Pub Date : 2022-12-12DOI: 10.1175/jtech-d-22-0028.1
I. Ibrahim, G. Kopp, D. Sills
The current study develops a variant of the VAD method to retrieve thunderstorm peak event velocities using low-elevation WSR-88D radar scans. The main challenge pertains to the localized nature of thunderstorm winds which complicates single-Doppler retrievals as it dictates the use of a limited spatial scale. Since VAD methods assume constant velocity in the fitted section, it is important that retrieved sections do not contain background flow. Accordingly, the current study proposes an image processing method to partition scans into regions, representing events and the background flows, that can be retrieved independently. The study compares the retrieved peak velocities to retrievals using another VAD method. The proposed technique is found to estimate peak event velocities that are closer to measured ASOS readings, making it more suitable for historical analysis. The study also compares the results of retrievals from over 2600 thunderstorm events from 19 radar-ASOS station combinations that are less than 10 km away from the radar. Comparisons of probability distributions of peak event velocities for ASOS readings and radar retrievals showed good agreement for stations within 4 km from the radar while more distant stations had a higher bias towards retrieved velocities compared to ASOS velocities. The mean absolute error for velocity magnitude increases with height ranging between 1.5 and 4.5 m s−1. A proposed correction based on the exponential trend of mean errors was shown to improve the probability distribution comparisons, especially for higher velocity magnitudes.
目前的研究开发了一种VAD方法的变体，使用低仰角WSR-88D雷达扫描来检索雷暴峰值事件速度。主要挑战与雷暴风的局部性质有关，这使单多普勒反演变得复杂，因为它要求使用有限的空间尺度。由于VAD方法假设拟合剖面中的速度恒定，因此检索剖面不包含背景流是很重要的。因此，当前的研究提出了一种图像处理方法，将扫描划分为表示事件和背景流的区域，这些区域可以独立检索。该研究将检索到的峰值速度与使用另一种VAD方法的检索结果进行了比较。所提出的技术被发现可以估计更接近ASOS测量读数的峰值事件速度，使其更适合于历史分析。该研究还比较了距离雷达不到10公里的19个雷达ASOS站组合的2600多个雷暴事件的检索结果。ASOS读数和雷达检索的峰值事件速度的概率分布的比较表明，距离雷达4公里以内的台站具有良好的一致性，而与ASOS速度相比，更远的台站对检索速度的偏差更大。速度大小的平均绝对误差随着高度在1.5和4.5 m s−1之间的变化而增加。基于平均误差的指数趋势提出的校正方法被证明可以改进概率分布的比较，特别是对于更高的速度幅度。
{"title":"Retrieval of Peak Thunderstorm Wind Velocities using WSR-88D Weather Radars","authors":"I. Ibrahim, G. Kopp, D. Sills","doi":"10.1175/jtech-d-22-0028.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0028.1","url":null,"abstract":"\u0000The current study develops a variant of the VAD method to retrieve thunderstorm peak event velocities using low-elevation WSR-88D radar scans. The main challenge pertains to the localized nature of thunderstorm winds which complicates single-Doppler retrievals as it dictates the use of a limited spatial scale. Since VAD methods assume constant velocity in the fitted section, it is important that retrieved sections do not contain background flow. Accordingly, the current study proposes an image processing method to partition scans into regions, representing events and the background flows, that can be retrieved independently. The study compares the retrieved peak velocities to retrievals using another VAD method. The proposed technique is found to estimate peak event velocities that are closer to measured ASOS readings, making it more suitable for historical analysis. The study also compares the results of retrievals from over 2600 thunderstorm events from 19 radar-ASOS station combinations that are less than 10 km away from the radar. Comparisons of probability distributions of peak event velocities for ASOS readings and radar retrievals showed good agreement for stations within 4 km from the radar while more distant stations had a higher bias towards retrieved velocities compared to ASOS velocities. The mean absolute error for velocity magnitude increases with height ranging between 1.5 and 4.5 m s−1. A proposed correction based on the exponential trend of mean errors was shown to improve the probability distribution comparisons, especially for higher velocity magnitudes.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45059312","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 : 2022-12-02DOI: 10.1175/jtech-d-22-0050.1
K. Virts, W. Koshak
Performance assessments of the Geostationary Lightning Mapper (GLM) are conducted via comparisons with independent observations from both satellite-based sensors and ground-based lightning detection (reference) networks. A key limitation of this evaluation is that the performance of the reference networks is both imperfect and imperfectly known, such that the true performance of GLM can only be estimated. Key GLM performance metrics such as detection efficiency (DE) and false alarm rate (FAR) retrieved through comparison with reference networks are affected by those networks’ own DE, FAR, and spatiotemporal accuracy, as well as the flash matching criteria applied in the analysis. This study presents a Monte Carlo simulation-based inversion technique that is used to quantify how accurately the reference