Pub Date : 2024-01-24DOI: 10.1175/jtech-d-23-0061.1
M. Paszkuta, Maciej Markowski, A. Krężel
Empirical verification of the reliability of estimating the amount of solar radiation entering the sea surface is a challenging topic due to the quantity and quality of data. The collected measurements of total and diffuse radiation from the Multifilter Rotating Shadowband Radiometer (MRF-7) commercial device over the Baltic Sea were compared with the satellite results of using modeling data. The obtained results, also divided into individual spectral bands, were analyzed for usefulness in satellite cloud and aerosol detection. The article presents a new approach to assessing radiation and cloud cover based on the use of models supported by satellite data. Measurement uncertainties were estimated for the obtained results. To reduce uncertainty, the results were averaged to the time constant of the device, day and month. The effectiveness of the method was determined by comparison against the SM Hel measurement point. The empirical results obtained confirm the effectiveness of using satellite methods for estimating radiation along with cloud cover detection over the sea with the adopted uncertainty values.
由于数据的数量和质量问题，对估计进入海面的太阳辐射量的可靠性进行经验验证是一个具有挑战性的课题。波罗的海上空多滤光片旋转影带辐射计（MRF-7）商用装置收集的总辐射和漫射辐射测量数据与卫星利用建模数据得出的结果进行了比较。获得的结果（也分为各个光谱波段）被分析用于卫星云层和气溶胶探测。文章介绍了一种基于卫星数据支持的模型评估辐射和云层的新方法。对所得结果的测量不确定性进行了估算。为减少不确定性，对结果按设备、日和月的时间常数进行了平均。通过与 SM Hel 测量点进行比较，确定了该方法的有效性。获得的经验结果证实，在采用不确定值的情况下，使用卫星方法估算辐射和探测海上云层是有效的。
{"title":"Empirical verification of satellite data on solar radiation and cloud cover over the Baltic Sea","authors":"M. Paszkuta, Maciej Markowski, A. Krężel","doi":"10.1175/jtech-d-23-0061.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0061.1","url":null,"abstract":"\u0000Empirical verification of the reliability of estimating the amount of solar radiation entering the sea surface is a challenging topic due to the quantity and quality of data. The collected measurements of total and diffuse radiation from the Multifilter Rotating Shadowband Radiometer (MRF-7) commercial device over the Baltic Sea were compared with the satellite results of using modeling data. The obtained results, also divided into individual spectral bands, were analyzed for usefulness in satellite cloud and aerosol detection. The article presents a new approach to assessing radiation and cloud cover based on the use of models supported by satellite data. Measurement uncertainties were estimated for the obtained results. To reduce uncertainty, the results were averaged to the time constant of the device, day and month. The effectiveness of the method was determined by comparison against the SM Hel measurement point. The empirical results obtained confirm the effectiveness of using satellite methods for estimating radiation along with cloud cover detection over the sea with the adopted uncertainty values.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139600396","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 : 2024-01-15DOI: 10.1175/jtech-d-23-0070.1
Igor R. Ivić
The two main metrics for the performance evaluation of radar-variable estimators are the bias and standard deviation (SD) of estimates. Depending on the estimator properties, the bias may increase as the signal-to-noise ratio (SNR) decreases. The standard deviation, however, always rises as the SNR becomes smaller. For instance, if estimates are computed from 16 samples (typically used for WSR-88D surveillance scans) using a rectangular data window and the maximum unambiguous velocity is ~9 m s−1, the standard deviation of reflectivity estimates increases 1.6 times as the SNR drops from 20 to 2 dB. But for estimates of differential reflectivity, differential phase, and copolar correlation coefficient, SDs increase ~6.7, ~6, and ~54 times, respectively. Hence, this effect impacts the polarimetric variables substantially more than the spectral moments. Additionally, the polarimetric variable SD is also sensitive to the correlation between signals in horizontal and vertical channels leading to reduced data quality in the regions where the correlation coefficient is low. Such increases in the variability of estimates are observable in the fields of dual polarization variables as an increased spatial inhomogeneity (or noisiness) in the areas where radar echoes exhibit low-to-moderate SNRs and/or decreased correlation coefficient. These effects can obscure the visual identification of weather features as well as adversely impact algorithms. Herein, a novel method that applies variable smoothing in the range where the smoothing intensity depends on the SDs of estimates is presented. It applies little or no range averaging in the regions where data SDs are deemed adequate while using more aggressive smoothing in areas where data appears noisy.
