Browse
Abstract
Loon LLC collected 794 000 h of corona current observations between 15 and ∼20 km above sea level with time resolution between 1 and 30 min. We are publicly releasing this dataset to enable the research community’s understanding of electrical activity in the stratosphere. We validate the reliability of these measurements by aligning our flight data with both nearby Geostationary Lightning Mapper (GLM) events and the Convective Diagnostic Oceanic (CDO) indicator. Corona current observations that exceeded the sensor maximum of 10 μA were associated with high GLM optical flux accumulations along the flight trajectory. Using the CDO indicator as a persistence forecast for future electrical activity was effective at predicting corona current events, and so we highly recommend this data source for real-time stratospheric navigation for vehicles sensitive to the harsh electrical environment of the stratosphere.
Significance Statement
Loon LLC operated a fleet of balloons in the stratosphere, between 15 and 20 km above sea level. The balloons were instrumented with a sensor that measured the current flowing through a wire dangling from the flight vehicle. The observed currents were caused by the motion of nearby charged particles that are often associated with thunderstorms and lightning activity. In this paper we show that Loon’s sensor registered current at the same time lightning was recorded near the balloon by other instruments like the Geostationary Lightning Mapper satellite. This is the first dataset of its kind and size, reaching 794 000 flight hours. We are publicly releasing these data in hopes of aiding scientific discovery by researchers and to help future stratospheric vehicle operators better understand and plan for the electrical environment.
Abstract
Loon LLC collected 794 000 h of corona current observations between 15 and ∼20 km above sea level with time resolution between 1 and 30 min. We are publicly releasing this dataset to enable the research community’s understanding of electrical activity in the stratosphere. We validate the reliability of these measurements by aligning our flight data with both nearby Geostationary Lightning Mapper (GLM) events and the Convective Diagnostic Oceanic (CDO) indicator. Corona current observations that exceeded the sensor maximum of 10 μA were associated with high GLM optical flux accumulations along the flight trajectory. Using the CDO indicator as a persistence forecast for future electrical activity was effective at predicting corona current events, and so we highly recommend this data source for real-time stratospheric navigation for vehicles sensitive to the harsh electrical environment of the stratosphere.
Significance Statement
Loon LLC operated a fleet of balloons in the stratosphere, between 15 and 20 km above sea level. The balloons were instrumented with a sensor that measured the current flowing through a wire dangling from the flight vehicle. The observed currents were caused by the motion of nearby charged particles that are often associated with thunderstorms and lightning activity. In this paper we show that Loon’s sensor registered current at the same time lightning was recorded near the balloon by other instruments like the Geostationary Lightning Mapper satellite. This is the first dataset of its kind and size, reaching 794 000 flight hours. We are publicly releasing these data in hopes of aiding scientific discovery by researchers and to help future stratospheric vehicle operators better understand and plan for the electrical environment.
Abstract
We identify and characterize an error in the National Data Buoy Center (NDBC) wave records due to the sustained tilt of a buoy under high winds. We use a standard, operational 3-m aluminum discus buoy from NDBC with two wave systems, one gimballed, and the other strapped down but uncorrected. By comparing the two, we find that the most extreme significant wave heights are systematically overestimated. The overestimation is shown to be confined to a region around the peak frequency in the spectra: 0.05–0.15 Hz. Wave direction and directional spread are unaffected. A bias due to tilt error can be observed starting at winds of 10 m s−1 or wave heights of 4 m. The bias increases as a function of wind speed and wave height, i.e., the bias is +10% when winds are 20 m s−1. Very high waves and winds are relatively rare, so while the tilt error does not affect overall statistics and basic analyses it could potentially affect analysis sensitive to the extremes. A correction is derived for significant wave height, which is a quadratic function of wind speed. The correction is shown to reduce wave heights in uncorrected records, but is found inadequate for general use. There is evidence of tilt error at other NDBC stations, but the full extent of prevalence in the record is not known at this time.
