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A Super-Earth and Sub-Neptune Transiting the Late-type M Dwarf LP 791-18

Planets occur most frequently around cool dwarfs, but only a handful of specific examples are known to orbit the latest-type M stars. Using TESS photometry, we report the discovery of two planets transiting the low-mass star called LP 791-18 (identified by TESS as TOI 736). This star has spectral type M6V, effective temperature 2960 K, and radius 0.17 Rꙩ, making it the third-coolest star known to host planets. The two planets straddle the radius gap seen for smaller exoplanets; they include a 1.1Rꚛ planet on a 0.95 day orbit and a 2.3Rꚛ planet on a 5 day orbit. Because the host star is small the decrease in light during these planets' transits is fairly large (0.4% and 1.7%). This has allowed us to detect both planets' transits from ground-based photometry, refining their radii and orbital ephemerides. In the future, radial velocity observations and transmission spectroscopy can both probe these planets' bulk interior and atmospheric compositions, and additional photometric monitoring would be sensitive to even smaller transiting planets.

Ian J. M. Crossfield↗

Bright Opportunities for Atmospheric Characterization of Small Planets: Masses and Radii of K2-3 b, c, and d and GJ3470 b from Radial Velocity Measurements and Spitzer Transits

We report improved masses, radii, and densities for four planets in two bright M-dwarf systems, K2-3 and GJ3470, derived from a combination of new radial velocity and transit observations. Supplementing K2 photometry with follow-up Spitzer transit observations refined the transit ephemerides of K2-3 b, c, and d by over a factor of 10. We analyze ground-based photometry from the Evryscope and Fairborn Observatory to determine the characteristic stellar activity timescales for our Gaussian Process fit, including the stellar rotation period and activity region decay timescale. The stellar rotation signals for both stars are evident in the radial velocity data and is included in our fit using a Gaussian process trained on the photometry. We find the masses of K2-3 b, K2-3 c, and GJ3470 b to be 6.48(+0.99,-0.93), 2.14(+1.08,-1.28), and 12.58(+1.31,-1.28)Mꚛ, respectively. K2-3 d was not significantly detected and has a 3σ upper limit of 2.80 Mꚛ. These two systems are training cases for future TESS systems; due to the low planet densities (ρ < 3.7 g/cu.cm) and bright host stars (K < 9 mag), they are among the best candidates for transmission spectroscopy in order to characterize the atmospheric compositions of small planets.

Molly R. Kosiarek↗

Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC(4)RS

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satellite‐borne Moderate‐resolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 μm) in cloud‐free scenes. Since MODIS' resolution (500‐m pixels, 3‐ or 10‐km product) is too coarse for studying near‐cloud aerosol, we ported the Dark Target algorithm to the high‐resolution (~50‐m pixels) enhanced‐MODIS Airborne Simulator (eMAS), which flew on the high‐altitude ER‐2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5‐km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degraded‐resolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and ground‐based Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into near‐cloud and far‐from‐cloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clear‐cloud transition zone microphysics such as aerosol swelling. However, 3‐D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds.

aerosol retrieval algorithm↗

Using Networked Pandora Observations to Capture Spatiotemporal Changes in Total Column Ozone Associated with Stratosphere-to-Troposphere Transport

Accurately capturing the evolution of episodic stratosphere-to-troposphere transport is critical due to the potential impacts on both climate and air quality. Until now, investigating associated spatiotemporal gradients in total column ozone (TCO) has primarily been the task of observations from polar-orbiting satellites as well as high-resolution models. We explore how a network of five ground-based Pandora spectrometer systems can be utilized in a similar fashion. The passage of a strong mid-latitude cyclone in March 2018 and its associated stratospheric intrusion is used as a case demonstrating the ability of networked Pandora observations to contextualize these regions of transport across space and time. Results show that the high temporal resolution of Pandora observations and the networked approach were able to resolve increases in TCO associated with stratosphere-to-troposphere transport and to capture the spatial context of the chosen episode. The use of networked Pandora observations shows promise for additional transport studies and for supporting future geostationary atmospheric composition satellite missions and modeling efforts.

