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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.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The interaction of climate change and methane hydrates

Gas hydrate, a frozen, naturally-occurring, and highly-concentrated form of methane, sequesters significant carbon in the global system and is stable only over a range of low-temperature and moderate-pressure conditions. Gas hydrate is widespread in the sediments of marine continental margins and permafrost areas, locations where ocean and atmospheric warming may perturb the hydrate stability field and lead to release of the sequestered methane into the overlying sediments and soils. Methane and methane-derived carbon that escape from sediments and soils and reach the atmosphere could exacerbate greenhouse warming. The synergy between warming climate and gas hydrate dissociation feeds a popular perception that global warming could drive catastrophic methane releases from the contemporary gas hydrate reservoir. Appropriate evaluation of the two sides of the climate-methane hydrate synergy requires assessing direct and indirect observational data related to gas hydrate dissociation phenomena and numerical models that track the interaction of gas hydrates/methane with the ocean and/or atmosphere. Methane hydrate is likely undergoing dissociation now on global upper continental slopes and on continental shelves that ring the Arctic Ocean. Many factors—the depth of the gas hydrates in sediments, strong sediment and water column sinks, and the inability of bubbles emitted at the seafloor to deliver methane to the sea-air interface in most cases—mitigate the impact of gas hydrate dissociation on atmospheric greenhouse gas concentrations though. There is no conclusive proof that hydrate-derived methane is reaching the atmosphere now, but more observational data and improved numerical models will better characterize the climate-hydrate synergy in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Thermal acclimation of plant photosynthesis and autotrophic respiration in a northern peatland

Peatlands contain one-third of global soil carbon (C), but the responses of peatland ecosystems to long-term warming are not well understood. Here, we pursue an emergent understanding of warming effects on ecosystem C fluxes at peatlands by constraining a process-oriented model, the terrestrial ECOsystem model, with observational data from a long-term warming experiment at the Spruce and Peatland Responses Under Changing Environments site. Model-based assessments show that ecosystem-level photosynthesis and autotrophic respiration exhibited significant thermal acclimation, with temperature sensitivities being linearly decreased with warming. Using the thermal-acclimated parameter values, simulated gross primary production, net primary production, and plant autotrophic respiration (R a ), were all lower than those simulated with non-thermal acclimated parameter values. In contrast, ecosystem respiration simulated with thermal acclimated parameter values was higher than that simulated with non-thermal acclimated parameter values. Net ecosystem CO 2 exchange was much higher after constraining model parameters with observational data from the warming treatments, releasing C at a rate of 28.3 g C m -2 yr -1 °C -1 . Our data-model integration study suggests that peatlands are likely to release more C than previously estimated. Earth system models may overestimate C uptake by peatlands under warming if physiological thermal acclimation of plants is not incorporated. Thus, it is critical to consider the long-term physiological thermal acclimation of plants in the models to better predict global C dynamics under future climate and their feedback to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

The abundance properties of nearby late-type galaxies. II. The relation between abundance distributions and surface brightness profiles

The relations between oxygen abundance and disk surface brightness (OH–SB relation) in the infrared W1 band are examined for nearby late-type galaxies. The oxygen abundances were presented in Paper I. The photometric characteristics of the disks are inferred here using photometric maps from the literature through bulge-disk decomposition. We find evidence that the OH–SB relation is not unique but depends on the galactocentric distance r (taken as a fraction of the optical radius R{sub 25}) and on the properties of a galaxy: the disk scale length h and the morphological T-type. We suggest a general, four-dimensional OH–SB relation with the values r, h, and T as parameters. The parametric OH–SB relation reproduces the observed data better than a simple, one-parameter relation; the deviations resulting when using our parametric relation are smaller by a factor of ∼1.4 than that of the simple relation. The influence of the parameters on the OH–SB relation varies with galactocentric distance. The influence of the T-type on the OH–SB relation is negligible at the centers of galaxies and increases with galactocentric distance. In contrast, the influence of the disk scale length on the OH–SB relation is at a maximum at the centers of galaxies and decreases with galactocentric distance, disappearing at the optical edges of galaxies. Two-dimensional relations can be used to reproduce the observed data at the optical edges of the disks and at the centers of the disks. The disk scale length should be used as a second parameter in the OH–SB relation at the center of the disk while the morphological T-type should be used as a second parameter in the relation at optical edge of the disk. The relations between oxygen abundance and disk surface brightness in the optical B and infrared K bands at the center of the disk and at optical edge of the disk are also considered. The general properties of the abundance–surface brightness relations are similar for the three considered bands B, K, and W1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Physics-embedded inverse analysis with algorithmic differentiation for the earth’s subsurface