Abstract
We identify and characterize an error in the National Data Buoy Center (NDBC) wave records due to the sustained tilt of a buoy under high winds. We use a standard, operational 3-m aluminum discus buoy from NDBC with two wave systems, one gimballed, and the other strapped down but uncorrected. By comparing the two, we find that the most extreme significant wave heights are systematically overestimated. The overestimation is shown to be confined to a region around the peak frequency in the spectra: 0.05–0.15 Hz. Wave direction and directional spread are unaffected. A bias due to tilt error can be observed starting at winds of 10 m s−1 or wave heights of 4 m. The bias increases as a function of wind speed and wave height, i.e., the bias is +10% when winds are 20 m s−1. Very high waves and winds are relatively rare, so while the tilt error does not affect overall statistics and basic analyses it could potentially affect analysis sensitive to the extremes. A correction is derived for significant wave height, which is a quadratic function of wind speed. The correction is shown to reduce wave heights in uncorrected records, but is found inadequate for general use. There is evidence of tilt error at other NDBC stations, but the full extent of prevalence in the record is not known at this time.
Abstract
Spaceborne precipitation radars, including the Tropical Rainfall Measuring Mission’s Precipitation Radar (PR) and the Global Precipitation Measurement Mission’s Dual-Frequency Precipitation Radar (DPR), measure not only precipitation echoes but surface echoes as well, the latter of which are used to estimate the path-integrated attenuation (PIA) in the surface reference technique (SRT). In our previous study based on analyzing PR measurements, we found that attenuation-free surface backscattering cross sections (denoted by
Abstract
Spaceborne precipitation radars, including the Tropical Rainfall Measuring Mission’s Precipitation Radar (PR) and the Global Precipitation Measurement Mission’s Dual-Frequency Precipitation Radar (DPR), measure not only precipitation echoes but surface echoes as well, the latter of which are used to estimate the path-integrated attenuation (PIA) in the surface reference technique (SRT). In our previous study based on analyzing PR measurements, we found that attenuation-free surface backscattering cross sections (denoted by
Abstract
The importance of quantifying the accuracy in wave measurements is critical to not only understand the complexities of wind-generated waves, but imperative for the interpretation of implied accuracy of the prediction systems that use these data for verification and validation. As wave measurement systems have unique collection and processing attributes that result in large accuracy ranges, this work quantifies bias that may be introduced into wave models from the newly operational NOAA National Data Buoy Center (NDBC) 2.1-m hull. Data quality consistency between the legacy NDBC 3-m aluminum hulls and the new 2.1-m hull is compared to a relative reference, and provides a standardized methodology and graphical representation template for future intrameasurement evaluations. Statistical analyses and wave spectral comparisons confirm that the wave measurements reported from the NDBC 2.1-m hulls show an increased accuracy from previously collected NDBC 3-m hull wave data for significant wave height and average wave period, while retaining consistent accuracy for directional results, purporting that hull size does not impact NDBC directional data estimates. Spectrally, the NDBC 2.1-m hulls show an improved signal-to-noise ratio, allowing for increase in energy retention in the lower-frequency spectral range, with an improved high-frequency spectral accuracy above 0.25 Hz within the short seas and wind chop wave component regions. These improvements in both NDBC bulk and spectral data accuracy provide confidence for the wave community’s use of NDBC wave data to drive wave model technologies, improvements, and validations.
Abstract
The importance of quantifying the accuracy in wave measurements is critical to not only understand the complexities of wind-generated waves, but imperative for the interpretation of implied accuracy of the prediction systems that use these data for verification and validation. As wave measurement systems have unique collection and processing attributes that result in large accuracy ranges, this work quantifies bias that may be introduced into wave models from the newly operational NOAA National Data Buoy Center (NDBC) 2.1-m hull. Data quality consistency between the legacy NDBC 3-m aluminum hulls and the new 2.1-m hull is compared to a relative reference, and provides a standardized methodology and graphical representation template for future intrameasurement evaluations. Statistical analyses and wave spectral comparisons confirm that the wave measurements reported from the NDBC 2.1-m hulls show an increased accuracy from previously collected NDBC 3-m hull wave data for significant wave height and average wave period, while retaining consistent accuracy for directional results, purporting that hull size does not impact NDBC directional data estimates. Spectrally, the NDBC 2.1-m hulls show an improved signal-to-noise ratio, allowing for increase in energy retention in the lower-frequency spectral range, with an improved high-frequency spectral accuracy above 0.25 Hz within the short seas and wind chop wave component regions. These improvements in both NDBC bulk and spectral data accuracy provide confidence for the wave community’s use of NDBC wave data to drive wave model technologies, improvements, and validations.
