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NASA NTRSDate not supplied

GEWEX SRB Release 4: Public Release

The NASA/GEWEX Surface Radiation Budget (SRB) project produces 3-hourly shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Here we announce the public availability of the new Release 4 Integrated data product (R4-IP). R4-IP uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Release 3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters constituting an “Integrated Product” for energy and water cycle studies. In addition to the input data improvements, several important algorithm improvements have been made since Release 3. These include recalculated shortwave (SW or solar wavelengths) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both SW and LW (longwave or thermal infrared) also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC). Both LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added. Here we analyze the new SW SRB datasets, comparing them to the previous Release 3, BSRN and PMEL surface measurements. Validation results show improved agreement compared to Release 3. Comparisons to ERBE and CERES TOA and surface satellite datasets before and after overlap periods show the long-term agreement with radiometric uncertainty. Monthly anomalies at global and zonal regions show very good correlation with the shorter ERBE and CERES flux anomalies linking those to the longer term. The uncertainties are discussed and periods of potential issues in inputs and/or algorithms are identified.

Earth Radiation Budget↗
NASA NTRS2019

The unexpected surface of asteroid (101955) Bennu

NASA’S Origins, Spectral Interpretation, Resource Identification and Security-Regolith Explorer (OSIRIS-REx) spacecraft recently arrived at the near-Earth asteroid (101955) Bennu, a primitive body that represents the objects that may have brought prebiotic molecules and volatiles such as water to Earth1. Bennu is a low-albedo B-type asteroid2 that has been linked to organic-rich hydrated carbonaceous chondrites3. Such meteorites are altered by ejection from their parent body and contaminated by atmospheric entry and terrestrial microbes. Therefore, the primary mission objective is to return a sample of Bennu to Earth that is pristine—that is, not affected by these processes4. The OSIRIS-REx spacecraft carries a sophisticated suite of instruments to characterize Bennu’s global properties, support the selection of a sampling site and document that site at a sub-centimetre scale5,6,7,8,9,10,11. Here we consider early OSIRIS-REx observations of Bennu to understand how the asteroid’s properties compare to pre-encounter expectations and to assess the prospects for sample return. The bulk composition of Bennu appears to be hydrated and volatile-rich, as expected. However, in contrast to pre-encounter modelling of Bennu’s thermal inertia12 and radar polarization ratios13—which indicated a generally smooth surface covered by centimetre-scale particles—resolved imaging reveals an unexpected surficial diversity. The albedo, texture, particle size and roughness are beyond the spacecraft design specifications. On the basis of our pre-encounter knowledge, we developed a sampling strategy to target 50-metre-diameter patches of loose regolith with grain sizes smaller than two centimetres4. We observe only a small number of apparently hazard-free regions, of the order of 5 to 20 metres in extent, the sampling of which poses a substantial challenge to mission success.

D. S. Lauretta↗
NASA NTRS2020

Decay of the Snow Cover Over Arctic Sea Ice From ICESat‐2 Acquisitions During Summer Melt in 2019

From the onset of melt in early June, corresponding declines in Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) freeboard and surface albedo can be seen over the entire Arctic sea ice cover. In the 2019 summer, area‐averaged freeboard decreased from 34 cm prior to melt to a minimum of 12 cm in August while the area‐averaged albedo decreased from ~0.7 to 0.38 for the same period. Calculations using ICESat‐2 freeboards and modeled ice thickness from Pan‐Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) give area‐averaged snow depths ranging from 17 cm prior to melt to 3 cm in August over seasonal ice and from 34 to 4 cm over multiyear ice. Mean rates of snow ablation (including evaporation) in mid‐June were as high as 2 cm/day, comparable to field records from other years. Increases in freeboard after mid‐August in the high latitude (>80°N) multiyear ice cover, north of the Greenland coast, are likely due to earlier freeze‐up and snow accumulation in these regions with shorter melt seasons.

