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Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

simulation↗

Pale Blue Dot Explorer: A Case for Adding Earth to the Planetary Sciences List of Targets

Obtaining observational data to inform the science of future missions focused on Earth-like exoplanets is of prime importance for NASA Planetary Science and Astrobiology. However, Earth observations as a proxy for an exoplanet is an area of interdivisional research not well captured by existing NASA programs. To accommodate this, we propose adding Earth to the list of planets allowable by NASA Planetary Science Division’s objectives and adding Earth observation to the cruise phase of planetary probes. A specific research investigation would be a spacecraft whose goal would be to characterize Earth as an exoplanet proxy — a Pale Blue Dot Explorer. Such a mission’s objective would be to monitor the habitability and biological signatures of Earth in reflected light over broad wavelengths and phase angles.

Sanjoy M. Som↗

On the Physical Nature of the So-Called Prominence Tornadoes

The term ‘tornado’ has been used in recent years to describe several solar phenomena, from large-scale eruptive prominences to small-scale photospheric vortices. It has also been applied to the generally stable quiescent prominences, sparking a renewed interest in what historically was called ‘prominence tornadoes’. This paper carries out an in-depth review of the physical nature of ‘prominence tornadoes’, where their name subconsciously makes us think of violent rotational dynamics. However, after careful consideration and analysis of the published observational data and theoretical models, we conclude that ‘prominence tornadoes’ do not differ in any substantial way from other stable solar prominences. There is simply no unequivocal observational evidence of sustained and coherent rotational movements in quiescent prominences that would justify a distinct category of prominences sharing the name with the well-known atmospheric phenomenon. The visual impression of the column-like silhouettes, the perceived helical motions, or the suggestive Doppler-shift patterns all have a simpler, more likely explanation. They are a consequence of projection effects combined with the presence of oscillations and/or counter-streaming flows. ‘Prominence tornadoes’ are thus just manifestations of the complex nature of solar prominences when observed in specific projections. These coincidental viewing angles, together with the presence of fine-structure dynamics and simple yet profoundly distorting projection effects, may sometimes play havoc with our intuitive understanding of perceived shapes and motions, leading to the incorrect analogy with atmospheric tornadoes.

Stanislav Gunar↗

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.↗

Using Hyperspectral Imagery to Identify Turfgrass Stresses

The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or subjected to a variety of controlled stresses were observed by use of a hand-held spectroradiometer. The spectroradiometer readings in the wavelength range from 350 to 1,000 nm were processed to extract hyperspectral reflectance data, which, in turn, were analyzed to find correlations with the controlled stresses. Several indices were found to be correlated with drought stress and to be potentially useful for identifying drought stress before visible symptoms appear.

Hutto, Kendall↗

Insights from the APOKASC determination of the evolutionary state of red-giant stars by consolidation of different methods

ABSTRACT The internal working of low-mass stars is of great significance to both the study of stellar structure and the history of the Milky Way. Asteroseismology has the power to directly sense the internal structure of stars and allows for the determination of the evolutionary state – i.e. has helium burning commenced or is the energy generated only by the fusion in the hydrogen-burning shell? We use observational data from red-giant stars in a combination (known as APOKASC) of asteroseismology (from the Kepler mission) and spectroscopy (from SDSS/APOGEE). The new feature of the analysis is that the APOKASC evolutionary state determination is based on the comparison of diverse approaches to the investigation of the frequency-power spectrum. The high level of agreement between the methods is a strong validation of the approaches. Stars for which there is not a consensus view are readily identified. The comparison also facilitates the identification of unusual stars including those that show evidence for very strong coupling between p and g cavities. The comparison between the classification based on the spectroscopic data and asteroseismic data have led to a new value for the statistical uncertainty in APOGEE temperatures. These consensus evolutionary states will be used as an input for methods that derive masses and ages for these stars based on comparison of observables with stellar evolutionary models (‘grid-based modelling’) and as a training set for machine-learning and other data-driven methods of evolutionary state determination.

Elsworth, Yvonne↗

Do Citizen Science Intense Observation Periods Increase Data Usability? A Deep Dive of the NASA GLOBE Clouds Data Set With Satellite Comparisons

