SEARCH · Search NASA

Results for “driver feedback”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Cost‐Responsive Optimization of Nickel Nanoparticle Synthesis

Abstract Early‐stage cost evaluation during catalyst development holds the potential to accelerate the commercialization and deployment of advanced catalytic materials for sustainable chemical processes. The modeling and assessment of manufacturing costs as early as the laboratory synthesis scale, for example, focusing on materials costs and synthesis performance metrics, can support the development of an experimental–economic feedback loop that enables rapid insight into cost drivers associated with catalyst synthesis and highlights areas that require focused research and development effort. Ultimately, this feedback loop supports the realization of an economic understanding of the overall synthetic process and highlights opportunities to reduce costs, serving as the foundation for the scale‐up of catalyst manufacturing. Herein, a case study is presented utilizing CatCost, a free and publicly available estimation tool for the evaluation of catalyst manufacturing costs, to perform a cost‐responsive optimization of the synthesis of nickel nanoparticles (Ni NPs). It is demonstrated that reagent substitutions with more cost‐effective analogs, coupled with stoichiometric optimization, afford a 58% reduction in raw materials cost without changing the product yield or properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Solid state light source driver establishing buck or boost operation

A solid state light source driver circuit that operates in either a buck convertor or a boost convertor configuration is provided. The driver circuit includes a controller, a boost switch circuit and a buck switch circuit, each coupled to the controller, and a feedback circuit, coupled to the light source. The feedback circuit provides feedback to the controller, representing a DC output of the driver circuit. The controller controls the boost switch circuit and the buck switch circuit in response to the feedback signal, to regulate current to the light source. The controller places the driver circuit in its boost converter configuration when the DC output is less than a rectified AC voltage coupled to the driver circuit at an input node. The controller places the driver circuit in its buck converter configuration when the DC output is greater than the rectified AC voltage at the input node.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Systems and methods of delivering rectified voltage to a load

Palmer, Fred↗

NASA NTRS2019

Water Vapour Adjustments and Responses Differ Between Climate Drivers

Water vapour in the atmosphere is the source of a major climate feedback mechanism and potential increases in the availability of water vapour could have important consequences for mean and extreme precipitation. Future precipitation changes further depend on how the hydrological cycle responds to different drivers of climate change, such as greenhouse gases and aerosols. Currently, neither the total anthropogenic influence on the hydrological cycle nor that from individual drivers is constrained sufficiently to make solid projections. We investigate how integrated water vapour (IWV) responds to different drivers of climate change. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulfate have been perturbed separately. While the global-mean IWV is usually assumed to increase by 7% per kelvin of surface temperature change, we find that the feedback response of IWV differs somewhat between drivers. Fast responses, which include the initial radiative effect and rapid adjustments to an external forcing, amplify these differences. The resulting net changes in IWV range from 6.4±0.9%K(exp -1) for sulfate to 9.8±2%K(exp -1) for BC. We further calculate the relationship between global changes in IWV and precipitation, which can be characterized by quantifying changes in atmospheric water vapour lifetime. Global climate models simulate a substantial increase in the lifetime, from 8.2±0.5 to 9.9±0.7d between 1986-2005 and 2081-2100 under a high-emission scenario, and we discuss to what extent the water vapour lifetime provides additional information compared to analysis of IWV and precipitation separately. We conclude that water vapour lifetime changes are an important indicator of changes in precipitation patterns and that BC is particularly efficient in prolonging the mean time, and therefore likely the distance, between evaporation and precipitation.

Hodnebrog, Øivind↗

DOE OSTI2022

Extratropical shortwave cloud feedbacks in the context of the global circulation and hydrological cycle

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

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2022

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

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

extratropical cloud response↗

DOE OSTI2017

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled control run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land-surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land-atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow-to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land-atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

Reliable inverter systems

Base driver with common-load-current feedback protects paralleled inverter systems from open or short circuits. Circuit eliminates total system oscillation that can occur in conventional inverters because of open circuit in primary transformer winding. Common feedback signal produced by functioning modules forces operating frequency of failed module to coincide with clock drive so module resumes normal operating frequency in spite of open circuit.

Nagano, S.↗

DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

Doppler lidar, aerosols, convection↗

DOE OSTI2021

Evaluation of the Large-Scale and Regional Climatic Response Across North Africa to Natural Variability in Oceanic Modes and Terrestrial Vegetation Among the CMIP5 Models

