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At least 829 records · Page 46

Analyses of Cometary Silicate Crystals: DDA Spectral Modeling of Forsterite

Comets are the Solar System's deep freezers of gases, ices, and particulates that were present in the outer protoplanetary disk. Where comet nuclei accreted was so cold that CO ice (approximately 50K) and other supervolatile ices like ethane (C2H2) were preserved. However, comets also accreted high temperature minerals: silicate crystals that either condensed (greater than or equal to 1400 K) or that were annealed from amorphous (glassy) silicates (greater than 850-1000 K). By their rarity in the interstellar medium, cometary crystalline silicates are thought to be grains that formed in the inner disk and were then radially transported out to the cold and ice-rich regimes near Neptune. The questions that comets can potentially address are: How fast, how far, and over what duration were crystals that formed in the inner disk transported out to the comet-forming region(s)? In comets, the mass fractions of silicates that are crystalline, f_cryst, translate to benchmarks for protoplanetary disk radial transport models. The infamous comet Hale-Bopp has crystalline fractions of over 55%. The values for cometary crystalline mass fractions, however, are derived assuming that the mineralogy assessed for the submicron to micron-sized portion of the size distribution represents the compositional makeup of all larger grains in the coma. Models for fitting cometary SEDs make this assumption because models can only fit the observed features with submicron to micron-sized discrete crystals. On the other hand, larger (0.1-100 micrometer radii) porous grains composed of amorphous silicates and amorphous carbon can be easily computed with mixed medium theory wherein vacuum mixed into a spherical particle mimics a porous aggregate. If crystalline silicates are mixed in, the models completely fail to match the observations. Moreover, models for a size distribution of discrete crystalline forsterite grains commonly employs the CDE computational method for ellipsoidal platelets (c:a:b=8.14x8.14xl in shape with geometrical factors of x:y:z=1:1:10, Fabian et al. 2001; Harker et al. 2007). Alternatively, models for forsterite employ statistical methods like the Distribution of Hollow Spheres (Min et al. 2008; Oliveira et al. 2011) or Gaussian Random Spheres (GRS) or RGF (Gielen et al. 200S). Pancakes, hollow spheres, or GRS shapes similar to wheat sheaf crystal habit (e.g., Volten et al. 2001; Veihelmann et al. 2006), however, do not have the sharp edges, flat faces, and vertices seen in images of cometary crystals in interplanetary dust particles (IDPs) or in Stardust samples. Cometary forsterite crystals often have equant or tabular crystal habit (J. Bradley). To simulate cometary crystals, we have computed absorption efficiencies of forsterite using the Discrete Dipole Approximation (DDA) DDSCAT code on NAS supercomputers. We compute thermal models that employ a size distribution of discrete irregularly shaped forsterite crystals (nonspherical shapes with faces and vertices) to explore how crystal shape affects the shape and wavelength positions of the forsterite spectral features and to explore whether cometary crystal shapes support either condensation or annealing scenarios (Lindsay et al. 2012a, b). We find forsterite crystal shapes that best-fit comet Hale-Bopp are tetrahedron, bricks or brick platelets, essentially equant or tabular (Lindsay et al. 2012a,b), commensurate with high temperature condensation experiments (Kobatake et al. 2008). We also have computed porous aggregates with crystal monomers and find that the crystal resonances are amplified. i.e., the crystalline fraction is lower in the aggregate than is derived by fitting a linear mix of spectral features from discrete subcomponents, and the crystal resonances 'appear' to be from larger crystals (Wooden et al. 2012). These results may indicate that the crystalline mass fraction in comets with comae dominated by aggregates may be lower than deduced by popular methods that only emoy ensembles of discrete crystals.

Wooden, Diane↗

The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, and water (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models' responses to CTW changes (Rotter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012). To fulfill this need, the Coordinated Climate-Crop Modeling Project (C3MP) (Ruane et al., 2014) was initiated within the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013). The submitted results from C3MP Phase 1 (February 15, 2013-December 31, 2013) are currently being analyzed. This chapter serves to present and update the C3MP protocols, discuss the initial participation and general findings, comment on needed adjustments, and describe continued and future development. AgMIP aims to improve substantially the climate, crop, and economic simulation tools that are used to characterize the agricultural sector, to assess future world food security under changing climate conditions, and to enhance adaptation capacity both globally and regionally. To understand better and improve the modeled crop responses, AgMIP has conducted detailed crop model intercomparisons at closely observed field sites for wheat (Asseng et al., 2013), rice (Li et al., in review), maize (Bassu et al., 2014), and sugarcane (Singels et al., 2013). A coordinated modeling exercise was one of the original motivations for AgMIP, and C3MP provides rapid estimation of crop responses to CO2, water, and temperature (CTW) changes, adding dimension and insight into the crop model intercomparisons, while facilitating interactions within the global community of modelers. C3MP also contributes a fast-track, multi-model climate sensitivity assessment for the AgMIP climate and crop modeling teams on Research Track 2 (Fig. 1), which seeks to understand the impact of projected climatic changes on crop production and food security (Rosenzweig et al., 2013; Ruane et al., 2014).

agriculture↗

Vertical Profiles of Mars 1.27 Micrometer O2 Dayglow from MRO CRISM Limb Spectra: Seasonal/global Behaviors, Comparisons to LMDGCM Simulations, and a Global Definition for Mars Water Vapor Profiles

Since July of 2009, The Compact Reconnaissance Imaging Spectral Mapper (CRISM) onboard the Mars Re- connaissance Orbiter (MRO) has periodically obtained pole-to-pole observations (i.e., full MRO orbits) of limb scanned visible/near IR spectra (lambda= 0.4 - 4.0 micrometers, delta lambda approx. 10 nm- Murchie et al., 2007). These CRISM limb observations support the first seasonally and spatially extensive set of Mars 1.27 micometers O2 (1 delta(sub g)) day-glow profile retrievals (approx. 1100) over greater than or equal to 8-80 km altitudes. Their comparison to Laboratoire de Meteorologie Dynamique (LMD) global climate model (GCM) simulated O2 (1 delta(sub g)) volume emission rate (VER) profiles, as a function of altitude, latitude, and season (solar longitude, L(sub s), supports several key conclusions regarding Mars atmospheric water vapor (which is derived from O2 (1 delta(sub g)) emission rates), Mars O3, and the collisional de-excitation of O2 (1 delta(sub g)) in the Mars CO2 atmosphere. Current (Navarro et al., 2014) LMDGCM simulations of Mars atmospheric water vapor fall 2-3 times below CRISM derived water vapor abundances at 20-40 km altitudes over low-to-mid latitudes in northern spring (L(sub s) = 30-60 deg), and northern mid-to-high latitudes over northern summer (L(sub s) = 60-140 deg). In contrast, LMDGCM simulated water vapor is 2-5 times greater than CRISM derived values at all latitudes and seasons above 40 km, within the aphelion cloud belt (ACB), and over high-southern to mid-southern latitudes in southern summer (L(sub s) = 190-340 deg) at 15-35 km altitudes. Overall, the solstitial summer-to-winter hemisphere gradients in water vapor are reversed between the LMDGCM modeled versus the CRISM derived water vapor abundances above 10-30 km altitudes. LMDGCM-CRISM differences in water vapor profiles correlate with LMDGCM-CRISM differences in cloud mixing profiles; and likely reflect limitations in simulating cloud microphysics and radiative forcing, both of which restrict meridional transport of water from summer- to-winter hemispheres on Mars (Clancy et al., 1996; Montmessin et al., 2004; Steele et al., 2014; Navarro et al., 2014) and depend on uncertain cloud microphysical properties (Navarro et al., 2014). The derived low-to-mid latitude changes in Mars water vapor vertical distributions should reduce current model- data disagreements in column O3 and H2O2 abundances over low-to-mid latitudes (e.g., within the ACB; Lefevre et al., 2008; Encrenaz et al., 2015; Clancy et al., 2016). Lastly, the global/seasonal average com- parison of CRISM and LMDGCM O2 (1 delta(sub g)) VER below 20 km altitudes indicates a factor of approx. 3 times lower value (0.25 x 10(exp -20) cu cm sec(exp -1)) for the CO2 collisional de-excitation rate coefficient of O2 (1 delta(sub g)) than derived recently by Guslyakova et al. (2016).

