","doi":"10.1175/jtech-d-23-0037.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0037.1","url":null,"abstract":"\u0000Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation.\u0000\u0000\u0000Convective vortices, or “dust devils,” contribute to regional dust loading in Earth’s atmosphere. However, long-duration convective vortex activity records are rare. We came up with a way to autonomously detect the pressure signatures left by convective vortices striking low-frequency sound, or “infrasound,” sensors. Since permanent infrasound stations have been active for decades, our method has the potential to add orders-of-magnitude more events than previously catalogued.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140407135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-29DOI: 10.1175/jtech-d-23-0111.1
Ning Yang, Debin Su, Luyao Sun, Tao Wang
Atmospheric ducting is a highly refractive propagation condition that frequently occurs at sea and significantly impacts radar and communication equipment. This paper analyzes the spatiotemporal distribution of Lower Atmospheric Ducts (LAD) in the South China Sea (SCS) and the variation of their occurrence rate with the monsoon by using reanalysis data from the ECMWF from 1980 to 2022. Additionally, the study discusses the relationship between ducting occurrences and atmospheric and oceanic conditions. The results indicate that wind dynamics in the SCS significantly impact ducting incidents. During the high-incidence period of LAD, humidity gradient-constructed ducts are the primary mechanism. Before the onset of the monsoon, the mountains in the western part of Luzon Island obstruct the easterly wind, resulting in high temperatures and strong evaporation along the western coast of the mountains. Meanwhile, low temperatures and humidity prevail in the eastern part of the mountains, it leads to a stratified atmosphere characterized by dry and cold upper layers and warm and humid lower layers in the western part of Luzon Island, which causes a distinct decrease in humidity with height. After the onset of the monsoon, the air from the Indochina Peninsula to the ocean is dry and cold, but the high-altitude area blocks it. This weakens the horizontal mobility of the low-level humid atmosphere over the sea, resulting in atmospheric stratification in the eastern coastal area of the Indochina Peninsula. This stratification leads to dry and cold upper layers and warm and humid lower layers.
{"title":"Lower Atmospheric Ducts Over the South China Sea Related to the Monsoon, Atmospheric and Ocean Conditions Based on ECMWF Reanalysis Data","authors":"Ning Yang, Debin Su, Luyao Sun, Tao Wang","doi":"10.1175/jtech-d-23-0111.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0111.1","url":null,"abstract":"\u0000Atmospheric ducting is a highly refractive propagation condition that frequently occurs at sea and significantly impacts radar and communication equipment. This paper analyzes the spatiotemporal distribution of Lower Atmospheric Ducts (LAD) in the South China Sea (SCS) and the variation of their occurrence rate with the monsoon by using reanalysis data from the ECMWF from 1980 to 2022. Additionally, the study discusses the relationship between ducting occurrences and atmospheric and oceanic conditions. The results indicate that wind dynamics in the SCS significantly impact ducting incidents. During the high-incidence period of LAD, humidity gradient-constructed ducts are the primary mechanism. Before the onset of the monsoon, the mountains in the western part of Luzon Island obstruct the easterly wind, resulting in high temperatures and strong evaporation along the western coast of the mountains. Meanwhile, low temperatures and humidity prevail in the eastern part of the mountains, it leads to a stratified atmosphere characterized by dry and cold upper layers and warm and humid lower layers in the western part of Luzon Island, which causes a distinct decrease in humidity with height. After the onset of the monsoon, the air from the Indochina Peninsula to the ocean is dry and cold, but the high-altitude area blocks it. This weakens the horizontal mobility of the low-level humid atmosphere over the sea, resulting in atmospheric stratification in the eastern coastal area of the Indochina Peninsula. This stratification leads to dry and cold upper layers and warm and humid lower layers.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140415437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Satellite remote sensing can monitor sea level changes at temporal and spatial scales, plays an important role in the study of tides, and is widely used in numerical tidal models. However, these tidal models are usually computationally expensive. The equidistant nodes orthogonal polynomial fitting (ENOPF) method may overcome that drawback. This study evaluates the accuracy of the ENOPF method in fitting the major tidal constituents in the region near the Ryukyu Islands, where the water depth on either side of the islands varies significantly. The results show that the ENOPF method can accurately fit the major tidal constituents in the presence of complex topography. Furthermore, this approach can also be used to generate reasonable cotidal charts and provide valuable tidal information for hydrodynamic model simulations in the East China Sea. For the high-resolution hydrodynamic model of the East China Sea in particular, reasonable open boundary conditions can be provided by the ENOPF method.
{"title":"Assessing Tidal Models in the Ryukyu Islands Region Using the ENOPF Method","authors":"Yibo Zhang, Chunzheng Kong, Zizhou Liu, Bingtian Li, Xianqing Lv","doi":"10.1175/jtech-d-23-0101.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0101.1","url":null,"abstract":"\u0000Satellite remote sensing can monitor sea level changes at temporal and spatial scales, plays an important role in the study of tides, and is widely used in numerical tidal models. However, these tidal models are usually computationally expensive. The equidistant nodes orthogonal polynomial fitting (ENOPF) method may overcome that drawback. This study evaluates the accuracy of the ENOPF method in fitting the major tidal constituents in the region near the Ryukyu Islands, where the water depth on either side of the islands varies significantly. The results show that the ENOPF method can accurately fit the major tidal constituents in the presence of complex topography. Furthermore, this approach can also be used to generate reasonable cotidal charts and provide valuable tidal information for hydrodynamic model simulations in the East China Sea. For the high-resolution hydrodynamic model of the East China Sea in particular, reasonable open boundary conditions can be provided by the ENOPF method.","PeriodicalId":507668,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140417498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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