Abstract
Observations of temperature and wind velocity in the 30–40-km altitude layer have been sparse since elimination of the standard rocketsonde sounding network in the 1990s. In an effort to extend the vertical range of radiosonde observations into the upper stratosphere, experiments were conducted with a 3-kg balloon at Tsukuba, Japan, on 5 November 2019. Using this relatively inexpensive balloon technology, four radiosondes were launched, with two reaching above 40-km altitude. These profiles were compared with satellite and reanalysis data in the 30–40-km layer, which showed an overall good agreement and an ability of radiosondes to capture shorter vertical-scale variations. The ability to quantify gravity wave parameters from the data is described, with application to wave events detected near 38–40 km. This type of balloon will be deployed extensively in an upcoming intensive observation campaign over the Maritime Continent, which will contribute toward achieving standard radiosonde observations in the 30–40-km altitude range. This system extends the ability to provide information regarding gravity wave and planetary wave activity upward to ∼40 km.
Abstract
Observations of temperature and wind velocity in the 30–40-km altitude layer have been sparse since elimination of the standard rocketsonde sounding network in the 1990s. In an effort to extend the vertical range of radiosonde observations into the upper stratosphere, experiments were conducted with a 3-kg balloon at Tsukuba, Japan, on 5 November 2019. Using this relatively inexpensive balloon technology, four radiosondes were launched, with two reaching above 40-km altitude. These profiles were compared with satellite and reanalysis data in the 30–40-km layer, which showed an overall good agreement and an ability of radiosondes to capture shorter vertical-scale variations. The ability to quantify gravity wave parameters from the data is described, with application to wave events detected near 38–40 km. This type of balloon will be deployed extensively in an upcoming intensive observation campaign over the Maritime Continent, which will contribute toward achieving standard radiosonde observations in the 30–40-km altitude range. This system extends the ability to provide information regarding gravity wave and planetary wave activity upward to ∼40 km.
Abstract
A magnetic signature is created by secondary magnetic field fluctuations caused by the phenomenon of seawater moving in Earth’s magnetic field. A laboratory experiment was conducted at the Surge Structure Atmosphere Interaction (SUSTAIN) facility to measure the magnetic signature of surface waves using a differential method: a pair of magnetometers, separated horizontally by one-half wavelength, were placed at several locations on the outer tank walls. This technique significantly reduced the extraneous magnetic distortions that were detected simultaneously by both sensors and additionally doubled the magnetic signal of surface waves. Accelerometer measurements and local gradients were used to identify magnetic noise produced from tank vibrations. Wave parameters of 4-m-long waves with a 0.56-Hz frequency and a 0.1-m amplitude were used in this experiment. Freshwater and saltwater experiments were completed to determine the magnetic difference generated by the difference in conductivity. Tests with an empty tank were conducted to identify the noise of the facility. When the magnetic signal was put through spectral analysis, it showed the primary peak at the wave frequency (0.56 Hz) and less pronounced higher-frequency harmonics, which are caused by the nonlinearity of shallow water surface waves. The magnetic noise induced by the wavemaker and related vibrations peaked around 0.3 Hz, which was removed using filtering techniques. These results indicate that the magnetic signature produced by surface waves was an order of magnitude larger than in traditional model predictions. The discrepancy may be due to the magnetic permeability difference between water and air that is not considered in the traditional model.
