Geostationary Operational Environmental Research Articles

One‐Minute Resolution GOES‐R Observations of Lamb and Gravity Waves Triggered by the Hunga Tonga‐Hunga Ha'apai Eruptions on 15 January 2022

AbstractWe use high temporal‐resolution mesoscale imagery from the Geostationary Operational Environmental Satellite‐R (GOES‐R) series to track the Lamb and gravity waves generated by the 15 January 2022 Hunga Tonga‐Hunga Ha'apai eruption. The 1‐min cadence of these limited area (∼1,000×1,000 km2) brightness temperatures ensures an order of magnitude better temporal sampling than full‐disk imagery available at 10‐min or 15‐min cadence. The wave patterns are visualized in brightness temperature image differences, which represent the time derivative of the full waveform with the level of temporal aliasing being determined by the imaging cadence. Consequently, the mesoscale data highlight short‐period variations, while the full‐disk data capture the long‐period wave packet envelope. The full temperature anomaly waveform, however, can be reconstructed reasonably well from the mesoscale waveform derivatives. The reconstructed temperature anomaly waveform essentially traces the surface pressure anomaly waveform. The 1‐min imagery reveals waves with ∼40–80 km wavelengths, which trail the primary Lamb pulse emitted at ∼04:29 UTC. Their estimated propagation speed is ∼315 ± 15 m s−1, resulting in typical periods of 2.1–4.2 min. Weaker Lamb waves were also generated by the last major eruption at ∼08:40–08:45 UTC, which were, however, only identified in the near field but not in the far field. We also noted wind effects such as mean flow advection in the propagation of concentric gravity wave rings and observed gravity waves traveling near their theoretical maximum speed.

High Energy Solar Particle Events and Their Relationship to Associated Flare, CME and GLE Parameters

AbstractLarge solar eruptive events, including solar flares and coronal mass ejections (CMEs), can lead to solar energetic particle (SEP) events. During these events, protons are accelerated up to several GeV and pose numerous space weather risks. These risks include, but are not limited to, radiation hazards to astronauts and disruption to satellites and electronics. The highest energy SEPs are capable of reaching Earth on timescales of minutes and can be detected in ground level enhancements (GLEs). Understanding and analyzing these events is critical to future forecasting models. However, the availability of high energy SEP data sets is limited, especially that which covers multiple solar cycles. The majority of analysis of SEP events considers data at energies <100 MeV. In this work, we use a newly calibrated data set using data from Geostationary Operational Environmental Satellite‐high energy proton and alpha detector between 1984 and 2017. Analysis of the SEP events in this time period over three high energy channels is performed, and SEP properties are compared to flare and CME parameters. In addition, neutron monitor (NM) observations are examined for the relevant GLE events. We find that correlations between SEP peak intensity and the CME speed are much weaker than for lower SEP energies. Correlations with flare intensity are broadly similar or weaker. Strong correlations are seen between >300 MeV data and GLE properties from NM data. The results of our work can be utilized in future forecasting models for both high energy SEP and GLE events.

The Diurnal Dynamics of Gross Primary Productivity Using Observations From the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite‐R Series at an Oak Savanna Ecosystem

AbstractGross primary productivity (GPP) is the largest flux in the global carbon cycle and satellite‐based GPP estimates have long been used to study the trends and interannual variability of GPP. With recent updates to geostationary satellites, we can now explore the diurnal variability of GPP at a comparable spatial resolution to polar‐orbiting satellites and at temporal frequencies comparable to eddy covariance (EC) tower sites. We used observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite‐R series (GOES‐R) to test the ability of subdaily satellite data to capture the shifts in the diurnal course of GPP at an oak savanna EC site in California, USA that is subject to seasonal soil moisture declines. We compared three methods to estimate GPP: (a) a light‐use efficiency model, (b) a linear relationship between the product of near‐infrared reflectance of vegetation and photosynthetically active radiation (LIN‐NIRvP) and EC tower GPP, and (c) a light response curve (LRC‐NIRvP) between NIRvP and EC GPP. The LRC‐NIRvP achieved the lowest mean absolute error for winter (2 µmol CO2 m−2 s−1), spring (2.51 µmol CO2 m−2 s−1), summer (1.43 µmol CO2 m−2 s−1), and fall (1.35 µmol CO2 m−2 s−1). The ecosystem experienced the largest shift in daily peak GPP in relation to the peak of incoming solar radiation toward the morning hours during the dry summers. The LRC‐NIRvP and the light‐use efficiency model were in agreement with these patterns of a shift in peak daily GPP toward the morning hours during summer. Our results can help develop diurnal estimates of GPP from geostationary satellites that are sensitive to fluctuating environmental conditions during the day.