Abstract Inverse analysis has been utilized to understand unknown underground geological properties by matching the observational data with simulators. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented with embedded physics and a technique known as algorithmic differentiation. We use a physics-embedded generative model, which takes statistically simple parameters as input and outputs subsurface properties (e.g., permeability or P-wave velocity), that embeds physical knowledge of the subsurface properties into inverse analysis and improves its performance. We tested the application of this approach on four geologic problems: two heterogeneous hydraulic conductivity fields, a hydraulic fracture network, and a seismic inversion for P-wave velocity. This physics-embedded inverse analysis approach consistently characterizes these geological problems accurately. Furthermore, the excellent performance in matching the observational data demonstrates the reliability of the proposed method. Moreover, the application of algorithmic differentiation makes this an easy and fast approach to inverse analysis when dealing with complicated geological structures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Conditioning multi-model ensembles for disease forecasting

In this study we investigate how an ensemble of disease models can be conditioned to observational data, in a bid to improve its predictive skill. We use the ensemble of influenza forecasting models gathered by the US Centers for Disease Control and Prevention (CDC) as the exemplar. This ensemble is used every year to forecast the annual influenza outbreak in the United States. The models constituting this ensemble draw on very different modeling assumptions and approximations and are a diverse collection of methods to approximate epidemiological dynamics. Currently, each models' predictions are accorded the same importance, or weight, when compiling the ensemble's forecast. We consider this equally-weighted ensemble as the baseline case which has to be improved upon. In this study, we explore whether an ensemble forecast can be improved by "conditioning" the ensemble to whatever observational data is available from the ongoing outbreak. "Conditioning" can imply according the ensemble's members different weights which evolve over time, or simply perform the forecast using the top k (equally-weighted) models. In the latter case, the composition of the "top-k-see of models evolves over time. This is called "model averaging" in statistics. We explore four methods to perform model-averaging, three of which are new. We find that the CDC ensemble responds best to the "top-k-models" approach to model-averaging. All the new MA methods perform better than the baseline equally-weighted ensemble. The four model-averaging methods treat the models as black-boxes and simply use their forecasts as inputs i.e., one does not need access to the models at all, but rather only their forecasts. The model-averaging approaches reviewed in this report thus form a general framework for model-averaging any model ensemble.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Line overlap and self-shielding of molecular hydrogen in galaxies

The effect of line overlap in the Lyman and Werner bands, often ignored in galactic studies of the atomic-to-molecular transition, greatly enhances molecular hydrogen self-shielding in low metallicity environments and dominates over dust shielding for metallicities below about 10% solar. We implement that effect in cosmological hydrodynamics simulations with an empirical model, calibrated against the observational data, and provide fitting formulae for the molecular hydrogen fraction as a function of gas density on various spatial scales and in environments with varied dust abundance and interstellar radiation field. We find that line overlap, while important for detailed radiative transfer in the Lyman and Werner bands, has only a minor effect on star formation on galactic scales, which, to a much larger degree, is regulated by stellar feedback.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Enhancements to VTK enabling Scientific Visualization in Immersive Environments

Modern scientific, engineering and medical computational sim- ulations, as well as experimental and observational data sens- ing/measuring devices, produce enormous amounts of data. While statistical analysis provides insight into this data, scientific vi- sualization is tactically important for scientific discovery, prod- uct design and data analysis. These benefits are impeded, how- ever, when scientific visualization algorithms are implemented from scratch—a time-consuming and redundant process in im- mersive application development. This process can greatly ben- efit from leveraging the state-of-the-art open-source Visualization Toolkit (VTK) and its community. Over the past two (almost three) decades, integrating VTK with a virtual reality (VR) environment has only been attempted to varying degrees of success. In this pa- per, we demonstrate two new approaches to simplify this amalga- mation of an immersive interface with visualization rendering from VTK. In addition, we cover several enhancements to VTK that pro- vide near real-time updates and efficient interaction. Finally, we demonstrate the combination of VTK with both Vrui and OpenVR immersive environments in example applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The Herschel Planetary Nebula Survey (HerPlaNS): A Comprehensive Dusty Photoionization Model of NGC6781

