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At least 955 records · Page 53

Temperature and Chemical Species Distributions in the Middle Atmosphere Observed during Titan's Late Northern Spring to Early Summer

We present a study of the seasonal evolution of Titan’s thermal field and distributions of haze, C2H2, C2H4, C2H6, CH3C2H, C3H8, C4H2, C6H6, HCN, and HC3N from March 2015 (Ls = 66°) to September 2017 (Ls = 93°) (i.e., from the last third of northern spring to early summer). We analyzed thermal emission of Titan’s atmosphere acquired by the Cassini Composite Infrared Spectrometer with limb and nadir geometry to retrieve the stratospheric and mesospheric temperature and mixing ratios pole-to-pole meridional cross sections from 5 mbar to 50 μbar (120–650 km). The southern stratopause varied in a complex way and showed a global temperature increase from 2015 to 2017 at high-southern latitudes. Stratospheric southern polar temperatures, which were observed to be as low as 120 K in early 2015 due to the polar night, showed a 30 K increase (at 0.5 mbar) from March 2015 to May 2017 due to adiabatic heating in the subsiding branch of the global overturning circulation. All photochemical compounds were enriched at the south pole by this subsidence. Polar cross sections of these enhanced species, which are good tracers of the global dynamics, highlighted changes in the structure of the southern polar vortex. These high enhancements combined with the unusually low temperatures (<120 K) of the deep stratosphere resulted in condensation at the south pole between 0.1 and 0.03 mbar (240–280 km) of HCN, HC3N, C6H6 and possibly C4H2 in March 2015 (Ls = 66°). These molecules were observed to condense deeper with increasing distance from the south pole. At high-northern latitudes, stratospheric enrichments remaining from the winter were observed below 300 km between 2015 and May 2017 (Ls = 90°) for all chemical compounds and up to September 2017 (Ls = 93°) for C2H2, C2H4, CH3C2H, C3H8, and C4H2. In September 2017, these local enhancements were less pronounced than earlier for C2H2, C4H2, CH3C2H, HC3N, and HCN, and were no longer observed for C2H6 and C6 H6, which suggests a change in the northern polar dynamics near the summer solstice. These enhancements observed during the entire spring may be due to confinement of this enriched air by a small remaining winter circulation cell that persisted in the low stratosphere up to the northern summer solstice, according to predictions of the Institut Pierre Simon Laplace Titan Global Climate Model (IPSL Titan GCM). In the mesosphere we derived a depleted layer in C2H2, HCN, and C2H6 from the north pole to mid-southern latitudes, while C4H2, C3H4, C2H4, and HC3N seem to have been enriched in the same region. In the deep stratosphere, all molecules except C2H4 were depleted due to their condensation sink located deeper than 5 mbar outside the southern polar vortex. HCN, C4H2, and CH3C2H volume mixing ratio cross section contours showed steep slopes near the mid-latitudes or close to the equator, which can be explained by upwelling air in this region. Upwelling is also supported by the cross section of the C2H4 (the only molecule not condensing among those studied here) volume mixing ratio observed in the northern hemisphere. We derived the zonal wind velocity up to mesospheric levels from the retrieved thermal field. We show that zonal winds were faster and more confined around the south pole in 2015 (Ls = 67−72°) than later. In 2016, the polar zonal wind speed decreased while the fastest winds had migrated toward low-southern latitudes.

S Vinatier↗

Assessment of NO2 Observations During DISCOVER-AQ and KORUS-AQ Field Campaigns

NASA’s Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated data sets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a actor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori pro-files) but mostly to OMI’s large footprint (>312 km2).

Nitrogen dioxide↗

GW190412: Observation of a binary-black-hole coalescence with asymmetric masses

We report the observation of gravitational waves from a binary-black-hole coalescence during the first two weeks of LIGO’s and Virgo’s third observing run. The signal was recorded on April 12, 2019 at05∶30∶44 UTC with a network signal-to-noise ratio of 19. The binary is different from observations during the first two observing runs most notably due to its asymmetric masses: a∼30M⊙black hole merged with a ∼8M⊙black hole companion. The more massive black hole rotated with a dimensionless spin magnitude between 0.22 and 0.60 (90% probability). Asymmetric systems are predicted to emit gravitational waves with stronger contributions from higher multipoles, and indeed we find strong evidence for gravitational radiation beyond the leading quadrupolar order in the observed signal. A suite of tests performed onGW190412 indicates consistency with Einstein’s general theory of relativity. While the mass ratio of this system differs from all previous detections, we show that it is consistent with the population model of stellar binary black holes inferred from the first two observing runs.