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

AbstractAirborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red‐Green‐Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision‐makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night‐time dust identification difficult even for experts. This study applies machine learning to the problem of night‐time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite‐16 (GOES‐16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area‐Under‐Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no‐dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no‐dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night‐time hours when visual dust detection is limited by the cooling ground surface characteristics.

Evolution of an Atmospheric Kármán Vortex Street From High‐Resolution Satellite Winds: Guadalupe Island Case Study

AbstractVortex streets formed in the stratocumulus‐capped wake of mountainous islands are the atmospheric analogues of the classic Kármán vortex street observed in laboratory flows past bluff bodies. The quantitative analysis of these mesoscale unsteady atmospheric flows has been hampered by the lack of satellite wind retrievals of sufficiently high spatial and temporal resolution. Taking advantage of the cutting‐edge Advanced Baseline Imager, we derived kilometer‐scale cloud‐motion winds at 5‐min frequency for a vortex street in the lee of Guadalupe Island imaged by Geostationary Operational Environmental Satellite‐16. Combined with Moderate Resolution Imaging Spectroradiometer data, the geostationary imagery also provided accurate stereo cloud‐top heights. The time series of geostationary winds, supplemented with snapshots of ocean surface winds from the Advanced Scatterometer, allowed us to capture the wake oscillations and measure vortex shedding dynamics. The retrievals revealed a markedly asymmetric vortex decay, with cyclonic eddies having larger peak vorticities than anticyclonic eddies at the same downstream location. Drawing on the vast knowledge accumulated about laboratory bluff body flows, we argue that the asymmetric island wake arises from the combined effects of Earth's rotation and Guadalupe's nonaxisymmetric shape resembling an inclined flat plate at low angle of attack. However, numerical simulations will need to establish whether or not the selective destabilization of the shallow atmospheric anticyclonic eddies is caused by the same mechanisms that destabilize the deep columnar anticyclones of laboratory flows, such as three‐dimensional vertical perturbations due to centrifugal or elliptical instabilities.

Meteorological Imagery for the Geostationary Lightning Mapper

AbstractThe Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite‐R series of weather satellites provides point geolocations of lightning flashes that are further comprised of a hierarchy of geolocated groups and events. This study describes an open‐source method for reconstruction of imagery from those point detections that retains the quantitative physical measurements made by GLM, restores the spatial footprint of the events, and connects that spatial footprint to the groups and flashes. Meteorological signals are demonstrated to be more apparent in the gridded imagery than in the point detections, leading to their adoption by the United States National Weather Service as the first GLM product available in their real‐time displays. Analysis of a mesoscale convective system over Argentina confirms that there is a class of propagating lightning observed by GLM (distinct from that in storm cores) that can be visualized and quantified using our imagery‐based approach.

The Hamburg meteorite fall: Fireball trajectory, orbit, and dynamics

AbstractThe Hamburg (H4) meteorite fell on 17 January 2018 at 01:08 UT approximately 10 km north of Ann Arbor, Michigan. More than two dozen fragments totaling under 1 kg were recovered, primarily from frozen lake surfaces. The fireball initial velocity was 15.83 ± 0.05 km s−1, based on four independent records showing the fireball above 50 km altitude. The radiant had a zenith angle of 66.14 ± 0.29° and an azimuth of 121.56 ± 1.2°. The resulting low inclination (<1°) Apollo‐type orbit has a large aphelion distance and Tisserand value relative to Jupiter (Tj) of ~3. Two major flares dominate the energy deposition profile, centered at 24.1 and 21.7 km altitude, respectively, under dynamic pressures of 5–7 MPa. The Geostationary Lightning Mapper on the Geostationary Operational Environmental Satellite‐16 also detected the two main flares and their relative timing and peak flux agree with the video‐derived brightness profile. Our preferred total energy for the Hamburg fireball is 2–7 T TNT (8.4–28 × 109 J), which corresponds to a likely initial mass in the range of 60–225 kg or diameter between 0.3 and 0.5 m. Based on the model of Granvik et al. (2018), the meteorite originated in an escape route from the mid to outer asteroid belt. Hamburg is the 14th known H chondrite with an instrumentally derived preatmospheric orbit, half of which have small (<5°) inclinations making connection with (6) Hebe problematic. A definitive parent body consistent with all 14 known H chondrite orbits remains elusive.