雷达变量估计器性能评估的两个主要指标是估计值的偏差和标准偏差（SD）。根据估计器的特性，偏差可能会随着信噪比（SNR）的降低而增加。然而，标准偏差总是随着信噪比变小而增大。例如，如果使用矩形数据窗口从 16 个样本（通常用于 WSR-88D 监视扫描）中计算出估计值，且最大明确速度为 ~9 m s-1，那么当信噪比从 20 dB 下降到 2 dB 时，反射率估计值的标准偏差会增加 1.6 倍。但对于差分反射率、差分相位和共极相关系数的估计值，标准偏差分别增加了 ~6.7、 ~6 和 ~54 倍。因此，这种效应对极坐标变量的影响远远大于对光谱矩的影响。此外，极坐标变量标度对水平和垂直信道信号之间的相关性也很敏感，导致相关系数较低区域的数据质量下降。在雷达回波信噪比低至中等和/或相关系数降低的区域，估算值的变异性增加，在双极化变量领域表现为空间不均匀性（或噪声）增加。这些影响会模糊气象特征的视觉识别，并对算法产生不利影响。本文提出了一种新方法，在平滑强度取决于估计值自标度的范围内应用可变平滑。该方法在数据自标度被认为足够的区域几乎不采用范围平均法，而在数据出现噪声的区域则采用更激进的平滑法。
{"title":"A weighted adaptive range-averaging technique to improve the precision consistency of polarimetric variable fields","authors":"Igor R. Ivić","doi":"10.1175/jtech-d-23-0070.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0070.1","url":null,"abstract":"\u0000The two main metrics for the performance evaluation of radar-variable estimators are the bias and standard deviation (SD) of estimates. Depending on the estimator properties, the bias may increase as the signal-to-noise ratio (SNR) decreases. The standard deviation, however, always rises as the SNR becomes smaller. For instance, if estimates are computed from 16 samples (typically used for WSR-88D surveillance scans) using a rectangular data window and the maximum unambiguous velocity is ~9 m s−1, the standard deviation of reflectivity estimates increases 1.6 times as the SNR drops from 20 to 2 dB. But for estimates of differential reflectivity, differential phase, and copolar correlation coefficient, SDs increase ~6.7, ~6, and ~54 times, respectively. Hence, this effect impacts the polarimetric variables substantially more than the spectral moments. Additionally, the polarimetric variable SD is also sensitive to the correlation between signals in horizontal and vertical channels leading to reduced data quality in the regions where the correlation coefficient is low. Such increases in the variability of estimates are observable in the fields of dual polarization variables as an increased spatial inhomogeneity (or noisiness) in the areas where radar echoes exhibit low-to-moderate SNRs and/or decreased correlation coefficient. These effects can obscure the visual identification of weather features as well as adversely impact algorithms. Herein, a novel method that applies variable smoothing in the range where the smoothing intensity depends on the SDs of estimates is presented. It applies little or no range averaging in the regions where data SDs are deemed adequate while using more aggressive smoothing in areas where data appears noisy.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139529195","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 : 2024-01-05DOI: 10.1175/jtech-d-23-0028.1
Mircea Grecu, J. Yorks
In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and sub-millimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of Ice Water Content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments e.g. frequencies, sensitivities, etc. are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, out of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-Means clustering algorithm. In the second step, the IWC profile is estimated using an Ensemble Kalman Smoother (EKS) algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.
