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CFD flowfield simulation of Delta Launch Vehicles in a power-on configuration

This paper summarizes recent work at McDonnell Douglas Aerospace (MDA) to develop and validate computational fluid dynamic (CFD) simulations of under expanded rocket plume external flowfields for multibody expendable launch vehicles (ELVs). Multi engine reacting gas flowfield predictions of ELV base pressures are needed to define vehicle base drag and base heating rates for sizing external nozzle and base region insulation thicknesses. Previous ELV design programs used expensive multibody power-on wind tunnel tests that employed chamber/nozzle injected high pressure cold or hot-air. Base heating and pressure measurements were belatedly made during the first flights of past ELV's to correct estimates from semi-empirical engineering models or scale model tests. Presently, CFD methods for use in ELV design are being jointly developed at the Space Transportation Division (MDA-STD) and New Aircraft Missiles Division (MDA-NAMD). An explicit three dimensional, zonal, finite-volume, full Navier-Stokes (FNS) solver with finite rate hydrocarbon/air and aluminum combustion kinetics was developed to accurately compute ELV power-on flowfields. Mississippi State University's GENIE++ general purpose interactive grid generation code was chosen to create zonal, finite volume viscous grids. Axisymmetric, time dependent, turbulent CFD simulations of a Delta DSV-2A vehicle with a MB-3 liquid main engine burning RJ-1/LOX were first completed. Hydrocarbon chemical kinetics and a k-epsilon turbulence model were employed and predictions were validated with flight measurements of base pressure and temperature. Zonal internal/external grids were created for a Delta DSV-2C vehicle with a MB-3 and three Castor-1 solid motors burning and a Delta-2 with an RS-27 main engine (LOX/RP-1) and 9 GEM's attached/6 burning. Cold air, time dependent FNS calculations were performed for DSV-2C during 1992. Single phase simulations that employ finite rate hydrocarbon and aluminum (solid fuel) combustion chemistry are currently in progress. Reliable and efficient Eulerian algorithms are needed to model two phase (solid-gas) momentum and energy transfer mechanisms for solid motor fuel combustion products.

Pavish, D. L.↗

Crystallization of amorphous water ice in the solar system

Electron diffraction studies of vapor-deposited water ice have characterized the dynamical structural changes during crystallization that affect volatile retention in cometary materials. Crystallization is found to occur by nucleation of small domains, while leaving a significant part of the amorphous material in a slightly more relaxed amorphous state that coexists metastably with cubic crystalline ice. The onset of the amorphous relaxation is prior to crystallization and coincides with the glass transition. Above the glass transition temperature, the crystallization kinetics are consistent with the amorphous solid becoming a "strong" viscous liquid. The amorphous component can effectively retain volatiles during crystallization if the volatile concentration is approximately 10% or less. For higher initial impurity concentrations, a significant amount of impurities is released during crystallization, probably because the impurities are trapped on the surfaces of micropores. A model for crystallization over long timescales is described that can be applied to a wide range of impure water ices under typical astrophysical conditions if the fragility factor D, which describes the viscosity behavior, can be estimated.

NASA Center ARC↗

Coupling of Dust Mineralogy to Radiation in NASA GISS ModelE: Impact Upon Dust Optical Properties and Direct Radiative Effect