networks can assess GLM performance, as well as suggest the optimal matching criteria for estimating GLM performance. This is accomplished by running simulations that clarify the specific effect of reference network quality (i.e., DE, FAR, spatiotemporal accuracy, and the geographical patterns of these attributes) on the retrieved GLM performance metrics. Baseline reference network statistics are derived from the Earth Networks Global Lightning Network (ENGLN) and the Global Lightning Dataset (GLD360). Geographic simulations indicate that the retrieved GLM DE is underestimated, with absolute errors ranging from 11% to 32%, while the retrieved GLM FAR is overestimated, with absolute errors of approximately 16-44%. GLM performance is most severely underestimated in the South Pacific. These results help quantify and bound the actual performance of GLM and the attendant uncertainties when comparing GLM to imperfect reference networks.
{"title":"Monte Carlo Simulations for Evaluating the Accuracy of Geostationary Lightning Mapper Detection Efficiency and False Alarm Rate Retrievals","authors":"K. Virts, W. Koshak","doi":"10.1175/jtech-d-22-0050.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0050.1","url":null,"abstract":"\u0000Performance assessments of the Geostationary Lightning Mapper (GLM) are conducted via comparisons with independent observations from both satellite-based sensors and ground-based lightning detection (reference) networks. A key limitation of this evaluation is that the performance of the reference networks is both imperfect and imperfectly known, such that the true performance of GLM can only be estimated. Key GLM performance metrics such as detection efficiency (DE) and false alarm rate (FAR) retrieved through comparison with reference networks are affected by those networks’ own DE, FAR, and spatiotemporal accuracy, as well as the flash matching criteria applied in the analysis.\u0000This study presents a Monte Carlo simulation-based inversion technique that is used to quantify how accurately the reference networks can assess GLM performance, as well as suggest the optimal matching criteria for estimating GLM performance. This is accomplished by running simulations that clarify the specific effect of reference network quality (i.e., DE, FAR, spatiotemporal accuracy, and the geographical patterns of these attributes) on the retrieved GLM performance metrics. Baseline reference network statistics are derived from the Earth Networks Global Lightning Network (ENGLN) and the Global Lightning Dataset (GLD360).\u0000Geographic simulations indicate that the retrieved GLM DE is underestimated, with absolute errors ranging from 11% to 32%, while the retrieved GLM FAR is overestimated, with absolute errors of approximately 16-44%. GLM performance is most severely underestimated in the South Pacific. These results help quantify and bound the actual performance of GLM and the attendant uncertainties when comparing GLM to imperfect reference networks.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43455675","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 : 2022-11-22DOI: 10.1175/jtech-d-22-0038.1
S. M. Martinaitis, Scott Lincoln, David S. Schlotzhauer, S. Cocks, Jian Zhang
There are multiple reasons as to why a precipitation gauge would report erroneous observations. Systematic errors relating to the measuring apparatus or resulting from observational limitations due to environmental factors (e.g., wind-induced undercatch or wetting losses) can be quantified and potentially corrected within a gauge dataset. Other challenges can arise from instrumentation malfunctions, such as clogging, poor siting, and software issues. Instrumentation malfunctions are challenging to quantify as most gauge quality control (QC) schemes focus on the current observation and not on whether the gauge has an inherent issue that would likely require maintenance of the gauge. This study focuses on the development of a temporal QC scheme to identify the likelihood of an instrumentation malfunction through the examination of hourly gauge observations and associated QC designations. The analyzed gauge performance resulted in a temporal QC classification using one of three categories: GOOD, SUSP, and BAD. The temporal QC scheme also accounts for and provides an additional designation when a significant percentage of gauge observations and associated hourly QC were influenced by meteorological factors (e.g., the inability to properly measure winter precipitation). Findings showed a consistent percentage of gauges that were classified as BAD through the running 7-day (2.9%) and 30-day (4.4%) analyses. Verification of select gauges demonstrated how the temporal QC algorithm captured different forms of instrumental-based systematic errors that influenced gauge observations. Results from this study can benefit the identification of degraded performance at gauge sites prior to scheduled routine maintenance.
