The most powerful optical emissions from lightning have been described as “superbolts” since the 1970s. Holzworth et al. (2019, https://doi.org/10.1029/2019jd030975) recently applied the superbolt ...label to the most energetic Radio Frequency emissions recorded by the World Wide Lightning Location Network (WWLLN). We compare the WWLLN energies to optical measurements by the photodiode detector on the Fast On‐orbit Recording of Transient Events satellite and the Geostationary Lightning Mappers on NOAA's Geostationary Operational Environmental Satellites to assess whether these energetic WWLLN events coincide with optical superbolts. We find no overlap between optical and WWLLN superbolts. Moreover, extreme WWLLN events occur in a contrasting meteorological context to optical superbolts. Despite similarities in their overall global patterns of occurrence, WWLLN superbolts correspond to a different phenomenon.
Plain Language Summary
Where do the most powerful lightning signals on Earth come from? The answer depends on the wavelength of radiation being measured. There is a long history of using the flashes of optical light produced by lightning to make this assessment. These top cases are known as “superbolts” and typically arise from long‐horizontal discharges that we call “megaflashes,” which are highly effective light sources. A recent study by Holzworth et al. (2019, https://doi.org/10.1029/2019jd030975) used radio waves in the Very Low Frequency (VLF) band recorded by the World Wide Lightning Location Network (WWLLN) to assess lightning intensity. While they use the same superbolt terminology for their high energy VLF events, our comparisons with optical sensors show that they are a distinct phenomenon. These WWLLN superbolts come from small flashes in the thunderstorm core rather than megaflashes in outlying electrified cloud regions.
Key Points
Optical and World Wide Lightning Location Network (WWLLN) Very Low Frequency energies are compared in superbolt cases
Optical superbolts are associated with large megaflashes typically found in stratiform clouds and do not reach the WWLLN 1 MJ threshold
WWLLN superbolts do not produce strong optical flashes, and arise in convective thunderstorm cores with low flash rates
The wildfires of August and September 2020 in the western part of the United States were characterized by an unparalleled duration and wide geographical coverage. A particular consequence of massive ...wildfires includes serious health effects due to short and long-term exposure to poor air quality. Using a variety of data sources including aerosol optical depth (AOD) and ultraviolet aerosol index (UVAI), obtained with the Moderate-Resolution Imaging Spectroradiometer (MODIS), Multi-Angle Implementation of Atmospheric Correction (MAIAC) and Tropospheric Monitoring Instrument (TROPOMI), combined with meteorological information from the European Center for Medium-Range Weather Forecasts (ECMWF) and other supporting data, the impact of wildfires on air quality is examined in the three western US states, California, Oregon, and Washington, and areas to the east. The results show that smoke aerosols not only led to a significant deterioration in air quality in these states but also affected all other states, Canada, and surrounding ocean areas. The wildfires increased the average daily surface concentration of PM2.5 posing significant health risks, especially for vulnerable populations. Large amounts of black carbon (BC) aerosols were emitted into the atmosphere. AOD and UVAI exceeded 1 and 2 over most of the country. In parts of the three western states, those values reached 3.7 and 6.6, respectively. Moreover, a reanalysis based on MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) showed that the maximum values of BC surface mass concentration during the wildfires were about 370 μg/m3. These various indicators provide a better understanding of the extent of environmental and atmospheric degradation associated with these forest fires.
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•Multi-satellite observation of wildfires•Spatial and temporal variations of PM2.5 were analyzed.•AOD and UVAI exceeded 1 and 2 over most of the country.•The hardest hit by wildfires are California, Oregon, and Washington.
The Lightning Cluster Filter Algorithm in the Geostationary Lightning Mapper (GLM) ground system identifies lightning flashes from the stream of event detections. It excels at clustering simple ...flashes but experiences anomalies with complex flashes that last longer than 3 s or contain more than 100 groups, leading to flashes being artificially split. We develop a technique that corrects these anomalies and apply it to the 2018 GLM data to document all lightning across the Americas. We produce statistics describing the characteristics and frequencies of reclustered GLM flashes and thunderstorm area features. The average GLM Americas flash rate in 2018 was 11.7 flashes per second with the greatest flash rate densities occurring over Lake Maracaibo (157 flashes per km2/year). Lloró, Chocó, Colombia had the most thunderstorm activity with 256 thunder days. The longest GLM flash spanned 673 km, the largest flash covered 114,997 km2, and the longest‐lasting flash had a 13.496‐s duration. The first case occurred over Rio Grande do Sul in Brazil, while the other two cases occurred in the central United States. All three extreme flashes are located in the stratiform regions of Mesoscale Convective Systems. The highest flash rate for a thunderstorm area feature was 17.6 flashes per second, while the largest thunderstorm was 216,865 km2 in size. Both storms occurred in South America. These initial results demonstrate the value that the development of a reprocessed GLM science product would offer and how such a product might be created at a reduced computational cost.
