Pub Date : 2023-10-01DOI: 10.1175/jtech-d-23-0015.1
Zhen Wang, Yini Chen, Liangyu Liu, Hao Yuan, Li Zou
Abstract Currents have a significant impact on wave parameters around islands. In this study, high-resolution unsteady current simulations based on island geography and wind fields from Weather Research and Forecasting (WRF) Model are used as input sources. The wave action balance model uses an unstructured grid to assess the wave conditions in the Atoll during Typhoon Noul. The characteristic wave parameters, with and without the effect of currents, are compared with the field observation data, including significant wave height, wave period, and the spatial distribution of significant wave height. The results show that simulated significant wave heights and wave periods are close to observed data, considering the effect of currents. The energy and shape of the spectrum are also verified during Typhoon Noul, and the observed agreement is improved when considering the currents. The effects of current within the Atoll are relatively weaker compared to the surroundings, while stronger current effects are observed in the deeper water outside the Atoll. Refraction caused by current expands the area of moderate sea state behind the island. Significance Statement Several innovations of this article are as follows: 1) the influence of currents on wave conditions at the Atoll; 2) exploring the impact of currents using key parameters, such as significant wave height, wave period, and wave spectrum, especially during the passage of Typhoon Noul; 3) swell emerges as the dominant factor influencing wave conditions as the center of Typhoon Noul gradually moves away; and 4) refraction caused by current expands the area of moderate sea state behind the island.
{"title":"Current Effect on Wave Condition around Island in the South China Sea","authors":"Zhen Wang, Yini Chen, Liangyu Liu, Hao Yuan, Li Zou","doi":"10.1175/jtech-d-23-0015.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0015.1","url":null,"abstract":"Abstract Currents have a significant impact on wave parameters around islands. In this study, high-resolution unsteady current simulations based on island geography and wind fields from Weather Research and Forecasting (WRF) Model are used as input sources. The wave action balance model uses an unstructured grid to assess the wave conditions in the Atoll during Typhoon Noul. The characteristic wave parameters, with and without the effect of currents, are compared with the field observation data, including significant wave height, wave period, and the spatial distribution of significant wave height. The results show that simulated significant wave heights and wave periods are close to observed data, considering the effect of currents. The energy and shape of the spectrum are also verified during Typhoon Noul, and the observed agreement is improved when considering the currents. The effects of current within the Atoll are relatively weaker compared to the surroundings, while stronger current effects are observed in the deeper water outside the Atoll. Refraction caused by current expands the area of moderate sea state behind the island. Significance Statement Several innovations of this article are as follows: 1) the influence of currents on wave conditions at the Atoll; 2) exploring the impact of currents using key parameters, such as significant wave height, wave period, and wave spectrum, especially during the passage of Typhoon Noul; 3) swell emerges as the dominant factor influencing wave conditions as the center of Typhoon Noul gradually moves away; and 4) refraction caused by current expands the area of moderate sea state behind the island.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135965843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.1175/jtech-d-23-0043.1
Katia Lamer, Pavlos Kollias, Edward P. Luke, Bernat P. Treserras, Mariko Oue, Brenda Dolan
Abstract Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at sub-km scale), and temporal evolution (at ~2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (the CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect 3 sector Plan Position Indicator (PPI) scans towards the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of 3-6 Range Height Indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a pre-determined set of criteria. Between 01 June and 30 September 2022 over 315,000 vertical cross-section observations were collected by the C-band radars through ~1,300 unique isolated convective cells, most of which were observed for over 15-min of their lifecycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.