R. Abbott↗

Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations

Since early 2000, NASA's Multi-angle Imaging SpectroRadiometer (MISR) instrument has been performing remote sensing retrievals of aerosol optical properties from the polar-orbiting Terra spacecraft. A noteworthy aspect of MISR observations over the ocean is that, for much of the Earth, some of the multi-angle views have contributions from solar reflection by the ocean surface (glint, or glitter), while others do not. Aerosol retrieval algorithms often discard these glint-influenced observations because they can overwhelm the signal and are difficult to predict without knowledge of the (wind-speed-driven) ocean surface roughness. However, theoretical studies have shown that multi-angle observations of a location at geometries with and without reflected sun glint can be a rich source of information, sufficient to support simultaneous retrieval of both the aerosol state and the wind speed at the ocean surface. We are in the early stages of creating such an algorithm. In this paper, we describe our assessment of the appropriate level of parameterization for simultaneous aerosol and ocean surface property retrievals using sun glint. For this purpose, we use generalized nonlinear retrieval analysis (GENRA), an information content assessment (ICA) technique employing Bayesian inference, and simulations from the Ahmad–Fraser iterative radiative transfer code. We find that four parameters are suitable: aerosol optical depth (τ), particle size distribution (expressed as the fine mode fraction f of small particles in a bimodal size distribution), surface wind speed (w), and relative humidity (r, to define the aerosol water content and complex refractive index). None of these parameters define ocean optical properties, as we found that the aerosol state could be retrieved with the nine MISR near-infrared views alone, where the ocean body is strongly absorbing in the open ocean. We also found that retrieval capability varies with observation geometry and that as τ increases so does the ability to determine aerosol intensive optical properties (r and f, while it decreases for w). Increases in w decrease the ability to determine the true value of that parameter but have minimal impact on retrieval of aerosol properties. We explored the benefit of excluding the two most extreme MISR view angles for which radiative transfer with the plane-parallel approximation is less certain, but we found no advantage in doing so. Finally, the impact of treating wind speed as a scalar parameter, rather than as a two-parameter directional wind, was tested. While the simpler scalar model does contribute to overall aerosol uncertainty, it is not sufficiently large to justify the addition of another dimension to parameter space. An algorithm designed upon these principles is in development. It will be used to perform an atmospheric correction with MISR for coincident ocean color (OC) observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on the NASA Terra spacecraft. Unlike MISR, MODIS is a single-view-angle instrument, but it has a more complete set of spectral channels ideal for determination of optical ocean properties. The atmospheric correction of MODIS OC data can therefore benefit from MISR aerosol retrievals. Furthermore, higher-spatial-resolution data from coincident MISR observations may also improve glint screening.

Kirk Knobelspiesse↗

Physical Properties of the Solar Atmosphere Derived from Comparison of Spectro-Polarimetric SDO/HMI Observables with 3D Radiative MHD Simulations

In this study, we compare the SDO/HMI line-of-sight observables (magnetic field, velocity, continuum intensity, and line depth) with the related physical properties for several dynamo simulation runs performed using the "StellarBox" 3D Radiative MHD code. The modeling of the Fe I 6173 A Stokes profiles is performed using the SPINOR radiative transfer code in the LTE approximation. The reproduced SDO/HMI line-of-sight pipeline is applied to the modeled spectra, and the observables are synthesized with high (numerical) and SDO/HMI (instrumental) resolutions. Correlations between the observables and the physical properties at various heights in the atmosphere are studied for a set of view angles (0, 30, 45, 60, 70, and 80 degrees away from the solar disk center). It is found that the SDO/HMI magnetic field and velocity measurements are unambiguously correlated with physical parameters at certain heights of the solar atmosphere. These heights increase from about 100 km above the photosphere for the disk center case to 300-600 km above the photosphere for the 80-degree case. The heights are found to be slightly lower in regions where stronger magnetic fields are found. The comparison of the photospheric magnetic flux and integrated continuum intensity derived from the SDO/HMI observables and high-resolution observations and spectra is discussed. The results of our study improve physics-based interpretations of the SDO/HMI observables and provide a better understanding of the physical properties of the solar atmosphere.

