Spatial, Temporal, and Electrical Characteristics of Lightning in Reported Lightning-Initiated Wildfire Events

Analysis was performed to determine if a lightning flash could be associated with every reported lightning-initiated wildfire that grew to at least 4 km². In total, 905 lightning-initiated wildfires within CONUS between 2012 and 2015 were analyzed. Fixed and fire radius search methods showed that 81-88% of wildfires had a corresponding lightning flash within a 14 day period prior to the report date. The two methods showed that 52-60% of lightning-initiated wildfire were reported on the same day as the closest lightning flash. The fire radius method indicated the most promising spatial results, where the median distance between the closest lightning and the wildfire start location was 0.83 km, followed by a 75^th percentile of 1.6 km, and a 95^th percentile of 5.86 km. Ninety percent of the closest lightning flashes to wildfires were negative polarity. Maximum flash densities were less than 0.41 flashes km2 for the 24 hour period at the fire start location. The majority of lightning-initiated holdover events were observed in the Western CONUS, with a peak density in north-central Idaho. A twelve day holdover event from New Mexico was also discussed; outlining the opportunities and limitations of using lightning data to characterize wildfires.

How much of the sediment in Gale crater's central mound was fluvially transported?

The origin of the sedimentary mound within Gale crater, the landing site for the Mars Science Laboratory rover Curiosity, remains enigmatic. Here we examine the total potential contribution of fluvial material by conducting a volume-based analysis. On the basis of these results, the mound can be divided into three zones: a lower, intermediate, and upper zone. The top boundary of the lowermost zone is defined by maximal contribution of water-lain sediments, which are ~13 to 20% of the total mound volume. The upper zone is defined by the elevation of the unbreached rim to the north (-2.46 km); sediments above this elevation cannot have been emplaced by flowing water. These volume balance calculations indicate that mechanisms other than flowing water are required to account for the overwhelming majority of the sediments transported into Gale crater. The most likely candidate process is settling from eolian suspension.

The unexpected surface of asteroid (101955) Bennu

NASA'S Origins, Spectral Interpretation, Resource Identification and Security-Regolith Explorer (OSIRIS-REx) spacecraft recently arrived at the near-Earth asteroid (101955) Bennu, a primitive body that represents the objects that may have brought prebiotic molecules and volatiles such as water to Earth1. Bennu is a low-albedo B-type asteroid2 that has been linked to organic-rich hydrated carbonaceous chondrites3. Such meteorites are altered by ejection from their parent body and contaminated by atmospheric entry and terrestrial microbes. Therefore, the primary mission objective is to return a sample of Bennu to Earth that is pristine-that is, not affected by these processes4. The OSIRIS-REx spacecraft carries a sophisticated suite of instruments to characterize Bennu's global properties, support the selection of a sampling site and document that site at a sub-centimetre scale5-11. Here we consider early OSIRIS-REx observations of Bennu to understand how the asteroid's properties compare to pre-encounter expectations and to assess the prospects for sample return. The bulk composition of Bennu appears to be hydrated and volatile-rich, as expected. However, in contrast to pre-encounter modelling of Bennu's thermal inertia12 and radar polarization ratios13-which indicated a generally smooth surface covered by centimetre-scale particles-resolved imaging reveals an unexpected surficial diversity. The albedo, texture, particle size and roughness are beyond the spacecraft design specifications. On the basis of our pre-encounter knowledge, we developed a sampling strategy to target 50-metre-diameter patches of loose regolith with grain sizes smaller than two centimetres4. We observe only a small number of apparently hazard-free regions, of the order of 5 to 20 metres in extent, the sampling of which poses a substantial challenge to mission success.

Intercomparison of MODIS AQUA and VIIRS I-Band Fires and Emissions in an Agricultural Landscape-Implications for Air Pollution Research