{"title":"A Temporal Gauge Quality Control Algorithm as a Method for Identifying Potential Instrumentation Malfunctions","authors":"S. M. Martinaitis, Scott Lincoln, David S. Schlotzhauer, S. Cocks, Jian Zhang","doi":"10.1175/jtech-d-22-0038.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0038.1","url":null,"abstract":"\u0000There are multiple reasons as to why a precipitation gauge would report erroneous observations. Systematic errors relating to the measuring apparatus or resulting from observational limitations due to environmental factors (e.g., wind-induced undercatch or wetting losses) can be quantified and potentially corrected within a gauge dataset. Other challenges can arise from instrumentation malfunctions, such as clogging, poor siting, and software issues. Instrumentation malfunctions are challenging to quantify as most gauge quality control (QC) schemes focus on the current observation and not on whether the gauge has an inherent issue that would likely require maintenance of the gauge. This study focuses on the development of a temporal QC scheme to identify the likelihood of an instrumentation malfunction through the examination of hourly gauge observations and associated QC designations. The analyzed gauge performance resulted in a temporal QC classification using one of three categories: GOOD, SUSP, and BAD. The temporal QC scheme also accounts for and provides an additional designation when a significant percentage of gauge observations and associated hourly QC were influenced by meteorological factors (e.g., the inability to properly measure winter precipitation). Findings showed a consistent percentage of gauges that were classified as BAD through the running 7-day (2.9%) and 30-day (4.4%) analyses. Verification of select gauges demonstrated how the temporal QC algorithm captured different forms of instrumental-based systematic errors that influenced gauge observations. Results from this study can benefit the identification of degraded performance at gauge sites prior to scheduled routine maintenance.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46228199","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 : 2022-11-08DOI: 10.1175/jtech-d-21-0144.1
Duncan C. Wheeler, S. Giddings
This manuscript presents several improvements to methods for despiking and measuring turbulent dissipation values with Acoustic Doppler Velocitmeters (ADVs). This includes an improved inertial sub-range fitting algorithm relevant for all experimental conditions as well as other modifications designed to address failures of existing methods in the presence of large infra-gravity (IG) frequency bores and other intermittent, nonlinear processes. We provide a modified despiking algorithm, wavenumber spectrum calculation algorithm, and inertial sub-range fitting algorithm that together produce reliable dissipation measurements in the presence of IG frequency bores, representing turbulence over a 30 minute interval. We use a semi-idealized model to show that our spectrum calculation approach works substantially better than existing wave correction equations that rely on Gaussian based velocity distributions. We also find that our inertial sub-range fitting algorithm provides more robust results than existing approaches that rely on identifying a single best fit and that this improvement is independent of environmental conditions. Finally, we perform a detailed error analysis to assist in future use of these algorithms and identify areas that need careful consideration. This error analysis uses error distribution widths to find, with 95% confidence, an average systematic uncertainty of ±15.2% and statistical uncertainty of ±7.8% for our final dissipation measurements. In addition, we find that small changes to ADV despiking approaches can lead to large uncertainties in turbulent dissipation and that further work is needed to ensure more reliable despiking algorithms.