Abstract
A magnetic signature is created by secondary magnetic field fluctuations caused by the phenomenon of seawater moving in Earth’s magnetic field. A laboratory experiment was conducted at the Surge Structure Atmosphere Interaction (SUSTAIN) facility to measure the magnetic signature of surface waves using a differential method: a pair of magnetometers, separated horizontally by one-half wavelength, were placed at several locations on the outer tank walls. This technique significantly reduced the extraneous magnetic distortions that were detected simultaneously by both sensors and additionally doubled the magnetic signal of surface waves. Accelerometer measurements and local gradients were used to identify magnetic noise produced from tank vibrations. Wave parameters of 4-m-long waves with a 0.56-Hz frequency and a 0.1-m amplitude were used in this experiment. Freshwater and saltwater experiments were completed to determine the magnetic difference generated by the difference in conductivity. Tests with an empty tank were conducted to identify the noise of the facility. When the magnetic signal was put through spectral analysis, it showed the primary peak at the wave frequency (0.56 Hz) and less pronounced higher-frequency harmonics, which are caused by the nonlinearity of shallow water surface waves. The magnetic noise induced by the wavemaker and related vibrations peaked around 0.3 Hz, which was removed using filtering techniques. These results indicate that the magnetic signature produced by surface waves was an order of magnitude larger than in traditional model predictions. The discrepancy may be due to the magnetic permeability difference between water and air that is not considered in the traditional model.
Abstract
Finescale strain parameterization (FSP) of turbulent kinetic energy dissipation rate has become a widely used method for observing ocean mixing, solving a coverage problem where direct turbulence measurements are absent but CTD profiles are available. This method can offer significant value, but there are limitations in its broad application to the global ocean. FSP often fails to produce reliable results in frontal zones where temperature–salinity (T/S) intrusive features contaminate the CTD strain spectrum, as well as where the aspect ratio of the internal wave spectrum is known to vary greatly with depth, as frequently occurs in the Southern Ocean. In this study we use direct turbulence measurements from Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean (DIMES) and glider microstructure measurements from Autonomous Sampling of Southern Ocean Mixing (AUSSOM) to show that FSP can have large biases (compared to direct turbulence measurement) below the mixed layer when physics associated with T/S fronts are meaningfully present. We propose that the FSP methodology be modified to 1) include a density ratio (Rρ )-based data exclusion rule to avoid contamination by double diffusive instabilities in frontal zones such as the Antarctic Circumpolar Current, the Gulf Stream, and the Kuroshio, and 2) conduct (or leverage available) microstructure measurements of the depth-varying shear-to-strain ratio Rω (z) prior to performing FSP in each dynamically unique region of the global ocean.
Significance Statement
Internal waves travel through the ocean and collide, turbulently mixing the interior ocean and homogenizing its waters. In the absence of actual turbulence measurements, oceanographers count the ripples associated with these internal waves and use them estimate the amount of turbulence that will transpire from their collisions. In this paper we show that the ripples in temperature and salinity that naturally occur at sharp fronts masquerade as internal waves and trick oceanographers into thinking there is up to 100 000 000 times more turbulence than there actually is in these frontal regions.
Abstract
Finescale strain parameterization (FSP) of turbulent kinetic energy dissipation rate has become a widely used method for observing ocean mixing, solving a coverage problem where direct turbulence measurements are absent but CTD profiles are available. This method can offer significant value, but there are limitations in its broad application to the global ocean. FSP often fails to produce reliable results in frontal zones where temperature–salinity (T/S) intrusive features contaminate the CTD strain spectrum, as well as where the aspect ratio of the internal wave spectrum is known to vary greatly with depth, as frequently occurs in the Southern Ocean. In this study we use direct turbulence measurements from Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean (DIMES) and glider microstructure measurements from Autonomous Sampling of Southern Ocean Mixing (AUSSOM) to show that FSP can have large biases (compared to direct turbulence measurement) below the mixed layer when physics associated with T/S fronts are meaningfully present. We propose that the FSP methodology be modified to 1) include a density ratio (Rρ )-based data exclusion rule to avoid contamination by double diffusive instabilities in frontal zones such as the Antarctic Circumpolar Current, the Gulf Stream, and the Kuroshio, and 2) conduct (or leverage available) microstructure measurements of the depth-varying shear-to-strain ratio Rω (z) prior to performing FSP in each dynamically unique region of the global ocean.
Significance Statement
Internal waves travel through the ocean and collide, turbulently mixing the interior ocean and homogenizing its waters. In the absence of actual turbulence measurements, oceanographers count the ripples associated with these internal waves and use them estimate the amount of turbulence that will transpire from their collisions. In this paper we show that the ripples in temperature and salinity that naturally occur at sharp fronts masquerade as internal waves and trick oceanographers into thinking there is up to 100 000 000 times more turbulence than there actually is in these frontal regions.