R Kwok↗
NASA NTRS2019

Multimodel Analysis of Future Land Use and Climate Change Impacts on Ecosystem Functioning

Land use and climate changes both affect terrestrial ecosystems. Here, we used three combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1xRCP26, SSP3xRCP60, and SSP5xRCP85) as input to three dynamic global vegetation models to assess the impacts and associated uncertainty on several ecosystem functions: terrestrial carbon storage and fluxes, evapotranspiration, surface albedo, and runoff. We also performed sensitivity simulations in which we kept either land use or climate (including atmospheric CO2) constant from year 2015 on to calculate the isolated land use versus climate effects. By the 2080–2099 period, carbon storage increases by up to 87 ± 47 Gt (SSP1xRCP26) compared to present day, with large spatial variance across scenarios and models. Most of the carbon uptake is attributed to drivers beyond future land use and climate change, particularly the lagged effects of historic environmental changes. Future climate change typically increases carbon stocks in vegetation but not soils, while future land use change causes carbon losses, even for net agricultural abandonment (SSP1xRCP26). Evapotranspiration changes are highly variable across scenarios, and models do not agree on the magnitude or even sign of change of the individual effects. A calculated decrease in January and July surface albedo (up to −0.021 ± 0.007 and −0.004 ± 0.004 for SSP5xRCP85) and increase in runoff (+67 ± 6 mm/year) is largely driven by climate change. Overall, our results show that future land use and climate change will both have substantial impacts on ecosystem functioning. However, future changes can often not be fully explained by these two drivers and legacy effects have to be considered.

land use change↗
NASA NTRS2019

The HST Lightcurve of (486958) 2014 MU69

We report Hubble Space Telescope (HST) lightcurve observations of the New Horizons spacecraft encounter Kuiper Belt object (KBO) (486958) 2014 MU69 acquired near opposition in July 2017. In order to plan the optimum flyby sequence the New Horizons mission planners needed to learn as much as possible about the target in advance of the encounter. Specifically, from lightcurve data, encounter timing could be adjusted to accommodate a highly elongated, binary, or rapidly rotating target. HST astrometric (Porter et al., 2018) and stellar occultation (Buie et al., 2018) observations constrained MU69's orbit and diameter (21–41 km for an albedo of 0.15–0.04), respectively. Photometry from the astrometric dataset suggested a variability of ≥0.3 mags, but they did not determine the period or provide shape information. To that end we strategically spaced 24 HST orbits over 9 days to investigate rotation periods from approximately 2–100 h and to better constrain the lightcurve amplitude. Until New Horizons detected MU69 in its optical navigation images beginning in August 2018, this HST lightcurve campaign provided the most accurate photometry to date. The mean variation in our data is 0.15 magnitudes which suggests that MU69 is either nearly spherical (a:b axis ratio of 1:1.15), or its pole vector is pointed near the line of sight to Earth; this interpretation does not preclude a near-contact binary or bi-lobed object. However, image stacks do conclude that MU69 does not have a binary companion ≥2000 km with a sensitivity to 29th magnitude (an object a few km in size for an albedo of 0.04–0.15). Our data are not of sufficient signal to noise to uniquely determine the period or amplitude, however, they did provide the necessary information for spacecraft planning. We report with confidence that MU69 is not both rapidly rotating and highly elongated (which we define as a lightcurve amplitude ≥ 0.5 magnitude). Since this paper is being published post fly-by, we note that our results are consistent with the fly-by imagery and orientation of MU69 (Stern et al., 2019). The combined dataset also suggests that within the KBO lightcurve literature there are likely other objects which share a geometric configuration like MU69 resulting in an underestimate of the contact binary fraction for the Cold Classical Kuiper Belt.

S D Benecchi↗
NASA NTRS2020

Statistical Characterization of Hot Jupiter Atmospheres Using Spitzer's Secondary Eclipses

We report 78 secondary eclipse depths for a sample of 36 transiting hot Jupiters observed at 3.6 and 4.5 μm using the Spitzer Space Telescope. Our eclipse results for 27 of these planets are new, and include highly irradiated worlds such as KELT-7b, WASP-87b, WASP-76b, and WASP-64b, and important targets for James Webb Space Telescope such as WASP-62b. We find that WASP-62b has a slightly eccentric orbit (e cos w = 0.00614 ± 0.00064), and we confirm the eccentricity of HAT-P-13b and WASP-14b. The remainder are individually consistent with circular orbits, but we find statistical evidence for eccentricity increasing with orbital period in our range from 1 to 5 days. Our day-side brightness temperatures for the planets yield information on albedo and heat redistribution, following Cowan & Agol (2011). Planets having maximum day-side temperatures exceeding ∼2200 K are consistent with having zero albedo and a distribution of stellar irradiance uniformly over the day-side hemisphere. Our most intriguing result is that we detect a systematic difference between the emergent spectra of these hot Jupiters as compared to blackbodies. The ratio of observed brightness temperatures, Tb(4.5)/Tb(3.6), increases with equilibrium temperature by 100 ± 24 parts-per-million per Kelvin, over the entire temperature range in our sample (800–2500 K). No existing model predicts this trend over such a large range of temperature. We suggest that this may be due to a structural difference in the atmospheric temperature profiles of real planetary atmospheres as compared to models.