{"title":"Measuring Turbulent Dissipation with Acoustic Doppler Velocimeters in the Presence of Large, Intermittent, Infragravity Frequency Bores","authors":"Duncan C. Wheeler, S. Giddings","doi":"10.1175/jtech-d-21-0144.1","DOIUrl":"https://doi.org/10.1175/jtech-d-21-0144.1","url":null,"abstract":"\u0000This manuscript presents several improvements to methods for despiking and measuring turbulent dissipation values with Acoustic Doppler Velocitmeters (ADVs). This includes an improved inertial sub-range fitting algorithm relevant for all experimental conditions as well as other modifications designed to address failures of existing methods in the presence of large infra-gravity (IG) frequency bores and other intermittent, nonlinear processes. We provide a modified despiking algorithm, wavenumber spectrum calculation algorithm, and inertial sub-range fitting algorithm that together produce reliable dissipation measurements in the presence of IG frequency bores, representing turbulence over a 30 minute interval. We use a semi-idealized model to show that our spectrum calculation approach works substantially better than existing wave correction equations that rely on Gaussian based velocity distributions. We also find that our inertial sub-range fitting algorithm provides more robust results than existing approaches that rely on identifying a single best fit and that this improvement is independent of environmental conditions. Finally, we perform a detailed error analysis to assist in future use of these algorithms and identify areas that need careful consideration. This error analysis uses error distribution widths to find, with 95% confidence, an average systematic uncertainty of ±15.2% and statistical uncertainty of ±7.8% for our final dissipation measurements. In addition, we find that small changes to ADV despiking approaches can lead to large uncertainties in turbulent dissipation and that further work is needed to ensure more reliable despiking algorithms.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43754367","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 : 2022-11-07DOI: 10.1175/jtech-d-22-0055.1
S. Brenner, J. Thomson, L. Rainville, D. Torres, M. Doble, J. Wilkinson, Craig M. Lee
Properties of the surface mixed layer (ML) are critical for understanding and predicting atmosphere-sea ice-ocean interactions in the changing Arctic Ocean. Mooring measurements are typically unable to resolve the ML in the Arctic due to the need for instruments to remain below the surface to avoid contact with sea ice and icebergs. Here, we use measurements from a series of three moorings installed for one year in the Beaufort Sea to demonstrate that upward looking Acoustic Doppler Current Profilers (ADCPs) installed on subsurface floats can be used to estimate ML properties. A method is developed for combining measured peaks in acoustic backscatter and inertial shear from the ADCPs to estimate the ML depth. Additionally, we use an inverse sound speed model to infer the summer ML temperature based on offsets in ADCP altimeter distance during open water periods. The ADCP estimates of ML depth and ML temperature compare favourably with measurements made from mooring temperature sensors, satellite SST, and from an autonomous Seaglider. These methods could be applied to other extant mooring records to recover additional information about ML property changes and variability.
{"title":"Acoustic sensing of ocean mixed layer depth and temperature from uplooking ADCPs","authors":"S. Brenner, J. Thomson, L. Rainville, D. Torres, M. Doble, J. Wilkinson, Craig M. Lee","doi":"10.1175/jtech-d-22-0055.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0055.1","url":null,"abstract":"\u0000Properties of the surface mixed layer (ML) are critical for understanding and predicting atmosphere-sea ice-ocean interactions in the changing Arctic Ocean. Mooring measurements are typically unable to resolve the ML in the Arctic due to the need for instruments to remain below the surface to avoid contact with sea ice and icebergs. Here, we use measurements from a series of three moorings installed for one year in the Beaufort Sea to demonstrate that upward looking Acoustic Doppler Current Profilers (ADCPs) installed on subsurface floats can be used to estimate ML properties. A method is developed for combining measured peaks in acoustic backscatter and inertial shear from the ADCPs to estimate the ML depth. Additionally, we use an inverse sound speed model to infer the summer ML temperature based on offsets in ADCP altimeter distance during open water periods. The ADCP estimates of ML depth and ML temperature compare favourably with measurements made from mooring temperature sensors, satellite SST, and from an autonomous Seaglider. These methods could be applied to other extant mooring records to recover additional information about ML property changes and variability.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48512705","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 : 2022-11-03DOI: 10.1175/jtech-d-22-0005.1