Abstract
A method to extract characteristics of the Gulf Stream (GS) surface flow field using high-frequency radar (HFR)–derived currents is described. Radial velocity measurements, from radar installations near Cape Hatteras, North Carolina, serve as input, chosen because of the greater spatial and temporal coverage provided compared to total velocity fields. The landward GS edge, jet axis, orientation, and cyclonic shear zone (CSZ) width are identified along bearings within the radar footprint. The method is applied to observations from two radar installations from November 2014 and provides GS estimates with daily temporal resolution. Results along eight bearings provide a consistent representation of GS variability dominated by the passage of meanders. Average distance to the GS edge along bearings varies from 50 to 100 km; distance estimate quality degrades with range from the radars. Monthly mean GS jet axis locations from satellite sea surface height (SSH) and the algorithm are consistent. Cross correlations between estimates of GS characteristics in the same region vary from 0.37 to 0.73 for the GS edge. Estimates of radar distance to the GS edge are negatively correlated with current velocity measurements nearest the surface from a moored 150-kHz acoustic Doppler current profiler and vary between −0.58 and −0.71. GS CSZ width metrics range from mean values of 29–31 km. Daily GS orientation estimates are affected by the crossing angle of the radial bearing relative to the GS. Lags from the cross correlations of monthly mean properties suggest meander propagation speed estimates increase from 43.2 km day−1 south of the cape, to 136.8 km day−1 just east of it.
Abstract
A method to extract characteristics of the Gulf Stream (GS) surface flow field using high-frequency radar (HFR)–derived currents is described. Radial velocity measurements, from radar installations near Cape Hatteras, North Carolina, serve as input, chosen because of the greater spatial and temporal coverage provided compared to total velocity fields. The landward GS edge, jet axis, orientation, and cyclonic shear zone (CSZ) width are identified along bearings within the radar footprint. The method is applied to observations from two radar installations from November 2014 and provides GS estimates with daily temporal resolution. Results along eight bearings provide a consistent representation of GS variability dominated by the passage of meanders. Average distance to the GS edge along bearings varies from 50 to 100 km; distance estimate quality degrades with range from the radars. Monthly mean GS jet axis locations from satellite sea surface height (SSH) and the algorithm are consistent. Cross correlations between estimates of GS characteristics in the same region vary from 0.37 to 0.73 for the GS edge. Estimates of radar distance to the GS edge are negatively correlated with current velocity measurements nearest the surface from a moored 150-kHz acoustic Doppler current profiler and vary between −0.58 and −0.71. GS CSZ width metrics range from mean values of 29–31 km. Daily GS orientation estimates are affected by the crossing angle of the radial bearing relative to the GS. Lags from the cross correlations of monthly mean properties suggest meander propagation speed estimates increase from 43.2 km day−1 south of the cape, to 136.8 km day−1 just east of it.
Abstract
Wave buoys are a popular choice for measuring sea surface waves, and there is also an increasing interest for wave information from ice-covered water bodies. Such measurements require cost-effective, easily deployable, and robust devices. We have developed LainePoiss (LP)—an ice-resistant and lightweight wave buoy. It calculates the surface elevation by double integrating the data from the inertial sensors of the microelectromechanical system (MEMS), and transmits wave parameters and spectra in real time over cellular or satellite networks. LP was validated through 1) sensor tests, 2) wave tank experiments, 3) a field validation against a Directional Waverider, 4) an intercomparison of several buoys in the field, and 5) field measurements in the Baltic Sea marginal ice zone. These extensive field and laboratory tests confirmed that LP performed well (e.g., the bias of Hm 0 in the field was 0.01 m, with a correlation of 0.99 and a scatter index of 8%; the mean absolute deviation of mean wave direction was 7°). LP was also deployed with an unmanned aerial vehicle and we present our experience of such operations. One issue that requires further development is the presence of low-frequency artifacts caused by the dynamic noise of the gyroscope. For now, a correction method is presented to deal with the noise.