Exoplanet astronomy↗
NASA NTRS2022

Seasonal Variability in the Mechanisms Behind the 2020 Siberian Heatwaves

Record-breaking heatwaves and wildfires immersed Siberia during the boreal spring of 2020 following an anomalously warm winter. Springtime heatwaves are becoming more common in the region, with statistically significant trends in the frequency, magnitude, and duration of heatwave events over the past four decades. Mechanisms by which the heatwaves occur and contributing factors differ by season. Winter heatwave frequency is correlated with the atmospheric circulation, particularly the Arctic Oscillation, while the frequency of heatwaves during the spring months is highly correlated with aspects of the land surface including snow cover, albedo, and latent heat flux. Idealized AMIP-style experiments are used to quantify the contribution of suppressed Arctic sea ice and snow cover over Siberia on the atmospheric circulation, surface energy budget, and surface air temperature in Siberia during the winter and spring of 2020. Sea ice concentration contributed to the strength of the stratospheric polar vortex and Arctic Oscillation during the winter months, thereby influencing the tropospheric circulation and surface air temperature over Siberia. Warm temperatures across the region resulted in an earlier-than-usual recession of the winter snowpack. The exposed land surface contributed to up to 20% of the temperature anomaly during the spring through the albedo feedback and changes in the ratio of the latent and sensible heat fluxes. This, in combination with favorable atmospheric circulation patterns, resulted in record-breaking heatwaves in Siberia in the spring of 2020.

Allison B. Marquardt Collow↗
NASA NTRS2021

The Dark Side of Pluto

During its departure from Pluto, New Horizons used its LORRI camera to image a portion of Pluto's southern hemisphere that was in a decades-long seasonal winter darkness, but still very faintly illuminated by sunlight reflected by Charon. Recovery of this faint signal was technically challenging. The bright ring of sunlight forward-scattered by haze in the Plutonian atmosphere encircling the nightside hemisphere was severely overexposed, defeating the standard smeared-charge removal required for LORRI images. Reconstruction of the overexposed portions of the raw images, however, allowed adequate corrections to be accomplished. The small solar elongation of Pluto during the departure phase also generated a complex scattered-sunlight background in the images that was three orders of magnitude stronger than the estimated Charon-light flux (the Charon-light flux is similar to the flux of moonlight on Earth a few days before first quarter). A model background image was constructed for each Pluto image based on principal component analysis applied to an ensemble of scattered-sunlight images taken at identical Sun−spacecraft geometry to the Pluto images. The recovered Charon-light image revealed a high-albedo region in the southern hemisphere. We argue that this may be a regional deposit of N2 or CH4 ice. The Charon-light image also shows that the south polar region currently has markedly lower albedo than the north polar region of Pluto, which may reflect the sublimation of N2 ice or the deposition of haze particulates during the recent southern summer.

Pluto↗
NASA NTRS2022

Extratropical Shortwave Cloud Feedbacks in the Context of the Global Circulation and Hydrological Cycle

Shortwave (SW) cloud feedback (SW FB ) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs in the Sixth Coupled Model Intercomparison Project (CMIP6) exceed 5K, above the fifth assessment report (AR5) ‘likely’ maximum (4.5K) due to extratropical SW FB ’s that are more positive than those simulated in previous generation CMIP5 GCMs. Here we show that across 57 GCMs Southern Ocean SW FB can be predicted from the sensitivity of column-integrated liquid water mass LWP) to moisture convergence and to surface temperature. The response of LWP to moisture convergence and the response of albedo to LWP anti-correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean-state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean SW FB — inconsistent with extreme ECS.

extratropical cloud response↗
NASA NTRSDate not supplied

NASA/GEWEX SRB Surface Radiation Budget Fluxes Through the Prism of Weather States