D. Cahl, G. Voulgaris, L. Leonard
We assess the performance of three different algorithms for estimating surface ocean currents from two linear array HF radar systems. The delay-and-sum beamforming algorithm, commonly used with beamforming systems, is compared with two direction finding algorithms, MUltiple Signal Classification (MUSIC) and direction finding using beamforming (Beamscan). A 7-month data set from two HF radar sites (CSW and GTN) on Long Bay, SC (USA) is used to compare the different methods. The comparison is carried out on three locations (mid-point along the baseline and two locations with in situ Eulerian current data available) representing different steering angles. Beamforming produces surface current data that show high correlation near the radar boresight (R2 ≥ 0.79). At partially sheltered locations far from the radar boresight directions (59° and 48° for radar sites CSW and GTN, respectively) there is no correlation for CSW (R2 = 0) and the correlation is reduced significantly for GTN (R2 = 0.29). Beamscan performs similarly near the radar boresight (R2 = 0.8 and 0.85 for CSW and GTN, respectively) but better than beamforming far from the radar boresight (R2 = 0.52 and 0.32 for CSW and GTN, respectively). MUSIC’s performance, after significant tuning, is similar near the boresight (R2 = 0.78 and 0.84 for CSW and GTN) while worse than Beamscan but better than beamforming far from the boresight (R2 = 0.42 and 0.27 for CSW and GTN, respectively). Comparisons at the mid-point (baseline comparison) show the largest performance difference between methods. Beamforming (R2 = 0.01) is the worst performer, followed by MUSIC (R2 = 0.37) while Beamscan (R2 = 0.76) performs best.
{"title":"A Comparison of Beamforming and Direction Finding Algorithms (Beamscan and MUSIC) on a Linear Array HF Radar in a Medium to Low Wave Energy Environment","authors":"D. Cahl, G. Voulgaris, L. Leonard","doi":"10.1175/jtech-d-22-0005.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0005.1","url":null,"abstract":"\u0000We assess the performance of three different algorithms for estimating surface ocean currents from two linear array HF radar systems. The delay-and-sum beamforming algorithm, commonly used with beamforming systems, is compared with two direction finding algorithms, MUltiple Signal Classification (MUSIC) and direction finding using beamforming (Beamscan). A 7-month data set from two HF radar sites (CSW and GTN) on Long Bay, SC (USA) is used to compare the different methods. The comparison is carried out on three locations (mid-point along the baseline and two locations with in situ Eulerian current data available) representing different steering angles. Beamforming produces surface current data that show high correlation near the radar boresight (R2 ≥ 0.79). At partially sheltered locations far from the radar boresight directions (59° and 48° for radar sites CSW and GTN, respectively) there is no correlation for CSW (R2 = 0) and the correlation is reduced significantly for GTN (R2 = 0.29). Beamscan performs similarly near the radar boresight (R2 = 0.8 and 0.85 for CSW and GTN, respectively) but better than beamforming far from the radar boresight (R2 = 0.52 and 0.32 for CSW and GTN, respectively). MUSIC’s performance, after significant tuning, is similar near the boresight (R2 = 0.78 and 0.84 for CSW and GTN) while worse than Beamscan but better than beamforming far from the boresight (R2 = 0.42 and 0.27 for CSW and GTN, respectively). Comparisons at the mid-point (baseline comparison) show the largest performance difference between methods. Beamforming (R2 = 0.01) is the worst performer, followed by MUSIC (R2 = 0.37) while Beamscan (R2 = 0.76) performs best.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46942492","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 : 2022-11-02DOI: 10.1175/jtech-d-22-0051.1
Yukio Kurihara
Stripe noise is a common issue in Sea Surface Temperatures (SSTs) retrieved from thermal infrared data obtained by satellite-based multi-detector radiometers. We developed a Bi-Spectral Filter (BSF) to reduce the stripe noise. The BSF is a Gaussian filter and an optimal estimation method for the differences between the data obtained at the split window. A kernel function based on the physical processes of radiative transfer has made it possible to reduce stripe and random noise in retrieved SSTs without degrading the spatial resolution or generating bias. The Second-Generation Global Imager (SGLI) is an optical sensor onboard the Global Change Observation Mission-Climate (GCOM-C) satellite. We applied the BSF to SGLI data and validated the retrieved SSTs. The validation results demonstrate the effectiveness of BSF, which reduced stripe noise in the retrieved SGLI SSTs without blurring SST fronts. It also improved the accuracy of the SSTs by about 0.04 K (about 13 %) in the robust standard deviation.