The Global Learning and Observations to Benefit the Environment (GLOBE) citizen science program has recently conducted a series of month-long intensive observation periods (IOPs), asking the public to submit daily reports on cloud and sky conditions from all regions of Earth. This provides a wealth of crowdsourced observations from the ground, which complements other conventional scientific cloud data. In addition, the GLOBE reports are matched in space and time with geostationary and low Earth orbit satellites, which allows for a straightforward comparison of cloud properties, and minimizes the biases associated with mismatched sampling between participants and satellites. The matched GLOBE dataset is used to calculate the mean observed cloud cover by atmospheric level both worldwide and by region. The overall magnitudes of cloud cover between the GLOBE participants and the matched satellites agree within 10%, which is notable given the distinctly different natures of the data sources. The mean vertical cloud profiles show GLOBE reporting more low-level clouds and fewer high-level clouds than satellites. The low cloud disagreement is likely related to satellites missing low clouds when high clouds block their view. Conversely, the high cloud disagreement is related primarily to cloud opacity, as satellites may miss some optically thin clouds. Monte Carlo testing shows the results to be robust, and the tripled amount of IOP data reduces uncertainty by half. These findings also highlight ways in which citizen science IOP data may be used to support scientific research while accounting for their unique properties. Plain Language Summary: Citizen science is becoming an increasingly prominent aspect of scientific research, and so it important to study how citizen science data can be used effectively. For example, The GLOBE Program has recently conducted a series of special data-collecting events, or “challenges”, which gathered large numbers of reports on cloud and sky conditions. Because NASA GLOBE Clouds matches the participant reports with cloud observations from satellites, we can use these data to get a combined view of clouds from above and below. When looking at the average cloud cover for different atmospheric levels across Earth, we find that the GLOBE participants and the satellites agree quite closely. This is a surprising and fascinating find, given how different in nature volunteer ground reports are to satellite measurements. However, there are some small but notable disagreements between GLOBE participants and satellites about the distribution of cloud cover at different levels. In addition, by testing the data for uncertainty, we show that the results from the GLOBE data are reliable, and that more public participation improves the reliability. So, by carefully designing the analysis methodology, and by testing for the uncertainty of the data, citizen science can make a meaningful contribution to scientific research.

J. Brant Dodson↗

Shoemaker-Levy 9 and Plume-Forming Collisions on Earth

Computational models for the July, 1994 collision of comet Shoemaker Levy 9 with Jupiter have provided a framework for interpreting the observational data. Imaging, photometry, and spectroscopy data from ground-based, Hubble Space Telescope, and Galileo spacecraft instruments are consistent with phenomena that were dominated by the generation of incandescent fireballs that were ballistically ejected to high altitudes, where they formed plumes that subsequently collapsed over large areas of Jupiter's atmosphere. Applications of similar computational models to collisions into Earth's atmosphere show that a very similar sequence of events should take place for NEO impacts with energies as low as 3 megatons, recurring on 100 year timescales or less. This result suggests that the 1908 Tunguska event was a plume-forming atmospheric explosion, and that some of the phenomena associated with it might be related to the ejection and collapse of a high plume. Hazards associated with plume growth and collapse should be included in the evaluation of the impact threat to Earth, and opportunities should be sought for observational validation of atmospheric impact models by exploiting data already being collected from the natural flux of multikiloton to megaton sized objects that constantly enter Earth's atmosphere on annual to decadal timescales.

Boslough, Mark B. E.↗

Common Envelope Light Curves. I. Grid-code Module Calibration

The common envelope (CE) binary interaction occurs when a star transfers mass onto a companion that cannot fully accrete it. The interaction can lead to a merger of the two objects or to a close binary. The CE interaction is the gateway of all evolved compact binaries, all stellar mergers, and likely many of the stellar transients witnessed to date. CE simulations are needed to understand this interaction and to interpret stars and binaries thought to be the byproduct of this stage. At this time, simulations are unable to reproduce the few observational data available and several ideas have been put forward to address their shortcomings. The need for more definitive simulation validation is pressing and is already being fulfilled by observations from time-domain surveys. In this article, we present an initial method and its implementation for post-processing grid-based CE simulations to produce the light curve so as to compare simulations with upcoming observations. Here we implemented a zeroth order method to calculate the light emitted from CE hydrodynamic simulations carried out with the 3D hydrodynamic code Enzo used in unigrid mode. The code implements an approach for the computation of luminosity in both optically thick and optically thin regimes and is tested using the first 135 days of the CE simulation of Passy et al., where a 0.8 M {sub ⊙} red giant branch star interacts with a 0.6 M {sub ⊙} companion. This code is used to highlight two large obstacles that need to be overcome before realistic light curves can be calculated. We explain the nature of these problems and the attempted solutions and approximations in full detail to enable the next step to be identified and implemented. We also discuss our simulation in relation to recent data of transients identified as CE interactions.

