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Earth and sun magnetic field production models as function of dynamo states, discussing solar field effects on terrestrial space environment
Convection of plasma within the terrestrial nightside plasma sheet contributes to the structure and, possibly, the dynamical evolution of the magnetotail. In order to characterize the steady state convection process, we have extended the finite tail width model of magnetotail plasma sheet convection. The model assumes uniform plasma sources and accounts for both the duskward gradient/curvature drift and the earthward E x B drift of ions in a two-dimensional magnetic geometry. During periods of slow convection (i.e., when the cross-tail electric potential energy is small relative to the source plasma's thermal energy), there is a significant net duskward displacement of the pressure-bearing ions. The electrons are assumed to be cold, and we argue that this assumption is appropriate for plasma sheet parameters. We generalize solutions previously obtained along the midnight meridian to describe the variation of the plasma pressure and number density across the width of the tail. For a uniform deep-tail source of particles, the plasma pressure and number density are unrealistically low along the near-tail dawn flank. We therefore add a secondary source of plasma originating from the dawnside low-latitude boundary layer (LLBL). The dual plasma sources contribute to the plasma pressure and number density throughout the magnetic equatorial plane. Model results indicate that the LLBL may be a significant source of near-tail central plasma sheet plasma during periods of weak convection. The model predicts a cross-tail pressure gradient from dawn to dusk in the near magnetotail. We suggest that the plasma pressure gradient is balanced in part by an oppositely directed magnetic pressure gradient for which there is observational evidence. Finally, the pressure to number density ratio is used to define the plasma 'temperature.' We stress that such quantities as temperature and polytropic index must be interpreted with care as they lose their nominal physical significance in regions where the two-source plasmas intermix appreciably and the distributions become non-Maxwellian.
The goal of this study is to provide technological support to ensure successful life and operation of a 50-300 kW dynamic power conversion system specifically with response to the rotor support system. By utilizing technical expertise in tribology, bearings, rotordynamic, solid lubricant coatings and extensive test facilities, valuable input for mission success is provided. A discussion of the history of closed cycle Brayton turboalternators (TA) will be included. This includes the 2 kW Mini-Brayton Rotating Unit (Mini-BRU), the 10kW Brayton Rotating Unit (BRU) and the 125 kW turboalternator-compressor (TAC) designed in mid 1970's. Also included is the development of air-cycle machines and terrestrial oil-free gas turbine power systems in the form of microturbines, specifically Capstone microturbines. A short discussion of the self-acting compliant surface hydrodynamic fluid film bearings, or foil bearings, will follow, including a short history of the load capacity advances, the NASA coatings advancements as well as design model advances. Successes in terrestrial based machines will be noted and NASA tribology and bearing research test facilities will be described. Finally, implementation of a four step integration process will be included in the discussion.
Tropical forest dynamics play a crucial role in the global carbon, water, and energy cycles. However, realistically simulating the dynamics of competition and coexistence between different plant functional types (PFTs) in tropical forests remains a significant challenge. This study aims to improve the modeling of PFT coexistence in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vegetation demography model implemented in the Energy Exascale Earth System Model (E3SM) land model (ELM), ELM-FATES. Specifically, we explore (1) whether plant trait relationships established from field measurements can constrain ELM-FATES simulations and (2) whether machine learning (ML)-based surrogate models can emulate the complex ELM-FATES model and optimize parameter selections to improve PFT coexistence modeling. We conducted three ensembles of ELM-FATES experiments at a tropical forest site near Manaus, Brazil. By comparing the ensemble experiments without (Exp-CTR) and with (Exp-OBS) consideration of observed trait relationships, we found that accounting for these relationships slightly improves the simulations of water, energy, and carbon variables when compared to observations but degrades the simulation of PFT coexistence. Using ML-based surrogate models trained on Exp-CTR, we optimized the trait parameters in ELM-FATES and conducted another ensemble of experiments (Exp-ML) with these optimized parameters. The proportion of PFT coexistence experiments significantly increased from 21 % in Exp-CTR to 73 % in Exp-ML. After filtering the experiments that allow for PFT coexistence to agree with observations (within 15 % tolerance), 33 % of the Exp-ML experiments were retained, which is a significant improvement compared to the 1.4 % in Exp-CTR. Exp-ML also accurately reproduces the annual means and seasonal variations in water, energy, and carbon fluxes and the field inventory of aboveground biomass. This study represents a reproducible method that utilizes machine learning to identify parameter values that improve model fidelity against observations and PFT coexistence in vegetation demography models for diverse ecosystems. Our study also suggests the need for new mechanisms to enhance the robust simulation of coexisting plants in ELM-FATES and has significant implications for modeling the response and feedbacks of ecosystem dynamics to climate change.