{"title":"Multisensor Agile Adaptive Sampling (MAAS): a methodology to collect radar observations of convective cell lifecycle","authors":"Katia Lamer, Pavlos Kollias, Edward P. Luke, Bernat P. Treserras, Mariko Oue, Brenda Dolan","doi":"10.1175/jtech-d-23-0043.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0043.1","url":null,"abstract":"Abstract Multisensor Agile Adaptive Sampling (MAAS), a smart sensing framework, was adapted to increase the likelihood of observing the vertical structure (with little to no gaps), spatial variability (at sub-km scale), and temporal evolution (at ~2-min resolution) of convective cells. This adaptation of MAAS guided two mechanically scanning C-band radars (the CSAPR2 and CHIVO) by automatically analyzing the latest NEXRAD data to identify, characterize, track, and nowcast the location of all convective cells forming in the Houston domain. MAAS used either a list of predetermined rules or real-time user input to select a convective cell to be tracked and sampled by the C-band radars. The CSAPR2 tracking radar was first tasked to collect 3 sector Plan Position Indicator (PPI) scans towards the selected cell. Edge computer processing of the PPI scans was used to identify additional targets within the selected cell. In less than 2 min, both the CSAPR2 and CHIVO radars were able to collect bundles of 3-6 Range Height Indicator (RHI) scans toward different targets of interest within the selected cell. Bundles were successively collected along the path of cell advection for as long as the cell met a pre-determined set of criteria. Between 01 June and 30 September 2022 over 315,000 vertical cross-section observations were collected by the C-band radars through ~1,300 unique isolated convective cells, most of which were observed for over 15-min of their lifecycle. To the best of our knowledge, this dataset, collected primarily through automatic means, constitutes the largest dataset of its kind.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135245748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-21DOI: 10.1175/jtech-d-23-0036.1
Briana M. Wyatt, Nathan Leber, Mark Olden
Abstract Accurate, timely, and accessible meteorological and soil moisture measurements are essential for a number of applications including weather forecasting, agricultural decision making, and flood and drought prediction. Such data are becoming increasingly available globally, but the large number of networks and various data reporting formats often make utilization of such data difficult. The TexMesonet is a “network of networks” developed within the state of Texas to collect, process, and make public data collected from more than 1,700 monitoring stations throughout the state. This paper describes the TexMesonet, with special attention paid to monitoring sites installed and managed by the Texas Water Development Board. It also provides a case study exemplifying how these data may be used and gives recommendations for future data applications.
{"title":"Technical overview of the TexMesonet- a network of networks for improved water management and prediction in Texas","authors":"Briana M. Wyatt, Nathan Leber, Mark Olden","doi":"10.1175/jtech-d-23-0036.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0036.1","url":null,"abstract":"Abstract Accurate, timely, and accessible meteorological and soil moisture measurements are essential for a number of applications including weather forecasting, agricultural decision making, and flood and drought prediction. Such data are becoming increasingly available globally, but the large number of networks and various data reporting formats often make utilization of such data difficult. The TexMesonet is a “network of networks” developed within the state of Texas to collect, process, and make public data collected from more than 1,700 monitoring stations throughout the state. This paper describes the TexMesonet, with special attention paid to monitoring sites installed and managed by the Texas Water Development Board. It also provides a case study exemplifying how these data may be used and gives recommendations for future data applications.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136136705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-21DOI: 10.1175/jtech-d-23-0007.1
Christopher J. Roach, Nathaniel L. Bindoff
Abstract We present a new global oxygen atlas. This atlas uses all of the available full water column profiles of oxygen, salinity and temperature available as part of the World Ocean Atlas released in 2018. Instead of optimal interpolation we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° × 1/2° degree atlas covers the period 1955 to 2018 in 1 year intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints thus offering improvements in the representations of oxygen, salinity and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84%±0.42%. For this period temperature driven solubility changes explain about 21% of the oxygen decline over the full water column, in the upper 100 m solubility changes can explain all of the oxygen decrease, for the 100-600 m depth range it can explain only 29%, 19% between 600 m and 1000 m, and just 11% in the deep ocean.
