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":" ","pages":""},"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":" ","pages":""},"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":" ","pages":""},"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。
{"title":"In-Situ Validation of Altimetry and CFOSAT SWIM Measurements in a High Wave Environment","authors":"Andrea Hay, Christopher Watson, Benoit Legresy, Matt A. King, Jack Beardsley","doi":"10.1175/jtech-d-23-0031.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0031.1","url":null,"abstract":"\u0000While 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.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47844268","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 : 2023-08-31DOI: 10.1175/jtech-d-23-0012.1
Ryan Lagerquist, David D. Turner, I. Ebert‐Uphoff, J. Stewart
Radiative transfer (RT) is a crucial but computationally expensive process in numerical weather/climate prediction. We develop neural networks (NN) to emulate a common RT parameterization called the Rapid Radiative-transfer Model (RRTM), with the goal of creating a faster parameterization for the Global Forecast System (GFS) v16. In previous work we emulated a highly simplified version of the shortwave RRTM only – excluding many predictor variables, driven by Rapid Refresh forecasts interpolated to a consistent height grid, using only 30 sites in the northern hemisphere. In this work we emulate the full shortwave and longwave RRTM – with all predictor variables, driven by GFSv16 forecasts on the native pressure-sigma grid, using data from around the globe. We experiment with NNs of widely varying complexity, including the U-net++ and U-net3+ architectures and deeply supervised training, designed to ensure realistic and accurate structure in gridded predictions. We evaluate the optimal shortwave NN and optimal longwave NN in great detail – as a function of geographic location, cloud regime, and other weather types. Both NNs produce extremely reliable heating rates and fluxes. The shortwave NN has an overall RMSE/MAE/bias of 0.14/0.08/-0.002 K day−1 for heating rate and 6.3/4.3/-0.1 W m−2 for net flux. Analogous numbers for the longwave NN are 0.22/0.12/-0.0006 K day−1 and 1.07/0.76/+0.01 W m−2. Both NNs perform well in nearly all situations, and the shortwave (longwave) NN is 7510 (90) times faster than the RRTM. Both will soon be tested online in the GFSv16.
在数值天气/气候预报中，辐射传输是一个重要但计算代价昂贵的过程。我们开发了神经网络(NN)来模拟称为快速辐射传输模型(RRTM)的常见RT参数化，目标是为全球预报系统(GFS) v16创建更快的参数化。在之前的工作中，我们只模拟了一个高度简化的短波RRTM版本——排除了许多预测变量，由快速刷新预测驱动，插值到一致的高度网格，仅使用北半球的30个站点。在这项工作中，我们模拟了全短波和长波RRTM -所有预测变量，由GFSv16在本地压力-西格玛网格上的预测驱动，使用来自全球的数据。我们对复杂程度变化很大的神经网络进行了实验，包括u -net++和U-net3+架构以及深度监督训练，旨在确保网格预测结构的真实性和准确性。我们非常详细地评估了最优短波神经网络和最优长波神经网络——作为地理位置、云状况和其他天气类型的函数。两种神经网络都能产生非常可靠的加热速率和通量。短波神经网络的加热速率的总体RMSE/MAE/偏差为0.14/0.08/-0.002 K day - 1，净通量的RMSE/MAE/偏差为6.3/4.3/-0.1 W m - 2。长波神经网络的类似数字为0.22/0.12/-0.0006 K day - 1和1.07/0.76/+0.01 W m - 2。两种神经网络在几乎所有情况下都表现良好，短波(长波)神经网络比RRTM快7510(90)倍。两者都将很快在GFSv16上进行在线测试。
{"title":"Estimating full longwave and shortwave radiative transfer with neural networks of varying complexity","authors":"Ryan Lagerquist, David D. Turner, I. Ebert‐Uphoff, J. Stewart","doi":"10.1175/jtech-d-23-0012.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0012.1","url":null,"abstract":"\u0000Radiative transfer (RT) is a crucial but computationally expensive process in numerical weather/climate prediction. We develop neural networks (NN) to emulate a common RT parameterization called the Rapid Radiative-transfer Model (RRTM), with the goal of creating a faster parameterization for the Global Forecast System (GFS) v16. In previous work we emulated a highly simplified version of the shortwave RRTM only – excluding many predictor variables, driven by Rapid Refresh forecasts interpolated to a consistent height grid, using only 30 sites in the northern hemisphere. In this work we emulate the full shortwave and longwave RRTM – with all predictor variables, driven by GFSv16 forecasts on the native pressure-sigma grid, using data from around the globe. We experiment with NNs of widely varying complexity, including the U-net++ and U-net3+ architectures and deeply supervised training, designed to ensure realistic and accurate structure in gridded predictions. We evaluate the optimal shortwave NN and optimal longwave NN in great detail – as a function of geographic location, cloud regime, and other weather types. Both NNs produce extremely reliable heating rates and fluxes. The shortwave NN has an overall RMSE/MAE/bias of 0.14/0.08/-0.002 K day−1 for heating rate and 6.3/4.3/-0.1 W m−2 for net flux. Analogous numbers for the longwave NN are 0.22/0.12/-0.0006 K day−1 and 1.07/0.76/+0.01 W m−2. Both NNs perform well in nearly all situations, and the shortwave (longwave) NN is 7510 (90) times faster than the RRTM. Both will soon be tested online in the GFSv16.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45115089","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 : 2023-08-30DOI: 10.1175/jtech-d-23-0019.1