Clancy, R. Todd↗

Towards an Enhanced Droplet Activation Scheme for Multi-Moment Bulk Microphysics Schemes

Initial droplet spectra produced upon activation impact the ensuing chain of microphysical processes andtherefore play a crucial role in cloud evolution. This work re-examines dependencies of newly formed clouddroplet size distribution (CDSD) characteristics on environmental and aerosol properties via parcel model simulationsthat serve as the basis for a multi-moment bulk microphysics droplet activation scheme suitable for acloud-resolving model (CRM). It is found that applying a fixed size threshold to define activated droplets versusemploying physical considerations can lead to erroneous activation and overly broad CDSDs for high aerosolconcentration and weak updraft conditions. Aerosol distributions characterized by larger median sizes and/orincreased solubility can result in greater activated droplet numbers, whereas impacts of these parameters onCDSD spectral width depend on both aerosol number concentration and updraft velocity. An expansion of theactivation scheme to include CDSD spectral width is proposed to aid efforts to extend high-order momentprediction to cloud droplet categories in CRMs as well as better represent variability in the activation process onthe cloud scale.simulations to investigate the regime dependence of the relative dispersion(d)1 of newly activated CDSDs, where d is the ratio of dropletradius standard deviation (σ) to the mean radius (r ). C16 demonstratedthat increasing Na resulted in increasing (decreasing) d values via reducedcondensational narrowing (spectral broadening) rates within theAL (UL) regime, with d values peaking in the TR regime. Their findingssuggest a similar regime dependence for d as R09 noted for Nc and helpexplain reportedly conflicting relationships between Na and CDSDspectral characteristics (cf. Hudson and Noble, 2014; Liu et al., 2014),although the applicability of these results within bulk microphysicalschemes was not addressed.Simulating aerosol-cloud interactions with CRMs employing bulkmicrophysics requires that the scheme minimally predict two CDSDparameters, namely mass and number concentrations, and represent thedroplet activation process. Various activation schemes aim to determineNc from aerosol and environmental properties and include analyticalexpressions (e.g., Abdul-Razzak et al., 1998; Morrison et al., 2005) aswell as lookup tables (LUTs) based on detailed parcel model calculations(e.g., Saleeby and Cotton, 2004, hereafter SC04; Segal and Khain,2006; Thompson and Eidhammer, 2014). Expressions to diagnose CDSDspectral width from Nc (Grabowski, 1998; Liu et al., 2006; Morrison andGrabowski, 2007) or cloud water content (Geoffroy et al., 2010) havealso been developed, although more robust methods to obtain CDSDspectral width upon activation are presently lacking. This latter point isrelevant for triple-moment (3 M) bulk microphysics that aim to predictdistribution spectral width alongside number and mass concentrations(e.g., Loftus et al., 2014; Milbrandt and Yau, 2005).The current work extends the findings of C16 to the current LUTbasedaerosol activation scheme used in the Regional AtmosphericModeling System (RAMS) (Cotton et al., 2003; SC04; Saleeby and vanden Heever, 2013, hereafter SvdH13) and additionally examinesaerosol size and solubility impacts on newly activated CDSD properties.Because early cloud development processes such as condensationalgrowth, evaporation, and droplet self-collection depend on and impactCDSD spectral width (Hudson and Yum, 1997; Seifert and Beheng 2001;Lu and Seinfeld, 2006; Igel and van den Heever, 2017), an expansion ofthe activation LUTs to include CDSD spectral width is proposed as apreliminary step for extending 3M prediction to CDSDs in CRMs forimproved simulations of aerosol-cloud interactions.2. MethodologyThe current RAMS two-moment microphysics module determinesthe fractional number of aerosol particles that activate to cloud dropletsfrom five-dimensional LUTs based on model predicted air temperature(T), w, Na, and the geometric median radius (rg) and soluble fraction (ε)of the aerosol size distribution (SvdH13). These LUTs are created offlineusing a one-dimensional Lagrangian adiabatic parcel model (Feingoldand Heymsfield, 1992; Heymsfield and Sabin, 1989; SC04) to simulateexplicit droplet activation and initial CDSD growth for a range of ambientatmospheric conditions [T, w] and binned lognormal aerosol sizedistributions given by= ⎡⎣ ⎢− ⎤⎦ ⎥N r Nr π σr rσ( )2 lnexp[ln( / )]2(ln )aggg22 (1)where r is the dry aerosol particle bin radius and σg is the geometricstandard deviation of the distribution. As the parcel model simulationsfocus on the activation process, other processes such as coalescence,sedimentation, and mixing are not considered. Details of the parcelmodel can be found in SC04 and SvdH13, and only a brief description isprovided here. At the onset of parcel model calculations, the initiallydry aerosol particles in all bins first deliquesce and reach theirequilibrium diameters in a sub-saturated environment based on theKöhler equation for solution droplets. The parcel is then lifted at a fixedupward velocity w, and particle growth by vapor diffusion, along withconcurrent changes in the ambient environment, are iteratively computedusing the Variable-coefficient Ordinary Differential Equation(VODE) solver (Brown et al., 1989). The time resolution of these calculationsis determined within the VODE solver, and the frequency atwhich the solver is called is controlled by a longer model time stepbased on fixed upward parcel displacement increments (Δz) at thespecified w (Δt=Δz/w). Model calculations proceed until the parcelreaches a height 50m beyond the level of maximum saturation ratio(Smax) or total parcel displacement exceeds 2 km. Upon model termination,Smax and the fractional number of aerosols (factv) resulting innewly formed cloud droplets, defined as particles having diameters of atleast 2 μm, are cataloged in the LUTs according to the specified T, w, Na,rg, and ε parameter values.A critical point regarding the creation of these LUTs is the use of afixed minimum diameter (Dmin) to define cloud droplets in the parcelmodel, which can produce erroneous CDSD characteristics, particularlywithin the UL regime. For aerosol distributions with large rg valuesunder low SS conditions, for example, deliquesced aerosols within thelarge tail of the distribution can exceed 2 μm in diameter yet remainunactivated as ‘haze’ particles (Levin and Cotton, 2009; McFigganset al., 2006). For this study, aerosol particles activate to cloud dropletsbased on the critical diameter Dcrit as a function of parcel supersaturationratio (Sr) as in R09:D = σ MS RTρ83 ln( ) critsol wr w (2)where σsol is the surface tension of a solution droplet, Mw and ρw are themolar mass and density of liquid water, respectively, and R is theuniversal gas constant. Additionally, at relatively large w values withinthe AL regime, Nc stabilizes shortly after reaching supersaturation.However, parcel ascent and condensational growth continue beyondthe level of Smax, potentially causing additional narrowing of the CDSD.In the current work, model calculations terminate upon reaching Smaxas changes in Nc are negligible with continued ascent (Peng et al., 2007;R09).Parcel model simulations are performed to examine the sensitivitiesof CDSD characteristics to w, Na, rg, and ε, with the ranges for theseparameters listed in Table 1. Aerosols are assumed to be a mix of solubleand insoluble material of equal density, specified by ε, where fullysoluble aerosols correspond to ammonium sulfate with hygroscopicityparameter κ=0.61 (Petters and Kreidenweis, 2007). FollowingSvdH13, aerosol geometric standard deviation is fixed at σg=1.8, andaerosol distributions (Eq. 1) are partitioned into 100 logarithmicallyspacedbins spanning a size range specific to each rg value. For all simulations,Δz=1 m, and initial values of relative humidity, air temperatureand pressure are set to RH=0.99, T=10 °C and p=900 hPa,respectively.