SMD↗

Optimizing Science Return from Plato's Observations of the Kepler Field

The Plato mission could substantially enhance its scientific yield by focusing a significant fraction of its observations with all 24 cameras viewing the Kepler Field of View (FOV). Kepler, while exceptionally productive, did not accomplish its goal of providing a direct measurement of the abundance of Earth-analog planet around sunlike stars. On this issue, Plato observations centered on the Kepler FOV would enable planet searches using the combined data sets to achieve more precise estimates of planetary occurrence rates than obtainable using data from either mission alone. The ecliptic latitude of the Kepler FOV is too low for Plato to observe with 24 cameras year-round, so current plan’s for Plato’s Northern Stare places the Kepler FOV in the periphery, reducing the number of photons collected from Kepler targets by factors of 2 or 4. We propose instead four ~6 - 8 month Plato stares with 24 cameras observing the Kepler FOV during the Plato primary mission, instead of a single 2 year stare with the Kepler FOV located to the periphery. This change would greatly increase the amount of 'Plato glass’ dedicated to the continued study of the Kepler FOV, while still enabling Plato to observe other parts of the sky during the majority of its prime mission. In addition to discovering planets below Kepler's detection threshold, this change would yield transit follow-up of thousands of known exoplanets with an effective throughput of a 0.6 m space telescope. It would also extend the observing baseline of the Kepler FOV to timescales of decades, providing key data for stellar cycles, the analysis of transit timing variations, and other decade-timescale variations. Such a campaign enhances the likelihood of the detection of true Earth-analog transiting planet candidates around sunlike stars, provide the best statistical study of exoplanet systems with transit timing variations and duration variations, and open up the study of stellar variability to new time-domains with precision on large numbers of faint targets that only 24 Plato cameras can provide.

Jack Lissauer↗

DDOTI Observations of Gravitational-Wave Sources Discovered in O3

We present optical follow-up observations with the Deca-Degree Optical Transient Imager (DDOTI) telescope of gravitational-wave (GW) events detected during the Advanced LIGO and Advanced Virgo O3 observing run. DDOTI is capable of responding to an alert in a few minutes, has an instantaneous field of about 69 deg2, and obtains 10σ upper limits of wlim = 18.5–20.5 AB mag in 1000 s of exposure, depending on the conditions. We observed 54 per cent (26 out of 48) of the unretracted GW alerts and did not find any electromagnetic counterparts. We compare our upper limits to various possible counterparts: the kilonova AT 2017gfo, models of radioactive- and magnetar-powered kilonovae, short gamma-ray burst afterglows, and active galactic nucleus (AGN) flares. Although the large positional uncertainties of GW sources do not allow us to place strong constraints during O3, DDOTI observations of well-localized GW events in O4 and beyond could meaningfully constrain models of compact binary mergers. We show that DDOTI is able to detect kilonovae similar to AT 2017gfo up to about 200 Mpc and magnetar-powered kilonovae up to 1 Gpc. We calculate that nearby (≲200 Mpc) afterglows have a high chance (≈70 per cent) to be detected by rapid (≲3 h) DDOTI observations if observed on-axis, whereas off-axis afterglows are unlikely to be seen. Finally, we suggest that long-term monitoring of massive BBH events with DDOTI could confirm or rule out late AGN flares associated with these events.

gravitational waves↗

Convective precipitation retrievals from space-borne dual frequency (Ka- and W-band) radar observations

The 2017 Decadal Survey highlighted Earth System Science themes, science and application questions that led to the inclusion aerosols (A), clouds, convection, and precipitation (CCP) in the list of designated observables (DOs) to be pursued within the decade following the survey. Multiple observing system architectures were considered during the NASA A-CCP study, and dual frequency Ka-W band radars have been identified as components of the most likely architectures due to their ability to significantly contribute to the achievement of the science objectives and their synergy with other essential instruments. We present an algorithm to estimate convective precipitation from dual frequency, Ka- and W-band, observations applicable to the observing system architectures considered in the A-CCP study. The algorithm is based on the radar profiling algorithm used within the operational NASA GPM combined algorithm but features an additional module that makes the retrieval problem well-posed in cases of severe attenuation and potential loss of signal below the freezing level. The additional module is developed from GPM combined retrievals and consists of a procedure that generates an ensemble of potential retrievals consistent with the portions of the Ka-band and W-band observation profiles above the noise level. The ensemble solution is refined based on estimates of Path Integrated Attenuation (PIA) from the Surface Reference Technique (SRT) and radiometric observations.