Ting-Yu Cha, M. Bell
The interaction of airflow with complex terrain has the potential to significantly amplify extreme precipitation events and modify the structure and intensity of precipitating cloud systems. However, understanding and forecasting such events is challenging, in part due to the scarcity of direct in-situ measurements. Doppler radar can provide the capability to monitor extreme rainfall events over land, but our understanding of airflow modulated by orographic interactions remains limited. The SAMURAI software is a three-dimensional variational (3DVAR) technique that uses the finite element approach to retrieve kinematic and thermodynamic fields. The analysis has high fidelity to observations when retrieving flows over a flat surface, but the capability of imposing topography as a boundary constraint is not previously implemented. Here we implement the immersed boundary method (IBM) as pseudo-observations at their native coordinates in SAMURAI to represent the topographic forcing and surface impermeability. In this technique, neither data interpolation onto a Cartesian grid nor explicit physical constraint integration during the cost function minimization is needed. Furthermore, the physical constraints are treated as pseudo-observations, offering the flexibility to adjust the strength of the boundary condition. A series of observing simulation sensitivity experiments (OSSEs) using a full-physics model and radar emulator simulating rainfall from Typhoon Chanthu (2021) over Taiwan are conducted to evaluate the retrieval accuracy and parameter settings. The OSSE results show that the strength of the IBM constraints can impact the overall wind retrievals. Analysis from real radar observations further demonstrates that the improved retrieval technique can advance scientific analyses for the underlying dynamics of orographic precipitation using radar observations.
{"title":"Three-Dimensional Variational Multi-Doppler Wind Retrieval over complex terrain","authors":"Ting-Yu Cha, M. Bell","doi":"10.1175/jtech-d-23-0019.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0019.1","url":null,"abstract":"\u0000The interaction of airflow with complex terrain has the potential to significantly amplify extreme precipitation events and modify the structure and intensity of precipitating cloud systems. However, understanding and forecasting such events is challenging, in part due to the scarcity of direct in-situ measurements. Doppler radar can provide the capability to monitor extreme rainfall events over land, but our understanding of airflow modulated by orographic interactions remains limited. The SAMURAI software is a three-dimensional variational (3DVAR) technique that uses the finite element approach to retrieve kinematic and thermodynamic fields. The analysis has high fidelity to observations when retrieving flows over a flat surface, but the capability of imposing topography as a boundary constraint is not previously implemented. Here we implement the immersed boundary method (IBM) as pseudo-observations at their native coordinates in SAMURAI to represent the topographic forcing and surface impermeability. In this technique, neither data interpolation onto a Cartesian grid nor explicit physical constraint integration during the cost function minimization is needed. Furthermore, the physical constraints are treated as pseudo-observations, offering the flexibility to adjust the strength of the boundary condition. A series of observing simulation sensitivity experiments (OSSEs) using a full-physics model and radar emulator simulating rainfall from Typhoon Chanthu (2021) over Taiwan are conducted to evaluate the retrieval accuracy and parameter settings. The OSSE results show that the strength of the IBM constraints can impact the overall wind retrievals. Analysis from real radar observations further demonstrates that the improved retrieval technique can advance scientific analyses for the underlying dynamics of orographic precipitation using radar observations.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47115307","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 : 2023-08-29DOI: 10.1175/jtech-d-23-0066.1