Continent‐Wide R1/R2 Current System and Ohmic Losses by Broad Dipolarization‐Injection Fronts

AbstractWe employ Magnetospheric Multiscale, Geostationary Operational Environmental and Los Alamos National Laboratory satellites, as well as the ground magnetometer networks over Greenland and North America to study a substorm on 9 August 2016 between 9 and 10 UT. We found that during the substorm two earthward flows, whose dipolarization‐injection fronts exceeded 6.5 and 4 Earth's radii (RE) in YGSM, impinged and rebounded from Earth's dipolar field lines at L=6–7 downtail, where L is the McIlwain number. The impingements and rebounds ended with a substorm current system of downward R1 and upward R2 currents which grew to azimuthally cover the whole North American continent. At the fronts, regions of enhanced negative j·E′ were formed and peaked toward the end of the impingements. These regions appeared to be conjugate with eastward moving aurora (along the growth phase arc and together with eastward drifting energetic electrons at geosynchronous equatorial orbit), which manifests ionospheric Ohmic losses.

Persistent Quasi-periodic Pulsations during a Large X-class Solar Flare

Abstract Solar flares often display pulsating and oscillatory signatures in the emission, known as quasi-periodic pulsations (QPP). QPP are typically identified during the impulsive phase of flares, yet in some cases, their presence is detected late into the decay phase. Here, we report extensive fine structure QPP that are detected throughout the large X8.2 flare from 2017 September 10. Following the analysis of the thermal pulsations observed in the Geostationary Operational Environmental Satellite/X-ray sensor and the 131 Å channel of Solar Dynamics Observatory/Atmospheric Imaging Assembly, we find a pulsation period of ∼65 s during the impulsive phase followed by lower amplitude QPP with a period of ∼150 s in the decay phase, up to three hours after the peak of the flare. We find that during the time of the impulsive QPP, the soft X-ray source observed with the Reuven Ramaty High Energy Solar Spectroscopic Imager rapidly rises at a velocity of approximately 17 km s−1 following the plasmoid/coronal mass ejection eruption. We interpret these QPP in terms of a manifestation of the reconnection dynamics in the eruptive event. During the long-duration decay phase lasting several hours, extended downward contractions of collapsing loops/plasmoids that reach the top of the flare arcade are observed in EUV. We note that the existence of persistent QPP into the decay phase of this flare are most likely related to these features. The QPP during this phase are discussed in terms of magnetohydrodynamic wave modes triggered in the post-flaring loops.

Benchmark Test of Differential Emission Measure Codes and Multi-thermal Energies in Solar Active Regions

We compare the ability of 11 differential emission measure (DEM) forward-fitting and inversion methods to constrain the properties of active regions and solar flares by simulating synthetic data using the instrumental response functions of the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) and EUV Variability Experiment (SDO/EVE), the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI), and the Geostationary Operational Environmental Satellite/X-ray Sensor (GOES/XRS). The codes include the single-Gaussian DEM, a bi-Gaussian DEM, a fixed-Gaussian DEM, a linear spline DEM, the spatial-synthesis DEM, the Monte-Carlo Markov Chain DEM, the regularized DEM inversion, the Hinode/X-Ray Telescope (XRT) method, a polynomial spline DEM, an EVE+GOES, and an EVE+RHESSI method. Averaging the results from all 11 DEM methods, we find the following accuracies in the inversion of physical parameters: the EM-weighted temperature $T_{\mathrm{w}}^{\mathrm{fit}}/T_{\mathrm{w}}^{\mathrm{sim}}=0.9\pm0.1$ , the peak emission measure $\mathit{EM}_{\mathrm{p}}^{\mathrm{fit}}/\mathit{EM}_{\mathrm{p}}^{\mathrm{sim}}=0.6\pm0.2$ , the total emission measure $\mathit{EM}_{\mathrm{t}}^{\mathrm{fit}}/\mathit{EM}_{\mathrm{t}}^{\mathrm{sim}}=0.8\pm0.3$ , and the multi-thermal energies $E_{\mathrm{th}}^{\mathrm{fit}}/\mathit{EM}_{\mathrm{th}}^{\mathrm {approx}}=1.2\pm0.4$ . We find that the AIA spatial-synthesis, the EVE+GOES, and the EVE+RHESSI method yield the most accurate results.