Plain Language Summary
NOAA's newest geostationary weather satellites (GOES‐16 and GOES‐17) are the first to feature lightning detectors. These sensors are known as Geostationary Lightning Mappers (GLMs) and use the flash of light illuminating the cloud during a lightning discharge to detect it and determine where it occurred. GLM uses specialized algorithms to identify individual lightning flashes. These algorithms only have 5 s to find all of the flashes that occurred across North and South America and can easily get bogged down by the tremendous amount of GLM data coming down from the satellite. To overcome this, the algorithms quit when flashes become too complex, and this results in single natural lightning flashes being artificially split into multiple degraded flashes. We develop a technique for fixing this splitting problem and apply it to all of the 2018 GLM data. This new data set allows us to examine all types of lightning, not just simple flashes. We use this corrected data to show how often lightning and thunderstorms occur, to document what flashes look like, and to identify extreme examples of lightning across the Americas.
Key Points
The average Americas flash rate was 11.7 flashes per second in 2018 and varied diurnally from 4 per second at 13:45 UTC to 25 per second at 20:30 UTC
Lake Maracaibo was the lightning hot spot in 2018, while Lloró, Chocó, Colombia was the thunderstorm hot spot
Extreme GLM flashes reach 673 km in length, 114,997 km2 in area, 13.496 s in duration
The most intense thunderstorms on Earth were surveyed using the comprehensive meteorological instrumentation on the Tropical Rainfall Measuring Mission (TRMM) satellite. Expansive land‐based ...Mesoscale Convective Systems (MCSs) were consistently identified among the Earth's most intense thunderstorms, with their organization into many convective cells spanning a large areal extent permitting exceptional overall flash rates for these storms. In this study, we identify a new class of extreme thunderstorm. Lightning‐dense thunderstorms are relatively compact convective storms whose concentrated lightning activity hinders our ability to accurately measure their flash rates. The top storms have a flash rate of one flash spanning many seconds, as there is insufficient separation to distinguish one flash from another. While any particularly active convective cell could be capable of producing high lightning densities, we find that thunderstorms with the greatest lightning densities on Earth are found in maritime thunderstorms that have not been appreciated in prior work due to the inaccurate flash rate measurements. These storms that are mostly found throughout the Gulf of Mexico and east of South Africa (among other coastal and oceanic regions) have measured TRMM proxies for convective intensity that rival the top MCS thunderstorms, but their horizontal and vertical dimensions are small by comparison. Thus, the necessary microphysical elements for electrification processes are more highly concentrated, enabling the observed extreme lightning densities.
Plain Language Summary
Using lightning flash rates as a measurement of thunderstorm intensity is complicated by the fact that thunderstorms produce lightning in different ways based on how they are organized. Isolated thunderstorms might consist of a single convective cell with all of the measured lightning coming from that one cell. Meanwhile, a Mesoscale Convective System (MCS) moving across the central United States would be comprised of many convective cells across a line spanning up to thousands of kilometers. All of the flashes produced by all of the cells count toward the total flash rate of the organized MCS. Due to this advantage, studies that assess the highest flash rate thunderstorms on Earth identify MCSs as their top storms. In this study, we ask a different but related question: where are the thunderstorms with the greatest lightning densities on Earth? Answering this question allows us to identify particularly active convection regardless of whether it describes an isolated thunderstorm or one of the cells in a broader MCS. We find that the storms with the greatest lightning densities are not organized MCSs over land, but rather smaller maritime thunderstorms.