J. Robinson↗

Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016

In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016. A strength of the comparison is a focus on the spatial distribution of a wider range of aerosol composition and optical properties than has been done previously. The sparse airborne observations are aggregated into approximately 2° grid boxes and into three vertical layers: 3–6 km, the layer from cloud top to 3 km, and the cloud-topped marine boundary layer. Simulated aerosol extensive properties suggest that the flight-day observations are reasonably representative of the regional monthly average, with systematic deviations of 30 % or less. Evaluation against observations indicates that all models have strengths and weaknesses, and there is no single model that is superior to all the others in all metrics evaluated. Whereas all six models typically place the top of the smoke layer within 0–500 m of the airborne lidar observations, the models tend to place the smoke layer bottom 300–1400 m lower than the observations. A spatial pattern emerges, in which most models underestimate the mean of most smoke quantities (black carbon, extinction, carbon monoxide) on the diagonal corridor between 16° S, 6° E, and 10° S, 0° E, in the 3–6 km layer, and overestimate them further south, closer to the coast, where less aerosol is present. Model representations of the above-cloud aerosol optical depth differ more widely. Most models overestimate the organic aerosol mass concentrations relative to those of black carbon, and with less skill, indicating model uncertainties in secondary organic aerosol processes. Regional-mean free-tropospheric model ambient single scattering albedos vary widely, between 0.83 and 0.93 compared with in situ dry measurements centered at 0.86, despite minimal impact of humidification on particulate scattering. The modeled ratios of the particulate extinction to the sum of the black carbon and organic aerosol mass concentrations (a mass extinction efficiency proxy) are typically too low and vary too little spatially, with significant inter-model differences. Most models overestimate the carbonaceous mass within the offshore boundary layer. Overall, the diversity in the model biases suggests that different model processes are responsible. The wide range of model optical properties requires further scrutiny because of their importance for radiative effect estimates.

Yohei Shinozuka↗

Forecasting Global Fire Emissions on Subseasonal to Seasonal (S2S) Time Scales

Fire emissions of gases and aerosols alter atmospheric composition and have substantial impacts on climate, ecosystem function, and human health. Warming climate and human expansion in fire‐prone landscapes exacerbate fire impacts and call for more effective management tools. Here we developed a global fire forecasting system that predicts monthly emissions using past fire data and climate variables for lead times of 1 to 6 months. Using monthly fire emissions from the Global Fire Emissions Database (GFED) as the prediction target, we fit a statistical time series model, the Autoregressive Integrated Moving Average model with eXogenous variables (ARIMAX), in over 1,300 different fire regions. Optimized parameters were then used to forecast future emissions. The forecast system took into account information about region‐specific seasonality, long‐term trends, recent fire observations, and climate drivers representing both large‐scale climate variability and local fire weather. We cross‐validated the forecast skill of the system with different combinations of predictors and forecast lead times. The reference model, which combined endogenous and exogenous predictors with a 1 month forecast lead time, explained 52% of the variability in the global fire emissions anomaly, considerably exceeding the performance of a reference model that assumed persistent emissions during the forecast period. The system also successfully resolved detailed spatial patterns of fire emissions anomalies in regions with significant fire activity. This study bridges the gap between the efforts of near‐real‐time fire forecasts and seasonal fire outlooks and represents a step toward establishing an operational global fire, smoke, and carbon cycle forecasting system.

vapor pressure↗

The Global Fire Atlas of Individual Fire Size, Duration, Speed and Direction

Natural and human-ignited fires affect all major biomes, altering ecosystem structure, biogeochemical cycles and atmospheric composition. Satellite observations provide global data on spatiotemporal patterns of biomass burning and evidence for the rapid changes in global fire activity in response to land management and climate. Satellite imagery also provides detailed information on the daily or sub-daily position of fires that can be used to understand the dynamics of individual fires. The Global Fire Atlas is a new global dataset that tracks the dynamics of individual fires to determine the timing and location of ignitions, fire size and duration, and daily expansion, fire line length, speed, and direction of spread. Here, we present the underlying methodology and Global Fire Atlas results for 2003–2016 derived from daily moderate-resolution (500 m) Collection 6 MCD64A1 burned-area data. The algorithm identified 13.3 million individual fires over the study period, and estimated fire perimeters were in good agreement with independent data for the continental United States. A small number of large fires dominated sparsely populated arid and boreal ecosystems, while burned area in agricultural and other human-dominated landscapes was driven by high ignition densities that resulted in numerous smaller fires. Long-duration fires in boreal regions and natural landscapes in the humid tropics suggest that fire season length exerts a strong control on fire size and total burned area in these areas. In arid ecosystems with low fuel densities, high fire spread rates resulted in large, short-duration fires that quickly consumed available fuels. Importantly, multiday fires contributed the majority of burned area in all biomass burning regions. A first analysis of the largest, longest and fastest fires that occurred around the world revealed coherent regional patterns of extreme fires driven by large-scale climate forcing. Global Fire Atlas data are publicly available through http://www.globalfiredata.org (last access: 9 August 2018) and https://doi.org/10.3334/ORNLDAAC/1642, and individual fire information and summary data products provide new information for benchmarking fire models within ecosystem and Earth system models, understanding vegetation–fire feedbacks, improving global emissions estimates, and characterizing the changing role of fire in the Earth system.