79 ASTRONOMY AND ASTROPHYSICS↗

Search for boosted low-mass resonances decaying into hadrons produced in association with a photon in pp collisions at $ \sqrt{s}$ = 13 TeV with the ATLAS detector

Many extensions of the Standard Model, including those with dark matter particles, propose new mediator particles that decay into hadrons. This paper presents a search for such low mass narrow resonances decaying into hadrons using 140 fb −1 of proton-proton collision data recorded with the ATLAS detector at a centre-of-mass energy of 13 TeV. The resonances are searched for in the invariant mass spectrum of large-radius jets with two-pronged substructure that are recoiling against an energetic photon from initial state radiation, which is used as a trigger to circumvent limitations on the maximum data recording rate. This technique enables the search for boosted hadronically decaying resonances in the mass range 20–100 GeV hitherto unprobed by the ATLAS Collaboration. The observed data are found to agree with Standard Model predictions and 95% confidence level upper limits are set on the coupling of a hypothetical new spin-1 Z′ resonance with Standard Model quarks as a function of the assumed Z′-boson mass in the range between 20 and 200 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

End-to-End Differentiable Modeling and Management of the Environment

Focal Area: (2) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization. We emphasize the importance of leveraging optimization techniques from AI/machine learning (ML) to solve challenging problems in Earth system modeling. Science Challenge: Automatic differentiation has had a transformative effect on ML by allowing the calculation of gradients of arbitrary functions in an incredibly large class of models. We can potentially realize similar improvements in parameter estimation and control for Earth system models (ESMs) by reimplementing them in computational frameworks from ML. Practitioners working with large (>10 7 parameters) models in ML and AI can obtain good predictive performance in a range of spatiotemporal tasks by making use of optimization via stochastic gradient descent and incorporating prior knowledge at multiple levels. We propose writing ESMs in open-source computational frameworks such as Torch, Tensorflow, and JAX to greatly expand the scope of environmental forecasting and management challenges, which can be addressed by leveraging automatic differentiation and gradient descent-like algorithms. We do not call for a wholesale replacement of physical models with data-driven surrogates, but rather advocate for interleaving physical and empirical equations in a manner that is most faithful to the extent of our scientific knowledge and observational data. Central to this topic is the merging of differentiable physical simulations with differentiable optimization layers, which are now both beginning to come to the forefront.

54 ENVIRONMENTAL SCIENCES↗

Gas Removal in the Ursa Minor Galaxy: Linking Hydrodynamics and Chemical Evolution Models

We present results from a non-cosmological, three-dimensional hydrodynamical simulation of the gas in the dwarf spheroidal galaxy Ursa Minor. Assuming an initial baryonic-to-dark-matter ratio derived from the cosmic microwave background radiation, we evolved the galactic gas distribution over 3 Gyr, taking into account the effects of the types Ia and II supernovae. For the first time, we used in our simulation the instantaneous supernovae rates derived from a chemical evolution model applied to spectroscopic observational data of Ursa Minor. We show that the amount of gas that is lost in this process is variable with time and radius, being the highest rates observed during the initial 600 Myr in our simulation. Our results indicate that types Ia and II supernovae must be essential drivers of the gas loss in Ursa Minor galaxy (and probably in other similar dwarf galaxies), but it is ultimately the combination of galactic winds powered by these supernovae and environmental effects (e.g., ram-pressure stripping) that results in the complete removal of the gas content.

79 ASTRONOMY AND ASTROPHYSICS↗

Photoionization Emission Models for the Cyg X-3 X-Ray Spectrum

We present model fits to the X-ray line spectrum of the well-known high-mass X-ray binary Cyg X-3. The primary observational data set is a spectrum taken with the Chandra X-ray Observatory High Energy Transmission Grating in 2006, though we compare it to all the other observations of this source taken so far by this instrument. We show that the density must be ≥10 12 cm –3 in the region responsible for most of the emission. We discuss the influence of the dust scattering halo on the broadband spectrum, and we argue that dust scattering and extinction is not the most likely origin for the narrow feature seen near the Si K edge. We identify the features of a wind in the profiles of the strong resonance lines and show that the wind is more apparent in the lines from the lighter elements. We argue that this wind is most likely associated with the companion star. We show that the intensities of most lines can be fitted, crudely, by a single-component photoionized model. Yet, the iron K lines do not fit with this model. We show that the iron K line variability as a function of orbital phase is different from the lower-energy lines, which indicates that the lines arise in physically distinct regions. We discuss the interpretation of these results in the context of what is known about the system and similar systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Geometric adjustment of the South American satellite densification (PC-1000) network

Reduced normal equations were computed from observation data and combined with reduced normal equations of other satellite networks to provide station coordinates from a single least square adjustment. Terrestrial data, which include base-lines, heights, and survey coordinates, provide the necessary relative position constraints between collocated stations of two satellite networks. Survey information regarding the observation stations is summarized, and constraints used in the solution are given. Geoidal undulations are computed by using the formula and constants shown.