Key Points
Certain intense thunderstorms produce extraordinary amounts of lightning concentrated in one area
Lightning‐dense thunderstorms are comparable in intensity to the top flash rate storms over land, but are smaller maritime storms
Measured flash rates are inaccurate for these lightning‐dense thunderstorms, adversely impacting weather forecasting and physical research
It is important to understand connections between society and the natural environment for anticipating hazards and anthropogenic effects on the Earth system. In this study, we conduct a detailed ...exploration of interactions between oceanic thunderstorms and maritime traffic. Shipping traffic produces aerosols that perturb the otherwise “clean” ocean environment. Prior work proposed these aerosol effects as the cause of increased lightning over certain shipping lanes. However, introducing tall grounded objects into a high electric field environment might also facilitate lightning discharges, as we see with upward lightning over land. We consider both possibilities. Our analyses of the thunderstorms responsible for enhanced lightning activity over the shipping lane with the clearest anthropogenic signal indicate that the enhancement results from an increased frequency of lightning‐producing storms. Observed variations in thunderstorm microphysics between the shipping lane and nearby oceans are small compared to natural factors such as the Indian monsoon, and are on the same scale as the local variability in the data. By contrast, matching lightning stroke data with ship transponder events in oceanic regions where public data are available reveals a strong signal from direct ship interactions. Lightning is 15× (66×) more likely to occur at a ship location compared to 2 km (25 km) away. These results highlight the central role of direct ship interactions in explaining lightning enhancements over shipping lanes. We also document the frequency of these direct lightning interactions across various categories of vessels and on individual ships present in the public data.
Plain Language Summary
It was previously shown that there is more lightning over certain shipping lanes compared to the surrounding oceans. These enhancements were attributed to pollution from shipping traffic making it easier for thunderstorms to intensify. However, tall objects in high electric field environments are also known to initiate lightning. An alternate scenario that should contribute to the lightning enhancement is tall well‐grounded ships facilitating lightning production—particularly in storms that are near the tipping point between remaining Electrified Shower Clouds (ESCs) that lightning sensors cannot detect and producing lightning to become detectable thunderstorms. Our analyses indicate that the differences between the thunderstorms over the shipping lane with the most pronounced lightning enhancement and nearby oceanic regions are small compared to natural local weather patterns. Trends are difficult to confirm because they are on the same magnitude as the noise in the satellite data. The enhancement arises because there are simply more thunderstorms over the shipping lane compared to the nearby oceanic regions. Moreover, directly matching lightning strokes with ship positions provides clear evidence of lightning enhancements at the ship location from direct interactions with the vessel.
Key Points
Lightning enhancements over shipping lanes are accompanied by more thunderstorms without pronounced evidence of storm invigoration
Lightning over maritime routes preferentially occurs close to current ship positions compared to other nearby locations surrounding the ship
Direct ship interactions, aerosol effects, and local weather patterns are all important for understanding lightning enhancements
Space‐based optical lightning sensors including the lightning imaging sensor (LIS) and geostationary lightning mapper (GLM) are pixelated imagers that detect lightning as transient increases in cloud ...top illumination. Detection requires optical emissions to escape the cloud top to space with sufficient energy to trigger a pixel on the imaging array. Through scattering and absorption, certain clouds are able to block most light from reaching the instrument, causing a reduction in detection efficiency (DE) and possibly location accuracy (LA). Radiant lightning emissions that illuminate large cloud top areas are used to examine scenarios where clouds block light from reaching orbit. In some cases, these anomalies in the spatial radiance distribution from the lightning pulse lead to “holes” in the optical lightning flash where certain pixels fail to trigger. Such holes are identified algorithmically in the Tropical Rainfall Measuring Mission satellite LIS record and the microphysical properties of the coincident storm region are queried. We find that holes primarily occur in tall (IR Tb < 235 K) convection (87%) and overhanging anvil clouds (10%). The remaining 3% of holes occur in moderate‐to‐weak convection or in clear air breaks between stormclouds. We further demonstrate how an algorithm that assesses the spatial radiance patterns from energetic lightning pulses might be used to construct an optical transmission gridded stoplight product for GLM that could help operators identify clouds with a potentially reduced DE and LA.
Plain Language Summary
Lightning sensors on satellites detect lightning by looking at how they illuminate the surrounding clouds. These instruments register lightning events by comparing high‐speed movies of cloud top brightness with the comparably steady‐state background. However, there are some cases where the cloud is able to block the light produced by lightning from passing through. If too little energy makes it to the top of the cloud, the instrument will not be able to differentiate the lightning illumination from the background—and the lightning will not be detected. This study examines how clouds are illuminated by lightning to identify scenarios where light is blocked from reaching the LIS instrument. LIS “holes” are compared with the meteorological measurements from the other sensors on the Tropical Rainfall Measuring Mission satellite to investigate what types of clouds can inhibit lightning detection. We find that it is not just the tall thunderclouds that are responsible for holes in optical flashes, but also overhanging anvil clouds, and even breaks in the clouds surrounding the thunderstorm. These insights might be used to construct a gridded stoplight product that can alert end users to issues with optical transmission.