Mircea Grecu↗

NASA GLOBE CLOUD GAZE: Creating Data Quality Flags for Citizen Science Cloud Observations Matched to NASA Satellite Data

The GLOBE Program, NASA’s largest and longest lasting citizen science program about the Earth, has been collecting cloud observations matched to multiple satellite data daily. The program’s cloud protocol is historically the most popular protocol as your eyes are the only instruments you need to collect observations of the sky. This dataset includes over 3,300,000 cloud observations with variables like total cloud cover, cloud type and opacity that are collocated to the nearest overpass times of geostationary satellites (GOES-15, GOES-16, GOES-17, Meteosat-8, Meteosat-11, or Himawari-8), or to Clouds and the Earth’s Radiant Energy System (CERES) instruments onboard Aqua and Terra, or the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. In order to increase the usability of this dataset, the Community science project Leveraging Online and User Data through GLOBE And Zooniverse Engagement (CLOUD GAZE) has been developed to generate data quality flags of these ground-up and top-down perspectives of sky and clouds. Recently funded through NASA’s Citizen Science for Earth Systems Program, CLOUD GAZE has partnered with the Zooniverse online platform to obtain reference data and image tagging of sky photographs collected through The GLOBE Program’s clouds protocol. This paper will present the GLOBE Clouds dataset matched to NASA satellite data, integration of CLOUD GAZE to develop data quality flags, and research applications of the dataset (includes ground-up and top-down perspective comparisons, ground observations of dust storms and smoke plumes, and cloud observations in polar regions). The paper will also present on techniques and recommendations for classroom use and for community engagement, particularly for those looking to online resources.

Marilé Colón Robles↗

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell us about Aerosol Composition?

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloe S F Kacenelenbogen↗

Evaluation of CloudSat Radiative Kernels Using ARM and CERES Observations and ERA5 Reanalysis

Despite the widespread use of the radiative kernel technique for studying radiative feedbacks and radiative forcings, there has not been any systematic, observation-based validation of the radiative kernel method. Here, we utilize observed and reanalyzed radiative fluxes and atmospheric profiles from the Atmospheric Radiation Measurement (ARM) program and ERA5 reanalysis to assess a set of observation-based radiative kernels from CloudSat for six ARM sites. The CloudSat radiative kernels, convoluted with the ERA5 state variables, can almost perfectly reconstruct the monthly anomalies of shortwave (SW) and longwave (LW) radiative fluxes in ERA5 at the surface (SFC) and top-of atmosphere (TOA) with correlations significantly being greater than 0.95. The biases of kernel-estimated flux anomalies calculated using the ARM-observed state variables can be more than twice as large when compared with the ARM-observed surface flux anomalies and Clouds and Earth’s Radiant Energy System (CERES) observed anomalies at the TOA. Generally, clouds contribute to most (>60%) of the variance of flux anomalies at Southern Great Plain (SGP), Tropical Western Pacific (TWP), and Eastern North Atlantic (ENA), and surface albedo dominates (>69%) the variance of SW flux anomalies at North Slope of Alaska (NSA). The radiative kernels exhibit the lowest correlation (r~[0.55,0.85]) when reconstructing SFC LW flux anomalies at SGP, TWP, and ENA, whose biases are related to the possibility that the kernels may not fully capture the characteristics 47 associated with MJO and ENSO at TWP and the presence of clouds at SGP and ENA.