{"title":"A bi-spectral approach for destriping and denoising the sea surface temperature from SGLI thermal infrared data","authors":"Yukio Kurihara","doi":"10.1175/jtech-d-22-0051.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0051.1","url":null,"abstract":"\u0000Stripe noise is a common issue in Sea Surface Temperatures (SSTs) retrieved from thermal infrared data obtained by satellite-based multi-detector radiometers. We developed a Bi-Spectral Filter (BSF) to reduce the stripe noise. The BSF is a Gaussian filter and an optimal estimation method for the differences between the data obtained at the split window. A kernel function based on the physical processes of radiative transfer has made it possible to reduce stripe and random noise in retrieved SSTs without degrading the spatial resolution or generating bias. The Second-Generation Global Imager (SGLI) is an optical sensor onboard the Global Change Observation Mission-Climate (GCOM-C) satellite. We applied the BSF to SGLI data and validated the retrieved SSTs. The validation results demonstrate the effectiveness of BSF, which reduced stripe noise in the retrieved SGLI SSTs without blurring SST fronts. It also improved the accuracy of the SSTs by about 0.04 K (about 13 %) in the robust standard deviation.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48690585","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 : 2022-11-01DOI: 10.1175/jtech-d-22-0011.1
W. E. Cook, J. S. Greene
Daily rainfall accumulation estimates have been derived from 1-min volume data collected via self-syphon rain gauges deployed in the Tropical Atmosphere–Ocean (TAO) array of oceanographic buoys. The underlying high-resolution volume data were obtained directly from the Global Tropical Moored Buoy Array (GTMBA) Project Office of NOAA/Pacific Marine Environmental Laboratory. The derived accumulations have been incorporated into the Pacific Rainfall (PACRAIN) database as estimated daily values to augment existing sea level oceanic rainfall records gathered using traditional rain gauges. They have also been included in the PACRAIN historical, monthly gridded rainfall product. The methodology presented, which employs differencing of least squares–regressed sensor levels about 0000 UTC and rain gauge syphon events, is shown to offer improved error characteristics over the methodology used to compute previously published GTMBA rain rates. In particular, the PACRAIN method yields larger coefficients of determination and smaller standard errors than the duplicated GTMBA method when applied to synthetic rainfall data with noise magnitude and decorrelation times encompassing those observed in the real 1-min data. These results are shown to be consistent with mathematical expectations. Sources of instrument and catchment errors, as well as evaporation, are discussed in the context of their potential effects on accumulation estimates for periods of a day or longer. In this paper, we describe the derivation of daily rainfall amounts from raw rain gauge data obtained from buoy-mounted rain gauges. These new accumulation estimates expand the store of rainfall estimates from locations approximating the open-ocean conditions of the tropical Pacific Ocean. The derivation technique we describe exhibits better performance than the method used to generate previously published estimates using the same dataset.