Barringer Meteorite Crater or Meteor Crater, AZ, has been a site of high interest for lunar and Mars analog crater and terrain studies since the early days of the Apollo-Saturn program. It continues to be a site of exceptional interest to lunar, Mars, and other planetary crater and impact analog studies because of its relatively young age (est. 50 thousand years) and well-preserved structure. High resolution (2 meter to 1 decimeter) digital terrain models of Meteor Crater in whole or in part were created at NASA Stennis Space Center to support several lunar surface analog modeling activities using photogrammetric and ground based laser scanning techniques. The dataset created by this activity provides new and highly accurate 3D models of the inside slope of the crater as well as the downslope rock distribution of the western ejecta field. The data are presented to the science community for possible use in furthering studies of Meteor Crater and impact craters in general as well as its current near term lunar exploration use in providing a beneficial test model for lunar surface analog modeling and surface operation studies.
Fire is the primary form of terrestrial ecosystem disturbance on a global scale and an important Earth system process. Most Earth system models (ESMs) have incorporated fire modeling, with 19 of them submitting model outputs of fire-related variables to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study provides the first comprehensive evaluation of CMIP6 historical fire simulations by comparing them with multiple satellite-based products and charcoal-based historical reconstructions. Our results show that most CMIP6 models simulate the present-day global burned area and fire carbon emissions within the range of satellite-based products. They also capture the major features of observed spatial patterns and seasonal cycles, the relationship of fires with precipitation and population density, and the influence of the El Niño–Southern Oscillation (ENSO) on the interannual variability of tropical fires. Regional fire carbon emissions simulated by the CMIP6 models from 1850 to 2010 generally align with the charcoal-based reconstructions, although there are regional mismatches, such as in southern South America and eastern temperate North America prior to the 1910s and in temperate North America, eastern boreal North America, Europe, and boreal Asia since the 1980s. The CMIP6 simulations have addressed three critical issues identified in CMIP5: (1) the simulated global burned area being less than half of that of the observations, (2) the failure to reproduce the high burned area fraction observed in Africa, and (3) the weak fire seasonal variability. Furthermore, the CMIP6 models exhibit improved accuracy in capturing the observed relationship between fires and both climatic and socioeconomic drivers and better align with the historical long-term trends indicated by charcoal-based reconstructions in most regions worldwide. However, the CMIP6 models still fail to reproduce the decline in global burned area and fire carbon emissions observed over the past 2 decades, mainly attributed to an underestimation of anthropogenic fire suppression, and the spring peak in fires in the Northern Hemisphere midlatitudes, mainly due to an underestimation of crop fires. In addition, the model underestimates the fire sensitivity to wet–dry conditions, indicating the need to improve fuel wet-ness estimation. Based on these findings, we present specific guidance for fire scheme development and suggest a postprocessing methodology for using CMIP6 multi-model outputs to generate reliable fire projection products.