We perform a comprehensive analysis of the planetary nebula (PN) NGC 6781 to investigate the physical conditions of each of its ionized, atomic, and molecular gas and dust components and the object’s evolution, based on panchromatic observational data ranging from UV to radio. Empirical nebular elemental abundances, compared with theoretical predictions via nucleosynthesis models of asymptotic giant branch (AGB) stars, indicate that the progenitor is a solar-metallicity, 2.25--3.0 M{sub ⊙} initial-mass star. We derive the best-fit distance of 0.46 kpc by fitting the stellar luminosity (as a function of the distance and effective temperature of the central star) with the adopted post-AGB evolutionary tracks. Our excitation energy diagram analysis indicates high-excitation temperatures in the photodissociation region (PDR) beyond the ionized part of the nebula, suggesting extra heating by shock interactions between the slow AGB wind and the fast PN wind. Through iterative fitting using the Cloudy code with empirically derived constraints, we find the best-fit dusty photoionization model of the object that would inclusively reproduce all of the adopted panchromatic observational data. The estimated total gas mass (0.41 M{sub ⊙}) corresponds to the mass ejected during the last AGB thermal pulse event predicted for a 2.5 M{sub ⊙} initial-mass star. A significant fraction of the total mass (about 70%) is found to exist in the PDR, demonstrating the critical importance of the PDR in PNe that are generally recognized as the hallmark of ionized/H{sup +} regions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2004

The Nonlinear Coupling of Alfven and Lower Hybrid Waves in Space Plasma

Space plasmas support a wide variety of waves, and wave-particle interactions as well as wave-wave interactions which are of crucial importance to magnetospheric and ionospheric plasma behavior. The excitation of lower hybrid waves (LHWs) in particular is a widely discussed mechanism of interaction between plasma species in space and is one of the unresolved questions of magnetospheric multi-ion plasmas. It is demonstrated that large-amplitude Alfven waves may generate LHWs in the auroral zone and ring current region and in some cases (particularly in the inner magnetosphere) this serves as the Alfven wave saturation mechanism. We present several examples of observational data which illustrate that the proposed mechanism is a plausible candidate to explain certain classes of LHW generation events in the ionosphere and magnetosphere and demonstrate electron and ion energization involving these processes. We discuss the morphology dynamics and level of LHW activity generated by electromagnetic ion cyclotron (EMIC) waves during the May 2-7 1998 storm period on the global scale. The LHWs were calculated based on a newly developed self-consistent model (Khazanov et. al. 2002) that couples the system of two kinetic equations: one equation describes the ring current (RC) ion dynamic and another equation describes the evolution of EMIC waves. It is found that the LHWs are excited by helium ions due to their mass dependent drift in the electric field of EMIC waves. The level of LHW activity is calculated assuming that the induced scattering process is the main saturation mechanism for these waves. The calculated LHWs electric fields are consistent with the observational data.

Khazanov, George V.↗
DOE OSTI2020

Fast Approximate Methods for Modified Gravity Cosmological Simulations

The accelerated expansion of the Universe poses a major theoretical puzzle. Although the assumption of a non-zero cosmological constant provides a minimal extension of general relativity that is consistent with observational data, many theories of modified gravity have been suggested as possible alternatives. Predictions of structure formation for these models in the fully nonlinear regime are very expensive and it is difficult, if not impossible, to explore such a huge space of models and parameters using high-resolution N-body simulations. Even in the mildly nonlinear regime, perturbative methods can become extremely complex. We explore whether simplified dynamical approximations, applicable for a certain set of cosmological probes, can be used to investigate models of modified gravity with acceptable accuracy in the latter instance. For the case of chameleon gravity, we find that these methods can indeed be used to explore the region around the baryon acoustic oscillation scale, k ~ 0:1 hMpc-1 but not much further.

cosmology↗
DOE OSTI2022

Efficacy and safety of warfarin in patients with non-valvular atrial fibrillation and CKD G3–G5D

ABSTRACT Background Observational data comparing warfarin with no treatment for patients with non-valvular atrial fibrillation (NVAF) and severely reduced glomerular filtration rate (GFR) are conflicting and randomized controlled trials (RCTs) are lacking. Most studies do not provide information on warfarin treatment quality, making them difficult to compare. Methods This national cohort study investigates the risk of ischaemic stroke and major bleeding during warfarin treatment compared with no oral anticoagulants in patients with NVAF, GFR category 3–5 (G3–G5) or on dialysis (G5D), with kidney transplant recipients excluded, between 2009 and 2018. Data extracted from high-quality Swedish national healthcare registries, including the Swedish Renal Registry, AuriculA—the Swedish national quality registry for atrial fibrillation and anticoagulation—and the Stroke Registry. Results At enrolment of 12 106 patients, 21.4% were G3, 43.5% were G4, 11.6% were G5 and 23.6% were G5D. The mean time in the therapeutic range was 70%. Warfarin compared with no treatment showed a lower risk for ischaemic stroke for G3 {hazard ratio [HR] 0.37 [95% confidence interval (CI) 0.18–0.76]}, G4 [0.53 (0.38–0.74)] and G5D [0.49 (0.30–0.79)] and an increased risk of major bleeding in G4 [HR 1.22 (1.02–1.46)], G5 [1.52 (1.15–2.01)] and G5D [1.23 (1.00–1.51)]. All-cause mortality was more than halved on warfarin compared with no treatment in all GFR categories. Conclusions Warfarin treatment is associated with a lower risk of ischaemic stroke for patients with NVAF and G3, G4 and G5D at the cost of a higher risk of major bleeding for G4–G5D. Existing observational data are conflicting, stressing the need for RCTs on warfarin compared with no treatment in G4–G5D. Awaiting RCTs, it seems reasonable to treat selected patients on dialysis and NVAF with warfarin.