The NASA/GEWEX Surface Radiation Budget Version 4 (SRB Rel4) product is now publicly available, covering the period from July 1983 through June 2017. This supersedes the SRB Rel3 (Stackhouse et al., 2011) product which has been used in the community for a wide variety of applications, including climate model validation, agriculture, solar energy, and architecture. SRB Rel4 uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Rel3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters. Rel4 incorporates several important algorithm improvements. These include recalculated shortwave (SW) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both shortwave and longwave (LW) now also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MACv1). LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added. Here we evaluate the SRB Rel4 top of atmosphere (TOA) and surface fluxes in the context of weather states and oceanic regions. Weather states (Tselioudis et al., 2013, Tselioudis et al., 2021) are defined by K-means clustering 2-D histograms of satellite-retrieved cloud optical depths and cloud top pressures. The most recent (Tselioudis et al., 2021) weather states derived from the International Satellite Cloud Climatology Project (ISCCP) H-series data results in eight cloud weather states and one clear sky weather state, for a total of nine weather states. We examine the statistics of SRB Rel4 fluxes for each weather state and a variety of relevant land and ocean regions. We compare to similar analyses performed on CERES EBAF and SYN1Deg flux products, and validate against Baseline Surface Radiometer Network (BSRN) land stations and Pacific Marine Environmental Laboratory (PMEL) ocean buoy data. It is demonstrated that the weather state concept is valuable when examining the comparative strengths and weaknesses of satellite radiative flux algorithms.

Atmospheric Radiation↗
NASA NTRSDate not supplied

Eruption Characterisitics of Lunar Localized Pyroclastic Deposits Based on Water Content, Mineralogy, Regolith Properties

Lunar pyroclastic deposits are low albedo deposits present throughout the lunar surface including both maria and highlands, nearside and farside, and high latitudes and equatorial regions [e.g., 1]. There are two main types of pyroclastic deposits based upon size: localized (<2500 km2) and regional pyroclastic deposits (>2500 km2) [1]. In this study, we focus on the smaller localized pyroclastic deposits. The first and most detailed study of localized pyroclastic deposits are the deposits in Alphonsus crater [2]. This study included examining the radar and volumetric properties of these deposits. They found that vulcanian-like eruptions are most consistent with their observations. They imagined that a dike intrudes into the crust and creates a cooled basaltic cap. With increasing pressure under the basaltic cap, the pressure eventually overwhelms the surrounding rocks and results in explosive decompression. Later studies examined several pyroclastic deposits across the lunar surface using radar [2–4], digital terrain models (DTMs) [2,4], visible and near-infrared spectrometers [1,4–7], and a radiometer [4] to determine the mineralogy (e.g., olivine, glass, clinopyroxene, orthopyroxene, and plagioclase), deposit thickness and volume, proportion of juvenile material, radar backscatter, surface rock abundance, and regolith density. These various properties were examined against one another to better group localized pyroclastic deposits and understand how they relate to one another [4]. One of the studies divided pyroclastic deposits into three groups based upon the shape of the 1-μm absorption feature. The three Groups could be interpretated as having highlands and pyroclastic material (Group I), mare and pyroclastic material (Group II), and glass and orthopyroxene material (Group III) [5]. Building on that foundation, another study divided the pyroclastic deposits into four groups based upon their surface rock abundance and glass abundance [4], where deposits are classified based upon low surface rock abundance and high glass abundance (Glassy deposits); high rock abundance, high glass abundance (Blocky deposits); moderate rock abundance and low glass abundance (Crystalline deposits); and high rock abundance and low glass abundance (Indistinct Group). In addition to these studies, we can now look at their water contents using the new Effective Single Particle Absorption Thickness (ESPAT) parameter map [8]. The ESPAT map measures the strength of the 3-μm absorption feature in single scattering albedo space. The strength of this feature and its relationship to water content has been calibrated to returned samples, which allows for water content to be derived from remote spectral data (i.e., Moon Mineralogy Mapper). The goal of this study is to examine how water content in the pyroclastic deposits varies with respect to the geometric, mineralogic, and physical properties of the localized pyroclastic deposits as measured by a previous study [i.e., 4]. A more complete version of this work is found in [9].

D Trang↗
NASA NTRS2021

Terrestrial Planet Optical Phase Curves: I. Direct Measurements of the Earth

NASA’s EPOXI mission used the Deep Impact spacecraft to observe the disk-integrated Earth as an analog to terrestrial exoplanets’ appearance. The mission took five 24 hr observations in 2008–2009 at various phase angles(57°.7–86°.4)and ranges(0.11–0.34 au), of which three equatorial(E1, E4, E5)and two polar(P1, North and P2,South). The visible data taken by the HRIV instrument ranges from 0.3 to 1.0μm, taken trough seven spectral filters that have spectral widths of about 100 nm, and which are centered about 100 nm apart, from 350 to 950 nm. The disk-integrated, 24 hr averaged signal is used in a phase angle analysis. A Lambertian-reflecting, spherical planet model is used to estimate geometric albedo for every observation and wavelength. The geometric albedos range from 0.143(E1, 950 nm)to 0.353(P2, 350 nm)and show wavelength dependence. The equatorial observations have similar values, while the polar observations have higher values due to the ice in view. Therefore, equatorial observations can be predicted for other phase angles, but(Earth-like)polar views(with ice)would be underestimated.