Loftus, Adrian M.↗

Identifying Chemical and Optical Smoke Signatures in Suborbital Observations to Improve Model Projections

Biomass Burning (BB) fires are expected to occur more frequently in the future due to climate change, the build‐up of fuels due to fire suppression, and the expansion of the wildland‐urban interface [Schoennagel et al., 2017; Shivdenko & Schepaschenko, 2013; Stevens et al., 2014; Turner et al., 2019; Yue et al., 2015; Tilman et al., 2001]. Accurate knowledge of the abundance, distribution, and optical properties of absorbing aerosols such as BB smoke is essential to understanding regional and global aerosol radiative effects [Boucher et al., 2013]. It is recognized that differing fuel types (e.g., rice straw, ponderosa pine), combustion modes (i.e., flaming, smoldering or both) and temperature/ moisture content produce smoke with differing optical characteristics (e.g., aerosol light scattering and absorption) and component mixing ratios [e.g., BC, OC and inorganic species such as sulfate, potassium, chloride; Streets et al. 2003; Reid et al., 2005a, b; Janhäll et al., 2010; Sayer et al., 2014]. However, climate models often ascribe a fixed set of emission factors [i.e., amount of particulate for a given species released in the atmosphere per unit dry fuel burned; Darmenov and Dasilva, 2013] and optical properties [Hess et al., 1998] to all BB aerosol plumes, inherently limiting accurate representation of the global and regional heterogeneity of BB. The overarching goal of the proposed work is to improve the microphysical and optical representation of different types of Biomass Burning in Chemistry Transport Models. Our strategy is to capitalize on multiple airborne campaigns (e.g., ARCTAS, SEAC4RS, ORACLES, FIREX-AQ), which sampled different types of BB plumes at different aging stages. Models, when improved and combined with satellite, airborne, and ground observations will help address many aerosol science objectives from the NASA Decadal survey [National Academies of Sciences, Engineering, and Medicine. 2018].

Meloe Shenandoah F Kacenelenbogen↗

Examining Weathering of Magnesite in an Arid Environment: Implications For Jezero Crater