Welander, Frida (ORCID:0000000311117215)↗
DOE OSTI2020

The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern global high-resolution models with a horizontal resolution of tens of kilometers, this is an oversight since there are likely grid cells where the physical output of a climate model is compared with a statistically interpolated quantity instead of actual measurements of the climate system. In this paper, we quantify the impact of geographic sampling on the relative performance of high-resolution climate model representations of precipitation extremes in boreal winter (December–January–February) over the contiguous United States (CONUS), comparing model output from five early submissions to the HighResMIP subproject of the CMIP6 experiment. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance. Across the models considered, failing to account for sampling impacts the different metrics (extreme bias, spatial pattern correlation, and spatial variability) in different ways (both increasing and decreasing). We argue that the geographic sampling of weather stations should be accounted for in order to yield a more straightforward and appropriate comparison between models and observational data sets, particularly for high-resolution models with a horizontal resolution of tens of kilometers. While we focus on the CONUS in this paper, our results have important implications for other global land regions where the sampling problem is more severe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The 1996 Mid-Atlantic Winter Flood: Exploring Climate Risk through a Storyline Approach

Abstract This article explores the application of thermodynamic perturbations to a historical midlatitude, wintertime, rain-on-snow flood event to evaluate how similar events may evolve under different climate forcings. In particular, we generate a hindcast of the 1996 Mid-Atlantic flood using an ensemble of 14-km variable-resolution simulations completed with the U.S. Department of Energy’s global Energy Exascale Earth System Model (E3SM). We show that the event is skillfully reproduced over the Susquehanna River Basin (SRB) by E3SM when benchmarked against in situ observational data and high-resolution reanalyses. In addition, we perform five counterfactual experiments to simulate the flood under preindustrial conditions and four different levels of warming as projected by the Community Earth System Model Large Ensemble. We find a nonlinear response in simulated surface runoff and streamflow as a function of atmospheric warming. This is attributed to changing contributions of liquid water input from a shallower initial snowpack (decreased snowmelt), increased surface temperatures and rainfall rates, and increased soil water storage. Flooding associated with this event peaks from around +1 to +2 K of global average surface warming and decreases with additional warming beyond this. There are noticeable timing shifts in peak runoff and streamflow associated with changes in the flashiness of the event. This work highlights the utility of using storyline approaches for communicating climate risk and demonstrates the potential nonlinearities associated with hydrologic extremes in areas that experience ephemeral snowpack, such as the SRB.

Meteorology & Atmospheric Sciences↗
DOE OSTI2019

UV background fluctuations and three-point correlations in the large-scale clustering of the Lyman α forest

Using the Lyman α (Lyα) Mass Association Scheme, we make theoretical predictions for the three-dimensional three-point correlation function (3PCF) of the Lyα forest at redshift z = 2.3. We bootstrap results from the (100 h -1 Mpc) 3 Horizon hydrodynamic simulation to a (1 h -1 Gpc) 3 N -body simulation, considering both a uniform ultraviolet background (UVB) and a fluctuating UVB sourced by quasars with a comoving n q ≈ 10 -5 h 3 Mpc -3 placed either in massive haloes or randomly. On scales of 10–30 h -1 Mpc, the flux 3PCF displays hierarchical scaling with the square of the two-point correlation function (2PCF), but with an unusual value of Q ≡ ζ 123 /(ξ 12 ξ 13 + ξ 12 ξ 23 + ξ 13 ξ 23 ) ≈ -4.5 that reflects the low bias of the Lyα forest and the anticorrelation between mass density and transmitted flux. For halo-based quasars and an ionizing photon mean free path of λ = 300 h -1 Mpc comoving, UVB fluctuations moderately depress the 2PCF and 3PCF, with cancelling effects on Q . For λ = 100 or 50 h -1 Mpc, UVB fluctuations substantially boost the 2PCF and 3PCF on large scales, shifting the hierarchical ratio to Q ≈ -3. We scale our simulation results to derive rough estimate of the detectability of the 3PCF in current and future observational data sets for the redshift range z = 2.1–2.6. At r = 10 and 20 h -1 Mpc, we predict a signal-to-noise ratio (SNR) of ~9 and ~7, respectively, for both Baryon Oscillation Spectroscopic Survey (BOSS) and extended BOSS (eBOSS), and ~37 and ~25 for Dark Energy Spectroscopic Instrument (DESI). At r = 40 h -1 Mpc the predicted SNR is lower by a factor of ~3–5. Measuring the flux 3PCF would provide a novel test of the conventional paradigm of the Lyα forest and help separate the contributions of UVB fluctuations and density fluctuations to Lyα forest clustering, thereby solidifying its foundation as a tool of precision cosmology.