B. A. Hodges, L. Grare, Benjamin Greenwood, Kayli Matsuyoshi, N. Pizzo, N. Statom, J. Farrar, L. Lenain
The development of autonomous surface vehicles, such as the Boeing Liquid Robotics Wave Glider, has revolutionized our ability to collect surface ocean–lower atmosphere observations, a crucial step toward developing better physical understanding of upper-ocean and air-sea interaction processes. However, due to the wave-following nature of these vehicles, they experience rapid shifting, rolling, and pitching under the action of surface waves, making motion compensation of observations of ocean currents particularly challenging. We present an evaluation of the accuracy of Wave Glider-based ADCP measurements by comparing them against coincident and collocated observations collected from a bottom-mounted ADCP over the course of a week-long experiment. A novel motion compensation method, tailored to wave-following surface vehicles, is presented and compared to standard approaches. We show that the use of an additional position and attitude sensor (GPS/IMU) significantly improves the accuracy of the observed currents.
{"title":"Evaluation of ocean currents observed from autonomous surface vehicles","authors":"B. A. Hodges, L. Grare, Benjamin Greenwood, Kayli Matsuyoshi, N. Pizzo, N. Statom, J. Farrar, L. Lenain","doi":"10.1175/jtech-d-23-0066.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0066.1","url":null,"abstract":"\u0000The development of autonomous surface vehicles, such as the Boeing Liquid Robotics Wave Glider, has revolutionized our ability to collect surface ocean–lower atmosphere observations, a crucial step toward developing better physical understanding of upper-ocean and air-sea interaction processes. However, due to the wave-following nature of these vehicles, they experience rapid shifting, rolling, and pitching under the action of surface waves, making motion compensation of observations of ocean currents particularly challenging. We present an evaluation of the accuracy of Wave Glider-based ADCP measurements by comparing them against coincident and collocated observations collected from a bottom-mounted ADCP over the course of a week-long experiment. A novel motion compensation method, tailored to wave-following surface vehicles, is presented and compared to standard approaches. We show that the use of an additional position and attitude sensor (GPS/IMU) significantly improves the accuracy of the observed currents.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41934251","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 : 2023-08-16DOI: 10.1175/jtech-d-23-0047.1
Todd McKinney, Nick Perlaky, A. Crawford, B. Brown, M. Newchurch
During the 2022/2023 Antarctic summer, eight pico balloon flights were depolyed from Neumayer Station III (70.6666° S, 8.2667° W), yielding valuable insights into the Antarctic stratospheric wind structure. Pico balloons maintain a lower altitude compared to larger super pressure balloons, floating between 9 to 15 km AMSL. The most impressive flight lasted an astounding 98 days, completing eight circumnavigations of the Southern Hemisphere. Throughout the flights, pico balloons encountered diverse air masses, displaying zonal velocities ranging from −50 to 250 km hr−1 and meridional velocities between ±100 km hr−1 . Total wind speeds observed were extensive, spanning from 2.0 to 270 km hr−1 . An significant finding revealed that lower-flying pico balloons could rise due to convection underneath the flight paths, influenced by high convective available potential energy environments, resulting in changes to the balloons’ float density. Moreover, the flights demonstrated that pico balloons tended to drift further south compared to larger stratospheric balloons, with some balloons reaching up to 8 degrees south of the equator and 2 degrees from the south pole. This article explores the pressure-testing process and deployment techniques for pico balloons, showcasing their transformation from inexpensive party balloons (costing less than 20 dollars) into efficient super pressure balloons. The logistical demands for pico balloon flights were minimal, with a single person transporting all materials for the balloons (excluding lifting gas) to the Antarctic continent in carry-on luggage. The authors aim to promote the application of pico balloons to a wider scientific community by demonstrating their usefulness.
