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":"2 11","pages":""},"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":"75 5","pages":""},"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}
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":"10 3","pages":""},"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 : 2023-12-01Epub Date: 2022-03-31DOI: 10.1097/WNO.0000000000001588
Wendy Phillips, John Somner
{"title":"A Case of Idiopathic Intracranial Hypertension/Pseudotumor Cerebri Syndrome Cured by Myomectomy.","authors":"Wendy Phillips, John Somner","doi":"10.1097/WNO.0000000000001588","DOIUrl":"10.1097/WNO.0000000000001588","url":null,"abstract":"","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":"10 1","pages":"e156-e158"},"PeriodicalIF":2.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86641862","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":"20 2","pages":""},"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":"119 1","pages":"0"},"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}
Pub Date : 2023-11-03DOI: 10.1175/jtech-d-22-0142.1
Fanwei Su, Yunhua Wang, Yining Bai, Daozhong Sun, Ge Chen, Chunyong Ma, Yanmin Zhang, Wenzheng Jiang
Abstract The interferometric radar altimeter (IRA) is an innovative remote sensing sensor that enables the observation of mesoscale and sub-mesoscale (meso-submesoscale) ocean dynamic phenomena. The neutral atmosphere introduces path delay and bending in signal propagation. In this study, three types of SSH errors caused by neutral atmosphere propagation path for IRA were identified: differential delay error (DDE), path delay error (PDE), and path bending error (PBE). Among them, DDE exhibits a proportionality to the negative zenith neutral delay (ZND) and demonstrates a significant increase with the incident angle; PDE is solely reliant on the ZND; PBE is like DDE in trend and magnitude resembling a ramp. Intriguingly, PBE exhibits insensitivity to variations in the neutral atmosphere, behaving more like a systematic error. Theoretically, PBE leads to an increase in the SSH error of about 1.2cm at far-range for SWOT. The ZND spectrum fitted from the Jason-3 zenith delay correction data is additionally utilized to simulate the spatial distribution of ZND anomaly within the SWOT observation swaths. Then, the impact of PDE anomaly (PDEA), PBE, and DDE anomaly (DDEA) on the observation performance of SWOT is also considered in conjunction with SSH data provided by Hycom. The findings indicate that both PDEA and PBE significantly reduce IRA's performance in oceanic phenomena, while the impact of DDEA can be disregarded. The PBE can distort the sea surface trend and increases the mean sea level within the range, requiring further attention.
{"title":"The Impact of Neutral Atmospheric Propagation Path on the Altimetry Performance of Interferometric Radar Altimeter","authors":"Fanwei Su, Yunhua Wang, Yining Bai, Daozhong Sun, Ge Chen, Chunyong Ma, Yanmin Zhang, Wenzheng Jiang","doi":"10.1175/jtech-d-22-0142.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0142.1","url":null,"abstract":"Abstract The interferometric radar altimeter (IRA) is an innovative remote sensing sensor that enables the observation of mesoscale and sub-mesoscale (meso-submesoscale) ocean dynamic phenomena. The neutral atmosphere introduces path delay and bending in signal propagation. In this study, three types of SSH errors caused by neutral atmosphere propagation path for IRA were identified: differential delay error (DDE), path delay error (PDE), and path bending error (PBE). Among them, DDE exhibits a proportionality to the negative zenith neutral delay (ZND) and demonstrates a significant increase with the incident angle; PDE is solely reliant on the ZND; PBE is like DDE in trend and magnitude resembling a ramp. Intriguingly, PBE exhibits insensitivity to variations in the neutral atmosphere, behaving more like a systematic error. Theoretically, PBE leads to an increase in the SSH error of about 1.2cm at far-range for SWOT. The ZND spectrum fitted from the Jason-3 zenith delay correction data is additionally utilized to simulate the spatial distribution of ZND anomaly within the SWOT observation swaths. Then, the impact of PDE anomaly (PDEA), PBE, and DDE anomaly (DDEA) on the observation performance of SWOT is also considered in conjunction with SSH data provided by Hycom. The findings indicate that both PDEA and PBE significantly reduce IRA's performance in oceanic phenomena, while the impact of DDEA can be disregarded. The PBE can distort the sea surface trend and increases the mean sea level within the range, requiring further attention.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":"43 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135820183","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}
