Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “disaggregation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

Landform Degradation and Slope Processes on Io: The Galileo View

The Galileo mission has revealed remarkable evidence of mass movement and landform degradation on Io. We recognize four major slope types observed on a number of intermediate resolution (250 m/pixel) images and several additional textures on very high resolution (10 m/pixel) images. Slopes and scarps on Io often show evidence of erosion, seen in the simplest form as alcove-carving slumps and slides at all scales. Many of the mass movement deposits on Io are probably mostly the consequence of block release and brittle slope failure. Sputtering plays no significant role. Sapping as envisioned by McCauley et al. remains viable. We speculate that alcove-lined canyons seen in one observation and lobed deposits seen along the bases of scarps in several locations may reflect the plastic deformation and 'glacial' flow of interstitial volatiles (e.g., SO2) heated by locally high geothermal energy to mobilize the volatile. The appearance of some slopes and near-slope surface textures seen in very high resolution images is consistent with erosion from sublimation-degradation. However, a suitable volatile (e.g., H2S) that can sublimate fast enough to alter Io's youthful surface has not been identified. Disaggregation from chemical decomposition of solid S2O and other polysulfur oxides may conceivably operate on Io. This mechanism could degrade landforms in a manner that resembles degradation from sublimation, and at a rate that can compete with resurfacing.

Moore, Jeffrey M.↗

Discovery of coesite and shocked quartz associated with the upper Eocene cpx spherule layer

At least two major impact ejecta layers have been discovered in upper Eocene strata. The upper layer is the North American microtektite layer. lt consists tektite fragments, microtektites, and shocked mineral grains (e.g., quartz and feldspar with multiple sets of PDFs, coesite and reidite (a high-pressure polymorph of zircon)). The slightly older layer contains clinopyroxene-bearing (cpx) spherules and microtektites associated with an Ir anomaly. The North American tektite layer may be derived from the Chesapeake Bay impact structure, and the cpx spherule layer may from the Popigai impact crater. A cpx spherule layer associated with a positive Ir anomaly was recently found at ODP Site 709, western Indian Ocean. A large sample (Hole 709C, core 31, section 4, 145-150 cm), originally used for a study of interstitial water by shipboard scientists, was acquired for the purpose of recovering a large number of spherules for various petrographic and geochemical studies. A split of the sample (50.35 g) was disaggregated and wet-sieved. More than 17,000 cpx spherules and several hundred microtektites (larger than 125 microns) were recovered from the sample. Rare white opaque grains were observed in the 125-250 micron size fraction after removal of the carbonate component using dilute HCI. Seven of the white opaque grains were X-rayed using a Gandolfi camera and six were found to be coesite (probably mixed with lechatelierite). Eighty translucent colorless grains from the 63-125 micron size fraction were studied with a petrographic microscope. Four of the grains exhibit one to two sets of planar deformation features (PDFs). The only other possible known occurrence of shocked minerals associated with the cpx spherule layer is at Massignano, Italy, where pancake-shaped clay spherules (thought to be diagenetically altered cpx spherules are associated with a positive Ir anomaly and Ni- rich spinel crystals. Shocked quartz grains with multiple sets of PDFs also occur at this site. Until now, unmelted impact ejecta have not been found associated with the cpx spherules at any of the other 20 sites around the world and this is the first time that coesite has been found associated with the cpx spherule layer. The discovery of coesite and shocked quartz associated with the cpx spherules at Site 709 in Indian Ocean is further evidence for the impact origin of the cpx spherule layer. We hope that future discovery of other unmelted minerals from this sample may provide materials to establish constraints on the provenance of this late Eocene ejecta.

Liu, S.↗

Pristine Presolar Silicon Carbide

In this talk we discuss a simple physical disaggregation technique coupled with an X-ray mapping procedure used to locate 81 micrometer-sized presolar SiC grains from the Murchison carbonaceous chondrite, that preserves them in their pristine state. We then describe pristine SiC surface characteristics and overall morphologies determined by high resolution field emission scanning electron microscopy (FESEM), and compare these features to those of presolar SiC grains that have been prepared using chemical dissolution techniques.