Introduction:Orbiter data indicatethe presence of carbonates in severallocations on the surface of Mars[1],but Jezero crater, landing site of the Perseverancerover,is the only known location where carbonatesap-pear coincident with evidence of fluvialand lacustrineactivity [2].On Earth, carbonates in close proximity to these paleoenvironments mayindicatethe presence of past microbial life,like stromatolites[3], that could re-sult inbiosignatures [2]. However,in other cases,car-bonates can also form throughthe alteration of mafic materialwiththe introductionof carbonic acid[4].Hy-drated magnesites have also been found in evaporative environments along lake shores, and in playas[5,6,7].Correctly interpreting past carbonates on Mars is there-fore critical in the search for past signs of life. In Jezero crater,both thenorthernand western fans haveMg-rich carbonates intermixed with olivine-rich material[8].According to CRISM data, magnesite(MgCO3), along with hydromagnesite(Mg5(CO3)4(OH)2•4H2O), arepotential candidatesfor these Mg-carbonates [2]. Considering the spatial con-text with olivine,there aremultiplepotential explana-tions for the presence ofMg-carbonatesin this locationincludingin-situformation via alterationof olivine-rich materialwith carbonic acid,transportationfrom farther up in the watershed, or precipitation of lacustrine car-bonates[2]. The formation of hydromagnesite rather than magnesite is favored when Mg2+saturated solutions have a high CO32-/HCO3-ratio, which, on Earth, is thought to be caused byinflow of groundwater [4]. Additionally, Mg-carbonates tend to precipitate under high pH condi-tions and are unstable at lower pH conditions [5]. Hy-dromagnesite is stable at atmospheric CO2pressure and temperature conditions common to most Earth surface environments [9]. However, it is subject to transfor-mation to magnesite after dehydration and concomitant brucite formation or dissolution and reprecipitation [10].Previousresearch suggests that hydrated car-bonates, including hydromagnesite, can formas weath-ering productsof mafic minerals in the presenceof H2O and CO2in subfreezing temperatures and would not de-hydrate under Martian atmospheric conditions [11,12].It is critical to understand the formation conditions of Mg-carbonatesbecause of the different implications for the past history of Martian environments. Therefore, in this work we are investigating the weathering of Mg-carbonatesin arid environments to helpbetter understand Mg-carbonates in Jezero crater. Study Area:The Ala-Mar Mines(East and West)near Ely, NVare the site ofmultiple magnesitedepositsfound within a calcareous tuff formationthat overlies Tertiary aged volcanic rocks.Here,magnesiteis formed via the alteration of the calcareous tuff and occurs innodules, veins,and lenses[13]. Previous work suggests magnesite deposits are associated with faults [13]. Within the West Mine, magnesite can be found in two maincontexts: (1) relatively circular zones of cauli-flower-like material found within (2) a more massivelensthat is heavily fractured on the surface.Methods.Samplesof both the cauliflower texture and more massive materialwere collectedat Ala Mar West Mine. Both samples were thenpowdered, sieved and analyzed with an inXitu Terra Portable XRD. The program QualX was used to identify potential mineral phases [14].Both samples were also optically inspected using 10x and 20x hand lenses.Figure 1. XRD patterns for the cauliflower magnesite (top) and massive magnesite (bottom). Ongoing and future work on the samples discussed above includes scanning electron microscopy (SEM), electron microprobe analysis (EMPA), and near-infra-red spectroscopy to determine whether hydromagnesite is present. Separation and analysis of the clay-size frac-tionby XRD will helpto better identify any phyllosili-cate phases present. Results and Discussion:Both textures are a white to light tan with a porcelain luster on weathered sur-faces, along with minor iron staining in some areas. Likewise, both textures are white with a porcelain luster on fresh surfaces. When broken apart, the massive mag-nesite shows macroscopic crystals, unlike the cauli-flower magnesite. XRD analysis shows that both samples have high concentrationsof magnesite with lesser amounts of thecarbonatemineral huntite(Mg3Ca(CO3)4; Figure1).The more massive samplecontainsa serpentine-groupmineral,with lizardite being apotential candidate. The cauliflower sample has several minor peaks that may correspond to hydromagnesite(Figure 1), although more work is needed to confirm this.Additionally, thecauliflower deposits closely resemble hydromagnesite deposits found in southwestern Turkey, formed via mi-crobialites[15].As such, it is likely that moreaqueous alterationor weatheringis occurring at the locations where the cauliflower magnesite is present. However, additional field work will need to be conducted to con-firm this hypothesis. Conclusions and Future Work:Future work will include field mapping of fault locations andadditional samplingof the different magnesite types as well as of the calcareous tuffmaterial.We will also look specifi-cally for potential weathering products of magnesite in this arid location, which may yield important insight into the Mg-carbonates located in Jezero crater. XRD analyses on aPANalytical XRDusing non-ambient stages will be used to investigate the stability of hydro-magnesiteat different humiditiesand temperatures, which has implications for samples to bereturned to Earth in the future. Additionally, thermal and evolved gas analysis of magnesite and hydromagnesite will be compared to results from Gale Craterto help interpret the mineralogy inthat location[16]. The results of this research will further ourunderstanding of carbonate for-mationin volcanic settingsandtheirweathering pro-cessesin arid environments. Acknowledgments:We acknowledge funding for this research from Jacobs Technology at the Johnson Space Center.We would also like to thank Ngoc Luu, Christopher Adcock, Richard Allanson, and the rest of the UNLV Soil Science Teamfor their continued sup-portwith troubleshooting and otherlab work. References:[1] Ehlmann, B.L., and Edwards, C.S. (2014) Annual Review of Earth and Planetary Sci., 42, 291–315. [2] Horgan, B.H.N., et al. (2020) Icarus, 339, 113526. [3] Bosak, T., et al. (2013) Annual Review of Earth and Planetary Sci, 41, 21–44. [4] Pohl, W.L. (1989) Gebriider Borntraege, 28, 1-13. [5] Müller, G., et al. (1972) Die Naturwissenschaften, 59, 158–164. [6] Walter, M.R., et al. (1973) Journal of Sedimentary Pe-trology, 43, 1021–1030. [7] Braithwaite, C.J.R., and Zedef, V. (1994) Sedimentary Geology, 92, 1–5. [8] Goudge, T.A., et al. (2015) JGR: Planets, 120, 775–808. [9] Langmuir, D. (1965) Journal of Geology, 73, 730–754. [10] Zhang, P., et al. (2000) Applied Geo-chem., 286, 1748–1753. [11] Calvin, W.M., et al. (1994) JGR, 99, 14659-14675. [12]Russell, M.J., et al. (1999) Journal of the Geological Society of London, v. 156, p. 869–888. [13] Faust, G.T., and Callaghan, E. (1948) GSA Bulletin, 59, 11–74. [14] Altomare, A., et al. (2015) J. of Applied Crystallography, 48, 598–603. [15] Zedef, V.,et al. (2000) Economic Geology, 95, 429–445. [16] Leshin, L.A. et al., (2013) Science, 341, 1–9

A W Provow↗

Editorial: Understanding the Causes of Asymmetries in Earth’S Magnetosphere-Ionosphere System

Geomagnetic activity observed in geospace, the upper atmosphere, and on the ground results from solar-terrestrial interactions. Such interactions correspond to the coupling between the solar wind, magnetosphere, and the thermosphere-ionosphere (MIT) system (Khazanov, 2016). However, given the complexity of the whole system and its large spatial scale and long-term solar variability, effects resulting from this coupling can be asymmetric. For example, inter-hemispherical asymmetric responses can arise when a hemisphere receives more energy than the other (e.g., Knipp et al., 2021; Pakhotin et al., 2021), local time effects can take place due to the occurrence of intense dawn-dusk interplanetary electric fields (e.g.,Haaland et al., 2017), and asymmetric geomagnetic field and mapping are caused by the Earth’s dipole offset and tilt (e.g., Laundal et al., 2017). The drivers that generate asymmetric MIT coupling response are generally recognized as long term: solar activity (Zhang et al., 2022) and dipole offset and tilt (Laundal et al., 2017); middle term: seasons (Lu et al., 2010); and short term: the y and z components of the interplanetary magnetic field (IMF) (Cowley, 1981; Li et al., 2011; Knipp et al., 2021). Thermospheric neutral mass density can present local time asymmetries associated with IMF By (Forster et al., 2017), and inter-hemispheric asymmetries can be generated by cross-hemispheric propagation of large-scale gravity waves (Bruinsma and Forbes, 2007). In addition, forcing from the mesosphere and lower thermosphere can generate inter-hemispheric neutral wind asymmetric patterns that can in turn asymmetrically impact neutral density in different hemispheres (Stober et al., 2021).

magnetosphere-ionophere coupling↗

Exposure of Highly Reflective Far-Ultraviolet Coatings to LEO Environment for TRL Advancement for the Habitable Worlds Observatory