{"title":"Methodology, Deployment, and Performance of Pico Balloons in Antarctica","authors":"Todd McKinney, Nick Perlaky, A. Crawford, B. Brown, M. Newchurch","doi":"10.1175/jtech-d-23-0047.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0047.1","url":null,"abstract":"\u0000During the 2022/2023 Antarctic summer, eight pico balloon flights were depolyed from Neumayer Station III (70.6666° S, 8.2667° W), yielding valuable insights into the Antarctic stratospheric wind structure. Pico balloons maintain a lower altitude compared to larger super pressure balloons, floating between 9 to 15 km AMSL. The most impressive flight lasted an astounding 98 days, completing eight circumnavigations of the Southern Hemisphere. Throughout the flights, pico balloons encountered diverse air masses, displaying zonal velocities ranging from −50 to 250 km hr−1 and meridional velocities between ±100 km hr−1 . Total wind speeds observed were extensive, spanning from 2.0 to 270 km hr−1 . An significant finding revealed that lower-flying pico balloons could rise due to convection underneath the flight paths, influenced by high convective available potential energy environments, resulting in changes to the balloons’ float density. Moreover, the flights demonstrated that pico balloons tended to drift further south compared to larger stratospheric balloons, with some balloons reaching up to 8 degrees south of the equator and 2 degrees from the south pole. This article explores the pressure-testing process and deployment techniques for pico balloons, showcasing their transformation from inexpensive party balloons (costing less than 20 dollars) into efficient super pressure balloons. The logistical demands for pico balloon flights were minimal, with a single person transporting all materials for the balloons (excluding lifting gas) to the Antarctic continent in carry-on luggage. The authors aim to promote the application of pico balloons to a wider scientific community by demonstrating their usefulness.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44708842","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 : 2023-08-14DOI: 10.1175/jtech-d-22-0141.1
Rachael N. Cross, D. Bodine, R. Palmer, Casey B. Griffin, B. Cheong, S. Torres, C. Fulton, J. Lujan, T. Maruyama
When a tornado lofts debris to the height of the radar beam, a signature known as the tornadic debris signature (TDS) can sometimes be observed on radar. The TDS is a useful signature for operational forecasters as it can confirm the presence of a tornado and provide information about the amount of damage occurring. Since real-time estimates of tornadic intensity do not have a high degree of accuracy, past studies have hypothesized that the TDS could also be an indicator of the strength of a tornado. However, few studies have related the tornadic wind field to TDS characteristics due to the difficulty of obtaining accurate, three-dimensional wind data in tornadoes from radar data. With this in mind, the goals of this study are twofold: 1) to investigate the relationships between polarimetric characteristics of TDSs and the three-dimensional tornadic winds, and 2) to define relationships between polarimetric radar variables and debris characteristics. Simulations are performed using a dual-polarization radar simulator called SimRadar; Large-Eddy Simulations (LESs) of tornadoes; and a single-volume, T-matrix based emulator. Results show that increases (decreases) in horizontal and vertical wind speeds are related to decreases (increases) in correlation coefficient and increases (decreases) in TDS area and height for all simulated debris types. However, the range of correlation coefficient values varies with debris type, indicating that TDSs comprised of similar debris types can appear remarkably different on radar compared to a TDS with diverse scatterers. Such findings confirm past, observational hypotheses and can aid operational forecasters in tornado detection and potentially the categorization of damage severity using radar data.