Quantifying emissions from crop residue burning is crucial as it is a significant source of air pollution. In this study, we first compared the fire products from two different sensors, the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG) and Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km fire product (MCD14ML) in an agricultural landscape, Punjab, India. We then performed an intercomparison of three different approaches for estimating total particulate matter (TPM) emissions which includes the fire radiative power (FRP) based approach using VIIRS and MODIS data, the Global Fire Emissions Database (GFED) burnt area emissions and a bottom-up emissions approach involving agricultural census data. Results revealed that VIIRS detected fires were higher by a factor of 4.8 compared to MODIS Aqua and Terra sensors. Further, VIIRS detected fires were higher by a factor of 6.5 than Aqua. The mean monthly MODIS Aqua FRP was found to be higher than the VIIRS FRP; however, the sum of FRP from VIIRS was higher than MODIS data due to the large number of fires detected by the VIIRS. Besides, the VIIRS sum of FRP was 2.5 times more than the MODIS sum of FRP. MODIS and VIIRS monthly FRP data were found to be strongly correlated (r2 = 0.98). The bottom-up approach suggested TPM emissions in the range of 88.19-91.19 Gg compared to 42.0-61.71 Gg, 42.59-58.75 Gg and 93.98-111.72 Gg using the GFED, MODIS FRP, and VIIRS FRP based approaches, respectively. Of the different approaches, VIIRS FRP TPM emissions were highest. Since VIIRS data are only available since 2012 compared to MODIS Aqua data which have been available since May 2002, a prediction model combining MODIS and VIIRS FRP was derived to obtain potential TPM emissions from 2003-2016. The results suggested a range of 2.56-63.66 (Gg) TPM emissions per month, with the highest crop residue emissions during November of each year. Our results on TPM emissions for seasonality matched the ground-based data from the literature. As a mitigation option, stringent policy measures are recommended to curtail agricultural residue burning in the study area.

Microphysical and kinematic processes associated with anomalous charge structures in isolated convection

Microphysical and kinematic characteristics of two storm populations, based on their macroscale charge structures, are investigated in an effort to increase our understanding of the processes that lead to anomalous (or inverted charge) structures. Nine normal polarity cases (mid-level negative charge) with dual-Doppler and polarimetric coverage that occurred in northern Alabama, and six anomalous polarity cases (mid-level positive charge) that occurred in northeastern Colorado are included in this study. The results show that even though anomalous polarity storms formed in environments with similar instability, they had significantly larger and stronger updrafts. Moreover, the anomalous polarity storms evidently have more robust mixed-phase microphysics, based on a variety of metrics. Anomalous polarity storms in Colorado have much higher cloud base heights and shallower warm cloud depths in this study, leading us to hypothesize that anomalous polarity storms have lower amounts of dilution and entrainment. We infer positively charged graupel, and therefore high supercooled water contents, in the mid-levels of the anomalous storms based on the relationship between colocations of graupel and inferred positive charge from Lightning Mapping Array data. Using representative updraft speeds and warm cloud depths, the time required for a parcel to traverse from cloud base to the freezing level was estimated for each storm observation. We suggest this metric is the key discriminator between the two storm populations and leads us to hypothesize that it strongly influences the amount of supercooled water and the probability of positive charge in the midlevels, leading to an anomalous charge structure.

Synthesis and Characterization of Ionene-Polyamide Materials as Candidates for New Gas Separation Membranes

A new family of six ionenes containing aromatic amide linkages has been synthesized from ready available starting materials at scales up to ~50 g. These ionene-polyamides are all constitutional isomers and vary only in the regiochemistry of the amide linkages (para, meta) and xylyl linkages (ortho, meta, para) which are present in the polymer backbone. This paper details the synthesis of these ionenes and associated characterizations. Ionene-polyamides exhibit relatively low melting points (~150 oC) allowing them to be readily processed into films and other objects. These ionene-polyamide materials are being developed for further study as polymer membranes for the separations of gases such as CO2, N2, CH4 and H2.

Improved rice residue burning emissions estimates: Accounting for practice-specific emission factors in air pollution assessments of Vietnam