{"title":"Synergistic retrievals of ice in high clouds from elastic backscatter lidar, Ku-band radar and submillimeter wave radiometer observations","authors":"Mircea Grecu, J. Yorks","doi":"10.1175/jtech-d-23-0028.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0028.1","url":null,"abstract":"\u0000In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and sub-millimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of Ice Water Content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments e.g. frequencies, sensitivities, etc. are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, out of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-Means clustering algorithm. In the second step, the IWC profile is estimated using an Ensemble Kalman Smoother (EKS) algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139381265","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 : 2024-01-01DOI: 10.1175/jtech-d-23-0010.1
Matteo Bramati, M. Schön, Daniel Schulz, Vasileios Savvakis, Yongtan Wang, J. Bange, A. Platis
The use of small uncrewed aircraft systems (UAS) can effectively capture the wind profile in the lower atmospheric boundary layer. This study presents a calibration process to estimate the horizontal wind vector using a rotary-wing UAS in hovering conditions. This procedure does not require wind tunnels or meteorological masts, only the data from the flight control unit and a specific set of calibration flights. A model based on the UAS drag coefficient was proposed and compared to a traditional approach. Validation flights at the German Weather Service MOL-RAO observatory showed that the system can accurately predict wind speed and direction. A modified DJI S900 hexacopter with a Styrofoam sphere casing was used for the study and calibrated for wind speeds between 1 and 14 m s−1. Power spectral density analysis showed the system’s ability to resolve atmospheric eddies up to 0.1 Hz. The overall root-mean-square error was less than 0.7 m s−1 for wind speed and less than 8° for wind direction.
使用小型无人驾驶航空器系统（UAS）可以有效捕捉低层大气边界层的风廓线。本研究介绍了在悬停条件下使用旋转翼无人机系统估算水平风矢量的校准过程。该程序不需要风洞或气象桅杆，只需要飞行控制单元的数据和一组特定的校准飞行。提出了一个基于无人机阻力系数的模型，并与传统方法进行了比较。在德国气象局 MOL-RAO 观测站进行的验证飞行表明，该系统可以准确预测风速和风向。研究使用了一架改装的大疆 S900 六旋翼飞行器，其外壳为泡沫塑料球体，校准风速为 1 至 14 m s-1。功率谱密度分析表明，该系统能够分辨高达 0.1 Hz 的大气涡流。风速的总体均方根误差小于 0.7 m s-1，风向的均方根误差小于 8°。
{"title":"A Versatile Calibration Method for Rotary-Wing UAS as Wind Measurement Systems","authors":"Matteo Bramati, M. Schön, Daniel Schulz, Vasileios Savvakis, Yongtan Wang, J. Bange, A. Platis","doi":"10.1175/jtech-d-23-0010.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0010.1","url":null,"abstract":"\u0000The use of small uncrewed aircraft systems (UAS) can effectively capture the wind profile in the lower atmospheric boundary layer. This study presents a calibration process to estimate the horizontal wind vector using a rotary-wing UAS in hovering conditions. This procedure does not require wind tunnels or meteorological masts, only the data from the flight control unit and a specific set of calibration flights. A model based on the UAS drag coefficient was proposed and compared to a traditional approach. Validation flights at the German Weather Service MOL-RAO observatory showed that the system can accurately predict wind speed and direction. A modified DJI S900 hexacopter with a Styrofoam sphere casing was used for the study and calibrated for wind speeds between 1 and 14 m s−1. Power spectral density analysis showed the system’s ability to resolve atmospheric eddies up to 0.1 Hz. The overall root-mean-square error was less than 0.7 m s−1 for wind speed and less than 8° for wind direction.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139393877","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 : 2024-01-01DOI: 10.1175/jtech-d-23-0073.1
Rich Pawlowicz, C. Chavanne, Dany Dumont
Many different surface drifter designs have been developed recently to track near-surface ocean currents, but the degree to which these drifters slip through the water because of mechanisms associated with the wind is poorly known. In the 2020 Tracer Release Experiment (TReX), 19 drifters of eight different designs, both commercially available and home-built, were simultaneously released with a patch of rhodamine dye. The dye rapidly spread vertically through the mixed layer but also more slowly dispersed horizontally. Although winds were light, drifters moved downwind from the dye patch at speeds of 3–17 cm s−1 (0.6%–4% of wind speed) depending on the design type. Measurements were made of wind and ocean conditions, and these were incorporated into a boundary layer model at the air–sea interface to estimate complete velocity profiles above and below the surface. Then, a steady-state drag model is used with these profiles to successfully predict drifter slip. Drogued drifters (those with a subsurface drag element) can be affected by Eulerian shear in the upper 0.5 m of the water column, as well as the Stokes drift, but undrogued drifters are in addition greatly affected by direct wind drag, and possibly by resonant interactions with waves. The dye, cycling vertically in the mixed layer, is largely unaffected by all of these factors; therefore, even “perfect” surface drifters do not move with a mixed layer tracer. Surface drifters are used by oceanographers to measure ocean surface currents. However, different designs also slip downwind through the water at rates that are poorly known but are typically around a few percent of the wind speed. In 2020 we simultaneously deployed drifters of eight different designs along with rhodamine dye in a field experiment to see how well the different designs track the water. Here we independently and successfully model drifter slippage for the different designs. Slip factors are then estimated for a range of wind and ocean conditions.