This study examines the impact of parameterization of two variables, light use efficiency (LUE) and the fraction of absorbed photosynthetically active radiation (fPAR or fAPAR), on gross primary production(GPP) modeling. Carbon sequestration by terrestrial plants is a key factor to a comprehensive under-standing of the carbon budget at global scale. In this context, accurate measurements and estimates of GPP will allow us to achieve improved carbon monitoring and to quantitatively assess impacts from cli-mate changes and human activities. Spaceborne remote sensing observations can provide a variety of land surface parameterizations for modeling photosynthetic activities at various spatial and temporal scales. This study utilizes a simple GPP model based on LUE concept and different land surface parameterizations to evaluate the model and monitor GPP. Two maize-soybean rotation fields in Nebraska, USA and the Bartlett Experimental Forest in New Hampshire, USA were selected for study. Tower-based eddy-covariance carbon exchange and PAR measurements were collected from the FLUXNET Synthesis Dataset. For the model parameterization, we utilized different values of LUE and the fPAR derived from various algorithms. We adapted the approach and parameters from the MODIS MOD17 Biome Properties Look-Up Table (BPLUT) to derive LUE. We also used a site-specific analytic approach with tower-based Net Ecosystem Exchange (NEE) and PAR to estimate maximum potential LUE (LUEmax) to derive LUE. For the fPAR parameter, the MODIS MOD15A2 fPAR product was used. We also utilized fAPAR chl, a parameter accounting for the fAPAR linked to the chlorophyll-containing canopy fraction. fAPAR chl was obtained by inversion of a radiative transfer model, which used the MODIS-based reflectances in bands 1-7 produced by Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. fAPAR chl exhibited seasonal dynamics more similar with the flux tower based GPP than MOD15A2 fPAR, especially in the spring and fall at the agricultural sites. When using the MODIS MOD17-based parameters to estimate LUE, fAPAR chl generated better agreements with GPP (r2= 0.79-0.91) than MOD15A2 fPAR (r2= 0.57-0.84).However, underestimations of GPP were also observed, especially for the crop fields. When applying the site-specific LUE max value to estimate in situ LUE, the magnitude of estimated GPP was closer to in situ GPP; this method produced a slight overestimation for the MOD15A2 fPAR at the Bartlett forest. This study highlights the importance of accurate land surface parameterizations to achieve reliable carbon monitoring capabilities from remote sensing information.
Abstract Lateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.
The bombardment history of the Earth-Moon system has been debated since the first recognition that the circular features on the Moon may be impact craters. Because the lunar impact record is the only planetary impact record to be calibrated with absolute ages, it underpins our understanding of geologic ages on every other terrestrial planet. One of the more remarkable results to come out of lunar sample analyses is the hypothesis that a large number of impact events occurred on the Moon during a narrow window in time approximately 3.8 to 4.1 billion years ago (the lunar cataclysm ). Subsequent work on the lunar and martian meteorite suites; remote sensing of the Moon, Mars, asteroids, and icy satellites; improved dynamical modeling; and investigation of terrestrial zircons extend the cataclysm hypothesis to the Earth, other terrestrial planets, and possibly the entire solar system. Renewed US and international interest in exploring the Moon offers new potential to constrain the Earth-Moon bombardment history. This paper will review the lunar bombardment record, timing and mechanisms for cataclysmic bombardment, and questions that may be answered in a new age of exploration.
The paper presents a generalized methodology for identification and evaluation of potential degradation and failure of terrestrial photovoltaic encapsulation. Failure progression modeling and an interaction matrix are utilized to complement the conventional approach to failure degradation mode identification. Comparison of the predicted performance based on these models can produce: (1) constraints on system or component design, materials or operating conditions, (2) qualification (predicted satisfactory function), and (3) uncertainty. The approach has been applied to an investigation of an unexpected delamination failure; it is being used to evaluate thermomechanical interactions in photovoltaic modules and to study corrosion of contacts and interconnects.