Astronomy & Astrophysics↗
NASA NTRSDate not supplied

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗
DOE OSTI2018

Verifying and assessing the performance of the perturbation strategy in polynomial chaos ensemble forecasts of the circulation in the Gulf of Mexico

Here we present an analysis of two recent efforts aimed at quantifying the uncertainties in a 30-day HYbrid Coordinate Ocean Model forecast of the circulation in the Gulf of Mexico, with particular emphasis on the separation of Loop Current Eddy Franklin, using Polynomial Chaos methods. The analysis herein explores whether the model perturbations lead to realistic representation of the uncertainty in the Gulf Circulation. Comparisons of model output with Sea Surface Height and current mooring data show that the observational data generally falls within the envelope of the ensemble and that the modal decomposition delivers “realistic” perturbations in the Loop Current region. We use information theory metrics to quantify the information gain and the computational trade-offs between different wind and initial conditions perturbation modes. The relative entropy measures indicate that two modes for initial condition perturbations are enough, in our model configuration, to represent the uncertainty in the Loop Current region; while two modes for wind forcing perturbations are necessary in order to estimate the uncertainty in the coastal zone. The ensemble statistics are then explored using the Polynomial Chaos surrogate and the newly developed contour boxplot methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Localized Actual Meteorological Year File Creator (LAF): A tool for using locally observed weather data in building energy simulations

The Localized Actual Meteorological Year File Creator (LAF) application provides web-based access to real meteorological data and processes it into a weather file suitable for building energy modeling. Building energy consumption is affected by what is inside the building (such as occupants, appliances, HVAC systems, etc.) and by what is outside: the weather conditions the building is exposed to. However, freely available weather data files are limited to a number of specific locations, usually airports, which are often located away from city centers where buildings are concentrated. The authors have developed a new tool that supports the investigation and quantification of micro-climate conditions on building energy consumption. LAF is built on the Python open-source programming language and has a Graphical User Interface (GUI) that allows users to create custom weather data files for building energy simulations. Many sets of actual meteorological year weather data for long time periods are publicly available online (such as the MesoWest database) for thousands of locations in the US. LAF selects weather data according to user specifications and automatically processes it through an API across multiple weather stations and multiple time periods. The user may easily select a specific location, time frame, and time step that best meets their needs. This article presents a useful tool for energy modelers, building designers and operators to assist with building performance analysis and optimization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Observed positive vegetation-rainfall feedbacks in the Sahel dominated by a moisture recycling mechanism

Classic, model-based theory of land-atmosphere interactions across the Sahel promote positive vegetation-rainfall feedbacks dominated by surface albedo mechanism. However, neither the proposed positive vegetation-rainfall feedback nor its underlying albedo mechanism has been convincingly demonstrated using observational data. Here, we present observational evidence for the region’s proposed positive vegetation-rainfall feedback on the seasonal to interannual time scale, and find that it is associated with a moisture recycling mechanism, rather than the classic albedo-based mechanism. Positive anomalies of remotely sensed vegetation greenness across the Sahel during the late and post-monsoon periods favor enhanced evapotranspiration, precipitable water, convective activity and rainfall, indicative of amplified moisture recycling. The identified modest low-level cooling and anomalous atmospheric subsidence in response to positive vegetation greenness anomalies are counter to the responses expected through the classic vegetation-albedo feedback mechanism. The observational analysis further reveals enhanced dust emissions in response to diminished Sahel vegetation growth, potentially contributing to the positive vegetation-rainfall feedback.

54 ENVIRONMENTAL SCIENCES↗