global fire atlas↗

Evaluation of Stratospheric Intrusions and Biomass Burning Plumes on the Vertical Distribution of Tropospheric Ozone Over the Midwestern U.S.

Naturally occurring ozone rich Stratosphere-to-Troposphere Transport (STT) intrusions and biomass burning plumes reaching the surface can contribute to exceedances of the U.S. National Ambient Air Quality Standards (NAAQS) for ground-level ozone (70 ppbv implemented in 2015). In addition, fires can inject significant pollution into the free troposphere where it can be transported long distances. The combined air quality impacts from these sources on ozone has only been analyzed in a few case studies for the Midwest U.S. Here we study ozone impacts in a major Midwestern city, for the first time in St. Louis, Missouri, using a series of ozonesonde profiles taken during the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) field campaign in August-September 2013. All ozonesondes showed some enhancements above the background profile levels (~55 ppbv) throughout each tropospheric column. Two models were used to estimate and quantify ozone origins within the columns. A chemical transport model identified enhancements from STT equivalent to 10to15 ppbv over the background with a 10 to15% contribution overall to the column. Two FLEXPART-WRF simulations, one with smoke in the boundary layer and the other with smoke above, identified enhancements from biomass burning equivalent to 10to 80 ppbv. Overall, the total biomass burning contribution is 15to 30% of the total column. Five ozonesondes showed signatures of mixed biomass burning plumes and STT intrusions. During this study period, biomass burning in the western U.S. contributed 70% to ozone enhancements in the total column compared to 3% from the central U.S and 27% from other areas.

National Ambient Air Quality Standards for ground‐↗

Near Real-time Air Quality Forecasts Using the NASA GEOS Model

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric composition at unprecedented horizontal resolution of 0.25 degrees (~25 km). This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 12) to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Future developments for the next GEOS-CF version will be discussed, including the assimilation system is being expanded to include chemically reactive trace gases, specifically using the capabilities of the GEOS Constituent Data Assimilation System (CoDAS).

CoDAS↗

Extreme Dimensional Stability Thermal Control Test

Two observatories under consideration in the 2020 decadal survey include coronagraphs for characterizing the atmospheric composition of exoplanets. The telescope in those observatories must provide a wavefront that is stable to the picometer level for the coronagraph to provide enough starlight rejection to capture light reflected off of an Earth-like exoplanet. Therefore, picometer dimensional stability and control are required for these missions. Analysis indicates the thermal environment around the primary mirror must be stable to milliKelvin for the primary mirror’s thermally induced wavefront error to be stable to picometers. Marshall Space Flight Center (MSFC) partnered with L3-Harris Corporation to design and build a 1.5mthermal control system capable of milliKelvin stability. MSFC tested this thermal control system in the X-Ray and Cryogenic Facility’s large chamber to characterize how well the system controlled a 1.5m ULE® mirror.

optomechanical↗

A Survey of Earth Observation Data Needed by U.S. Federal Agencies

The Satellite Needs Working Group (SNWG), part of the U.S. Group on Earth Observations (USGEO), surveys U.S. Federal civil agencies every two years regarding the Earth observation data they need in order to accomplish their high-priority agency objectives. The 2020 SNWG survey marked the third assessment cycle (after 2016 and 2018). Information solicited by the survey includes the nature of the need, features and phenomena being observed, data measurement characteristics, satellites and data products the agency uses or plans to use, agency satisfaction with currently available data, and limitations to agency use of satellite data. For analysis purposes, agency needs are assigned to science Focus Areas such as atmospheric composition, carbon/ecosystems, solid Earth, water, etc. Analysis of the survey responses yields insights on the current landscape of Earth observation needs across the U.S. Government agencies. The evolution over multiple survey cycles has been analyzed by the SNWG Assessment team at the Interagency Implementation and Advanced Concepts Team (IMPACT) at Marshall Space Flight Center (MSFC). Key trends emerged in the agency-agnostic analysis that can be helpful to NASA decision-makers evaluating the ongoing, evolving, and emerging needs for NASA missions and instrument datasets expressed by participating agencies in the SNWG.