Over the past several years, our team at the NASA Goddard Space Flight Center (GSFC), in collaboration with the Jet Propulsion Laboratory (JPL) and the Naval Research Laboratory (NRL), have developed several new protected Al coating technologies with improved Far-Ultraviolet (FUV) reflectance performance and more robust environmental stability. These include Al protected with lithium-based fluoride (LiF) coatings such as hot deposited LiF (eLiF), XeF 2 -passivated LiF coatings (XeLiF), Li 3 AlF 6 overcoats, AlF 3 (plasma passivated), and XeF 2 passivated MgF 2 coatings (XeMgF 2 ). However, despite these developments, relatively little experimental information exists regarding the long-term stability of these coatings after simultaneous exposure to the Low Earth Orbit (LEO) environment. To evaluate their environmental durability and advance their Technology Readiness Level (TRL), representative samples of these coating technologies, Al+XeLiF, Al+eLiF, Al+Li 3 AlF 6 , Al+AlF 3 , Al+XeMgF 2 , and bare Al as reference samples, were flown onboard the International Space Station (ISS) as part of the Materials International Space Station Experiment 20 (MISSE-20). The MISSE platform is operated by Aegis Aerospace for relatively long-duration (e.g. 6 months) external exposure experiments in a space environment. The coatings were deposited on ULE and Zerodur substrates, and witness samples deposited on the same coatings runs, but on glass slides were left on Earth as control. A subset of the flight samples were fitted with MgF 2 windows to reduce direct exposure to atomic oxygen (AO) and charged particles, and still let through UV and other types of radiation on these samples. After approximately 6 months of exposure in the forward-facing (RAM) direction, the samples were returned to Earth and characterized by performing FUV/NUV/VIS/NIR reflectance measurements to quantify degradation, spectroscopic ellipsometry to evaluate coating thickness and optical constants, atomic force microscopy (AFM) to quantify surface roughness evolution during the flight in the ISS. The MgF 2 protective windows were also analyzed through FUV transmission measurements. Comparison with the witness samples left on the ground and with the flown bare Al samples (with just the naturally occurring Al 2 O 3 layer) provided a quantitative assessment of coating thickness variations, optical performance degradation, and morphological changes induced by prolonged exposure to the LEO environment.

Far Ultraviolet (FUV)↗

Comparison of HITRAN Calculated Spectra with Laboratory Measurements of the 820, 940, 1130, and 1370 nm Water Vapor Bands

Several groups have recently been working to improve the near-infrared spectrum of water vapor on HITRAN. The unit-conversion errors found by Giver, et al have now been corrected on the recently released HITRAN-2000. The most important aspect of this article for atmospheric absorption was increasing all the HITRAN-1996 intensities of the 940 nm band by nearly 15%. New intensity measurements of this band by Brown, et al (submitted to J. Mol. Spec.) have now been included in the latest HITRAN. However, Belmiloud, et al discuss new data in the 633-1175 nm region which they expect will substantially increase the calculated absorption of solar radiation by water vapor. They suggest the 4 bands at 725, 820, 940, and 1130 nm are all stronger than the sum of the line intensities currently on HITRAN. For the 725 and 820 nm bands, their recommended intensity increases are 10% and 15%, about the same as previously noted by Grossmann and Browell and Ponsardin and Browell. Belmiloud, et al only suggest a 6% increase for the 940 nm. band over the corrected HITRAN-1996 intensities, but a large 38% increase for the 1130 nm band. The new data discussed by Belmiloud, et al have now been published in greater detail by Schermaul, et al. The intensity increase for the 1130 nm band discussed by Belmiloud, et al is very substantial; it is important to quickly determine if the HITRAN intensity values are in error by as much as they claim. Only intensity errors for the strong lines could result in the total band intensity being in error by such a large amount. To quickly get a number of spectra of the entire near-infrared region from 650 to 1650 nm, we used the Solar Spectral Flux Radiometer with our 25-meter base path White absorption cell. This moderate resolution spectrometer is a flight instrument that has flown on the Sandia Twin Otter for the ARESE 11 experiment. The measured band profiles were then compared to calculated spectra using the latest HITRAN line intensities, convolved with the instrumental resolution. Our spectra for the 725 and 820 nm bands show somewhat more absorption than the HITRAN simulations, about as expected by Belmiloud, el al. The total absorption for our spectra of the 940 nm band agrees well with the HITRAN simulations; this HITRAN spectral region now has the new measurements of Brown, et al. Our spectra of the 1130 nm band have somewhat more absorption than the HITRAN simulations, but not as much as the 38% intensity increase for this band suggested by Belmiloud, et al. An intensity increase of about 20% on average would be more compatible with our data. Finally, our spectra of the 1370 nm band are fairly well modeled by the HITRAN simulations, despite the known problems of the older HITRAN data in this region.

Giver, Lawrence P.↗

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

Peters-Lidard, Christa D.↗

Saturn's Magnetosphere Interaction with Titan for T9 Encounter: 3D Hybrid Modeling and Comparison with CAPS Observations

Global dynamics of ionized and neutral gases in the environment of Titan plays an important role in the interaction of Saturn s magnetosphere with Titan. Several hybrid simulations of this problem have already been done (Brecht et al., 2000; Kallio et al., 2004; Modolo et al., 2007a; Simon et al., 2007a, 2007b; Modolo and Chanteur, 2008). Observational data from CAPS for the T9 encounter (Sittler et al., 2009) indicates an absence of O(+) heavy ions in the upstream that change the models of interaction which were discussed in current publications (Kallio et al., 2004; Modolo et al., 2007a; Simon et al., 2007a, 2007b; Ma et al., 2007; Szego et al., 2007). Further analysis of the CAPS data shows very low density or even an absence of H(+) ions in upstream. In this paper we discuss two models of the interaction of Saturn s magnetosphere with Titan: (A) high density of H(+) ions in the upstream flow (0.1/cu cm), and (B) low density of H(+) ions in the upstream flow (0.02/cu cm). The hybrid model employs a fluid description for electrons and neutrals, whereas a particle approach is used for ions. We also take into account charge-exchange and photoionization processes and solve self-consistently for electric and magnetic fields. The model atmosphere includes exospheric H(+), H(2+), N(2+)and CH(4+) pickup ion production as well as an immobile background ionosphere and a shell distribution for active ionospheric ions (M(sub i)=28 amu). The hybrid model allows us to account for the realistic anisotropic ion velocity distribution that cannot be done in fluid simulations with isotropic temperatures. Our simulation shows an asymmetry of the ion density distribution and the magnetic field, including the formation of Alfven wing-like structures. The results of the ion dynamics in Titan s environment are compared with Cassini T9 encounter data (CAPS).