Hydrologic variability is a serious threat to the poverty-stricken regions of North Africa. Meanwhile, the scientific community struggles to attribute these extreme climatic episodes to specific oceanic and land drivers. Prior modeling studies have not assessed simulated feedbacks over North Africa against an established observational benchmark, so their results are considered as untested, model-specific findings. The Coupled Model Intercomparison Project Phase Five (CMIP5) archive represents the state-of-the-art in climate projections, with most CMIP5 models now containing interactive vegetation phenology; however, there have been no studies to date of their simulated vegetation feedbacks. The capability of CMIP5 models at accurately simulating the forcing of both sea-surface temperature (SST) and regional leaf area index (LAI) anomalies on North African climate needs to be a key consideration in assessing the models’ overall credibility and determining appropriate model weighting for developing climate projections. The Generalized Equilibrium Feedback Assessment (GEFA) is a promising statistical method, which can be applied to either model output or observations, for isolating the local and remote impacts of individual oceanic or terrestrial forcings on regional climate. We performed a combined observational and modeling assessment of land-ocean-atmosphere interactions across the distinct ecological and moisture gradients of North Africa. We evaluated and demonstrated the reliability of the GEFA statistical method over North Africa using the Community Earth System Model (CESM), applied GEFA to observational data to quantify the observed forcing of ocean basin SST anomalies and regional LAI anomalies on North African climate, evaluated the CMIP5 models’ performance in terms of representing these key observed feedbacks, and formulated CMIP5 feedback performance metrics for weighting North African climate projections. Our study represented the first attempt to separate the observed roles of oceanic and vegetation feedbacks across North Africa, the first systematic assessment and intercomparison of land-ocean-atmosphere feedbacks in CMIP5, and the first exploration of vegetation feedbacks among CMIP5 models. The following work was accomplished. (1) The team generated 14 scientific publications and 30 presentations based on the DOE-funded research. (2) A stepwise version of the GEFA statistical method was developed in which unimportant forcings were dropped to increase the reliability of the results. (3) SGEFA was successfully validated through experiments with CESM in terms of its ability to isolate the atmospheric responses to individual oceanic or land forcings. (4) Observational evidence was revealed for the Sahel’s positive vegetation-rainfall feedback on the seasonal to interannual time scale, and it was attributed to a moisture recycling mechanism rather than an albedo mechanism. (5) An approach with SGEFA was developed in which the individual contributions of soil moisture versus vegetation forcings could be separated, revealing that the former forcing outweighed the latter for sub-Saharan Africa. (6) Tropical ocean temperatures were found to be key regulators of pan-tropical vegetation variability, especially for arid and semi-arid regions, including sub-Saharan Africa. (7) The CMIP5 models largely underestimated the importance of land feedbacks across the Sahel. (8) The general consensus among CMIP5 models indicates, for the late 21st century, a diminished seasonal predictability of sub-Saharan African regional climate and an elevated role of the land surface compared to oceanic drivers in regulating regional climate variability. (9) Land-ocean-atmosphere interactions were demonstrated to be key contributors to the seasonal predictability of African wildfire activity. (10) The El Djouf was determined to be of greater importance than the Bodélé depression in terms of providing trans-Atlantic dust transport to the Americas.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

Chapter 15: Potential Surprises: Compound Extremes and Tipping Elements

The Earth system is made up of many components that interact in complex ways across a broad range of temporal and spatial scales. As a result of these interactions the behavior of the system cannot be predicted by looking at individual components in isolation. Negative feedbacks, or self-stabilizing cycles, within and between components of the Earth system can dampen changes (Ch. 2: Physical Drivers of Climate Change). However, their stabilizing effects render such feedbacks of less concern from a risk perspective than positive feedbacks, or self-reinforcing cycles. Positive feedbacks magnify both natural and anthropogenic changes. Some Earth system components, such as arctic sea ice and the polar ice sheets, may exhibit thresholds beyond which these self-reinforcing cycles can drive the component, or the entire system, into a radically different state. Although the probabilities of these state shifts may be difficult to assess, their consequences could be high, potentially exceeding anything anticipated by climate model projections for the coming century.

Kopp, R. E.↗

DOE OSTI2023

Plant–soil feedback under drought: does history shape the future?

Plant–soil feedback (PSF) is widely recognised as a driver of plant community composition, but understanding of its response to drought remains in its infancy. Here, we provide a conceptual framework for the role of drought in PSF, considering plant traits, drought severity, and historical precipitation over ecological and evolutionary timescales. Comparing experimental studies where plants and microbes do or do not share a drought history (through co-sourcing or conditioning), we hypothesise that plants and microbes with a shared drought history experience more positive PSF under subsequent drought. To reflect real-world responses to drought, future studies need to explicitly include plant–microbial co-occurrence and potential co-adaptation and consider the precipitation history experienced by both plants and microbes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Model-Data Fusion Approaches for Retrospective and Predictive Assessment of the Pan-Arctic Scale Permafrost Carbon Feedback to Global Climate