Estimates of dust direct radiative effect (DRE) are still largely uncertain mainly due to the poor constraining of regional variations of dust absorption, whose known connection with mineral composition is still largely neglected by most Earth System Models. The inaccurate knowledge of soil mineralogy and insufficient measurements of dust physical and optical properties still present the main challenges for a proper representation of the dust-radiation interaction in climate models. We recently upgraded the coupling of dust minerals to shortwave radiation in the NASA GISS ModelE. In particular, we extended the interaction to online-calculated minerals and implemented two different mixing configurations: i) external mixing of three main mineral components and ii) internal mixing of all minerals, allowing a dynamic fraction of iron oxides. We used a semi-empirical approach for the optical calculations, mostly based on aerosol chamber measurements from natural soils, aiming to reduce the influence of uncertain assumptions on the optical properties and mixing state of individual minerals. In this contribution, we present the results of our first calculations of dust optical properties and DREs based on different mixing configurations of interactive minerals. We show the changes to dust optical depth and single scattering albedo, with respect to the control case using homogeneous dust composition, and the consequent global and regional variations in dust DREs at the top of atmosphere and at surface. We also compare the model optical properties with AERONET data, filtered to identify dust scenes. We find that accounting for the diverse properties of dust minerals modifies the pattern of regional dust absorption and therefore its impact upon climate. We also show that the mineralogy effect is sensitive to the assumed mixing state of minerals.

dust direct radiative effect↗

Wavelet Approximation in Data Assimilation

Estimation of the state of the atmosphere with the Kalman filter remains a distant goal because of high computational cost of evolving the error covariance for both linear and nonlinear systems. Wavelet approximation is presented here as a possible solution that efficiently compresses both global and local covariance information. We demonstrate the compression characteristics on the the error correlation field from a global two-dimensional chemical constituent assimilation, and implement an adaptive wavelet approximation scheme on the assimilation of the one-dimensional Burger's equation. In the former problem, we show that 99%, of the error correlation can be represented by just 3% of the wavelet coefficients, with good representation of localized features. In the Burger's equation assimilation, the discrete linearized equations (tangent linear model) and analysis covariance are projected onto a wavelet basis and truncated to just 6%, of the coefficients. A nearly optimal forecast is achieved and we show that errors due to truncation of the dynamics are no greater than the errors due to covariance truncation.

Tangborn, Andrew↗

New York City Panel on Climate Change 2019 Report Chapter 9: Perspectives on a City in a Changing Climate 2008-2018

Cities experience multiple environmental shifts, stresses, and shocks—such as air and water pollution—and a variety of extreme events simultaneously and continuously. Current urban programs have focused on limiting the impacts of these conditions through a portfolio of multifaceted strategies, such as regulations and codes, management and restoration projects, and citizen engagement. Global climate change represents a new environmental dynamic to which cities now have to respond. While global climate change by definition has impacts world wide, residents and managers of cities, like New York, typically perceive changes in their own local environments. In most cities, temperature is warming with increasingly hotter and longer heatwaves, and heavier downpours are leading to more frequent inland flooding. In coastal cities, sea levels are rising, exacerbating coastal flooding. Analyzing and understanding the impacts of climate change on cities is important because of the dramatic growth in urban populations throughout the world. An estimated nearly 4.0 billion people reside in urban areas, accounting for 52% of the world’s population (UN, 2017). That percentage will increase dramatically in the coming decades as almost all of the growth to take place up to 2050 will be in urban areas (UN, 2017). The New York City metropolitan region (NYMR)—the five boroughs (equivalent to counties) of New York City and the adjacent 26 counties in the states of New York, New Jersey, and Connecticut—is an ideal model of an urban agglomeration. Approximately 8.6 million people live in the five boroughs and more than 15 million people live in the neighboring smaller cities, towns, and villages (City of New York, 2018a; US Census, 2017). The population of the five boroughs is projected to add 1 million people by 2030, while the total region is projected to reach 26.1 million (NYTC, 2015).