Lipatov, A. S.↗

P69 Using the NASA-Unified WRF to Assess the Impacts of Real-Time Vegetation on Simulations of Severe Weather

Since June 2010, the NASA Short-term Prediction Research and Transition (SPoRT; Goodman et al. 2004; Darden et al. 2010; Stano et al. 2012; Fuell et al. 2012) Center has been generating a real-time Normalized Difference Vegetation Index (NDVI) and corresponding Green Vegetation Fraction (GVF) composite based on reflectances from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. This dataset is generated at 0.01 resolution across the Continental United States (CONUS), and updated daily. The goal of producing such a vegetation dataset is to improve over the default climatological GVF dataset in land surface and numerical weather prediction models, in order to have better simulations of heat and moisture exchange between the land surface and the planetary boundary layer. Details on the SPoRT/MODIS vegetation composite algorithm are presented in Case et al. (2011). Vegetation indices such as GVF and Leaf Area Index (LAI) are used by land surface models (LSMs) to represent the horizontal and vertical density of plant vegetation (Gutman and Ignatov 1998), in order to calculate transpiration, interception and radiative shading. Both of these indices are related to the NDVI; however, there is an inherent ambiguity in determining GVF and LAI simultaneously from NDVI, as described in Gutman and Ignatov (1998). One practice is to specify the LAI while allowing the GVF to vary both spatially and temporally, as is done in the Noah LSM (Chen and Dudhia 2001; Ek et al. 2003). Operational versions of Noah within several of the National Centers for Environmental Prediction (NCEP) global and regional modeling systems hold the LAI fixed, while the GVF varies according to a global monthly climatology. This GVF climatology was derived from NDVI data on the NOAA Advanced Very High Resolution Radiometer (AVHRR) polar orbiting satellite, using information from 1985 to 1991 (Gutman and Ignatov 1998; Jiang et al. 2010). Representing data at the mid-point of every month, the climatological dataset is on a grid with 0.144 (~16 km) spatial resolution and is distributed with the community WRF model (Ek et al. 2003; Jiang et al. 2010; Skamarock et al. 2008).

Case, Jonathan L.↗

Emerging and Reemeriging Human Bunyavirus Infections and Climate Change

The Bunyaviridae family includes a growing number of viruses that have contributed to the burden of emerging and reemerging infectious diseases around the globe. Many of these viruses cause severe clinical outcomes in human and animal populations, the results of which can be detrimental to public health and the economies of affected communities. The threat to endemic and non-native regions is particularly high, and national and international public health agencies are often on alert. Many of the bunyaviruses cause severe clinical disease including hemorrhage, organ failure, and death leading to their high-risk classification. Hantaviruses and Rift Valley fever virus (RVFV) (genus Phlebovirus) are National Institute of Allergy and Infectious Diseases Category A priority pathogens in the United States. Viral hemorrhagic fevers, a classification that includes many bunyaviruses, are immediately notifiable in the European Union. The emergence of new and reemerging bunyaviruses has resulted in numerous human and animal fatalities. Outbreaks of Rift Valley fever (RVF) in East Africa (1997/1998, 2006/2007), Sudan (2007), Southern Africa (2008-2010), Kenya (1997/1998, 2006/2007) (Anyamba et al., 2009, 2010; Breiman et al., 2010; Grobbelaar et al., 2011; Woods et al., 2002) and Saudi Arabia & Yemen (2000, 2010) (Food and Agriculture Organization, 2000; Hjelle and Glass, 2000; Madani et al., 2003) and the emergence of Sin Nombre virus (1993) (Hjelle and Glass, 2000) and most recently Schmallenberg virus (2011) (DEFRA, 2012) are prime examples of the devastating and worldwide toll bunyaviruses have on health and economies. Climate variability (precipitation and temperature in particular) greatly influence the ecological conditions that drive arboviral disease outbreaks across the globe. Several human and animal disease outbreaks have been influenced by changes in climate associated with the El Niño Southern Oscillation (ENSO) phenomenon including the bunyaviruses RVFV and Sin Nombre (an etiologic agent of hantavirus pulmonary syndrome (HPS)), as well as Murray Valley encephalitis, chikungunya, and malaria to name but a few (Anyamba et al., 2009; Bouma and Dye, 1997; Chretien et al., 2007; Engelthaler et al., 1999; Kovats et al., 2003; Linthicum et al., 1999; Nicholls, 1986). Most bunyaviruses exhibit episodic outbreak patterns with seasonal or annual trends dependent upon climate conditions, vector abundance, and the proximity of a susceptible population. The implications for continued climate change are dire, especially with regard to vector-borne diseases, many of which can cause severe morbidity, sequelae, and death. Increased rainfall and widening endemicity as a result of climate change, compounded by the emergence of new viruses, poses a serious threat to a greater geographic range beyond the regions of endemicity.

Bunyavirus↗

NASA Child Fitness Promotion Program in Young Children in South Korea

Childhood obesity is a serious global public health concern (WHO, 2015; Wang Y & Lobstein T, 2006). Low self-esteem and related mental health problems are common in obese children (Strauss RS, 2000) as well as poor academic performance and career development (Gurley-Calvez T, 2010).Westernized dietary habits and sedentary lifestyles are identified as the major risk factors of current alarming rate of obesity along with genetic susceptibility (Popkin BM, 1999). Children in many countries, including South Korea, have become increasingly sedentary due to urbanization changes in their respective societies (Ng SW, et al. 2009, Salmon J et al. 2011). In particular, South Korea had abundant dissemination of mobile technology, such as tablet and smart phone devices. Children have become reliant on mobile devices and are less likely to perform physical activities (Do, et al, 2013). Effective and sustainable intervention programs are needed to fight the global obesity epidemic (IOM, 2012; Wang Y et al, 2013; Wang Y et al, 2015). Previous studies suggested focus on prevention strategies that begin in early childhood, a period when children establish their life habits. (Salmon J et al. 2011). Recent systematic reviews and meta-analysis including ours found that obesity prevention programs for young children have a greater intervention effect (Waters E, et al, 2011; Wang Y et al, 2013; Wang Y et al, 2015). The NASA Mission X: Train Like an Astronaut (MX) program was developed to promote children's exercise and healthy eating with excitement for training like an astronaut (Lloyd C, 2012).At present, the NASA MX Program covered 28 countries, enrolled children through their teachers in school setting (MX report 2014, 2015). This pilot study adapted the NASA MX intervention program for young children in South Korea. We assessed its feasibility and effectiveness in promoting physical activity (PA) in children and in improving parents' perspectives. We also examined the status of PA in young children. More than 80% of five-year-old children go to a Kindergarten or day care center in South Korea (MH Suh et al, 2013).Thus, reaching young children through child care and education settings could be a good approach for early childhood obesity prevention.