Accurate lunar navigation and timing knowledge provides for the development of safety-critical services in the cislunar and lunar surface domain. Currently under development, the Goddard Space Flight Center’s (GSFC) Search and Rescue Mission Office is investigating and integrating search and rescue (SAR) capability into planned and future lunar communication and navigation interfaces. Lunar Search and Rescue (LunaSAR) development has a stated end-goal for assured, reliable, and timely indication of distress events for a wide variety of lunar surface users, including government-sponsored, commercial, and international users. LunaSAR performance requirements are modelled after the current terrestrial Cospas-Sarsat distress notification system, leveraging an internationally robust global navigation satellite system (GNSS) ecosystem as a core element of survivor locating capability. This presentation will discuss NASA’s work to develop user-focused distress messaging capabilities including infusion of example sensor data for triggering of automated distress alerts coupled with location-tagging. Additionally, the presentation will examine overall message structures, rotating fields for use in bi-directional distress messaging, and specific use cases based on NASA’s lunar exploration and lunar communication relay architectures. Modelling and simulation of LunaSAR use by individual lunar explorers will be discussed, based on notional industry and government design reference missions and mission considerations. Results from GSFC-funded Internal Research and Development (IRAD) efforts will be detailed, including successful distress message formulation simulating the ingestion of example legacy space suit telemetry fields. Hardware-in-the-loop testing using high-reliability software defined radio (SDR) modules serve as an example of IRAD successes and the framework for technical requirements. Architectural development and technical evolution from 2020 to 2021 included alignment of LunaSAR distress waveforms with ongoing NASA LunaNet interoperability development, as well as engagement with NASA Lunar Spectrum authorities for allocation of UHF-band distress frequencies on the lunar surface. S-Band and UHF-band transmission characteristics will be detailed, along with band-specific applications of each emission type. Additionally, examples of ingestion and formatting of GNSS signals (using historical terrestrial National Marine Electronics Association-formatted GNSS data) will be detailed, underscoring lunar user needs for a common lunar GNSS receiver output message framework. Maturity and ability to support evolving lunar exploration goals has been demonstrated and will be detailed, with maturity gaps such as position, navigation, and timing (PNT) and lunar reference frames identified within the context of distress message generation. Provision of LunaSAR services for lunar surface users represents a new era of ensured safety for lunar explorers and builds off of forty years of the Cospas-Sarsat program, underscoring the importance of lunar GNSS for safety-critical applications and growing interest in safe, reliable lunar surface operations. Enabled by new GNSS systems being developed by government and industry partners, NASA will continue to evolve and integrate lunar GNSS types into distress message generation, with a focus on compact and efficient message transmission over various lunar communication links. When fielded, LunaSAR will be the first dedicated search and rescue notification system employed on another celestial body. Robust lunar navigation and timing services form the core of LunaSAR capabilities, allowing for system syncing with time-dominant sensors, and high-accuracy location of those in distress while engaged in lunar surface activities.
Combined inferences from seismology, high-pressure experiment and theory, geomagnetism, fluid dynamics, and current views of terrestrial planetary evolution lead to models of the earth's core with five basic properties. These are that core formation was contemporaneous with earth accretion; the core is not in chemical equilibrium with the mantle; the outer core is a fluid iron alloy containing significant quantities of lighter elements and is probably almost adiabatic and compositionally uniform; the more iron-rich inner solid core is a consequence of partial freezing of the outer core, and the energy release from this process sustains the earth's magnetic field; and the thermodynamic properties of the core are well constrained by the application of liquid-state theory to seismic and labroatory data.
The terrestrial biosphere exchanges a large amount of CO 2 with the atmosphere through photosynthesis and respiration, determining the magnitude of land carbon sink and consequently influencing the rate of global warming. The magnitudes of global photosynthesis and respiration, however, vary widely across models (100-200 PgC/year), constituting a key and persistent source of uncertainty in carbon cycle and climate modelling. Here, we argue that the uncertainty in the land carbon cycle modelling is largely attributable to the uncertainty in biogeography – the distribution of plant functional types (PFTs). Using an ensemble of dynamic global vegetation models (DGVMs), we find a strong dependence of total photosynthesis on total area for each PFT. The dependence allows us to reduce the spread of land carbon cycle estimates by ~75% using remote sensing-based PFT maps. We further find that 56 ± 21% of climate-driven changes in global photosynthesis modelled by DGVMs are caused by changes in PFT distribution in the last two decades. Our study identifies vegetation biogeography as a main controlling factor of uncertainty in land carbon cycle modelling and highlights the importance of biogeography-climate interactions in carbon cycle and climate studies.