Bernatowicz, T. J.↗

Obliquity, Ice Sheets, and Layered Sediments on Mars: What Spacecraft Observations and Climate Models are Telling Us

The Mars Odyssey Gamma-Ray Spectrometer (GRS) data present a quandary: On the one hand, large deposits of (inferred) water ice are located where thermal models suggest they would form and best be protected, e.g., if deposited during periods of higher obliquity. On the other hand, the volume mixing ratios (approx. 70%) are so high that diffusive deposition of water in regolith pore space (which is the process assumed by these models) cannot be the primary formation mechanism. Furthermore, given that the water is inferred to be so close to the surface (less than a few 10's of cm's), it must be in communication with the atmosphere on time scales that are geologically relatively short (10(exp 3)-10(exp 6) years); therefore the water cannot be archaic. Considering the GRS data, images of mantled, fretted, and disaggregated terrain, and new climate modeling of Mars orbital cycles, we are led to an alternate conclusion about the ice deposits: that they form as subaerial ice sheets. This scenario not only provides a simple explanation for these observations, but may also help explain the formation of globally distributed, sedimentary layered deposits.

Richardson, M. I.↗

Hydrologic Applications of GRACE Terrestrial Water Storage Data

Gravimetry-based terrestrial water storage time series have great potential value for hydrological research and applications, because no other observing system can provide global maps of the integrated quantity of water stored on and below the land surface. However, these data are challenging to use because their spatial and temporal resolutions are low relative to other hydrological observations and because total terrestrial water storage is a measurement unfamiliar to hydrologists. In this presentation we will review techniques for temporal, horizontal, and vertical disaggregation of GRACE terrestrial water storage anomalies, including data assimilation and integration within a land surface model. We will then discuss initial results from three efforts to use the methods for water resources applications. These include drought monitoring across North America, water cycle assessment over the Middle East North African region, and groundwater depletion estimates for northern India.

Rodell, Matthew↗

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Housborg, Rasmus↗

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Underwood, L. W.↗

Drought Indicators Based on Model Assimilated GRACE Terrestrial Water Storage Observations

The Gravity Recovery and Climate Experiment (GRACE) twin satellites observe time variations in Earth's gravity field which yield valuable information about changes in terrestrial water storage (TWS). GRACE is characterized by low spatial (greater than 150,000 square kilometers) and temporal (greater than 10 day) resolution but has the unique ability to sense water stored at all levels (including groundwater) systematically and continuously. The GRACE Data Assimilation System (GRACE-DAS), based on the Catchment Land Surface Model (CLSM) enhances the value of the GRACE water storage data by enabling spatial and temporal downscaling and vertical decomposition into moisture 39 components (i.e. groundwater, soil moisture, snow), which individually are more useful for scientific applications. In this study, GRACE-DAS was applied to North America and GRACE-based drought indicators were developed as part of a larger effort that investigates the possibility of more comprehensive and objective identification of drought conditions by integrating spatially, temporally and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors. Previously, the Drought Monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive datasets of groundwater storage from USGS monitoring wells and soil moisture from the Soil Climate Analysis Network (SCAN) were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically significant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of GRACE assimilated water storage field for improving drought detection.

Houborg, Rasmus↗

Climate Change: A New Metric to Measure Changes in the Frequency of Extreme Temperatures using Record Data

Consensus on global warming is the result of multiple and varying lines of evidence, and one key ramification is the increase in frequency of extreme climate events including record high temperatures. Here we develop a metric- called "record equivalent draws" (RED)-based on record high (low) temperature observations, and show that changes in RED approximate changes in the likelihood of extreme high (low) temperatures. Since we also show that this metric is independent of the specifics of the underlying temperature distributions, RED estimates can be aggregated across different climates to provide a genuinely global assessment of climate change. Using data on monthly average temperatures across the global landmass we find that the frequency of extreme high temperatures increased 10-fold between the first three decades of the last century (1900-1929) and the most recent decade (1999-2008). A more disaggregated analysis shows that the increase in frequency of extreme high temperatures is greater in the tropics than in higher latitudes, a pattern that is not indicated by changes in mean temperature. Our RED estimates also suggest concurrent increases in the frequency of both extreme high and extreme low temperatures during 2002-2008, a period when we observe a plateauing of global mean temperature. Using daily extreme temperature observations, we find that the frequency of extreme high temperatures is greater in the daily minimum temperature time-series compared to the daily maximum temperature time-series. There is no such observable difference in the frequency of extreme low temperatures between the daily minimum and daily maximum.