Min, Jungwon↗

Recent Variability Observations of Solar System Giant Planets: Fresh Context for Understanding Exoplanet and Brown Dwarf Weather

Over the past several years a number of high cadence photometric observations of solar system giant planets have been acquired by various platforms. Such observations are of interest as they provide points of comparison to the already expansive set of brown dwarf variability observations and the small, but growing, set of exoplanet variability observations. By measuring how rapidly the integrated light from solar system giant planets can evolve, variability observations of substellar objects that are unlikely to ever be resolved can be placed in a fuller context. Examples of brown dwarf variability observations include extensive work from the ground (e.g., Radigen et al. 2014), Spitzer (e.g., Metchev et al. 2015), Kepler (Gizis et al. 2015), and HST (Yang et al. 2015).Variability has been measured on the planetary mass companion to the brown dwarf 2MASS 1207b (Zhou et al. 2016) and further searches are planned in thermal emission for the known directly imaged planets with ground based telescopes (Apai et al. 2016) and in reflected light with future space based telescopes. Recent solar system variability observations include Kepler monitoring of Neptune (Simon et al. 2016) and Uranus, Spitzer observations of Neptune (Stauffer et al. 2016), and Cassini observations of Jupiter (West et al. in prep). The Cassini observations are of particular interest as they measured the variability of Jupiter at a phase angle of approximately 60 deg, comparable to the viewing geometry expected for space based direct imaging of cool extrasolar Jupiters in reflected light. These solar system analog observations capture many of the characteristics seen in brown dwarf variability, including large amplitudes and rapid light curve evolution on timescales as short as a few rotation periods. Simon et al. (2016) attribute such variations at Neptune to a combination of large scale, stable cloud structures along with smaller, more rapidly varying, cloud patches. The observed brown dwarf and exoplanet variability may well arise from comparable cloud structures. In my presentation I will compare and contrast the nature of the variability observed for the various solar system and other substelar objects and present a wish list for future observations.

giant planets↗

Chemical, Structural, and Microstructural Changes in Metallic and Silicon-Based Coating Materials Exposed to Iodine Vapor

The chemical, structural and microstructural behavior of steels (304, 316 and A36), titanium-aluminum alloy (Ti-Al, (6Al-4V)), aluminum-magnesium alloy (Al-Mg, 6061), and coatings (Silcolloy and Dursan (SilcoTek Corporation)) were probed after exposure to iodine laminar flow. Exposures were carried out in a custom-built Iodine Vapor RIG (IVR) at 300 degrees C to an iodine laminar vapor flow of 1 mg min(exp. -1), carried by 145 mL-min(exp. -1) argon gas, for 5, 15 and 30 days. Samples were characterized before and after the experiment by gravimetric analysis, X-ray diffraction (XRD) and cross section electron microscopy analysis coupled with energy dispersive X-ray spectroscopy (EDS). All steels exposed for 30 days formed scales consisting mainly of metal (Cr, Fe, Ni) oxides showing different chemistry, microstructure and crystalline phases. Elemental iodine was only detected by EDS analysis in the scales of stainless steels 304 and 316. After 30 days, the Ti-Al exhibited no detectable scale, suggesting only a very thin film was formed. A scale consisting mainly of aluminum, iodine, and oxygen formed on the Al-Mg sample exposed to 30 days. Some pockets rich in magnesium, iodine and oxygen also formed in this Al-Mg alloy. Stainless steel 316, low carbon steel A36 and Ti-Al alloy coated with Silcolloy and stainless steel 304 coated with Dursan that were exposed for 30 days exhibited no oxidation. Stainless steel 304 coated with Silcolloy exposed for 30 days did not exhibit corrosion although the sample gained weight and the coating exhibited expansion. The weight gain per area performance of the materials exposed in iodine lamina flow containing oxygen at impurity level for 10, 15 and 30 days are reported from the lowest to the highest weight gain per area as follows: Steels: Less than 316 less than 304 less than A36; Ti-Al-Mg based alloys: Al-Mg less than Ti-Al: Considering the experimental uncertainties, no weight change was observed for Stainless steel 316, low carbon steel A36 and Ti-Al alloy coated with Silcolloy and stainless steel 304 coated with Dursan. The corrosion of the alloys is catalyzed by iodine in the presence of oxygen as impurity.

Costa, Gustavo C. C.↗

Electron Bombardment on Dione: Surface Compositional Effects and Temperature Abnormalities

Saturn’s icy moons are composed primarily of water ice with minor other “contaminants,” such as CO2 ice, and a dark component thought to be organics, hematite and/or metallic Fe [1]. The space weathering process of electron bombardment is expected to be particularly important on the surfaces of Saturn’s inner moons (Mimas, Tethys, Dione, and Rhea), as they orbit within Saturn’s inner magnetosphere. Terrains exhibiting thermal anomalies (i.e., colder temperatures in the day and warmer temperatures at night than surrounding areas) correspond to regions of high energy electron bombardment [2; 3; 4; 5]. Energetic electrons impact the surfaces, sintering ice grains together, and this process becomes more effective for increasing particle energies [6]. Solar UV radiation, cosmic rays, dust in-fall, and cold plasma particles trapped in Saturn’s magnetic field also play an important role in altering the nature and the structure of the native surface ices by the implantation of contaminants, ionization, sputtering, and dissociation of water ice molecules [7]. Additionally, CO2 could be sourced from irradiation of dark organic material [8]. Many of these surface alterations are observable in Cassini’s Visible and Infrared Mapping Spectrometer (VIMS) spectra [9]. We used similar methodologies as have been employed in previous works [e.g., 10] to derive surface temperatures from Cassini’s Composite Infrared Spectrometer (CIRS), which helped to isolate areas where space weathering due to electron bombardment is more predominant. The subtle changes in VIMS spectra were investigated using machine learning techniques. We present here our results for Dione. [1] Clark, R. N., et al. (2012) Icarus, 218, 831–860 [2] Howett, C. J. A., et al. (2020) Icarus, 113745 [3] Nordheim, T. A., et al. (2017) Icarus, 286, 56-68 [4] Paranicas, C., et al. (2012) Planetary and Space Science, 61, 60–65 [5] Paranicas, C., et al. (2014) Icarus, 234, 155–161 [6] Schaible, M. J., et al. (2016) Icarus, 0, 1–13 [7] Baragiola, R. A., et al., (2013) Astrophysics and Space Science Library, vol. 356. Springer [8] Mennella, V., et al. (2006) The Astrophysical Journal, 643(2), 923 [9] Scipioni, F., et al. (2017) Icarus, 290, 183-200 [10] Howett, C. J. A., et al. (2014) Icarus, 241, 239-247

C L Young↗

VALENTInE: A Concept for a New Frontiers Class Long Duration In-Situ Balloon Mission to Venus