{"title":"The Water-Following Performance of Various Lagrangian Surface Drifters Measured in a Dye Release Experiment","authors":"Rich Pawlowicz, C. Chavanne, Dany Dumont","doi":"10.1175/jtech-d-23-0073.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0073.1","url":null,"abstract":"\u0000Many different surface drifter designs have been developed recently to track near-surface ocean currents, but the degree to which these drifters slip through the water because of mechanisms associated with the wind is poorly known. In the 2020 Tracer Release Experiment (TReX), 19 drifters of eight different designs, both commercially available and home-built, were simultaneously released with a patch of rhodamine dye. The dye rapidly spread vertically through the mixed layer but also more slowly dispersed horizontally. Although winds were light, drifters moved downwind from the dye patch at speeds of 3–17 cm s−1 (0.6%–4% of wind speed) depending on the design type. Measurements were made of wind and ocean conditions, and these were incorporated into a boundary layer model at the air–sea interface to estimate complete velocity profiles above and below the surface. Then, a steady-state drag model is used with these profiles to successfully predict drifter slip. Drogued drifters (those with a subsurface drag element) can be affected by Eulerian shear in the upper 0.5 m of the water column, as well as the Stokes drift, but undrogued drifters are in addition greatly affected by direct wind drag, and possibly by resonant interactions with waves. The dye, cycling vertically in the mixed layer, is largely unaffected by all of these factors; therefore, even “perfect” surface drifters do not move with a mixed layer tracer.\u0000\u0000\u0000Surface drifters are used by oceanographers to measure ocean surface currents. However, different designs also slip downwind through the water at rates that are poorly known but are typically around a few percent of the wind speed. In 2020 we simultaneously deployed drifters of eight different designs along with rhodamine dye in a field experiment to see how well the different designs track the water. Here we independently and successfully model drifter slippage for the different designs. Slip factors are then estimated for a range of wind and ocean conditions.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139537613","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 : 2024-01-01DOI: 10.1175/jtech-d-22-0100.1
S. Sokolovskiy, Zhen Zeng, D. Hunt, Jan-Peter Weiss, John J. Braun, W. Schreiner, R. Anthes, Ying-Hwa Kuo, Hailing Zhang, D. Lenschow, T. Vanhove
Superrefraction at the top of the atmospheric boundary layer introduces problems for assimilation of radio occultation data in weather models. A method of detection of superrefraction by spectral analysis of deep radio occultation signals introduced earlier has been tested using 2 years of COSMIC-2/FORMOSAT-7 radio occultation data. Our analysis shows a significant dependence of the probability of detection of superrefraction on the signal-to-noise ratio, which results in a certain sampling nonuniformity. Despite this nonuniformity, the results are consistent with the known global distribution of superrefraction (mainly over the subtropical oceans) and show some additional features and seasonal variations. Comparisons to the European Centre for Medium-Range Weather Forecasts analyses and limited set of radiosondes show reasonable agreement. Being an independent measurement, detection of superrefraction from deep radio occultation signals is complementary to its prediction by atmospheric models and thus should be useful for assimilation of radio occultation data in the atmospheric boundary layer.