Katrina Virts↗

A Classification of Ice Crystal Habits Using Combined Lidar and Scanning Polarimeter Observations during the SEAC4RS Campaign

Using collocated NASA Cloud Physics Lidar (CPL) and Research Scanning Polarimeter (RSP) data from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign, a new observational-based method was developed which uses a K-means clustering technique to classify ice crystal habit types into seven categories: column, plates, rosettes, spheroids, and three different type of irregulars. Intercompared with the collocated SPEC, Inc., Cloud Particle Imager (CPI) data, the frequency of the detected ice crystal habits from the proposed method presented in the study agrees within 5% with the CPI-reported values for columns, irregulars, rosettes, and spheroids, with more disagreement for plates. This study suggests that a detailed ice crystal habit retrieval could be applied to combined space-based lidar and polarimeter observations such as CALIPSO and POLDER in addition to future missions such as the Aerosols, Clouds, Convection, and Precipitation (A-CCP).

Natalie Midzak↗

Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-Term Exposure to Surface NO2 over South Korea

Since April 2018, the TROPOspheric Monitoring Instrument (TROPOMI) has provided data on tropospheric NO2 column concentrations (CTROPOMI) with unprecedented spatial resolution. This study aims to assess the capability of TROPOMI to acquire high spatial resolution data regarding surface NO2 mixing ratios. In general, the instrument effectively detected major and moderate sources of NO2 over South Korea with a clear weekday–weekend distinction. We compared the CTROPOMI with surface NO2 mixing ratio measurements from an extensive ground-based network over South Korea operated by the Korean Ministry of Environment (SKME; more than 570 sites), for 2019. Spatiotemporally collocated CTROPOMI and SKME showed a moderate correlation (correlation coefficient, r = 0.67), whereas their annual mean values at each site showed a higher correlation (r = 0.84). The CTROPOMI and SKME were well correlated around the Seoul metropolitan area, where significant amounts of NO2 prevailed throughout the year, whereas they showed lower correlation at rural sites. We converted the tropospheric NO2 from TROPOMI to the surface mixing ratio (STROPOMI) using the EAC4 (ECMWF Atmospheric Composition Reanalysis 4) profile shape, for quantitative comparison with the SKME. The estimated STROPOMI generally underestimated the in-situ value obtained, SKME (slope = 0.64), as reported in previous studies.

TROPOMI↗

Comparison of chemical lateral boundary conditions for air quality predictions over the contiguous United States during pollutant intrusion events

The National Air Quality Forecast Capability (NAQFC) operated in U.S.’s National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matters with aerodynamic diameters less than 2.5μm (PM2.5) over the contiguous 48 U.S. states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions ( CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to the CMAQ’s Carbon Bond 5 (CB05)-Aero6 species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015.The simulated PM2.5 was improved from 0.18 to 0.37 and the mean bias was reduced from -6.74 μg/m3 to -2.96 μg/m3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study, and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the global model CLBCs, such as GEOS CLBCs, are not available.

Community Multi-scale Air Quality (CMAQ) model↗

A Newly Developing Community-Oriented Data System from NASA GES DISC

Data services are essential to facilitate data access and to aid efficiency of conducting research and application activities. With emerging technologies such as cloud computing and AI/ML (Artificial Intelligence/Machine Learning) leading the pace of the data world, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), home to the permanent archive for multidisciplinary Earth Observation (EO) geospatial data to study atmospheric composition, weather and climate variability, and water and energy cycles is no exception.Interfacing directly with users as part of data center work, we understand the challenges for the required time and effort to discover, visualize, and analyze large varieties and quantities of Earth Observation information for research, monitoring, and decision-making, largely due to the existing data and information systems aim to support experienced users, but has been proved difficult for non-earth scientists and new users that are unfamiliar with the variety of formats and structures in which data, metadata, and information are stored, as well as the required methods to use them. To address these challenges, I will update our latest activities with regard to water-and energy-related products and community-oriented and user-friendly services at the GES DISC, including our plans for the emerging technologies.