{"title":"Exploring Tornadic Debris Signature Hypotheses Using Radar Simulations and Large-Eddy Simulations","authors":"Rachael N. Cross, D. Bodine, R. Palmer, Casey B. Griffin, B. Cheong, S. Torres, C. Fulton, J. Lujan, T. Maruyama","doi":"10.1175/jtech-d-22-0141.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0141.1","url":null,"abstract":"\u0000When a tornado lofts debris to the height of the radar beam, a signature known as the tornadic debris signature (TDS) can sometimes be observed on radar. The TDS is a useful signature for operational forecasters as it can confirm the presence of a tornado and provide information about the amount of damage occurring. Since real-time estimates of tornadic intensity do not have a high degree of accuracy, past studies have hypothesized that the TDS could also be an indicator of the strength of a tornado. However, few studies have related the tornadic wind field to TDS characteristics due to the difficulty of obtaining accurate, three-dimensional wind data in tornadoes from radar data. With this in mind, the goals of this study are twofold: 1) to investigate the relationships between polarimetric characteristics of TDSs and the three-dimensional tornadic winds, and 2) to define relationships between polarimetric radar variables and debris characteristics. Simulations are performed using a dual-polarization radar simulator called SimRadar; Large-Eddy Simulations (LESs) of tornadoes; and a single-volume, T-matrix based emulator. Results show that increases (decreases) in horizontal and vertical wind speeds are related to decreases (increases) in correlation coefficient and increases (decreases) in TDS area and height for all simulated debris types. However, the range of correlation coefficient values varies with debris type, indicating that TDSs comprised of similar debris types can appear remarkably different on radar compared to a TDS with diverse scatterers. Such findings confirm past, observational hypotheses and can aid operational forecasters in tornado detection and potentially the categorization of damage severity using radar data.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46770652","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 : 2023-08-11DOI: 10.1175/jtech-d-23-0057.1
A. Protat, V. Louf, M. Curtis
Doppler radars measure Doppler velocity within the [-VN, VN] range, where VN is the Nyquist velocity. Doppler velocities outside of this range are “folded” within this interval. All Doppler “unfolding” techniques use the folded velocities themselves. In this work, we investigate the potential of using velocities derived from optical flow techniques applied to the radar reflectivity field for that purpose. The analysis of wind speed errors using six months of multi-Doppler wind retrievals showed that 99.9% of all points are characterized by errors smaller than 26 ms-1 below 5 km height, corresponding to a failure rate of less than 0.01% if optical flow winds were used to unfold Doppler velocities for VN = 26 ms-1. These errors largely increase above 5 km height, indicating that vertical continuity tests should be included to reduce failure rates at higher elevations. Following these results, we have developed the Two-step Optical Flow Unfolding (TOFU) technique, with the specific objective to accurately unfold Doppler velocities with VN = 26 ms-1. The TOFU performance was assessed using challenging case studies, comparisons with an advanced Doppler unfolding technique using higher Nyquist velocities, and six months of high VN (47.2 ms-1) data artificially folded to 26 ms-1. TOFU failure rates were found to be very low. Three main situations contributed to these errors: high low-level wind shear, elevated cloud layers associated with high winds, and radar data artefacts. Our recommendation is to use these unfolded winds as the first step of advanced Doppler unfolding techniques.
{"title":"A Novel Doppler Unfolding Technique Using Optical Flow","authors":"A. Protat, V. Louf, M. Curtis","doi":"10.1175/jtech-d-23-0057.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0057.1","url":null,"abstract":"\u0000Doppler radars measure Doppler velocity within the [-VN, VN] range, where VN is the Nyquist velocity. Doppler velocities outside of this range are “folded” within this interval. All Doppler “unfolding” techniques use the folded velocities themselves. In this work, we investigate the potential of using velocities derived from optical flow techniques applied to the radar reflectivity field for that purpose. The analysis of wind speed errors using six months of multi-Doppler wind retrievals showed that 99.9% of all points are characterized by errors smaller than 26 ms-1 below 5 km height, corresponding to a failure rate of less than 0.01% if optical flow winds were used to unfold Doppler velocities for VN = 26 ms-1. These errors largely increase above 5 km height, indicating that vertical continuity tests should be included to reduce failure rates at higher elevations. Following these results, we have developed the Two-step Optical Flow Unfolding (TOFU) technique, with the specific objective to accurately unfold Doppler velocities with VN = 26 ms-1.\u0000The TOFU performance was assessed using challenging case studies, comparisons with an advanced Doppler unfolding technique using higher Nyquist velocities, and six months of high VN (47.2 ms-1) data artificially folded to 26 ms-1. TOFU failure rates were found to be very low. Three main situations contributed to these errors: high low-level wind shear, elevated cloud layers associated with high winds, and radar data artefacts. Our recommendation is to use these unfolded winds as the first step of advanced Doppler unfolding techniques.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45365082","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}
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