{"title":"Developing a New Oxygen Atlas of the World’s Oceans Using Data Interpolating Variational Analysis","authors":"Christopher J. Roach, Nathaniel L. Bindoff","doi":"10.1175/jtech-d-23-0007.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0007.1","url":null,"abstract":"Abstract We present a new global oxygen atlas. This atlas uses all of the available full water column profiles of oxygen, salinity and temperature available as part of the World Ocean Atlas released in 2018. Instead of optimal interpolation we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° × 1/2° degree atlas covers the period 1955 to 2018 in 1 year intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints thus offering improvements in the representations of oxygen, salinity and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84%±0.42%. For this period temperature driven solubility changes explain about 21% of the oxygen decline over the full water column, in the upper 100 m solubility changes can explain all of the oxygen decrease, for the 100-600 m depth range it can explain only 29%, 19% between 600 m and 1000 m, and just 11% in the deep ocean.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136236465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-20DOI: 10.1175/jtech-d-23-0029.1
Jeremiah Sjoberg, Richard Anthes, Hailing Zhang
Abstract Estimation of uncertainties (random error statistics) of radio occultation (RO) observations is important for their effective assimilation in numerical weather prediction (NWP) models. Average uncertainties can be estimated for large samples of RO observations and these statistics may be used for specifying the observation errors in NWP data assimilation. However, the uncertainties of individual RO observations vary, and so using average uncertainty estimates will overestimate the uncertainties of some observations and underestimate those of others, reducing their overall effectiveness in the assimilation. Several parameters associated with RO observations or their atmospheric environments have been proposed to estimate individual RO errors. These include the standard deviation of bending angle (BA) departures from either climatology in the upper stratosphere and lower mesosphere (STDV) or the sample mean between 40 and 60 km (STD4060), the local spectral width (LSW), and the magnitude of the horizontal gradient of refractivity (|∇ H N|). In this paper we show how the uncertainties of two RO data sets, COSMIC-2 and Spire BA, as well as their combination, vary with these parameters. We find that the uncertainties are highly correlated with STDV and STD4060 in the stratosphere, and with LSW and |∇ H N| in the lower troposphere. These results suggest a hybrid error model for individual BA observations that uses an average statistical model of RO errors modified by STDV or STD4060 above 30 km, and LSW or |∇ H N| below 8 km.
{"title":"Estimating individual radio occultation uncertainties using the observations and environmental parameters","authors":"Jeremiah Sjoberg, Richard Anthes, Hailing Zhang","doi":"10.1175/jtech-d-23-0029.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0029.1","url":null,"abstract":"Abstract Estimation of uncertainties (random error statistics) of radio occultation (RO) observations is important for their effective assimilation in numerical weather prediction (NWP) models. Average uncertainties can be estimated for large samples of RO observations and these statistics may be used for specifying the observation errors in NWP data assimilation. However, the uncertainties of individual RO observations vary, and so using average uncertainty estimates will overestimate the uncertainties of some observations and underestimate those of others, reducing their overall effectiveness in the assimilation. Several parameters associated with RO observations or their atmospheric environments have been proposed to estimate individual RO errors. These include the standard deviation of bending angle (BA) departures from either climatology in the upper stratosphere and lower mesosphere (STDV) or the sample mean between 40 and 60 km (STD4060), the local spectral width (LSW), and the magnitude of the horizontal gradient of refractivity (|∇ H N|). In this paper we show how the uncertainties of two RO data sets, COSMIC-2 and Spire BA, as well as their combination, vary with these parameters. We find that the uncertainties are highly correlated with STDV and STD4060 in the stratosphere, and with LSW and |∇ H N| in the lower troposphere. These results suggest a hybrid error model for individual BA observations that uses an average statistical model of RO errors modified by STDV or STD4060 above 30 km, and LSW or |∇ H N| below 8 km.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136313591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-07DOI: 10.1175/jtech-d-23-0045.1
S. Stevens, Rich Pawlowicz
Neutrally buoyant floats have been widely used to measure flows in the ocean, but deploying them in large numbers can be costly and impractical. This is particularly true near coastlines due to the elevated risk of instrument grounding or vessel collisions, resulting in a lack of subsurface Lagrangian measurements in coastal regions. Here, we describe an inexpensive neutrally buoyant satellite-tracked float (named “Swallow-ish”, or “Swish” floats) which has been designed and tested as a cost-effective strategy to measure subsurface dispersion in coastal areas on timescales up to a month. These autonomous instruments are inexpensive, constructed at a material cost of $300 CAD per unit; lightweight, with a mass of 5.4 kg; isopycnal; and constructed from commercially available components, using recently-available global navigation satellite system technology to provide the user with a point-to-point measure of subsurface transport. We describe the float design, ballasting techniques, and the governing equations that determine their behavior. Further, through 29 deployments in two coastal seas, we calculate an uncertainty budget and determine a ballasting error of ±1.6 g, corresponding to a local depth targeting error of 16–30 m, analyze the float resurfacing data to calculate subsurface dispersion coefficients, and examine the float depth records to quantify the local internal wave field. Finally, we evaluate surface dispersion using the post-resurfacing trajectories. Our findings indicate that Swish floats offer a cost-effective alternative for Lagrangian measurements of subsurface flows in coastal regions.