Roderick De Cock↗
NASA NTRS2020

Snow Property Inversion from Remote Sensing (SPIReS): A Generalized Multispectral Unmixing Approach with Examples from MODIS and Landsat 8 OLI

Spectral mixture analysis has a history in mappingsnow, especially where mixed pixels prevail. Using multiplespectral bands rather than band ratios or band indices, retrievalsof snow properties that affect its albedo lead to more accu-rate estimates than widely used age-based models of albedoevolution. Nevertheless, there is substantial room for improve-ment. We present the Snow Property Inversion from RemoteSensing (SPIReS) approach, offering the following improve-ments: 1) Solutions for grain size and concentrations of lightabsorbing particles are computed simultaneously; 2) Only snowand snow-free endmembers are employed; 3) Cloud-maskingand smoothing are integrated; 4) Similar spectra are groupedtogether and interpolants are used to reduce computation time.The source codes are available in an open repository. Com-putation is fast enough that users can process imagery ondemand. Validation of retrievals from Landsat 8 operational landimager (OLI) and moderate-resolution imaging spectroradiome-ter (MODIS) against WorldView-2/3 and the Airborne SnowObservatory shows accurate detection of snow and estimatesof fractional snow cover. Validation of albedo shows low errorsusing terrain-correctedin situmeasurements. We conclude bydiscussing the applicability of this approach to any airborne orspaceborne multispectral sensor and options to further improve retrievals.

Edward H Blair↗
NASA NTRS2022

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↗
NASA NTRS2022

TESS in the Extended Mission: A Powerful Tool for Time-Domain Exoplanet Science

Since its launch in 2018, the Transiting Exoplanet Survey Satellite (TESS) has embarked on an ambitious mission to image almost the entire sky in search of nearby transiting exoplanet systems. Upon completion of its Primary Mission in July 2020, TESS transitioned to its first Extended Mission, during which it has returned to both the southern and northern ecliptic hemispheres and revisited most of the targets it observed during the first two years of operation. With future Extended Missions likely, the end-to-end time baseline provided by TESS will significantly exceed that of Kepler, enabling a plethora of scientific investigations into time-domain exoplanet science. TESS has already established itself as an extremely productive tool for studying visible-wavelength exoplanet phase curves. During the Primary Mission, we carried out a systematic phase-curve analysis of more than 30 transiting exoplanet systems. These datasets constrained the dayside hemisphere brightness temperatures, day-night brightness contrasts, and optical geometric albedos of a wide range of gas giant planets, revealing some tantalizing trends that warrant further study. In particular, we uncovered a tentative positive correlation between geometric albedo and equilibrium temperature for gas giants with 1500 < Teq < 3000 K. The new light curves from the Extended Mission have refined the measured astrophysical parameters of the previously studied systems and yielded statistically significant secondary eclipse and phase-curve detections for dozens of more systems. By comparing the phase-curve properties obtained from TESS observations separated by months or years, we have also probed for possible atmospheric variability, as well as transit-timing variations due to orbital decay or additional companions. In this presentation, I will provide an overview of the main results from our ongoing multiyear study of TESS light curves and discuss potentially fruitful avenues for further research as TESS continues its all-sky survey into the future.