Munasinghe, L.↗

Evaluating Downscaling Methods for Seasonal Climate Forecasts over East Africa

The U.S. National Multi-Model Ensemble seasonal forecasting system is providing hindcast and real-time data streams to be used in assessing and improving seasonal predictive capacity. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of NMME forecasts specifically for use in impact modeling within hub regions including East Africa, the Hindu Kush-Himalayan (HKH) region and Mesoamerica. One of the participating models in NMME is the NASA Goddard Earth Observing System (GEOS5). This work will present an intercomparison of downscaling methods using the GEOS5 seasonal forecasts of temperature and precipitation over East Africa. The current seasonal forecasting system provides monthly averaged forecast anomalies. These anomalies must be spatially downscaled and temporally disaggregated for use in application modeling (e.g. hydrology, agriculture). There are several available downscaling methodologies that can be implemented to accomplish this goal. Selected methods include both a non-homogenous hidden Markov model and an analogue based approach. A particular emphasis will be placed on quantifying the ability of different methods to capture the intermittency of precipitation within both the short and long rain seasons. Further, the ability to capture spatial covariances will be assessed. Both probabilistic and deterministic skill measures will be evaluated over the hindcast period.

Robertson, Franklin R.↗

Evaluating Downscaling Methods for Seasonal Climate Forecasts over East Africa

The U.S. National Multi-Model Ensemble seasonal forecasting system is providing hindcast and real-time data streams to be used in assessing and improving seasonal predictive capacity. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of NMME forecasts specifically for use in impact modeling within hub regions including East Africa, the Hindu Kush-Himalayan (HKH) region and Mesoamerica. One of the participating models in NMME is the NASA Goddard Earth Observing System (GEOS5). This work will present an intercomparison of downscaling methods using the GEOS5 seasonal forecasts of temperature and precipitation over East Africa. The current seasonal forecasting system provides monthly averaged forecast anomalies. These anomalies must be spatially downscaled and temporally disaggregated for use in application modeling (e.g. hydrology, agriculture). There are several available downscaling methodologies that can be implemented to accomplish this goal. Selected methods include both a non-homogenous hidden Markov model and an analogue based approach. A particular emphasis will be placed on quantifying the ability of different methods to capture the intermittency of precipitation within both the short and long rain seasons. Further, the ability to capture spatial covariances will be assessed. Both probabilistic and deterministic skill measures will be evaluated over the hindcast period

Roberts, J. Brent↗

Nanoscale Compositional Relations in Lunar Rock Patina: Deciphering Sources for Patina Components on an Apollo 17 Station 6 Boulder

Space weathering on the Moon and other airless bodies modifies the surfaces of regolith grains as well as the space-exposed surfaces of larger rocks and boulders. As space weathering witness plates, rocks and boulders are distinguished from regolith grains based on their ability to persist as physically intact substrates over longer time scales before being disaggregated by impact processes. Because lunar surfaces, including exposed rocks, quickly develop an optically thick layer of patina, it is important to understand the compositional relationship between patinas and their underlying rock substrates, particularly to support remote-sensing of rocky lunar terrains. Based on analytical TEM techniques, supported by focused ion beam (FIB) cross-sectioning, we have begun to systematize the multi-layer microstructural complexity of patinas on rock samples with a range of space exposure histories. Our on-going work has particularly focused on lunar rock 76015, both because it has a long (approx. 22 my) exposure history, and because its surface was exposed to patina development approximately 1 m off the regolith surface on a boulder in the Apollo 17 Station 6 boulder field. Potential sources for the 76015 patina therefore include impact-melted and vaporized material derived from the local rock substrate, as well as from the mix of large boulders and regolith in the Station 6 area. While similar, there are differences in the mineralogy and chemistry of the rocks and regolith at Station 6. We were interested to see if these, or other sources, could be distinguished in the average composition, as well as the compositional nanostratigraphy of the 76015 patina. To date we have acquired a total of 9 TEM FIB cross-sections from the 76015 patina, giving us reasonable confidence of being able to arrive at an integrated average for the patina major element composition based on analytical TEM methods.

Christoffersen, R.↗

Observation-Corrected Precipitation Estimates in GEOS-5

Several GEOS-5 applications, including the GEOS-5 seasonal forecasting system and the MERRA-Land data product, rely on global precipitation data that have been corrected with satellite and or gauge-based precipitation observations. This document describes the methodology used to generate the corrected precipitation estimates and their use in GEOS-5 applications. The corrected precipitation estimates are derived by disaggregating publicly available, observationally based, global precipitation products from daily or pentad totals to hourly accumulations using background precipitation estimates from the GEOS-5 atmospheric data assimilation system. Depending on the specific combination of the observational precipitation product and the GEOS-5 background estimates, the observational product may also be downscaled in space. The resulting corrected precipitation data product is at the finer temporal and spatial resolution of the GEOS-5 background and matches the observed precipitation at the coarser scale of the observational product, separately for each day (or pentad) and each grid cell.