Key Points
Certain clouds block optical lightning emissions from reaching orbit, which can lead to missed lightning detections
Poorly transmissive clouds modify the spatial energy distribution of large and bright optical pulses—in some cases creating holes
These anomalies in the spatial radiance data are used to identify poorly transmissive clouds in the lightning imager observations
We previously observed that long‐horizontal lightning flashes exceeding 100 km in length, known as “megaflashes,” occur preferentially in certain thunderstorms. In this study, we develop a cluster ...feature approach for automatically documenting the evolutions of thunderstorm systems from continuous lightning observations provided by the Geostationary Lightning Mapper (GLM) on NOAA's Geostationary Operational Environmental Satellites (GOES). We apply this methodology to GOES‐16 GLM observations from 2018 to mid‐2022 to improve our understanding of megaflash‐producing storms. We find that megaflashes occur in long‐lived (median: 14 hr) storms that grow to exceptional sizes (median: 11,984 km2) while they propagate across long distances (median: 622 km) compared to ordinary storms. The first megaflashes are typically produced within 15 min of the storm reaching its peak intensity and extent. However, most megaflashes occur ≥13 hr after the initial megaflash activity, and are sufficiently close to convection to suggest initiation in the thunderstorm core (where GLM has difficulty detecting faint early light sources from megaflashes). Megaflashes generated outside of convection are rare, accounting for 2.7% of the sample using a 50 km convective distance threshold, but also tend to be larger than normal megaflashes, possibly due to having direct access to electrified stratiform clouds through which megaflashes propagate.
Plain Language Summary
Long‐horizontal “megaflashes” that exceed 100 km across are now being routinely detected across the Americas by NOAA's Geostationary Lightning Mappers (GLMs). Initial studies on where/when megaflashes arise have shown that these exceptional flashes preferentially occur in certain storms. In this study, we develop a methodology to automatically identify megaflash‐producing thunderstorms and track them over time. We apply it to GOES‐16 GLM observations to investigate the types of storms capable of generating lightning at the megaflash scale. We find that megaflashes are produced by storms that grow to large sizes over long periods, and these storms can generate megaflashes over many hours. Most of these megaflashes appear to originate from the convective line, but the small numbers of megaflashes generated deep within the stratiform region tend to be larger. These findings are consistent with our understanding of the life cycle of megaflash‐producing Mesoscale Convective Systems.
Key Points
Megaflashes are produced by Mesoscale Convective Systems (MCSs) that grow large electrified stratiform cloud regions over many hours
We developed a methodology to track thunderstorm systems, including those that produce megaflashes, and applied it to 4 years of data
Megaflash timing statistics reflect the life cycle of MCSs—with megaflash onset accompanying peak storm sizes/flash rates
We previously documented geographic distributions of the optically brightest lightning on Earth—known as “superbolts”—using two space‐based instruments: the photodiode detector (PDD) on the Fast ...On‐orbit Recording of Transient Events (FORTE) satellite and the Geostationary Lightning Mapper (GLM) on NOAA's Geostationary Operational Environmental Satellites. In this study, we further examine the superbolts identified by the PDD and GLM to reconcile the differences between their geographic distributions. We find that both the physical extent of the parent flash and the development speed of its leaders are important for making a superbolt. The oceanic PDD superbolts tend to occur early in flashes that rapidly expand laterally into long horizontal “megaflashes.” The top GLM superbolts occur over land at later times in particularly large megaflashes. These land‐based flashes grow more slowly until they extend over multiple hundreds of kilometers. The FORTE PDD missed these delayed superbolts due to limitations in its triggering. Coincident Tropical Rainfall Measuring Mission measurements show that the warm season megaflash superbolts detected by Lightning Imaging Sensor/GLM and wintertime oceanic superbolts observed by the PDD occur in otherwise similar thunderstorm environments. Both are marked by: low storm heights (<10 km), widespread precipitation near the surface, small infrared brightness temperature gradients, and low flash rates. We suggest that the vertically compact, stratiform nature of these clouds provides favorable conditions for superbolt production.
Plain Language Summary
The brightest optical pulses from lightning seen from space have been termed “superbolts.” Superbolts are incredibly rare and represent flashes of light that are at least 100 times brighter than what we typically see from lightning. Curiously, the locations and times associated with these brightest optical pulses differ based on the instrument and satellite used. Previous assessments with the photodiode detector (PDD) on the Fast On‐orbit Recording of Transient Events (FORTE) satellite identify wintertime lightning around Japan, along the Gulf Stream in the Atlantic Ocean, and in the Mediterranean Sea as frequent sources of superbolts. However, assessments with NOAA's Geostationary Lightning Mapper (GLM) find hotspots in regions with large‐horizontal “megaflashes”—particularly, the La Plata basin in south America and the south‐central United States in North America. In this study, we examine how these differences in optical superbolt detections arise. We find that the differing global distributions can be explained by the FORTE PDD missing superbolts that occur late in the flash due to its trigger count limit—an issue not encountered by GLM.