{"title":"Detection of Superrefraction at the Top of the Atmospheric Boundary Layer from COSMIC-2 Radio Occultations","authors":"S. Sokolovskiy, Zhen Zeng, D. Hunt, Jan-Peter Weiss, John J. Braun, W. Schreiner, R. Anthes, Ying-Hwa Kuo, Hailing Zhang, D. Lenschow, T. Vanhove","doi":"10.1175/jtech-d-22-0100.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0100.1","url":null,"abstract":"\u0000Superrefraction at the top of the atmospheric boundary layer introduces problems for assimilation of radio occultation data in weather models. A method of detection of superrefraction by spectral analysis of deep radio occultation signals introduced earlier has been tested using 2 years of COSMIC-2/FORMOSAT-7 radio occultation data. Our analysis shows a significant dependence of the probability of detection of superrefraction on the signal-to-noise ratio, which results in a certain sampling nonuniformity. Despite this nonuniformity, the results are consistent with the known global distribution of superrefraction (mainly over the subtropical oceans) and show some additional features and seasonal variations. Comparisons to the European Centre for Medium-Range Weather Forecasts analyses and limited set of radiosondes show reasonable agreement. Being an independent measurement, detection of superrefraction from deep radio occultation signals is complementary to its prediction by atmospheric models and thus should be useful for assimilation of radio occultation data in the atmospheric boundary layer.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139635286","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 : 2024-01-01DOI: 10.1175/jtech-d-22-0129.1
H. M. Aravind, H. Huntley, A. D. Kirwan, Michael R. Allshouse
Surface convergence in the ocean is associated with accumulation of buoyant pollutants as well as with vertical transport that is important to biological activity. Such surface convergence regions are marked by a high dilation rate, i.e., the finite time Lagrangian average divergence. Dilation-rate observations are most easily derived from the change of the area encompassed by a drifter swarm over time. The technological advances that have enabled the deployment of large numbers of drifters in a single experiment have raised new questions about optimal deployment strategies for extracting dilation-rate information with acceptable accuracy and as much spatial coverage as possible. Using a submesoscale-resolving operational model of the Mediterranean Sea, we analyze synthetic trajectories of drifter polygons to evaluate the impact of the number of drifters and their initial separation on the accuracy of the resulting dilation-rate estimates. The results confirm that estimates improve as the circumradius of the polygon decreases and as more drifters are added, but with only a marginal improvement for drifter polygons containing more than four drifters. Moreover, GPS positions obtained from drifters in the ocean are subject to uncertainty on the order of 2–50 m, and when this uncertainty is taken into account, an optimal circumradius can be identified that balances uncertainty from position measurements with that from the area approximations. Locating regions of convergence over a finite time interval on the ocean surface can help in pollution mitigation, locating biological hotspots, and even search-and-rescue operations. Finite time convergence can be quantified using the dilation rate, but it is hard to measure in the ocean. Hence, we present a method to estimate the dilation rate using trajectories of drifters, which are instruments widely used by oceanographers during field experiments to understand the local flow features. We show that even though the drifter-based dilation rates are prone to error as a result of a finite number of drifters and limited GPS accuracy, the estimates locate around 90% of the strongest convergent features in our model.