Jennifer Wei↗

Plasma Activated Water Developments for Lunar and Martian Applications

Plasma activated water (PAW) would be of great use for space applications, due to the myriad of on-demand uses. Some of these applications were directly explored at NASA’s Kennedy Space Center including: Space crop production, Martian systems, and acid-base production. The presence of any nitrogen in the gas stream, including in a simulated Martian atmospheric composition, allows for nitrates to form in water during plasma treatment. These nitrates form nitric acid and drive down the pH while also being in a readily useable form by plants. Inedible biomass ash, which can be created using the same plasma system that treats the water, can be added into the acidic PAW to raise the pH. Measured pH values ranged from 2.7 to 11.5 using this process. Both the nitrates and the nutrients from the inedible biomass are beneficial for the plants, and the pH control allows for use with many different plant species. This methodology is also enabling for space-based hydroponic systems. At KSC, growth studies of Cherry Belle radishes showed comparable dry masses of edible biomass grown with Hoagland’s nutrient solution (a best-case scenario solution that is impractical for launch transportation) and the edible biomass grown with plasma water with the added ash. Both solutions showed substantial improvements over the deionized water that is most similar to what is available in Space systems via the water processor assembly. Additionally, the ability to produce both acidic PAW and basic PAW has benefits for sanitation as well. Preliminary studies showed a 5.8 log reduction of P. Aeruginosa when exposed to PAW mixtures, which shows the ability to remove this common biofilm.

Ryan Patrick Gott↗

Plasma Activated Water Developments for Lunar and Martian Applications

Plasma activated water (PAW) could be of great use for space applications, due to the myriad of on-demand uses. The presence of any nitrogen in the gas stream, including in a simulated Martian atmospheric composition, allows for nitrates to form in water during plasma treatment. These nitrates form nitric acid and drive down the pH while also being in a readily useable form by plants. By varying the reactions and mixing in natural additives, pH values from 2.7 to 11.5 were achieved. The pH control allows for use with many different plant species. This methodology is also enabling for space-based hydroponic systems. Growth studies of Cherry Belle radishes showed comparable dry masses of edible biomass grown with Hoagland’s nutrient solution (a best-case scenario solution that is impractical for launch transportation) and the edible biomass grown with PAW. Both solutions showed substantial improvements over the deionized water that is most similar to what is available in Space systems via the water processor assembly. Additionally, the ability to produce both acidic PAW and basic PAW has benefits for sanitation as well. Preliminary studies showed a 5.8 log reduction of P. Aeruginosa when exposed to PAW mixtures, which shows the ability to remove this common biofilm.

Ryan Gott↗

Diesel Passenger Vehicle Shares Influenced Covid-19 Changes in Urban Nitrogen Dioxide Pollution

Diesel-powered vehicles emit several times more nitrogen oxides than comparable gasoline-powered vehicles, leading to ambient nitrogen dioxide (NO2) pollution and adverse health impacts. The COVID-19 pandemic and ensuing changes in emissions provide a natural experiment to test whether NO2 reductions have been starker in regions of Europe with larger diesel passenger vehicle shares. Here we use a semi-empirical approach that combines in-situ NO2 observations from urban areas and an atmospheric composition model within a machine learning algorithm to estimate business-as-usual NO2 during the first wave of the COVID-19 pandemic in 2020. These estimates account for the moderating influences of meteorology, chemistry, and traffic. Comparing the observed NO2 concentrations against business-as-usual estimates indicates that diesel passenger vehicle shares played a major role in the magnitude of NO2 reductions. European cities with the five largest shares of diesel passenger vehicles experienced NO2 reductions ∼ 2.5 times larger than cities with the five smallest diesel shares. Extending our methods to a cohort of non-European cities reveals that NO2 reductions in these cities were generally smaller than reductions in European cities, which was expected given their small diesel shares. We identify potential factors such as the deterioration of engine controls associated with older diesel vehicles to explain spread in the relationship between cities’ shares of diesel vehicles and changes in NO2 during the pandemic. Our results provide a glimpse of potential NO2 reductions that could accompany future deliberate efforts to phase out or remove passenger vehicles from cities.

Nitrogen Dioxide↗