Solecki, William↗

Internal Dynamics and Crustal Evolution of Mars

The objective of this work is to improve understanding of the internal structure, crustal evolution, and thermal history of Mars by combining geophysical data analysis of topography, gravity and magnetics with results from analytical and computational modeling. Accomplishments thus far in this investigation include: (1) development of a new crustal thickness model that incorporates constraints from Mars meteorites, corrections for polar cap masses and other surface loads, Pratt isostasy, and core flattening; (2) determination of a refined estimate of crustal thickness of Mars from geoid/topography ratios (GTRs); (3) derivation of a preliminary estimate of the k(sub 2) gravitational Love number and a preliminary estimate of possible dissipation within Mars consistent with this value; and (4) an integrative analysis of the sequence of evolution of early Mars. During the remainder of this investigation we will: (1) extend models of degree-1 mantle convection from 2-D to 3-D; (2) investigate potential causal relationships and effects of major impacts on mantle plume formation, with primary application to Mars; (3) develop exploratory models to assess the convective stability of various Martian core states as relevant to the history of dynamo action; and (4) develop models of long-wavelength relaxation of crustal thickness anomalies to potentially explain the degree-1 structure of the Martian crust.

Zuber, Maria↗

The Arctic Sea Ice Cover of 2016: A Year of Record-Low Highs and High-Than-Expected Lows

The Arctic sea ice cover of 2016 was highly noteworthy, as it featured record low monthly sea ice extents at the start of the year but a summer (September) extent that was higher than expected by most seasonal forecasts. Here we explore the 2016 Arctic sea ice state in terms of its monthly sea ice cover, placing this in the context of the sea ice conditions observed since 2000. We demonstrate the sensitivity of monthly Arctic sea ice extent and area estimates, in terms of their magnitude and annual rankings, to the ice concentration input data (using two widely used datasets) and to the averaging methodology used to convert concentration to extent (daily or monthly extent calculations). We use estimates of sea ice area over sea ice extent to analyse the relative “compactness†of the Arctic sea ice cover, highlighting anomalously low compactness in the summer of 2016 which contributed to the higher-than-expected September ice extent. Two cyclones that entered the Arctic Ocean during August appear to have driven this low-concentration/compactness ice cover but were not sufficient to cause more widespread melt-out and a new record-low September ice extent. We use concentration budgets to explore the regions and processes (thermodynamics/ dynamics) contributing to the monthly 2016 extent/area estimates highlighting, amongst other things, rapid ice intensification across the central eastern Arctic through September. Two different products show significant early melt onset across the Arctic Ocean in 2016, including record-early melt onset in the North Atlantic sector of the Arctic. Our results also show record-late 2016 freeze-up in the central Arctic, North Atlantic and the Alaskan Arctic sector in particular, associated with strong sea surface temperature anomalies that appeared shortly after the 2016 minimum (October onwards). We explore the implications of this low summer ice compactness for seasonal forecasting, suggesting that sea ice area could be a more reliable metric to forecast in this more seasonal, "New Arctic", sea ice regime.

sea ice↗

Development of response models for the Earth Radiation Budget Experiment (ERBE) sensors. Part 1: Dynamic models and computer simulations for the ERBE nonscanner, scanner and solar monitor sensors

Dynamic models and computer simulations were developed for the radiometric sensors utilized in the Earth Radiation Budget Experiment (ERBE). The models were developed to understand performance, improve measurement accuracy by updating model parameters and provide the constants needed for the count conversion algorithms. Model simulations were compared with the sensor's actual responses demonstrated in the ground and inflight calibrations. The models consider thermal and radiative exchange effects, surface specularity, spectral dependence of a filter, radiative interactions among an enclosure's nodes, partial specular and diffuse enclosure surface characteristics and steady-state and transient sensor responses. Relatively few sensor nodes were chosen for the models since there is an accuracy tradeoff between increasing the number of nodes and approximating parameters such as the sensor's size, material properties, geometry, and enclosure surface characteristics. Given that the temperature gradients within a node and between nodes are small enough, approximating with only a few nodes does not jeopardize the accuracy required to perform the parameter estimates and error analyses.