{"title":"Drifter Deployment Strategies to Determine Lagrangian Surface Convergence in Submesoscale Flows","authors":"H. M. Aravind, H. Huntley, A. D. Kirwan, Michael R. Allshouse","doi":"10.1175/jtech-d-22-0129.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0129.1","url":null,"abstract":"\u0000Surface convergence in the ocean is associated with accumulation of buoyant pollutants as well as with vertical transport that is important to biological activity. Such surface convergence regions are marked by a high dilation rate, i.e., the finite time Lagrangian average divergence. Dilation-rate observations are most easily derived from the change of the area encompassed by a drifter swarm over time. The technological advances that have enabled the deployment of large numbers of drifters in a single experiment have raised new questions about optimal deployment strategies for extracting dilation-rate information with acceptable accuracy and as much spatial coverage as possible. Using a submesoscale-resolving operational model of the Mediterranean Sea, we analyze synthetic trajectories of drifter polygons to evaluate the impact of the number of drifters and their initial separation on the accuracy of the resulting dilation-rate estimates. The results confirm that estimates improve as the circumradius of the polygon decreases and as more drifters are added, but with only a marginal improvement for drifter polygons containing more than four drifters. Moreover, GPS positions obtained from drifters in the ocean are subject to uncertainty on the order of 2–50 m, and when this uncertainty is taken into account, an optimal circumradius can be identified that balances uncertainty from position measurements with that from the area approximations.\u0000\u0000\u0000Locating regions of convergence over a finite time interval on the ocean surface can help in pollution mitigation, locating biological hotspots, and even search-and-rescue operations. Finite time convergence can be quantified using the dilation rate, but it is hard to measure in the ocean. Hence, we present a method to estimate the dilation rate using trajectories of drifters, which are instruments widely used by oceanographers during field experiments to understand the local flow features. We show that even though the drifter-based dilation rates are prone to error as a result of a finite number of drifters and limited GPS accuracy, the estimates locate around 90% of the strongest convergent features in our model.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139637468","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}
Ocean acoustic tomography (OAT) deploys most moored stations on the periphery of the tomographic region to sense the solenoidal current field. Moving vehicle tomography (MVT), an advancement of OAT, not only samples the region from various angles for improving the resolution of mapped currents but also acquires information about the irrotational flow due to the sampling points inside the region. To reconstruct a complete two-dimensional current field, the spatial modes derived from the open-boundary modal analysis (OMA) are preferable to the conventional truncated Fourier series since the OMA technique describes the solenoidal and irrotational flows efficiently in which all modes satisfy the coastline and open boundary conditions. Comparisons of the reconstructions are presented using three different representations of currents. The first two representations explain only the solenoidal flow: the truncated Fourier series and the OMA Dirichlet modes. The third representation, accounting for the solenoidal and irrotational flows, uses all the OMA modes. For reconstructing the solenoidal flow, the OMA representation with the Dirichlet modes performs better than the Fourier series. A large difference appears near the bay mouth, where the OMA-Dirichlet reconstruction shows a better fit to the uniform currents. However, considerable uncertainty exists outside the bay mouth where the irrotational currents dominate. This can be improved by the third representation with the inclusion of the Neumann and boundary modes. The reconstruction results using field data were validated against the acoustic Doppler current profiler (ADCP) measurements. Additionally, incorporating constraints from ADCP measurements enhances the accuracy of the reconstruction. This study contributes toward improving our understanding of accurately measuring oceanic circulation patterns over large areas without relying solely upon stationary sensors or satellite imagery. The study combines multiple sources, such as shipboard ADCP and tomographic techniques, to obtain a complete picture of what is happening beneath surface waters across entire regions under investigation. It has important implications for fields such as climate science, marine biology, and fisheries management, where accurate knowledge of the movement and distribution of water masses is crucial for predicting future trends and making informed decisions.