{"title":"Swish floats: an inexpensive neutrally buoyant float to monitor dispersion in coastal seas","authors":"S. Stevens, Rich Pawlowicz","doi":"10.1175/jtech-d-23-0045.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0045.1","url":null,"abstract":"\u0000Neutrally buoyant floats have been widely used to measure flows in the ocean, but deploying them in large numbers can be costly and impractical. This is particularly true near coastlines due to the elevated risk of instrument grounding or vessel collisions, resulting in a lack of subsurface Lagrangian measurements in coastal regions. Here, we describe an inexpensive neutrally buoyant satellite-tracked float (named “Swallow-ish”, or “Swish” floats) which has been designed and tested as a cost-effective strategy to measure subsurface dispersion in coastal areas on timescales up to a month. These autonomous instruments are inexpensive, constructed at a material cost of $300 CAD per unit; lightweight, with a mass of 5.4 kg; isopycnal; and constructed from commercially available components, using recently-available global navigation satellite system technology to provide the user with a point-to-point measure of subsurface transport. We describe the float design, ballasting techniques, and the governing equations that determine their behavior. Further, through 29 deployments in two coastal seas, we calculate an uncertainty budget and determine a ballasting error of ±1.6 g, corresponding to a local depth targeting error of 16–30 m, analyze the float resurfacing data to calculate subsurface dispersion coefficients, and examine the float depth records to quantify the local internal wave field. Finally, we evaluate surface dispersion using the post-resurfacing trajectories. Our findings indicate that Swish floats offer a cost-effective alternative for Lagrangian measurements of subsurface flows in coastal regions.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43898043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-07DOI: 10.1175/jtech-d-22-0137.1
Yoonjin Lee, Soo-Hyun Kim, Yoo-Jeong Noh, Jung-Hoon Kim
Turbulence is what we want to avoid the most during flight. Numerical weather prediction (NWP) model-based methods for diagnosing turbulence have offered valuable guidance for pilots. NWP-based turbulence diagnostics show high accuracy in detecting turbulence in general. However, there is still room for improvements such as capturing convectively induced turbulence. In such cases, observation data can be beneficial to correctly locate convective regions and help provide corresponding turbulence information. Geostationary satellite data is commonly used for upper-level turbulence detection by utilizing its water vapor band information. The Geostationary Operational Environmental Satellite (GOES)-16 carries the Advanced Baseline Imager (ABI) which enables us to observe further down the atmosphere with improved spatial, temporal, and spectral resolutions. Its three water vapor bands allow us to observe different vertical parts of the atmosphere, and from its infrared window bands, convective activity can be inferred. Such multi-spectral information from ABI can be helpful in inferring turbulence intensity at different vertical levels. This study develops U-Net based machine learning models that take ABI imagery as inputs to estimate turbulence intensity at three vertical levels: 10-18 kft, 18-24 kft, and above 24 kft. Among six different U-Net-based models, U-Net3+ model with a filter size of three showed the best performance against the pilot report (PIREP). Two case studies are presented to show the strengths and weaknesses of the U-Net3+ model. The results tend to be overestimated above 24 kft, but estimates of 10-18 kft and 18-24 kft agree well with the PIREP, especially near convective regions.