Key Points
The top Fast On‐orbit Recording of Transient Events (FORTE) photodiode detector, Lightning Imaging Sensor (LIS), and Geostationary Lightning Mapper (GLM) detections capture different portions of the population of the top optical lightning events
These differences arise from nuances in the design and operation of these sensors that introduce detection biases
The FORTE superbolt distribution only represents a subset of all superbolts, which should also include the top LIS/GLM events
Of the >17,943 thousand barrels per calendar day (bbl/d) of oil refining capacity located in the US, the Petroleum Administration for Defense District 3 (PADD-3) region has the largest number of ...refineries and accounts for >53 % (or 9607 tbbl/d) of all US oil refining capacity. Processing facilities in this area are mainly located on the Gulf of Mexico coast in Texas and Louisiana. This study selected a sub-region for analysis within the Mississippi River delta in the state of Louisiana between the cities of New Orleans and Baton Rouge. This region is characterized by intensive industrial activity connected with oil refining and related activities. The TROPOspheric Monitoring Instrument (TROPOMI) detected highly localized NO2 vertical column densities (VCDs) over the two largest US refineries in Baton Rouge (503,000 bbl/d) and Garyville (578,000 bbl/d). TROPOMI NO2 VCD over these stations were 100 μmol/m2 and 80 μmol/m2, respectively. A high correlation coefficient (r = 0.65, p < 0.05) was also found between TROPOMI NO2 and population density. Data from the National Emissions Inventory (NEI) showed high NOx emissions from refineries and other industries including coal-fired power generation, chemical, and aluminum processing plants. The results of the NO2 analysis are of practical interest for a comparative assessment of air pollution, as well as for the exchange of best practices in the field of low-waste fuel combustion technologies.
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•Satellite radiometers can detect NOx emissions from individual refineries.•Refineries and petrochemical plants combine to produce large amounts of NOx emissions.•Refineries have different pollution control devices that lower emissions.•Large capacity refineries can emit lower amounts of pollutants than smaller refineries.•Insufficient ground monitoring stations will necessitate increased use of radiometers.
While multiple lightning detection systems provide geographical locations of lightning events across the globe, robust lightning altitude measurements on a global scale have proven elusive. ...Space‐based platforms have an advantageous viewing geometry for making these measurements, but prior studies with the Fast On‐orbit Recording of Transient Events (FORTE) satellite were limited to a few thousand events. In this study, we apply the same technique for calculating source altitude from the previous efforts to a large catalog of hundreds of thousands of global FORTE in‐cloud lightning events that were coincident with flashes geolocated by its lightning imager between 1997 and 2003. We use this new data set to document global variations in lightning altitude. As in previous studies, we find that FORTE primarily resolves sources from the upper (positive) charge layer at ∼11 km altitude in normal thunderstorms. However, sources are also recorded from other charge layers in the storm and from leaders developing between layers. In particular, we note a pronounced increase in source altitude in the first 20 ms of FORTE flashes from the negative leader developing upward into the upper positive charge layer. Regions known for wintertime and/or stratiform lightning have increased contributions from low‐altitude sources, while tropical regions particularly around Panama and the Maritime Continent have the greatest concentrations of high‐altitude sources.
Plain Language Summary
After many years of observing lightning from multiple sensors, we have a good understanding of how the global frequency of lightning varies from region to region. However, the lightning that we witness on the ground (which is also the primary phenomenon detected by the global lightning detection networks) is only a small portion of the expansive lightning channels. Most of the flash extends through the clouds, hidden from view. The altitudes of lightning flashes in the clouds are particularly important because they reveal changes to convection and play a key role in atmospheric chemistry. In this study, we use a large catalog of in‐cloud lightning events recorded by the Fast On‐orbit Recording of Transient Events satellite to document variations in lightning altitudes across the globe.
Key Points
A new robust data set of very high frequency (VHF) source altitudes from lightning is presented that covers the global Fast On‐orbit Recording of Transient Events (FORTE) satellite domain
Source altitude profiles depend on location, land or ocean terrain, season, and time in the parent flash
Charge structures can be inferred from FORTE VHF measurements, but accuracy is limited by short view times
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