In Southeast Asia and Vietnam, rice residues are routinely burned after the harvest to prepare fields for the next season. Specific to Vietnam, the two prevalent burning practices include: a). piling the residues after hand harvesting; b). burning the residues without piling, after machine harvesting. In this study, we synthesized field and laboratory studies from the literature on rice residue burning emission factors for PM2.5. We found significant differences in the resulting burning-practice specific emission factors, with 16.9 g kg-2(±6.9) for pile burning and 8.8 g kg-2(±3.5) for non-pile burning. We calculated burning-practice specific emissions based on rice area data, region-specific fuel-loading factors, combined emission factors, and estimates of burning from the literature. Our results for year 2015 estimate 180 Gg of PM2.5 result from the pile burning method and 130 Gg result from non-pile burning method, with the most-likely current emission scenario of 150 Gg PM2.5 emissions for Vietnam. For comparison purposes, we calculated emissions using generalized agricultural emission factors employed in global biomass burning studies. These results estimate 80 Gg PM2.5, which is only 44% of the pile burning-based estimates, suggesting underestimation in previous studies. We compare our emissions to an existing all-combustion sources inventory, results show emissions account for 14-18% of Vietnam's total PM2.5 depending on burning practice. Within the highly-urbanized and cloud-covered Hanoi Capital region (HCR), we use rice area from Sentinel-1A to derive spatially-explicit emissions and indirectly estimate residue burning dates. Results from HYSPLIT back-trajectory analysis stratified by season show autumn has most emission trajectories originating in the North, while spring has most originating in the South, suggesting the latter may have bigger impact on air quality. From these results, we highlight locations where emission mitigation efforts could be focused and suggest measures for pollutant mitigation. Our study demonstrates the need to account for emissions variation due to different burning practices.

Use of an End-to-End-Simulator to Analyze CYGNSS

Tropical convection during the onset of two Madden-Julian oscillation (MJO) events, in October and December of 2011, was simulated using the Weather Research and Forecasting (WRF) Model. Observations from the Dynamics of the MJO (DYNAMO) field campaign were assimilated into the WRF Model for an improved simulation of the mesoscale features of tropical convection. The WRF simulations with the assimilation of DYNAMO data produced realistic representations of mesoscale convection related to westerly wind bursts (WWBs) as well as downdraft-induced gust fronts. An end-to-end simulator (E2ES) for the Cyclone Global Navigation Satellite System (CYGNSS) mission was then applied to the WRF dataset, producing simulated CYGNSS near-surface wind speed data. The results indicated that CYGNSS could detect mesoscale wind features such as WWBs and gust fronts even in the presence of simulated heavy precipitation. This study has two primary conclusions as a consequence: 1) satellite simulators could be used to examine a mission's capabilities for accomplishing secondary tasks and 2) CYGNSS likely will provide benefits to future tropical oceanic field campaigns that should be considered during their planning processes.

Land cover, land use changes and air pollution in Asia: a synthesis

A better understanding of land cover/land use changes (LCLUC) and their interactions with the atmospheric environment is essential for the sustainable management of natural resources, environmental protection, air quality, agricultural planning and food security. The 15 papers published in this focus issue showcase a variety of studies relating to drivers and impacts of LCLUC and air pollution in different South/Southeast Asian (S/SEA) countries. This synthesis article, in addition to giving context to the articles in this focus issue, also reviews the broad linkages between population, LCLUC and air pollution. Additionally, we identify knowledge gaps and research priorities that are essential in addressing air pollution issues in the region. We conclude that for effective pollution mitigation in S/SEA countries, quantifying drivers, sources and impacts of pollution need a thorough data analysis through ground-based instrumentation, models and integrated research approaches. We also stress the need for the development of sustainable technologies and strengthening the scientific and resource management communities through capacity building and training activities to address air pollution issues in S/SEA countries.

Improving Photometric Calibration of Meteor Video Camera Systems

We present the results of new calibration tests performed by the NASA Meteoroid Environment Office (MEO) designed to help quantify and minimize systematic uncertainties in meteor photometry from video camera observations. These systematic uncertainties can be categorized by two main sources: an imperfect understanding of the linearity correction for the MEO's Watec 902H2 Ultimate video cameras and uncertainties in meteor magnitudes arising from transformations between the Watec camera's Sony EX-View HAD bandpass and the bandpasses used to determine reference star magnitudes. To address the first point, we have measured the linearity response of the MEO's standard meteor video cameras using two independent laboratory tests on eight cameras. Our empirically determined linearity correction is critical for performing accurate photometry at low camera intensity levels. With regards to the second point, we have calculated synthetic magnitudes in the EX bandpass for reference stars. These synthetic magnitudes enable direct calculations of the meteor's photometric flux within the camera band pass without requiring any assumptions of its spectral energy distribution. Systematic uncertainties in the synthetic magnitudes of individual reference stars are estimated at ∼ 0.20 mag, and are limited by the available spectral information in the reference catalogs. These two improvements allow for zero-points accurate to ∼ 0.05 - 0.10 mag in both filtered and unfiltered camera observations with no evidence for lingering systematics. These improvements are essential to accurately measuring photometric masses of individual meteors and source mass indexes.