{"title":"Deep learning-based summertime turbulence intensity estimation using satellite observations","authors":"Yoonjin Lee, Soo-Hyun Kim, Yoo-Jeong Noh, Jung-Hoon Kim","doi":"10.1175/jtech-d-22-0137.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0137.1","url":null,"abstract":"\u0000Turbulence is what we want to avoid the most during flight. Numerical weather prediction (NWP) model-based methods for diagnosing turbulence have offered valuable guidance for pilots. NWP-based turbulence diagnostics show high accuracy in detecting turbulence in general. However, there is still room for improvements such as capturing convectively induced turbulence. In such cases, observation data can be beneficial to correctly locate convective regions and help provide corresponding turbulence information. Geostationary satellite data is commonly used for upper-level turbulence detection by utilizing its water vapor band information. The Geostationary Operational Environmental Satellite (GOES)-16 carries the Advanced Baseline Imager (ABI) which enables us to observe further down the atmosphere with improved spatial, temporal, and spectral resolutions. Its three water vapor bands allow us to observe different vertical parts of the atmosphere, and from its infrared window bands, convective activity can be inferred. Such multi-spectral information from ABI can be helpful in inferring turbulence intensity at different vertical levels. This study develops U-Net based machine learning models that take ABI imagery as inputs to estimate turbulence intensity at three vertical levels: 10-18 kft, 18-24 kft, and above 24 kft. Among six different U-Net-based models, U-Net3+ model with a filter size of three showed the best performance against the pilot report (PIREP). Two case studies are presented to show the strengths and weaknesses of the U-Net3+ model. The results tend to be overestimated above 24 kft, but estimates of 10-18 kft and 18-24 kft agree well with the PIREP, especially near convective regions.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43841995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, an effective method of estimating the volume transport of the Kuroshio Extension (KE) is proposed using surface geostrophic flow inferred from satellite altimetry and vertical stratification derived from climatological Temperature/Salinity (T/S) profiles. Based on velocity measurements by a subsurface mooring array across the KE, we found that the vertical structure of horizontal flow in this region is dominated by the barotropic and first baroclinic normal modes, which is commendably described by the leading mode of Empirical Orthogonal Functions (EOFs) of the observed velocity profiles as well. Further analysis demonstrates that the projection coefficient of moored velocity onto the superimposed vertical normal mode can be represented by the surface geostrophic velocity as derived from satellite altimetry. Given this relationship, we proposed a dynamical method to estimate the volume transport across the KE jet, which is well verified with both ocean reanalysis and repeated hydrographic data. This finding implicates that, in the regions where the currents render quasi-barotropic structure, it takes only satellite altimetry observation and climatological T/S to estimate the volume transport across any section.