海洋声学层析成像技术（OAT）在层析成像区域的外围部署大多数系泊站，以感知螺线管流场。移动车辆层析成像技术（MVT）是海洋声学层析成像技术的一个进步，它不仅能从不同角度对该区域进行采样，以提高测绘海流的分辨率，还能获取该区域内采样点所产生的非旋转流的信息。为了重建完整的二维海流场，开放边界模态分析（OMA）得出的空间模态优于传统的截断傅里叶级数，因为开放边界模态分析技术能有效地描述螺线流和旋转流，其中所有模态都满足海岸线和开放边界条件。我们使用三种不同的海流表示方法对重建结果进行了比较。前两种表示法只解释了螺线流：截断傅里叶级数和 OMA Dirichlet 模式。第三种表示法使用所有 OMA 模式，解释了螺线流和非旋转流。在重建螺线管流时，使用 Dirichlet 模式的 OMA 表示法比傅里叶级数表示法效果更好。在湾口附近出现了较大的差异，OMA-Dirichlet 重构对均匀流的拟合效果更好。然而，在湾口外，非旋转海流占主导地位，存在相当大的不确定性。第三种表示方法包含了诺伊曼模式和边界模式，可以改善这种情况。利用现场数据重建的结果与声学多普勒海流剖面仪（ADCP）的测量结果进行了验证。这项研究有助于我们更好地理解如何在不完全依赖固定传感器或卫星图像的情况下精确测量大面积海洋环流模式。这项研究结合了船载 ADCP 和层析成像技术等多种来源，从而获得了整个调查区域表层水下情况的全貌。它对气候科学、海洋生物学和渔业管理等领域具有重要意义，因为准确了解水团的运动和分布对预测未来趋势和做出明智决策至关重要。
{"title":"Optimum Estimation of Coastal Currents Using Moving Vehicles","authors":"KuanYu Chen, Chen-Fen Huang, Zhe-Wen Zheng, Sheng-Fong Lin, Jin-Yuan Liu, Jenhwa Guo","doi":"10.1175/jtech-d-23-0039.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0039.1","url":null,"abstract":"\u0000Ocean acoustic tomography (OAT) deploys most moored stations on the periphery of the tomographic region to sense the solenoidal current field. Moving vehicle tomography (MVT), an advancement of OAT, not only samples the region from various angles for improving the resolution of mapped currents but also acquires information about the irrotational flow due to the sampling points inside the region. To reconstruct a complete two-dimensional current field, the spatial modes derived from the open-boundary modal analysis (OMA) are preferable to the conventional truncated Fourier series since the OMA technique describes the solenoidal and irrotational flows efficiently in which all modes satisfy the coastline and open boundary conditions. Comparisons of the reconstructions are presented using three different representations of currents. The first two representations explain only the solenoidal flow: the truncated Fourier series and the OMA Dirichlet modes. The third representation, accounting for the solenoidal and irrotational flows, uses all the OMA modes. For reconstructing the solenoidal flow, the OMA representation with the Dirichlet modes performs better than the Fourier series. A large difference appears near the bay mouth, where the OMA-Dirichlet reconstruction shows a better fit to the uniform currents. However, considerable uncertainty exists outside the bay mouth where the irrotational currents dominate. This can be improved by the third representation with the inclusion of the Neumann and boundary modes. The reconstruction results using field data were validated against the acoustic Doppler current profiler (ADCP) measurements. Additionally, incorporating constraints from ADCP measurements enhances the accuracy of the reconstruction.\u0000\u0000\u0000This study contributes toward improving our understanding of accurately measuring oceanic circulation patterns over large areas without relying solely upon stationary sensors or satellite imagery. The study combines multiple sources, such as shipboard ADCP and tomographic techniques, to obtain a complete picture of what is happening beneath surface waters across entire regions under investigation. It has important implications for fields such as climate science, marine biology, and fisheries management, where accurate knowledge of the movement and distribution of water masses is crucial for predicting future trends and making informed decisions.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139015214","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 : 2023-11-21DOI: 10.1175/jtech-d-23-0067.1
G. Boer, Brian J. Butterworth, Jack S. Elston, Adam Houston, Elizabeth A. Pillar-Little, B. Argrow, Tyler M. Bell, Phillip Chilson, Christopher Choate, B. R. Greene, Ashraful Islam, Ryan Martz, Michael Rhodes, Daniel Rico, M. Stachura, Francesca M. Lappin, Antonio R. Segales, Seabrooke Whyte, Matthew Wilson
Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially-available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.