{"title":"Derivation of New Daily Rainfall Values from TAO 1-Min Rain Gauge Data","authors":"W. E. Cook, J. S. Greene","doi":"10.1175/jtech-d-22-0011.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0011.1","url":null,"abstract":"\u0000Daily rainfall accumulation estimates have been derived from 1-min volume data collected via self-syphon rain gauges deployed in the Tropical Atmosphere–Ocean (TAO) array of oceanographic buoys. The underlying high-resolution volume data were obtained directly from the Global Tropical Moored Buoy Array (GTMBA) Project Office of NOAA/Pacific Marine Environmental Laboratory. The derived accumulations have been incorporated into the Pacific Rainfall (PACRAIN) database as estimated daily values to augment existing sea level oceanic rainfall records gathered using traditional rain gauges. They have also been included in the PACRAIN historical, monthly gridded rainfall product. The methodology presented, which employs differencing of least squares–regressed sensor levels about 0000 UTC and rain gauge syphon events, is shown to offer improved error characteristics over the methodology used to compute previously published GTMBA rain rates. In particular, the PACRAIN method yields larger coefficients of determination and smaller standard errors than the duplicated GTMBA method when applied to synthetic rainfall data with noise magnitude and decorrelation times encompassing those observed in the real 1-min data. These results are shown to be consistent with mathematical expectations. Sources of instrument and catchment errors, as well as evaporation, are discussed in the context of their potential effects on accumulation estimates for periods of a day or longer.\u0000\u0000\u0000In this paper, we describe the derivation of daily rainfall amounts from raw rain gauge data obtained from buoy-mounted rain gauges. These new accumulation estimates expand the store of rainfall estimates from locations approximating the open-ocean conditions of the tropical Pacific Ocean. The derivation technique we describe exhibits better performance than the method used to generate previously published estimates using the same dataset.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47829711","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 : 2022-10-28DOI: 10.1175/jtech-d-22-0035.1
B. Ferron, P. Aubertot, Y. Cuypers, C. Vic
To calculate a turbulent kinetic energy dissipation 11 rate from the microstructure vertical shear of the horizontal velocity via a spectral analysis, shear spectra need first to be cleaned from vibrations of the moving vehicle. Unambiguously, this study shows that the spectral cleaning must be applied all over the frequency range and not only at frequencies larger than 10 Hz, as a recent study suggested. For a Vertical Microstructure Profiler VMP-6000, not correcting for vehicle vibrations below 10 Hz leads to overestimated dissipation rates from 50 to 700% for usual downcast velocities and for weak dissipation rates (ε < 1 × 10−9 W kg−1). Vibrations concern all vehicles but the exact vibrational frequency signature depends on the vehicle shape and its downcast velocity. In any case, a spectral cleaning over the whole frequency range is strongly advised. This study also reports on a systematic low bias of inferred dissipation rates induced by the spectral cleaning when too few degrees of freedom are available for the cleaning, which is usually the default of the standard processing. Whatever the dissipation rate level, not correcting for the bias leads to underestimated dissipation rates by a factor 1.4 to 2.7 (with usual parameters), the exact amplitude of the bias depending on the number of degrees of freedom and on the number of independent accelerometer-axis used for the cleaning. It is strongly advised that such a bias is taken into account to recompute dissipation rates of past data sets and for future observations.
为了通过光谱分析从水平速度的微观结构垂直剪切计算湍流动能耗散率，首先需要从移动车辆的振动中清除剪切光谱。毫无疑问，这项研究表明，正如最近的一项研究所建议的那样，频谱清洁必须应用于整个频率范围，而不仅仅是大于10Hz的频率。对于垂直微结构剖面仪VMP-6000，如果不对低于10 Hz的车辆振动进行校正，则会导致对通常下行速度和弱耗散率（ε<1×10−9 W kg−1）的耗散率估计过高，从50%到700%。振动涉及所有车辆，但确切的振动频率特征取决于车辆形状及其下行速度。在任何情况下，强烈建议在整个频率范围内进行频谱清理。本研究还报告了当可用于清洁的自由度太少时，光谱清洁引起的推断耗散率的系统低偏差，这通常是标准处理的默认情况。无论耗散率水平如何，不校正偏差都会导致耗散率被低估1.4至2.7倍（使用通常的参数），偏差的确切幅度取决于自由度的数量和用于清洁的独立加速度计轴的数量。强烈建议在重新计算过去数据集的耗散率和未来观测时考虑这种偏差。