Ian Wong↗
NASA NTRSDate not supplied

Isolating the Surface Type Influence on Arctic Cloud Properties

In response to anthropogenic climate change, substantial declines in sea ice have been observed. An urgent question is whether and how clouds respond to the changing Arctic surface. Due to the important radiative influence of clouds, the response of clouds to sea ice cover change constitutes a potentially important climate feedback within the Arctic. The sign of this feedback is strongly influenced by the seasonality of the cloud response to sea ice loss. Given the importance of this phenomenon, previous research focused on using observations of inter-annual variability to quantify the cloud-sea ice relationship. However, the reliance on inter-annual variability to assess the covariance between clouds and sea ice make it challenging to control for the influence of large-scale meteorology on the clouds. We have devised an approach that applies an in situ, airborne observational strategy to quantify the influence of surface type on Arctic clouds to satellite data. Our event-based method composites cloud property differences for ocean, marginal ice zone, and sea ice surface types for >5000 MIZ crossing events. We find that cloud properties in non-summer months below ~1.5 km are influenced by surface type such that greater cloud fraction and water content are found over ocean relative to sea ice regions. Results are statistically significantly at the 95% confidence level. During summer, the surface type does not influence the cloud properties. The primary cause of the surface type dependent cloud property differences is the thermodynamic profiles differences that occur between the two surface types: namely, ocean footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their sea ice counterparts. We find that the differences in thermodynamic profiles by surface type that correspond to the cloud property differences also explains a significant portion of the variability across events. Our analysis provides evidence that the influence of surface type on cloud properties fundamentally occurs due to the inherent surface temperature differences between the surface types. Significant surface type influences on cloud properties are only found in the presence of surface temperature differences between the surface types and only non-summer months meet this criterion. A conceptual model of this process is as follows, fundamental properties of the ocean and sea ice surface types (e.g., surface albedo, heat capacity/thermal inertia, surface roughness, and thermal conductance) lead to systematic differences in the surface temperature by surface type. In response to this surface temperature difference, atmosphere boundary layer processes (including turbulent mixing and radiation) communicate the surface temperature differences to the lower atmosphere driving the greater stability over sea ice than ocean. These differences in the background thermodynamic state profiles between the surface types yield atmospheric conditions that are more conducive to cloud development over ocean than sea ice. The details of these boundary layer processes are sensitive to the surface type but may not be fundamental to the resulting thermodynamic structure and cloud differences. Thus, our results indicate that to accurately model that cloud response to sea ice loss in climate models the surface type properties that yield the systematic differences in ocean and sea ice temperature (e.g., surface albedo, surface turbulent fluxes parameters, and thermal conductance) must be accurately represented.

Arctic radiation budget↗
NASA NTRS2022

Using commercial high-resolution satellite imagery to monitor a nuisance macroalga in the largest marine protected area in the U.S.A.

Satellite imagery is a useful tool for monitoring and mapping the distribution of invasive or nuisance algal species on coral reefs over the temporal and spatial scales needed for ecosystem management. Visual inspections of high-resolution satellite imagery were used to detect the newly discovered nuisance alga, Chondria tumulosa , at Manawai (Pearl and Hermes Atoll) in combination with ground-truthing surveys. Low-albedo (“dark”) survey sites on spur habitats were associated with mean C. tumulosa cover seven times higher than adjacent high-albedo (“light”) sites. There was an inverse relationship between C. tumulosa percent cover at ground-truthing sites and mean reflectance values. Archival satellite imagery showed that areas of high C. tumulosa cover (i.e., dark patches) were not evident on or before 2015 on the northeast backreef. This case study is the first to apply satellite imagery to target a nuisance red macroalgal bloom on a coral reef. The ability to use satellites for the detection of nuisance or invasive benthic species, such as expansive mats of C. tumulosa , provides managers with a valuable tool, especially in remote regions.

Invasive↗
NASA NTRS2015

Comparative Habitability of Transiting Exoplanets

Exoplanet habitability is traditionally assessed by comparing a planet’s semimajor axis to the location of its host star’s “habitable zone,” the shell around a star for which Earth-like planets can possess liquid surface water. The Kepler space telescope has discovered numerous planet candidates near the habitable zone, and many more are expected from missions such as K2, TESS, and PLATO. These candidates often require significant follow-up observations for validation, so prioritizing planets for habitability from transit data has become an important aspect of the search for life in the universe. We propose a method to compare transiting planets for their potential to support life based on transit data, stellar properties and previously reported limits on planetary emitted flux. For a planet in radiative equilibrium, the emitted flux increases with eccentricity, but decreases with albedo. As these parameters are often unconstrained, there is an “eccentricity-albedo degeneracy” for the habitability of transiting exoplanets. Our method mitigates this degeneracy, includes a penalty for large-radius planets, uses terrestrial mass–radius relationships, and, when available, constraints on eccentricity to compute a number we call the “habitability index for transiting exoplanets” that represents the relative probability that an exoplanet could support liquid surface water. We calculate it for Kepler objects of interest and find that planets that receive between 60% and 90% of the Earth’s incident radiation, assuming circular orbits, are most likely to be habitable. Finally, we make predictions for the upcoming TESS and James Webb Space Telescope missions.

Planet and satellite surfaces↗