Using SURFRAD to Verify the NOAA Single-Channel Land Surface Temperature Algorithm

AbstractBecause of spectral shifts from instrument to instrument in the operational NOAA satellite imager longwave infrared channels, the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) has developed a single-channel land surface temperature (LST) algorithm based on the observed 11-μm radiances, numerical weather prediction data, and radiative transfer modeling that allows for consistent results from the Geostationary Operational Environmental Satellite-I/L (GOES-I/L), GOES-M–P, and Advanced Very High Resolution Radiometer (AVHRR)/1 through 3 sensor versions. This approach is implemented in the real-time NESDIS processing systems [GOES Surface and Insolation Products (GSIP) and Clouds from AVHRR Extended (CLAVR-x)], and in the Pathfinder Atmospheres–Extended (PATMOS-x) climate dataset. An analysis of the PATMOS-x LST against that derived from the upwelling broadband longwave flux at each Surface Radiation Network (SURFRAD) site showed that biases in PATMOS-x were approximately 1 K or less. The standard deviations of the PATMOS-x minus SURFRAD LST biases are generally 2.5 K or less at all sites for all sensors. Using the PATMOS-x minus SURFRAD LST distributions to validate the PATMOS-x cloud detection, the PATMOS-x cloud probability of correct detection values were shown to meet the GOES-R specifications for all sites.

GOES up

The U.S. National Oceanic and Atmospheric Administration (NOAA) is preparing to launch the third in series of five advanced weather satellites in order to “ensure the continuity” of satellite weather data. NOAA's Geostationary Operational Environmental Satellite‐K (GOES‐K) is scheduled for launch on April 24 from NASA's Cape Canaveral Air Station. GOES‐K will be renamed GOES 10 once it is securely in orbit.

Overview of an aircraft expedition into the Brazilian cerrado for the observation of atmospheric trace gases

Tropospheric trace gases were measured from an aircraft platform. The flights were organized to sample air masses from the geographic area of central Brazil, where the vegetation, a savanna‐type environment with the local name of “cerrado”, is subject to burning every year, especially through August, September, and October. These measurements were made as a Brazilian local contribution to the international field campaign organized by NASA, the Transport and Atmospheric Chemistry Near the Equator‐Atlantic (TRACE A) mission, and the Southern African Fire Atmospheric Research Initiative (SAFARI). The major NASA TRACE A mission used the NASA DC 8 aircraft, with most flights over the South Atlantic Ocean region. In Brazil, missions using small aircraft measured ozone and carbon dioxide continuously, and carbon monoxide, nitrous oxide, and methane using grab sampling. In addition, ground‐based measurements were made continuously over most of the dry months of 1992, and ozonesondes were launched at three different sites. Geostationary Operational Environment Satellite‐East (GOES E) images and a special network of radio soundings provided meteorological information, and advanced very high resolution radiometer (AVHRR) images indicated the distribution of fire pixels in the region of interest. Most of the biomass burning in 1992 occurred in the state of Tocantins, with about 22% of all the burning in Brazil. The state of Mato Grosso was second, with 19% of all burning. The Brazilian aircraft was used mostly in these two states, near the cities of Porto Nacional and Cuiabá, for in situ sampling; 31 vertical profiles were made in air masses considered to be well mixed, that is, not in fresh plumes. Although the major interest was the dry season, sampling was also made during the previous wet season period in April 1992 for comparison; 10 vertical profiles were obtained using the same aircraft and measurement techniques. There is a clear difference between these two opposite seasonal periods, most evident in the O3 and CO data. Both Cuiabá and Porto Nacional show some 30–60 parts per billion by volume (ppbv) larger methane concentrations, for example, during the dry season, in comparison to the wet season, the difference at Cuiabá being larger. The methane data for the wet season show no significant differences between Cuiabá and Porto Nacional mixing ratios, which seems to exclude the existence of significant sources or sinks at these sites during this wet season. The ozone mixing ratios vary around 15 ± 5 ppbv in the wet season, and from a minimum of 35 to a maximum of 70 ± 10 ppbv, depending on height, in the dry season. The largest variability is seen in the carbon monoxide mixing ratios which vary from 90–100 ppbv in the wet season to maxima of 300 at 3.3 km and 600 ppbv at 1.2 km height in the dry season.

Commercial LANDSAT?

Private industry should assume responsibility either for the United States' land satellite (LANDSAT) system or for both the land and the weather satellite systems, recommends the Land Remote Sensing Satellite Advisory Committee. The committee (Eos, June 29, 1982, p. 553), composed of representatives from academia, industry, and government, has a working group that is evaluating the potential for commercialization of remote sensing satellites.The recommendations call for industry ownership or operation of either or both of the remote sensing systems, but only up to and including the holding of raw, unprocessed data. The National Aeronautics and Space Administration (NASA) currently operates LANDSAT but will be relinquishing its responsibility to the National Oceanic and Atmospheric Administration (NOAA) on January 31. NOAA already operates the U.S. civilian weather satellite service, which includes the NOAA‐5, NOAA‐6, and the Geostationary Operational Environmental (GOES) satellites (Eos, June 2, 1981, p. 522).