{"title":"Removing biases in oceanic turbulent kinetic energy dissipation rate estimated from microstructure shear data","authors":"B. Ferron, P. Aubertot, Y. Cuypers, C. Vic","doi":"10.1175/jtech-d-22-0035.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0035.1","url":null,"abstract":"\u0000To calculate a turbulent kinetic energy dissipation 11 rate from the microstructure vertical shear of the horizontal velocity via a spectral analysis, shear spectra need first to be cleaned from vibrations of the moving vehicle. Unambiguously, this study shows that the spectral cleaning must be applied all over the frequency range and not only at frequencies larger than 10 Hz, as a recent study suggested. For a Vertical Microstructure Profiler VMP-6000, not correcting for vehicle vibrations below 10 Hz leads to overestimated dissipation rates from 50 to 700% for usual downcast velocities and for weak dissipation rates (ε < 1 × 10−9 W kg−1). Vibrations concern all vehicles but the exact vibrational frequency signature depends on the vehicle shape and its downcast velocity. In any case, a spectral cleaning over the whole frequency range is strongly advised.\u0000This study also reports on a systematic low bias of inferred dissipation rates induced by the spectral cleaning when too few degrees of freedom are available for the cleaning, which is usually the default of the standard processing. Whatever the dissipation rate level, not correcting for the bias leads to underestimated dissipation rates by a factor 1.4 to 2.7 (with usual parameters), the exact amplitude of the bias depending on the number of degrees of freedom and on the number of independent accelerometer-axis used for the cleaning. It is strongly advised that such a bias is taken into account to recompute dissipation rates of past data sets and for future observations.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48633936","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 : 2022-10-19DOI: 10.1175/jtech-d-22-0062.1
Guangping Liu, Yong-ping Jin, Youduo Peng, Deshun Liu, Liang Liu
A new full-ocean-depth macro-organisms pressure-retaining sampler (FMPS) was designed to collect pressure-retaining macro-organisms samples from the abyssal seafloor. A mathematical model for pressure compensation in the FMPS recovery process was developed. The effects of FMPS structural parameters, pressure compensator structural parameters and sampling environment on the pressure retention performance of FMPS were analyzed. Using the developed FMPS engineering prototype, FMPS internal pressure test, high-pressure chamber simulation sampling, and pressure-retaining test was carried out. The test results show that the key components of FMPS can carry 115MPa pressure, FMPS can complete the sampling action in the high-pressure chamber of 115MPa, the pressure is maintained at 105.5MPa, and the pressure drop rate (ratio of pressure drop during FMPS recovery to sampling point pressure) is 9.13%, the experimental results are consistent with the theoretical calculation. The test verified the feasibility of FMPS design and the reliability of pressure retention, providing a theoretical basis and technical support for the design and manufacture of full-ocean-depth sampling devices.
{"title":"Scheme Design and Pressure-Retaining Performance Analysis of Macro-biological Sampler in the Full-Ocean-Depth Operating Environment","authors":"Guangping Liu, Yong-ping Jin, Youduo Peng, Deshun Liu, Liang Liu","doi":"10.1175/jtech-d-22-0062.1","DOIUrl":"https://doi.org/10.1175/jtech-d-22-0062.1","url":null,"abstract":"\u0000A new full-ocean-depth macro-organisms pressure-retaining sampler (FMPS) was designed to collect pressure-retaining macro-organisms samples from the abyssal seafloor. A mathematical model for pressure compensation in the FMPS recovery process was developed. The effects of FMPS structural parameters, pressure compensator structural parameters and sampling environment on the pressure retention performance of FMPS were analyzed. Using the developed FMPS engineering prototype, FMPS internal pressure test, high-pressure chamber simulation sampling, and pressure-retaining test was carried out. The test results show that the key components of FMPS can carry 115MPa pressure, FMPS can complete the sampling action in the high-pressure chamber of 115MPa, the pressure is maintained at 105.5MPa, and the pressure drop rate (ratio of pressure drop during FMPS recovery to sampling point pressure) is 9.13%, the experimental results are consistent with the theoretical calculation. The test verified the feasibility of FMPS design and the reliability of pressure retention, providing a theoretical basis and technical support for the design and manufacture of full-ocean-depth sampling devices.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49312380","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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