Abstract In the equilibrium range of the wave spectrum’s high frequency tail, energy levels are proportional to the wind friction velocity. As a consequence of this intrinsic coupling, spectral tail energy levels can be used as proxy observations of surface stress and wind speed when direct observations are unavailable. Proxy observations from drifting wave-buoy networks can therefore augment existing remote sensing capabilities by providing long dwell observations of surface winds. Here we consider the skill of proxy wind estimates obtained from observations recorded by the globally distributed Sofar Spotter network (observations from 2021–2022) when compared with collocated observations derived from satellites (yielding over 20000 collocations) and reanalysis data. We consider physics motivated parameterizations (based on frequency −4 universal tail assumption), inverse modelling (estimate wind speed from spectral energy balance), and a data driven approach (artificial neural network) as potential methods. Evaluation of trained/calibrated models on unseen test-data reveals comparable performance across methods with generally order 1 m/s root-mean-square-difference with satellite observations.
{"title":"Proxy observations of surface wind from a globally distributed network of wave buoys","authors":"Ciara Dorsay, Galen Egan, Isabel Houghton, Christie Hegermiller, Pieter B. Smit","doi":"10.1175/jtech-d-23-0044.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0044.1","url":null,"abstract":"Abstract In the equilibrium range of the wave spectrum’s high frequency tail, energy levels are proportional to the wind friction velocity. As a consequence of this intrinsic coupling, spectral tail energy levels can be used as proxy observations of surface stress and wind speed when direct observations are unavailable. Proxy observations from drifting wave-buoy networks can therefore augment existing remote sensing capabilities by providing long dwell observations of surface winds. Here we consider the skill of proxy wind estimates obtained from observations recorded by the globally distributed Sofar Spotter network (observations from 2021–2022) when compared with collocated observations derived from satellites (yielding over 20000 collocations) and reanalysis data. We consider physics motivated parameterizations (based on frequency −4 universal tail assumption), inverse modelling (estimate wind speed from spectral energy balance), and a data driven approach (artificial neural network) as potential methods. Evaluation of trained/calibrated models on unseen test-data reveals comparable performance across methods with generally order 1 m/s root-mean-square-difference with satellite observations.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":"42 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135819875","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 : 2023-11-01DOI: 10.1175/jtech-d-23-0065.1
Tom Akkermans, N. Clerbaux
The third edition of the CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data (CLARA-A3) contains for the first time the top-of-atmosphere products reflected solar flux (RSF) and outgoing longwave radiation (OLR), which are presented and validated using CERES, HIRS, and ERA5 reference data. The products feature an unprecedented resolution (0.25°) and time span (4 decades) and offer synergy and compatibility with other CLARA-A3 products. The RSF is relatively stable; its bias with respect to (w.r.t.) ERA5 remains mostly within ±2 W m−2. Deviations are predominantly caused by absence of either morning or afternoon satellite, mostly during the first decade. The radiative impact of the Pinatubo volcanic eruption is estimated at 3 W m−2. The OLR is stable w.r.t. ERA5 and HIRS, except during 1979–80. OLR regional uncertainty w.r.t. HIRS is quantified by the mean absolute bias (MAB) and correlates with observation density and time (satellite orbital configuration), which is optimal during 2002–16, with monthly and daily MAB of approximately 1.5 and 3.5 W m−2, respectively. Daily OLR uncertainty is higher (MAB +40%) during periods with only morning or only afternoon observations (1979–87). During the CERES era (2000–20), the OLR uncertainties w.r.t. CERES-EBAF, CERES-SYN, and HIRS are very similar. The RSF uncertainty achieves optimal results during 2002–16 with a monthly MAB w.r.t. CERES-EBAF of ∼2 W m−2 and a daily MAB w.r.t. CERES-SYN of ∼5 W m−2, and it is more sensitive to orbital configuration than is OLR. Overall, validation results are satisfactory for this first release of TOA flux products in the CLARA-A3 portfolio.