Mueller, I. I.↗

Reconstruction of an infrared band of meteorological satellite imagery with abductive networks

As the current fleet of meteorological satellites age, the accuracy of the imagery sensed on a spectral channel of the image scanning system is continually and progressively degraded by noise. In time, that data may even become unusable. We describe a novel approach to the reconstruction of the noisy satellite imagery according to empirical functional relationships that tie the spectral channels together. Abductive networks are applied to automatically learn the empirical functional relationships between the data sensed on the other spectral channels to calculate the data that should have been sensed on the corrupted channel. Using imagery unaffected by noise, it is demonstrated that abductive networks correctly predict the noise-free observed data.

Singer, Harvey A.↗

Big bang nucleosynthesis: The standard model and alternatives

Big bang nucleosynthesis provides (with the microwave background radiation) one of the two quantitative experimental tests of the big bang cosmological model. This paper reviews the standard homogeneous-isotropic calculation and shows how it fits the light element abundances ranging from He-4 at 24% by mass through H-2 and He-3 at parts in 10(exp 5) down to Li-7 at parts in 10(exp 10). Furthermore, the recent large electron positron (LEP) (and the stanford linear collider (SLC)) results on the number of neutrinos are discussed as a positive laboratory test of the standard scenario. Discussion is presented on the improved observational data as well as the improved neutron lifetime data. Alternate scenarios of decaying matter or of quark-hadron induced inhomogeneities are discussed. It is shown that when these scenarios are made to fit the observed abundances accurately, the resulting conlusions on the baryonic density relative to the critical density, omega(sub b) remain approximately the same as in the standard homogeneous case, thus, adding to the robustness of the conclusion that omega(sub b) approximately equals 0.06. This latter point is the driving force behind the need for non-baryonic dark matter (assuming omega(sub total) = 1) and the need for dark baryonic matter, since omega(sub visible) is less than omega(sub b).

Schramm, David N.↗

TOPEX/POSEIDON tides estimated using a global inverse model

Altimetric data from the TOPEX/POSEIDON mission will be used for studies of global ocean circulation and marine geophysics. However, it is first necessary to remove the ocean tides, which are aliased in the raw data. The tides are constrained by the two distinct types of information: the hydrodynamic equations which the tidal fields of elevations and velocities must satisfy, and direct observational data from tide gauges and satellite altimetry. Here we develop and apply a generalized inverse method, which allows us to combine rationally all of this information into global tidal fields best fitting both the data and the dynamics, in a least squares sense. The resulting inverse solution is a sum of the direct solution to the astronomically forced Laplace tidal equations and a linear combination of the representers for the data functionals. The representer functions (one for each datum) are determined by the dynamical equations, and by our prior estimates of the statistics or errors in these equations. Our major task is a direct numerical calculation of these representers. This task is computationally intensive, but well suited to massively parallel processing. By calculating the representers we reduce the full (infinite dimensional) problem to a relatively low-dimensional problem at the outset, allowing full control over the conditioning and hence the stability of the inverse solution. With the representers calculated we can easily update our model as additional TOPEX/POSEIDON data become available. As an initial illustration we invert harmonic constants from a set of 80 open-ocean tide gauges. We then present a practical scheme for direct inversion of TOPEX/POSEIDON crossover data. We apply this method to 38 cycles of geophysical data records (GDR) data, computing preliminary global estimates of the four principal tidal constituents, M(sub 2), S(sub 2), K(sub 1) and O(sub 1). The inverse solution yields tidal fields which are simultaneously smoother, and in better agreement with altimetric and ground truth data, than previously proposed tidal models. Relative to the 'default' tidal corrections provided with the TOPEX/POSEIDON GDR, the inverse solution reduces crossover difference variances significantly (approximately 20-30%), even though only a small number of free parameters (approximately equal to 1000) are actually fit to the crossover data.

Egbert, Gary D.↗

Survey of Pancake-Shaped Warm Ion Distributions at Geosynchronous Orbit

It has been proposed that the electromagnetic proton cyclotron instability is a strong source of heating for the anisotropic warm ions observed at geosynchronous orbit. We present here the results of a statistical study of pancake-shaped warm ion distributions, using a one-year interval of data observed with the Los Alamos magnetospheric plasma analyzer (MPA) on the geosynchronous satellite 1994-084. Our results support previous findings that pancake-shaped warm ion distributions occur more frequently on the dayside of the magnetosphere and under magnetically quiet conditions. We also confirm that the electromagnetic proton cyclotron instability is operating and is constraining the hot proton temperature anisotropy. However, our results indicate that the pancake-shaped warm ion distributions observed at geosynchronous orbit are probably not generated by this instability but must be due to a different mechanism, possibly to heating by lower hybrid waves.

Ober, Daniel↗