Halyo, Nesim↗

NASA Tech Briefs, March 2007

Topics include: Advanced Systems for Monitoring Underwater Sounds; Wireless Data-Acquisition System for Testing Rocket Engines; Processing Raw HST Data With Up-to-Date Calibration Data; Mobile Collection and Automated Interpretation of EEG Data; System for Secure Integration of Aviation Data; Servomotor and Controller Having Large Dynamic Range; Digital Multicasting of Multiple Audio Streams; Translator for Optimizing Fluid-Handling Components; AIRSAR Web-Based Data Processing; Pattern Matcher for Trees Constructed From Lists; Reducing a Knowledge-Base Search Space When Data Are Missing; Ground-Based Correction of Remote-Sensing Spectral Imagery; State-Chart Autocoder; Pointing History Engine for the Spitzer Space Telescope; Low-Friction, High-Stiffness Joint for Uniaxial Load Cell; Magnet-Based System for Docking of Miniature Spacecraft; Electromechanically Actuated Valve for Controlling Flow Rate; Plumbing Fixture for a Microfluidic Cartridge; Camera Mount for a Head-Up Display; Core-Cutoff Tool; Recirculation of Laser Power in an Atomic Fountain; Simplified Generation of High-Angular-Momentum Light Beams; Imaging Spectrometer on a Chip; Interferometric Quantum-Nondemolition Single-Photon Detectors; Ring-Down Spectroscopy for Characterizing a CW Raman Laser; Complex Type-II Interband Cascade MQW Photodetectors; Single-Point Access to Data Distributed on Many Processors; Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data; Computing a Stability Spectrum by Use of the HHT; Theoretical Studies of Routes to Synthesis of Tetrahedral N4; Estimation Filter for Alignment of the Spitzer Space Telescope; Antenna for Measuring Electric Fields Within the Inner Heliosphere; Improved High-Voltage Gas Isolator for Ion Thruster; and Hybrid Mobile Communication Networks for Planetary Exploration.

Source record↗

Characterizing Volcanic Eruptions on Venus: Some Realistic (?) Scenarios

When Pioneer Venus arrived at Venus in 1978, it detected anomalously high concentrations of SO2 at the top of the troposphere, which subsequently declined over the next five years. This decline in SO2 was linked to some sort of dynamic process, possibly a volcanic eruption. Observations of SO2 variability have persisted since Pioneer Venus. More recently, scientists from the Venus Express mission announced that the SPICAV (Spectroscopy for Investigation of Characteristics of the Atmosphere of Venus) instrument had measured varying amounts of SO2 in the upper atmosphere; VIRTIS (Visible and Infrared Thermal Imaging Spectrometer) measured no similar variations in the lower atmosphere (ESA, 4 April, 2008). In addition, Fegley and Prinn stated that venusian volcanoes must replenish SO2 to the atmosphere, or it would react with calcite and disappear within 1.9 my. Fegley and Tremain suggested an eruption rate on the order of approx 1 cubic km/year to maintain atmospheric SO2; Bullock and Grinspoon posit that volcanism must have occurred within the last 20-50 my to maintain the sulfuric acid/water clouds on Venus. The abundance of volcanic deposits on Venus and the likely thermal history of the planet suggest that it is still geologically active, although at rates lower than Earth. Current estimates of resurfacing rates range from approx 0.01 cubic km/yr to approx 2 cubic km/yr. Demonstrating definitively that Venus is still volcanically active, and at what rate, would help to constrain models of evolution of the surface and interior, and help to focus future exploration of Venus.

Stofan, E. R.↗

Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)

Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.