Radiative kernels↗

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗

An Evaluation of Biomass Burning Aerosol Mass, Extinction, and Size Distribution in Geos Using Observations From Camp2EX

Biomass burning aerosol impacts aspects of the atmosphere and Earth system through radiative forcing, serving as cloud condensation nuclei, and air quality. Despite its importance, the representation of biomass burning aerosol is not always accurate in numerical weather prediction and climate models or reanalysis products. Using observations collected as part of the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) in August through October of 2019, aerosol concentration and optical properties are evaluated within the Goddard Earth Observing System (GEOS) and its underlying aerosol module, GOCART. In the operational configuration, GEOS assimilates aerosol optical depth observations at 550 nm to constrain aerosol fields. Particularly for biomass burning aerosol, without the assimilation of aerosol optical depth, aerosol extinction is underestimated compared to observations collected in the Philippines region during the CAMP2Ex campaign. The assimilation process adds excessive amounts of carbon to account for the underestimated extinction, resulting in positive biases in the mass of black and organic carbon, especially within the boundary layer, relative to in situ observations from the Langley Aerosol Research Group Experiment. Counteracting this, GEOS is deficient in sulphate and nitrate aerosol just above the boundary layer. Aside from aerosol mass, extinction within GEOS is a function of ambient relative humidity and an assumed particle size distribution. The relationship between dry and ambient extinction in GEOS reveals that hygroscopic growth is too aggressive within the model for biomass burning aerosol. An additional concern lies in the assumed particle size distribution for GEOS, which has a mode radius that is too small for organic carbon. Variability in the observed particle size distribution for biomass burning aerosol within a single flight also illuminates the fact that a single assumed particle size distribution is not sufficient and that for a proper representation, a more advanced aerosol module with GEOS may be necessary.

Aerosol Mass↗

Application of Earth Observation Data for Improved Environmental and Disaster Monitoring in Central America

Since its establishment in 1991, the Central American Integration System (SICA, in Spanish) has served as a force for integrating the eight countries of Central America and the Dominican Republic, and in recent years, SICA’s General Secretariat and its various technical secretariats have focused on integrating Earth observations into various regional and national processes. In 2019, for instance, a joint statement was signed between SICA’s General Secretariat and NASA, toward strengthening the region’s use of Earth observations. SICA has also pursued cooperation with the Group on Earth Observations’ AmeriGEO regional initiative, the Japanese Aerospace Agency (JAXA), the United Nations Office of Outer Space Affairs (UNOOSA), and the Copernicus program, among others. Just in the framework of the NASA-SICA Joint Statement, and towards the goal of strengthening the region’s use of Earth observations across sectors, a large number of training webinars has been conducted, particularly benefiting national institutions, non-governmental organizations, and universities. Additionally, targeted support has been provided in the areas of environmental monitoring and disaster management. From 2019 through 2021, for instance, a number of feasibility studies were implemented by NASA’s DEVELOP program in collaboration with SICA technical secretariats. In 2020, in response to devastating Hurricanes Eta and Iota, the SERVIR program also provided support for extending the HYDRAFloods algorithm which had been originally developed for the Mekong to Central America. Support is also being provided toward monitoring land cover change across the Mesoamerican Biological Corridor. In the framework of the “observing the Earth for the benefit of all” theme, this presentation will also focus on how Central America can serve as a case study for the development of Earth observation capacity, applicable to other regions of the world.

applied sciences↗

Comparison of Observed Longwave, Shortwave Irradiance and Surface Temperature from “MOSAiC” to CERES Radiative Transfer Calculations and Inputs

As atmospheric temperatures rise due to increased anthropogenic forcing, the effect is expected to be larger over the arctic than midlatitude and tropics, known as polar amplification. A multi-national program, the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was ran between Sept 2019 and Oct 2020. The project deployed scientific instruments on board the German research vessel Polarstern with the ship remaining across a year to observe all aspects of polar climate. The US DOE deployed the ARM AMF2 aboard the ship along with several off-ship sites for extended spatial observations. Of particular importance was the measurement of the energetics of the ice/ocean/atmosphere interactions through observations of surface irradiance and surface temperatures. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project produces the SYN1deg Edition 4 data product. This product provides high quality, hourly, globally gridded and temporally complete maps of top of atmosphere (TOA), in atmosphere, and surface irradiances. TOA fluxes are derived from CERES instruments and geostationary satellites. In addition, TOA, in atmosphere, and surface irradiances are computed using the Langley Fu and Liou radiative transfer model. The radiative transfer model is run hourly at 1 degree ~equal area spatial resolution. Meteorological profiles are provided by Global Modeling and Assimilation Office’s GEOS-541 reanalysis product. Cloud properties are derived solely from Terra and Aqua MODIS imagers northward of 60°. Here we compare SYN1deg hourly calculations of surface irradiance to observations from the AMF2 to validate the products estimates of surface irradiance in this challenging area. Along with the irradiance comparisons we take a close look at the surface temperature record in the GEOS-541 product and compare it over both time and space to several surface observations provided by MOSAiC. Along with the comparison to the re-analysis record we will compare these observed surface temperatures to those derived from the AIRS product, which is known to have some difficulty in extreme high latitude areas. The goals of this study are 1) understand computed surface downward irradiance and temperature error separated by surface type (e.g. sea ice or open water) and by season, and 2) error covariance in spatial and temporal space. We seek to use this information to extrapolate the error from the MOSAiC domain to a larger arctic region.