Venus and Earth are similar in bulk composition, size, density, and approximate distance from the Sun, yet Venus’s modern-day climate and surface geology is distinctly different [1]. Previous missions to Venus revealed unusual volcanic features, possible continental crust, widespread volcanic plains, a weak magnetic field [2], and insights into the Venusian atmosphere [3,4]. Unfortunately, data from these missions were limited in spatial and temporal resolution and global extent. A future mission to Venus is critical to address fundamental questions surrounding the chemical composition and dynamics of the Venusian atmosphere [5], its geologic history [6,7], its internal structure [8,9], and its habitability throughout time [10,11]. We present the Venus Air and Land Expedition: a Novel Trailblazer for In situ Exploration (VALENTInE) mission to meet this need. VALENTInE is a variable altitude balloon that will passively float in Venus’s atmosphere between 45 and 55 km altitude. VALENTInE will acquire atmospheric data at varying latitudes and longitudes in addition to mapping the surface geomorphology and mineralogy across multiple terrains. Mission Objectives: The VALENTInE mission concept is driven by four main science objectives: 1. Determine whether the driving force of the superrotation of Venus’s atmosphere is caused by horizontal or vertical momentum transport. 2. Determine whether the atmospheric composition and noble gas inventory of the Venusian atmosphere is a product of outgassing from the initial protoplanetary source or if there are significant contributions from exogenic sources. 3. Determine whether the tesserae regions (particularly Aphrodite Terra) are felsic and relatively older than surrounding regions. 4. Determine if there is any evidence of a recent dynamo preserved in the rock record of Venus. Mission Overview: A balloon architecture provides a robust system that can survive long-term in the Venusian environment while taking accurate measurements of the lower cloud deck and surface. Two prior balloon missions to Venus, VEGA 1 and VEGA 2 in 1984, have demonstrated the potential for such planetary exploration; however, these missions were short-lived (46 hr), with limited range (54 km). Our spacecraft concept consists of a battery powered balloon with a gondola and flyby carrier stage (Fig. 1). Our novel design allows for at least 15 days of atmospheric exploration, including multiple ascents and descents in the Venus atmosphere. VALENTInE is baselined to launch in 2032, cruise on solar power for 128 days, enter, descend, and inflate (EDI) into Venus’s atmosphere above Aphrodite Terra, and float in Venus’s atmosphere for a total nominal mission duration of 15 days. The balloon, able to control its altitude by changing its buoyancy, will make one full circumnavigation every 4–8 days and move poleward ~1 o latitude per day; it will be passively directed by the horizontal air currents on Venus. The balloon can only be controlled in the z direction, and the expected latitude range is ±10° from EDI. The balloon itself will be a tracer for atmospheric structures such as zonal winds [5, 12]. During the 15-day operational period, there will be five dips to 45 km for a compositional study of the lower atmosphere and geological and magnetic mapping of the surface. Dips are used to take images and measurements closer to the surface and to obtain in situ vertical atmospheric profiles between 45 and 55 km. Instruments: The VALENTInE instrument payload will allow for extensive study of the geology, atmosphere, and interior of Venus. The instrument suite consists of six instruments. The mission profile for each instrument is shown in Fig. 2. Lower Atmosphere Meteorology Analyzer (LAMA) is an atmospheric structure instrument consisting of a thermometer, barometer, and accelerometer to continuously measure temperature and pressure as a function of altitude, longitude, and latitude. TracE and Noble Gas Investigator (TENGI) is aneutral mass spectrometer used to sample the dense atmosphere. TENGI will operate continuously at 45 km and 55 km and will measure D/H ratios, as well as Ne, Ar, and O isotopic ratios. Kilometer Scale Spectral Imager (KSSI) is amultispectral imager (850-1150 nm) used to resolve surface features on the order of km. Near InfraRed Multispectral Photometer (NIRMP) is an Infrared (IR) photometer used to image the surface through the clouds to characterize mineral assemblages at five different areas of the surface. NIRMP will be operated during dwell. ELevation REConnaissance (ELREC) is a light detection and ranging (LIDAR) instrument used for measuring topography at five different areas of the surface. The ELREC data will be combined with those of NIRMP to determine mineral assemblages and how they correlate to topography. Magnetic Exploration and Interior Detective (MEID) is a magnetometer used to detect any near-surface magnetic anomalies. The magnetometer will continuously operate at all altitudes. Mission Design: The spacecraft’s propulsion system will have a wet mass of 930 kg and will be launched on an Atlas V rocket. The spacecraft will jettison the payload upon arrival in Venus’s atmosphere before decelerating to orbital velocity. Figure 2. Notional power-dip profile while the balloon is on the dayside. Risks and Challenges: Raising and lowering the spacecraft to dip beneath the haze layer require a large amount of energy. This issue was partly compensated by limiting the number of dips over the 15 day prime mission. Power needs for pumping helium are reduced by slowing the descent speed, which consequently increases spatial resolution of in situ measurements between 45 and 55 km. The main limitation for the duration of the mission is the need to carry 15 days’ worth of batteries. The bus experiences external Venusian temperatures ranging from ~27°C at 55 km altitude to ~110°C at 45 km altitude. These high atmospheric temperatures require thermal protection for the bus (instruments, electronics, and flight systems) during its descent, dwell at 45 km, and ascent. The bus is maintained at a mechanically safe temperature range of -10°C to 50°C using white external paint, multi-layer insulation (MLI), mechanical/thermal isolation (e.g. Ti, composites), and ~57 kg of Phase Change Materials (PCM). Images and spectra taken below the haze dominate the available data transmission regardless of the time spent at 45 km. Therefore, less time at the lower altitude mainly reduces the coverage of in situ measurements there. Further, we assumed an unrealistically low-density material for the helium storage tanks on the gondola. However, this issue is partially resolved if we were to jettison 75% of the spent helium storage tanks. After the entry process, the balloon volume remains mostly inflated and storage tanks are required only for reducing balloon volume in dipping to 45 km. This mission was planned against an expected New Frontiers 5 (NF5) cost cap of $1B, as the NF5 call had not yet been released. The mission we describe fits within the predicted cost cap if the flyby carrier stage, responsible for powering the spacecraft during cruise and for relaying in situ measurements back to Earth, can be contributed by another space agency. Acknowledgments: We thank the JPL Planetary Science Summer School, especially A. Nash, J. Scully, K. Mitchell, L. Lowes, and J. Armijo, and our mentors from JPL Team X. Thank you to our review panel for their insightful review. References: [1] Kane, S. et al. (2019) JGR:Ps, 124 , 2015–2028. [2] Phillips, J. L., & Russell, C. T. (1987). JGR: Space Physics , 92 (A3), 2253-2263. [3] Nakamura, M. et al. (2018) Earth Planets Space, 70 (1), 144. [4] Svedhem, H. et al. (2009) JGR:P 114 (E5). [5] Limaye et al. (2009) Decadal Survey White Paper . [6] Ivanov, M. and Head, J. (2011) PSS, 59 (13) , 1559-1600. [7] Smrekar, S. et al. (2018) Space Sci Rev, 214 (5), 88. [8] O’Rourke, J. et al. (2018) EPSL, 502 , 46-56. [9] O’Rourke J. et al. (2019) GRL , (46), 5768–5777 [10] Way, M. et al. (2016) GRL, 43 (16), 8376-8383. [11] Way, M. et al. (2020) JGR:P, 125 (5), e2019JE006276. [12] Preston, R. A. et al. (1986) Science, 231 (4744), 1414-1416.

Mission Concept↗