Significance Statement
Operational wave buoys are large and therefore expensive and inconvenient to deploy. Many commercially available devices cannot measure short waves and are not tested in ice. Our purpose was to develop an affordable wave buoy that is lightweight, ice resistant, capable of measuring short waves, and also has a longer operating life than existing research buoys. The buoy is easily deployed with a small boat or even an industrial drone, thus reducing operating costs. The buoy is accurate, and captures waves that are too short for operational wave buoys. This is relevant for coastal planning in, e.g., archipelagos and narrow fjords. We measured waves in ice in the Baltic Sea, and are planning to extend these measurements to Antarctica.
Abstract
Wave buoys are a popular choice for measuring sea surface waves, and there is also an increasing interest for wave information from ice-covered water bodies. Such measurements require cost-effective, easily deployable, and robust devices. We have developed LainePoiss (LP)—an ice-resistant and lightweight wave buoy. It calculates the surface elevation by double integrating the data from the inertial sensors of the microelectromechanical system (MEMS), and transmits wave parameters and spectra in real time over cellular or satellite networks. LP was validated through 1) sensor tests, 2) wave tank experiments, 3) a field validation against a Directional Waverider, 4) an intercomparison of several buoys in the field, and 5) field measurements in the Baltic Sea marginal ice zone. These extensive field and laboratory tests confirmed that LP performed well (e.g., the bias of Hm 0 in the field was 0.01 m, with a correlation of 0.99 and a scatter index of 8%; the mean absolute deviation of mean wave direction was 7°). LP was also deployed with an unmanned aerial vehicle and we present our experience of such operations. One issue that requires further development is the presence of low-frequency artifacts caused by the dynamic noise of the gyroscope. For now, a correction method is presented to deal with the noise.
Significance Statement
Operational wave buoys are large and therefore expensive and inconvenient to deploy. Many commercially available devices cannot measure short waves and are not tested in ice. Our purpose was to develop an affordable wave buoy that is lightweight, ice resistant, capable of measuring short waves, and also has a longer operating life than existing research buoys. The buoy is easily deployed with a small boat or even an industrial drone, thus reducing operating costs. The buoy is accurate, and captures waves that are too short for operational wave buoys. This is relevant for coastal planning in, e.g., archipelagos and narrow fjords. We measured waves in ice in the Baltic Sea, and are planning to extend these measurements to Antarctica.
Abstract
The Air-Launched Autonomous Micro Observer (ALAMO) is a versatile profiling float that can be launched from an aircraft to make temperature and salinity observations of the upper ocean for over a year with high temporal sampling. Similar in dimensions and weight to an airborne expendable bathythermograph (AXBT), but with the same capability as Argo profiling floats, ALAMOs can be deployed from an A-sized (sonobuoy) launch tube, the stern ramp of a cargo plane, or the door of a small aircraft. Unlike an AXBT, however, the ALAMO float directly measures pressure, can incorporate additional sensors, and is capable of performing hundreds of ocean profiles compared to the single temperature profile provided by an AXBT. Upon deployment, the float parachutes to the ocean, releases the air-deployment package, and immediately begins profiling. Ocean profile data along with position and engineering information are transmitted via the Iridium satellite network, automatically processed, and then distributed by the Global Telecommunications System for use by the operational forecasting community. The ALAMO profiling mission can be modified using the two-way Iridium communications to change the profiling frequency and depth. Example observations are included to demonstrate the ALAMO’s utility.
Abstract
The Air-Launched Autonomous Micro Observer (ALAMO) is a versatile profiling float that can be launched from an aircraft to make temperature and salinity observations of the upper ocean for over a year with high temporal sampling. Similar in dimensions and weight to an airborne expendable bathythermograph (AXBT), but with the same capability as Argo profiling floats, ALAMOs can be deployed from an A-sized (sonobuoy) launch tube, the stern ramp of a cargo plane, or the door of a small aircraft. Unlike an AXBT, however, the ALAMO float directly measures pressure, can incorporate additional sensors, and is capable of performing hundreds of ocean profiles compared to the single temperature profile provided by an AXBT. Upon deployment, the float parachutes to the ocean, releases the air-deployment package, and immediately begins profiling. Ocean profile data along with position and engineering information are transmitted via the Iridium satellite network, automatically processed, and then distributed by the Global Telecommunications System for use by the operational forecasting community. The ALAMO profiling mission can be modified using the two-way Iridium communications to change the profiling frequency and depth. Example observations are included to demonstrate the ALAMO’s utility.