Data Assimilation↗

NMME Monthly / Seasonal Forecasts for NASA SERVIR Applications Science

This work details use of the North American Multi-Model Ensemble (NMME) experimental forecasts as drivers for Decision Support Systems (DSSs) in the NASA / USAID initiative, SERVIR (a Spanish acronym meaning "to serve"). SERVIR integrates satellite observations, ground-based data and forecast models to monitor and forecast environmental changes and to improve response to natural disasters. Through the use of DSSs whose "front ends" are physically based models, the SERVIR activity provides a natural testbed to determine the extent to which NMME monthly to seasonal projections enable scientists, educators, project managers and policy implementers in developing countries to better use probabilistic outlooks of seasonal hydrologic anomalies in assessing agricultural / food security impacts, water availability, and risk to societal infrastructure. The multi-model NMME framework provides a "best practices" approach to probabilistic forecasting. The NMME forecasts are generated at resolution more coarse than that required to support DSS models; downscaling in both space and time is necessary. The methodology adopted here applied model output statistics where we use NMME ensemble monthly projections of sea-surface temperature (SST) and precipitation from 30 years of hindcasts with observations of precipitation and temperature for target regions. Since raw model forecasts are well-known to have structural biases, a cross-validated multivariate regression methodology (CCA) is used to link the model projected states as predictors to the predictands of the target region. The target regions include a number of basins in East and South Africa as well as the Ganges / Baramaputra / Meghna basin complex. The MOS approach used address spatial downscaling. Temporal disaggregation of monthly seasonal forecasts is achieved through use of a tercile bootstrapping approach. We interpret the results of these studies, the levels of skill by several metrics, and key uncertainties.

Robertson, Franklin R.↗

A Climate Generator for Agricultural Planning in Southeastern South America

A method is described for the generation of climate scenarios in a form suitable for driving agricultural models. The scenarios are tailored to the region in southeastern South America bounded by 25-40 deg S, 45-65 deg W, denoted here as SESA. SESA has been characterized by increasing summer precipitation, particularly during the late 20th century, which, in the context of favorable market conditions, has enabled increases in agricultural production. Since about year 2000, however, the upward tendency appears to have slowed or possibly stopped, raising questions about future climate inputs to regional agricultural yields. The method is not predictive in the deterministic sense, but rather attempts to characterize uncertainty in near-term future climate, taking into account both forced trends and unforced, natural climate fluctuations. It differs from typical downscaling methods in that GCM information is utilized only at the regional scale, subregional variability being modeled based on the observational record. Output, generated on the monthly time scale, is disaggregated to daily values with a weather generator and used to drive soybean yields in the crop model DSSAT-CSM, for which preliminary results are discussed. The simulations produced permit assessment of the interplay between long-range trends and near-term climate variability in terms of agricultural production.

climate simulation↗

How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null-hypothesis that simulating the presence of a large mass fraction of phyllosilicates in dust aerosols in the size range 2 m, in comparison to a simple model assumption where this is neglected, does not yield a significant effect on the magnitude and geographical distribution of the predicted IFN number. Results from sensitivity experiments are presented as well.

Dust↗

Martian Atmospheric Methane Plumes from Meteor Shower Infall: A Hypothesis

Methane plumes in the martian atmosphere have been detected using Earth-based spectroscopy, the Planetary Fourier Spectrometer on the ESA Mars Express mission, and the NASA Mars Science Laboratory. The methane's origin remains a mystery, with proposed sources including volcanism, exogenous sources like impacts and interplanetary dust, aqueous alteration of olivine in the presence of carbonaceous material, release from ancient deposits of methane clathrates, and/or biological activity. To date, none of these phenomena have been found to reliably correlate with the detection of methane plumes. An additional source exists, however: meteor showers could generate martian methane via UV pyrolysis of carbon-rich infall material. We find a correlation between the dates of Mars/cometary orbit encounters and detections of methane on Mars. We hypothesize that cometary debris falls onto Mars during these interactions, depositing freshly disaggregated meteor shower material in a regional concentration. The material generates methane via UV photolysis, resulting in a localized "plume" of short-lived methane.

Fries, M.↗