Policy decisions regarding climate change mitigation and adaptation rely on having reliable projections of future climate change. Coupled climate-carbon models predict that the northern high latitudes will serve as a substantial land carbon sink during the 21stcentury, but these models lack many of the key processes governing high-latitude ecosystem processes. Arctic tundra and boreal forests are unique from other biomes particularly because of the presence of snow, ice and frozen ground, and it is important to understand the mechanisms that drive interconnected processes in these landscapes. Increasing our confidence in climate projections requires an integrated approach where existing, on-going and planned observational and experimental studies of high-latitude ecosystem processes are organized and analyzed in a framework designed to target improvements in understanding key ecosystem-climate feedbacks. For this project we designed an approach to improve our scientific understanding of the permafrost carbon feedback through broad-scale assessment of the drivers and responses of the Arctic system carbon cycle using data-driven models of simple-to-intermediate complexity. The made a valuable contribution to the first of its kind, data-driven quantitative assessment of the impact of permafrost thaw on pan-Arctic scale carbon cycle feedbacks to the global climate system. The approach drew on a conceptual framework for integrating the key system components and their underlying data within a “book-keeping” framework for assessment of the key processes driving the permafrost carbon feedback. The results provided quantitative model-data benchmarking to constrain future projections of carbon cycle responses to a warming Arctic. The framework used environmental proxy data sets examining recent-era geomorphologic land-form transitions and vegetation dynamics, through remotely-sensed data, to guide the extrapolation of site-based data on the key system components to larger regions. These products contribute to the development of finer-scale, more complex representation of permafrost carbon processes in terrestrial biogeochemistry models, to operate within coupled Earth system modeling frameworks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Global-Scale Convergence Obscures Inconsistencies in Soil Carbon Change Predicted by Earth System Models

Soil carbon (C) responses to environmental change represent a major source of uncertainty in the global C cycle. Feedbacks between soil C stocks and climate drivers could impact atmospheric CO 2 levels, further altering the climate. Here, we assessed the reliability of Earth system model (ESM) predictions of soil C change using the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). ESMs predicted global soil C gains under the high emission scenario, with soils taking up 43.9 Pg (95% CI: 9.2–78.5 Pg) C on average during the 21st century. The variation in global soil C change declined significantly from CMIP5 (with average of 48.4 Pg [95% CI: 2.0–94.9 Pg] C) to CMIP6 models (with average of 39.3 Pg [95% CI: 23.9–54.7 Pg] C). For some models, a small C increase in all biomes contributed to this convergence. For other models, offsetting responses between cold and warm biomes contributed to convergence. Although soil C predictions appeared to converge in CMIP6, the dominant processes driving soil C change at global or biome scales differed among models and in many cases between earlier and later versions of the same model. Random Forest models, for soil carbon dynamics, accounted for more than 63% variation of the global soil C change predicted by CMIP5 ESMs, but only 36% for CMIP6 models. Although most CMIP6 models apparently agree on increased soil C storage during the 21st century, this consensus obscures substantial model disagreement on the mechanisms underlying soil C response, calling into question the reliability of model predictions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A molecular conveyor belt-associated protein controls the rotational direction of the bacterial type 9 secretion system

ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.

Microbiology↗

DOE OSTI2022

Radio AGN in nearby dwarf galaxies: the important role of AGN in dwarf galaxy evolution

ABSTRACT We combine deep optical and radio data, from the Hyper Suprime-Cam and the Low-Frequency Array (LOFAR), respectively, to study 78 radio active galactic nuclei (AGN) in nearby (z < 0.5) dwarf galaxies. Comparison to a control sample, matched in stellar mass and redshift, indicates that the AGN and controls reside in similar environments, show similar star formation rates (which trace gas availability) and exhibit a comparable incidence of tidal features (which indicate recent interactions). We explore the AGN properties by combining the predicted gas conditions in dwarfs from a cosmological hydrodynamical simulation with a Monte Carlo suite of simulated radio sources, based on a semi-analytical model for radio-galaxy evolution. In the subset of LOFAR-detectable simulated sources, which have a similar distribution of radio luminosities as our observed AGN, the median jet powers, ages, and accretion rates are ∼1035 W, ∼5 Myr, and ∼10−3.4 M⊙ yr−1, respectively. The median mechanical energy output of these sources is ∼100 times larger than the median binding energy expected in dwarf gas reservoirs, making AGN feedback plausible. Since special circumstances (in terms of environment, gas availability, and interactions) are not necessary for the presence of AGN, and the central gas masses are predicted to be an order of magnitude larger than that required to fuel the AGN, AGN triggering in dwarfs is likely to be stochastic and a common phenomenon. Together with the plausibility of energetic feedback, this suggests that AGN could be important drivers of dwarf galaxy evolution, as is the case in massive galaxies.

Davis, F. (ORCID:0000000285224980)↗

NASA NTRS2020

Attribution of Chemistry-Climate Model Initiative (CCMI) Ozone Radiative Flux Bias from Satellites

The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6-μm ozone band is a fundamental quantity for understanding chemistry-climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting radiative forcing evolution. To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6-μm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Inter-comparison Project (ACCMIP) simulations. The principal culprits are tropical mid and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mWm-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mWm-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mWm-2). We found that AM3 and CMAM have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to difference processes. Overall, the multi-model ensemble mean bias is –133±98 mWm-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (OLR) difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation.

Aura Tropospheric Emission Spectrometer (TES) meas↗