WMO World Record Lightning Extremes: Longest Reported Flash Distance and Longest Reported Flash Duration

A World Meteorological Organization weather and climate extremes committee has judged that the world's longest reported distance for a single lightning flash occurred with a horizontal distance of 321 km (199.5 mi) over Oklahoma in 2007, while the world's longest reported duration for a single lightning flash is an event that lasted continuously for 7.74 seconds over southern France in 2012. In addition, the committee has unanimously recommended amendment of the AMS Glossary of Meteorology definition of lightning discharge as a "series of electrical processes taking place within 1 second" by removing the phrase "within one second" and replacing with "continuously." Validation of these new world extremes (a) demonstrates the recent and on-going dramatic augmentations and improvements to regional lightning detection and measurement networks, (b) provides reinforcement regarding the dangers of lightning, and

Parameter Estimation for Gravitational-wave Bursts with the BayesWave Pipeline

We provide a comprehensive multi-aspect study of the performance of a pipeline used by the LIGO-Virgo Collaboration for estimating parameters of gravitational-wave bursts. We add simulated signals with four different morphologies (sine-Gaussians (SGs), Gaussians, white-noise bursts, and binary black hole signals) to simulated noise samples representing noise of the two Advanced LIGO detectors during their first observing run. We recover them with the BayesWave (BW) pipeline to study its accuracy in sky localization, waveform reconstruction, and estimation of model-independent waveform parameters. BW localizes sources with a level of accuracy comparable for all four morphologies, with the median separation of actual and estimated sky locations ranging from 25°.1 to 30°.3. This is a reasonable accuracy in the two-detector case, and is comparable to accuracies of other localization methods studied previously. As BW reconstructs generic transient signals with SG wavelets, it is unsurprising that BW performs best in reconstructing SG and Gaussian waveforms. The BW accuracy in waveform reconstruction increases steeply with the network signal-to-noise ratio (S/Nnet), reaching a 85% and 95% match between the reconstructed and actual waveform below S/Nnet ≈ 20 and S/Nnet ≈ 50, respectively, for all morphologies. The BW accuracy in estimating central moments of waveforms is only limited by statistical errors in the frequency domain, and is also affected by systematic errors in the time domain as BW cannot reconstruct low-amplitude parts of signals that are overwhelmed by noise. The figures of merit we introduce can be used in future characterizations of parameter estimation pipelines.

Gravity Spy: integrating advanced LIGO detector characterization, machine learning, and citizen science

With the first direct detection of gravitational waves, the advanced laser interferometer gravitational-wave observatory (LIGO) has initiated a new field of astronomy by providing an alternative means of sensing the universe. The extreme sensitivity required to make such detections is achieved through exquisite isolation of all sensitive components of LIGO from non-gravitational-wave disturbances. Nonetheless, LIGO is still susceptible to a variety of instrumental and environmental sources of noise that contaminate the data. Of particular concern are noise features known as glitches, which are transient and non-Gaussian in their nature, and occur at a high enough rate so that accidental coincidence between the two LIGO detectors is non-negligible. Glitches come in a wide range of time-frequency-amplitude morphologies, with new morphologies appearing as the detector evolves. Since they can obscure or mimic true gravitational-wave signals, a robust characterization of glitches is paramount in the effort to achieve the gravitational-wave detection rates that are predicted by the design sensitivity of LIGO. This proves a daunting task for members of the LIGO Scientific Collaboration alone due to the sheer amount of data. In this paper we describe an innovative project that combines crowdsourcing with machine learning to aid in the challenging task of categorizing all of the glitches recorded by the LIGO detectors. Through the Zooniverse platform, we engage and recruit volunteers from the public to categorize images of time-frequency representations of glitches into pre-identified morphological classes and to discover new classes that appear as the detectors evolve. In addition, machine learning algorithms are used to categorize images after being trained on human-classified examples of the morphological classes. Leveraging the strengths of both classification methods, we create a combined method with the aim of improving the efficiency and accuracy of each individual classifier. The resulting classification and characterization should help LIGO scientists to identify causes of glitches and subsequently eliminate them from the data or the detector entirely, thereby improving the rate and accuracy of gravitational-wave observations. We demonstrate these methods using a small subset of data from LIGO's first observing run.