Bohdan O Wesely↗

Dynamic Orbital Slingshot for Rendezvous with Interstellar Objects

The solar sail “statite” concept presents a potential means to study interstellar objects (ISOs). A new class of asteroids and comets, ISOs offer a unique scientific opportunity to answer fundamental scientific questions about the origin of solar system volatiles, the compositions of exo-solar systems, and the transfer rates of material between solar systems. Unfortunately, they are also challenging to study due to their high excess energies and the short lead time offered by present detection infrastructure. By using its solar sail to “hover” in place, a statite is able to await the discovery of an ISO and, when called upon, convert the enormous potential energy of its stationary state into the velocity necessary to rendezvous with the targeted comet or asteroid. The investigation completed in Phase I focused on establishing the viability of the proposed mission concept. To do so, optimal trajectories to the two known ISOs were demonstrated and the relationship between statite placement and the resulting trajectory was explored. Post-launch trajectories from the Earth to strategic statite states were also shown to be feasible. Concurrently with these efforts, a thorough review of published ISO population estimates was conducted and preliminary steps towards creating a database of synthetic ISO ephemerides were completed. If renewed for a Phase II, this will be used to characterize the capabilities of the statite concept.

NIAC Phase I↗

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗

PheniX: A New Vision for the Hard X-ray Sky

We are proposing a mission devoted to high energy X-ray astronomy that is based on a focusing telescope operating in the 1-200 keV energy range but optimized for the hard X-ray range. The main scientific topics concern: Physics of compact objects: The proximity of compact objects provides a unique laboratory to study matter and radiation in extreme conditions of temperature and density in strong gravitational environment. The emission of high energy photons from these objects is far from being understood. The unprecedented sensitivity in the high energy domain will allow a precise determination of the non-thermal processes at work in the vicinity of compact objects. The full 1-200 keV energy coverage will be ideal to disentangle the emission processes produced in the spacetime regions most affected by strong-gravity, as well as the physical links: disk-thermal emission-iron line-comptonisation-reflection-non-thermal emission-jets. Neutron stars-magnetic field-cyclotron lines: Time resolved spectroscopy (and polarimetry) at ultra-high sensitivity of AXP, milliseconds pulsars and magnetars will give new tools to study the role of the synchrotron processes at work in these objects. Cyclotron lines-direct measurement of magnetic filed-equation of state constraints-short bursts-giant flares could all be studied with great details. AGN: The large sensitivity improvement will provide detailed spectral properties of the high energy emission of AGN's. This will give a fresh look to the connection between accretion and jet emission and will provide a new understanding of the physical processes at work. Detection of high-redshift active nuclei in this energy range will allow to introduce an evolutionary aspect to high-energy studies of AGN, probing directly the origin of the Cosmic X-ray Background also in the non-thermal range (> 20 keV). Element formation-Supernovae: The energy resolution achievable for this mission (<0.5 keV) and a large high energy effective area are ideally suited for the 44Ti line study (68 and 78 keV). This radioactive nuclei emission will give an estimate of their quantities and speed in their environment. In addition the study of the spatial structure and spectral emission of SNR will advance our knowledge of the dynamics of supernovae explosions, of particles acceleration mechanisms and how the elements are released in the interstellar medium. Instrumental design: The progress of X-ray focusing optics techniques allows a major step in the instrumental design: the collecting area becomes independent of the detection area. This drastically reduces the instrumental background and will open a new era. The optics will be based on depth-graded multi-layer mirrors in a Wolter I configuration. To obtain a significant effective area in the hundred of keV range a focal length in the 40-50 meters range (attainable with a deployable mast) is needed. In addition such a mission could benefit from recent progress made on mirror coating. We propose to cover the 1-200 keV energy range with a single detector, a double-sided Germanium strip detector operating at 80 K. The main features will be: (a) good energy resolution (.150 keV at 5 keV and <.5 keV at 100 keV), (b) 3 dimensional event localization with a low number of electronic chains, (c) background rejection by the 3D localization, (d) polarisation capabilities in the Compton regime.

PHENIX↗

An Overview of Approaches and Challenges for Retrieving Marine Inherent Optical Properties from Ocean Color Remote Sensing

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.

Bio-optics↗

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land-Atmosphere Coupling

The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from ‘off-the-shelf’ products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high resolution land surface model and in-situ soil moisture estimates. Case studies are analyzed using the local land-atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land vs. atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

Southern Great Plains↗

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO2. The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO 2 . The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