小型无人驾驶飞行器系统（sUAS）经常被用来进行大气研究，并开始通过数据同化作为为天气模式提供信息的数据源。然而，目前只有数量有限的研究对这些系统的性能进行了评估，并评估了它们复制无线电探空仪和塔等传统传感器测量结果的能力。在目前的工作中，我们利用在俄克拉荷马州中部收集的为期两周的数据，深入分析了五种不同的 sUAS 平台和相关传感器在测量关键天气数据方面的性能。这些数据来自三个旋转翼和两个固定翼无人机系统，包括两个商用系统和三个大学开发的研究系统。飞行数据与在飞行地点发射的常规无线电探空仪、塔台观测数据进行了比较，并与其他无人机系统平台的数据进行了相互比较。结果表明，所有平台都能以合理的精度测量大气状态，但也发现个别平台存在一些一致的偏差。这些信息可为今后使用这些平台进行研究提供参考，目前正用于提供估计误差协方差，以支持将无人机系统数据同化到天气预报系统中。
{"title":"Evaluation and Intercomparison of Small Uncrewed Aircraft Systems Used for Atmospheric Research","authors":"G. Boer, Brian J. Butterworth, Jack S. Elston, Adam Houston, Elizabeth A. Pillar-Little, B. Argrow, Tyler M. Bell, Phillip Chilson, Christopher Choate, B. R. Greene, Ashraful Islam, Ryan Martz, Michael Rhodes, Daniel Rico, M. Stachura, Francesca M. Lappin, Antonio R. Segales, Seabrooke Whyte, Matthew Wilson","doi":"10.1175/jtech-d-23-0067.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0067.1","url":null,"abstract":"Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially-available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139254527","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 : 2023-11-10DOI: 10.1175/jtech-d-23-0020.1
Cathrine Hancock, Olaf Boebel
Abstract In sea ice covered polar oceans, profiling Argo floats are often unable to surface for 9 months or longer, rendering acoustic RAFOS (Ranging And Fixing Of Sound) tracking the only method to obtain unambiguous under-ice positions. Tracking RAFOS-enabled floats has historically relied on the ARTOA3 software, which had originally been tailored towards non-profiling floats in regions featuring the SOFAR (SOund Fixing And Ranging) channel with acoustic ranges of approximately 1000km. However, in sea ice covered regions, RAFOS tracking is challenged due to: (a) reduced acoustic ranges of RAFOS signals, and (b) enhanced uncertainties in float and sound source clock offsets. A new software, built on methodologies of previous ARTOA versions, called artoa4argo, has been created to overcome these issues by exploiting additional float satellite fixes, resolving ambiguous float positions when tracking with only two sources and systematically resolving float and sound source clock offsets. To gauge the performance of artoa4argo, 21 RAFOS-enabled profiling floats deployed in the Weddell Sea during 2008-2012 were tracked. These have previously been tracked in independent studies with a Kalman Smoother and a Multi-Constraint method. artoa4argo improves tracking by automating and streamlining methods. Although artoa4argo does not necessarily produce positions for every timestep, which the Kalman Smoother and Multi-Constraint methods do, whenever a track location is available, it outperforms both methods.
{"title":"Improved Acoustic Tracking of RAFOS-Enabled Profiling Floats Through the New Software Package artoa4argo","authors":"Cathrine Hancock, Olaf Boebel","doi":"10.1175/jtech-d-23-0020.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0020.1","url":null,"abstract":"Abstract In sea ice covered polar oceans, profiling Argo floats are often unable to surface for 9 months or longer, rendering acoustic RAFOS (Ranging And Fixing Of Sound) tracking the only method to obtain unambiguous under-ice positions. Tracking RAFOS-enabled floats has historically relied on the ARTOA3 software, which had originally been tailored towards non-profiling floats in regions featuring the SOFAR (SOund Fixing And Ranging) channel with acoustic ranges of approximately 1000km. However, in sea ice covered regions, RAFOS tracking is challenged due to: (a) reduced acoustic ranges of RAFOS signals, and (b) enhanced uncertainties in float and sound source clock offsets. A new software, built on methodologies of previous ARTOA versions, called artoa4argo, has been created to overcome these issues by exploiting additional float satellite fixes, resolving ambiguous float positions when tracking with only two sources and systematically resolving float and sound source clock offsets. To gauge the performance of artoa4argo, 21 RAFOS-enabled profiling floats deployed in the Weddell Sea during 2008-2012 were tracked. These have previously been tracked in independent studies with a Kalman Smoother and a Multi-Constraint method. artoa4argo improves tracking by automating and streamlining methods. Although artoa4argo does not necessarily produce positions for every timestep, which the Kalman Smoother and Multi-Constraint methods do, whenever a track location is available, it outperforms both methods.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135137230","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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