David A Rutan↗

Simultaneous X-Ray and Infrared Observations of Sagittarius A*'s Variability

Emission from Sagittarius A* is highly variable at both X-ray and infrared (IR) wavelengths. Observations over the last ∼20 yr have revealed X-ray flares that rise above a quiescent thermal background about once per day, while faint X-ray flares from Sgr A* are undetectable below the constant thermal emission. In contrast, the IR emission of Sgr A* is observed to be continuously variable. Recently, simultaneous observations have indicated a rise in IR flux density around the same time as every distinct X-ray flare, while the opposite is not always true (peaks in the IR emission may not be coincident with an X-ray flare). Characterizing the behavior of these simultaneous X-ray/IR events and measuring any time lag between them can constrain models of Sgr A* ʼs accretion flow and the flare emission mechanism. Using 100+ hours of data from a coordinated campaign between the Spitzer Space Telescope and the Chandra X-ray Observatory, we present results of the longest simultaneous IR and X-ray observations of Sgr A* taken to date. The cross-correlation between the IR and X-ray light curves in this unprecedented data set, which includes four modest X-ray/IR flares, indicates that flaring in the X-ray may lead the IR by approximately 10–20 min with 68% confidence. However, the 99.7% confidence interval on the time-lag also includes zero, i.e., the flaring remains statistically consistent with simultaneity. Long-duration and simultaneous multi-wavelength observations of additional bright flares will improve our ability to constrain the flare timing characteristics and emission mechanisms, and must be a priority for Galactic Center observing campaigns.

H. Boyce↗

Transition Region Contribution to AIA Observations in the Context of Coronal Heating

We investigate the ratio of coronal and transition region intensity in coronal loops observed by the AtmosphericImaging Assembly(AIA)on the Solar Dynamics Observatory(SDO). Using Enthalpy-based Thermal Evolution ofLoops(EBTEL)hydrodynamic simulations, we model loops with multiple lengths and energyfluxes heatedrandomly by events drawn from power-law distributions with different slopes and minimum delays between eventsto investigate how each of these parameters influences observable loop properties. We generate AIA intensitiesfrom the corona and transition region for each realization. The variations within and between models generatedwith these different parameters illustrate the sensitivity of narrowband imaging to the details of coronal heating.We then analyze the transition region and coronal emission from a number of observed active regions andfindbroad agreement with the trends in the models. In both models and observations, the transition region brightness issignificant, often greater than the coronal brightness in all six“coronal”AIA channels. We also identify an inverserelationship, consistent with heating theories, between the slope of the differential emission measure(DEM)coolward of the peak temperature and the observed ratio of coronal to transition region intensity. These resultshighlight the use of narrowband observations and the importance of properly considering the transition region ininvestigations of coronal heating

S J Schonfeld↗

The GMAO Observing System Simulation Experiment (OSSE) Framework

We present the current status of the OSSE system at the Global Modeling and Assimilation Office at the National Aeronautics and Space Administration (NASA/GMAO). Some of the OSSE techniques developed at GMAO including simulation of realistic observations, e.g., adding errors to simulated observations, are now widely used by the community to evaluate the impact of new observations on the weather forecasts. This talk presents some of the recent progresses and challenges in simulating realistic observations, radiative transfer modeling support for the GMAO OSSE activities, assimilation of OSSE observations into data assimilation systems, and evaluating the impact of simulated observations on the forecast skills.

Isaac Moradi↗