Understanding the underlying processes that control the carbon cycle is key to predicting future global change. Much of the uncertainty in the magnitude and variability of the atmospheric carbon dioxide (CO2) stems from uncertainty in terrestrial carbon fluxes, and the relative impacts of temperature and moisture variations on regional and global scales are poorly understood. Here we investigate the impact of a regional drought on terrestrial carbon fluxes and CO2 mixing ratios over North America using the NASA Goddard Earth Observing System (GEOS) Model. Results show a sequence of changes in carbon fluxes and atmospheric CO2, induced by the drought. The relative contributions of meteorological changes to the neighboring carbon dynamics are also presented. The coupled modeling approach allows a direct quantification of the impact of the regional drought on local and proximate carbon exchange at the land surface via the carbon-water feedback processes.
Abstract. Extreme droughts are a major determinant of ecosystem disturbance that impacts plant communities and feeds back into climate change through changes in plant functioning. However, the complex relationships between aboveground and belowground plant hydraulic traits and their role in governing plant responses to drought are not fully understood. In this study, we use a model, the Functionally Assembled Terrestrial Ecosystem Simulator in a configuration that includes plant hydraulics (FATES-Hydro), to investigate ecosystem responses to the 2012–2015 California drought in comparison with observations at a site in the southern Sierra Nevada that experienced widespread tree mortality during this drought. We conduct a sensitivity analysis to explore how different plant water sourcing and hydraulic strategies lead to differential responses during normal and drought conditions. The analysis shows the following. Deep roots that sustain productivity through the dry season are needed for the model to capture observed seasonal cycles of evapotranspiration (ET) and gross primary productivity (GPP) in normal years, and deep-rooted strategies are nonetheless subject to large reductions in ET and GPP when the deep soil reservoir is depleted during extreme droughts, in agreement with observations. Risky stomatal strategies lead to greater productivity during normal years as compared to safer stomatal control, but they also lead to a high risk of xylem embolism during the 2012–2015 drought. For a given stand density, stomatal and xylem traits have a stronger impact on plant water status than on ecosystem-level fluxes. Our study highlights the significance of resolving plant water sourcing strategies to represent drought impacts on plants and consequent feedbacks in models.
Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin-up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi-Analytical Spin-Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin-up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin-up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin-up on site and globally in comparison with other spin-up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.
Numerical simulations are essential tools for understanding the complex hydrologic response of Arctic regions to a warming climate. However, strong coupling among thermal and hydrological processes on the surface and in the subsurface and the significant role that subtle variations in surface topography have in regulating flow direction and surface storage lead to significant uncertainties. Careful model evaluation against field observations is thus important to build confidence.We evaluate the integrated surface/subsurface permafrost thermal hydrology models in the Advanced Terrestrial Simulator (ATS) against field observations from polygonal tundra at the Barrow Environmental Observatory. ATS couples a multiphase, 3D representation of subsurface thermal hydrology with representations of overland nonisothermal flows, snow processes, and surface energy balance. We simulated thermal hydrology of a 3D ice-wedge polygon with geometry that is abstracted but broadly consistent with the surface microtopography at our study site. The simulations were forced by meteorological data and observed water table elevations in ice-wedge polygon troughs. With limited calibration of parameters appearing in the soil evaporation model, the 3-year simulations agreed reasonably well with snow depth, summer water table elevations in the polygon center, and high-frequency soil temperature measurements at several depths in the trough, rim, and center of the polygon. Upscaled evaporation is in good agreement with flux tower observations. The simulations were found to be sensitive to parameters in the bare soil evaporation model, snowpack, and the lateral saturated hydraulic conductivity.Timing of fall freeze-up was found to be sensitive to initial snow density, illustrating the importance of including snow aging effects. The study provides new support for an emerging class of integrated surface/subsurface permafrost simulators.
Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.