{"title":"Estimating the Volume Transport of Kuroshio Extension based on Satellite Altimetry and Hydrographic Data","authors":"Haihong Guo, Zhaohui Chen, Haiyuan Yang, Yu Long, Ruichen Zhu, Yueqi Zhang, Zhao Jing, Chunming Yang","doi":"10.1175/jtech-d-23-0018.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0018.1","url":null,"abstract":"\u0000In this study, an effective method of estimating the volume transport of the Kuroshio Extension (KE) is proposed using surface geostrophic flow inferred from satellite altimetry and vertical stratification derived from climatological Temperature/Salinity (T/S) profiles. Based on velocity measurements by a subsurface mooring array across the KE, we found that the vertical structure of horizontal flow in this region is dominated by the barotropic and first baroclinic normal modes, which is commendably described by the leading mode of Empirical Orthogonal Functions (EOFs) of the observed velocity profiles as well. Further analysis demonstrates that the projection coefficient of moored velocity onto the superimposed vertical normal mode can be represented by the surface geostrophic velocity as derived from satellite altimetry. Given this relationship, we proposed a dynamical method to estimate the volume transport across the KE jet, which is well verified with both ocean reanalysis and repeated hydrographic data. This finding implicates that, in the regions where the currents render quasi-barotropic structure, it takes only satellite altimetry observation and climatological T/S to estimate the volume transport across any section.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41725688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1175/jtech-d-23-0031.1
Andrea Hay, Christopher Watson, Benoit Legresy, Matt A. King, Jack Beardsley
While satellite altimeters have revolutionized ocean science, validation measurements in high wave environments are rare. Using geodetic Global Navigation Satellite System (GNSS) data collected from the Southern Ocean Flux Station (SOFS, −47°S, 142°E) since 2019, as part of the Southern Ocean Time Series (SOTS), we present a validation of satellite missions in this energetic region. Here we show that high rate GNSS observations at SOFS can successfully measure waves in the extreme conditions of the Southern Ocean and obtain robust measurements in all wave regimes (significant wave height, SWH, ranging from 1.5 m to 12.6 m). We find good agreement between the in-situ and nadir altimetry SWH (RMSE = 0.16 m, mean bias = 0.04 m, n = 60). Directional comparisons to the Chinese-French Ocean SATellite (CFOSAT) SWIM instrument also show good agreement, with dominant directions having an RMSE of 9.1° (n=22), and correlation coefficients between the directional spectra ranging between 0.57 and 0.79. Initial sea level anomaly (SLA) estimates capture eddies propagating through the region. Comparisons show good agreement with daily gridded SLA products (RMSE = 0.03 m, n = 205), with scope for future improvement. These results demonstrate the utility of high rate geodetic GNSS observations on moored surface platforms in highly energetic regions of the ocean. Such observations are important to maximize the geophysical interpretation from altimeter missions. In particular, the ability to provide co-located directional wave observations and SLA estimates will be useful for the validation of the recently launched Surface Water Ocean Topography (SWOT) mission where understanding the interactions between sea state and sea surface height poses a major challenge.
虽然卫星高度计已经彻底改变了海洋科学，但在高波浪环境下的验证测量很少。利用自2019年以来从南大洋通量站(SOFS， - 47°S, 142°E)收集的大地测量全球导航卫星系统(GNSS)数据，作为南大洋时间序列(SOTS)的一部分，我们对这一高能区域的卫星任务进行了验证。研究结果表明，SOFS的高速率GNSS观测可以成功地测量南大洋极端条件下的波浪，并获得所有波浪状态(有效波高，SWH，范围为1.5 m至12.6 m)的稳健测量结果，我们发现原位和最低点测高SWH之间的一致性很好(RMSE = 0.16 m，平均偏差= 0.04 m, n = 60)。与中法海洋卫星(CFOSAT) SWIM仪器的方向比较也显示出较好的一致性，优势方向的RMSE为9.1°(n=22)，方向光谱的相关系数在0.57 ~ 0.79之间。初始海平面异常(SLA)估计捕获了在该区域传播的涡旋。对比显示与每日网格化SLA产品(RMSE = 0.03 m, n = 205)有良好的一致性，有未来改进的余地。这些结果证明了在海洋高能量区域的系泊地面平台上进行高速率大地测量GNSS观测的实用性。这些观测对于最大限度地利用高度计任务进行地球物理解释非常重要。特别是，提供同位置定向波观测和SLA估计的能力将有助于最近启动的地表水海洋地形(SWOT)任务的验证，在该任务中，了解海况和海面高度之间的相互作用是一个主要挑战。
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Pub Date : 2023-09-01DOI: 10.1175/jtech-d-23-0103.1
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