利用高级甚高分辨率辐射计数据制作的第三版 CM SAF 云层、反照率和表面辐射数据集（CLARA-A3）首次包含了大气层顶层产品反射太阳通量（RSF）和外向长波辐射（OLR），并利用 CERES、HIRS 和 ERA5 参考数据对其进行了展示和验证。这些产品具有前所未有的分辨率（0.25°）和时间跨度（40 年），并与 CLARA-A3 的其他产品具有协同性和兼容性。RSF 相对稳定；相对于 ERA5 的偏差基本保持在 ±2 W m-2 范围内。偏差主要是由于缺少上午或下午的卫星造成的，大部分发生在第一个十年。皮纳图博火山爆发的辐射影响估计为 3 W m-2。相对于ERA5和HIRS，OLR是稳定的，1979-1980年期间除外。与 HIRS 相比，OLR 的区域不确定性由平均绝对偏差（MAB）量化，并与观测密度和时间（卫星轨道配置）相关。在只有上午或只有下午观测的时期（1979-1987 年），每日 OLR 的不确定性更高（MAB +40%）。在 CERES 时代（2000-20 年），CERES-EBAF、CERES-SYN 和 HIRS 的 OLR 不确定性非常相似。在 2002-16 年期间，RSF 的不确定性达到了最佳结果，与 CERES-EBAF 相比的月 MAB 为 ∼2 W m-2，与 CERES-SYN 相比的日 MAB 为 ∼5 W m-2，它对轨道配置比 OLR 更敏感。总体而言，CLARA-A3 组合中首次发布的 TOA 通量产品的验证结果令人满意。
{"title":"Validation of the CLARA-A3 Top-of-Atmosphere Radiative Fluxes Climate Data Record","authors":"Tom Akkermans, N. Clerbaux","doi":"10.1175/jtech-d-23-0065.1","DOIUrl":"https://doi.org/10.1175/jtech-d-23-0065.1","url":null,"abstract":"The third edition of the CM SAF Cloud, Albedo and Surface Radiation dataset from AVHRR data (CLARA-A3) contains for the first time the top-of-atmosphere products reflected solar flux (RSF) and outgoing longwave radiation (OLR), which are presented and validated using CERES, HIRS, and ERA5 reference data. The products feature an unprecedented resolution (0.25°) and time span (4 decades) and offer synergy and compatibility with other CLARA-A3 products. The RSF is relatively stable; its bias with respect to (w.r.t.) ERA5 remains mostly within ±2 W m−2. Deviations are predominantly caused by absence of either morning or afternoon satellite, mostly during the first decade. The radiative impact of the Pinatubo volcanic eruption is estimated at 3 W m−2. The OLR is stable w.r.t. ERA5 and HIRS, except during 1979–80. OLR regional uncertainty w.r.t. HIRS is quantified by the mean absolute bias (MAB) and correlates with observation density and time (satellite orbital configuration), which is optimal during 2002–16, with monthly and daily MAB of approximately 1.5 and 3.5 W m−2, respectively. Daily OLR uncertainty is higher (MAB +40%) during periods with only morning or only afternoon observations (1979–87). During the CERES era (2000–20), the OLR uncertainties w.r.t. CERES-EBAF, CERES-SYN, and HIRS are very similar. The RSF uncertainty achieves optimal results during 2002–16 with a monthly MAB w.r.t. CERES-EBAF of ∼2 W m−2 and a daily MAB w.r.t. CERES-SYN of ∼5 W m−2, and it is more sensitive to orbital configuration than is OLR. Overall, validation results are satisfactory for this first release of TOA flux products in the CLARA-A3 portfolio.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":"20 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139304957","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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