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At least 595 records · Page 33

Separating Magnetospheric and Heliospheric SWCX in X-ray Spectra

Solar wind charge exchange (SWCX) emission contaminates all astrophysical observations in X-rays regardless of the direction. This contamination is particularly problematic when measuring astrophysical plasma temperatures due to the similar spectral distribution of the two phenomena. Since its discovery, literature has distinguished between SWCX emission resulting from solar wind-neutral interactions within the Earth’s magnetosphere, called magnetospheric SWCX, and similar interactions occurring more generally throughout the heliosphere, called heliospheric SWCX. Previous work demonstrated accurate modeling of the heliospheric SWCX contribution for astrophysical observations performed at low ecliptic latitude with HaloSat, a CubeSat X-ray mission of medium spectral resolution. Here, we apply this model to similarly orchestrated observations to measure the magnetospheric SWCX contribution separately from the heliospheric SWCX and the astrophysical background contributions. We describe our observational strategy, the heliospheric SWCX model used, and our spectral fitting methods. In particular, we report on four observations with lines of sight through the Earth’s magnetospheric flank with total O VII line fluxes at least 3σ above that predicted by the heliospheric SWCX model and the astrophysical background, possibly indicative of magnetospheric SWCX. We then discuss the excess emission in comparison with available magnetospheric SWCX simulations requested through the Community Coordinated Modeling Center.

X-ray↗

Effects of Water Limitation and Competition on Tree Carbon Allocation in an Earth System Modeling Framework

Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality-based approaches that predict trait–environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality-based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture. We used two models, LM3-PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3-PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two-dimensional trait space under different precipitation and mortality scenarios. At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought-tolerance). Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress. Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3-PPA vs. BiomeE) and uncalibrated vs. calibrated BiomeE versions. Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality-based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity.

vegetation demographic model↗

The Substorm Cycle as Reproduced by Global MHD Models

Recently, Gordeev et al. (2015) suggested a method to test global MHD models against statistical empirical data. They showed that four community-available global MHD models supported by the Community Coordinated Modeling Center (CCMC) produce a reasonable agreement with reality for those key parameters (the magnetospheric size, magnetic field, and pressure) that are directly related to the large-scale equilibria in the outer magnetosphere. Based on the same set of simulation runs, here we investigate how the models reproduce the global loading-unloading cycle. We found that in terms of global magnetic flux transport, three examined CCMC models display systematically different response to idealized2 h north then 2 h south interplanetary magnetic field (IMF) Bz variation. The LFM model shows a depressed return convection and high loading rate during the growth phase as well as enhanced return convection and high unloading rate during the expansion phase, with the amount of loaded unloaded magnetotail flux and the growth phase duration being the closest to their observed empirical values during isolated substorms. Two other models exhibit drastically different behavior. In the BATS-R-US model the plasma sheet convection shows a smooth transition to the steady convection regime after the IMF southward turning. In the Open GGCM a weak plasma sheet convection has comparable intensities during both the growth phase and the following slow unloading phase. We also demonstrate potential technical problem in the publicly available simulations which is related to post processing interpolation and could affect the accuracy of magnetic field tracing and of other related procedures.

Gordeev, E.↗

Breaking the reproducibility barrier with standardized protocols for plant–microbiome research

Inter-laboratory replicability is crucial yet challenging in microbiome research. Leveraging microbiomes to promote soil health and plant growth requires understanding underlying molecular mechanisms using reproducible experimental systems. In a global collaborative effort involving five laboratories, we aimed to help advance reproducibility in microbiome studies by testing our ability to replicate synthetic community assembly experiments. Our study compared fabricated ecosystems constructed using two different synthetic bacterial communities, the model grass Brachypodium distachyon, and sterile EcoFAB 2.0 devices. All participating laboratories observed consistent inoculum-dependent changes in plant phenotype, root exudate composition, and final bacterial community structure, where Paraburkholderia sp. OAS925 could dramatically shift microbiome composition. Comparative genomics and exudate utilization linked the pH-dependent colonization ability of Paraburkholderia, which was further confirmed with motility assays. The study provides detailed protocols, benchmarking datasets, and best practices to help advance replicable science and inform future multi-laboratory reproducibility studies.

Novak, Vlastimil↗

Leveraging High-resolution Molecular Composition of Soil Organic Matter to Enhance Carbon Cycling Modeling

Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.

54 ENVIRONMENTAL SCIENCES↗

Simulations of Water Vapor in the Upper Troposphere and Lower Stratosphere

A detailed study of the water vapor budget in the upper troposphere and lower stratosphere of the "Finite Volume CCM3" (FVCCM3) model is presented. The model is based on a combination of a finite-volume dynamical core (developed by Lin and Rood) and the physical package from Version 3 of the Community Climate Model (CCM3, developed at NCAR). The model was used with a horizontal resolution of 2 by 2.5 degrees and 55 levels, with the upper boundary at 0.0lhPa and a vertical resolution of about 1.2km near the tropopause. Most results presented are from a 17-year simulation performed for the Atmospheric Model Intercomparison Project. It is shown that the model simulates a realistic thermal structure in the tropical tropopause region and that water vapor distributions are in qualitative accord with observations (which are uncertain). The longitudinal structure of the tropical atmosphere is slightly too asymmetric, compared to reasonable estimates of the truth. The processes leading to the horizontal and vertical transport of water vapor in the tropopause region are analyzed in detail. Special attention is given to the realism of horizontal transport events (the ability of the model to retain sharply defined features) and to the role of localized vertical motions in transporting air (and water vapor) between the troposphere and stratosphere. It is shown that the vertical transport of water vapor in the tropical lower stratosphere occurs at about the same rate as that observed, while in many other models this vertical transport is too fast.

Pawson, Steven↗

RAM-SCB Runs on Request at CCMC

The Ring current–Atmosphere interactions Model (RAM) with Self-Consistent magnetic (B) field (SCB) combines a large-scale kinetic model of ring current plasma with a three-dimensional (3-D) force-balanced model of the terrestrial magnetic field. RAM-SCB simulates the evolution of major ion species (H + , O + , and He + by default) and electrons as a function of azimuth, radial distance, energy, and pitch angle. Simulation outputs include the Dst index, and pressure and differential flux of the modeled species, thus providing benefit as a science code and to inform surface charging hazard within the model domain. Version 2.2 of this open-source simulation code has now—as of 8 August 2023—been made available for Runs-On-Request via the Community Coordinated Modeling Center.

79 ASTRONOMY AND ASTROPHYSICS↗

Impact of host climate model on contrail cirrus effective radiative forcing estimates

Estimates of aviation effective radiative forcing (ERF) indicate that contrail cirrus is currently its largest contributor, although with a substantial associated uncertainty of ∼ 70 %. Here, we implement the contrail parameterisation developed for the Community Atmosphere Model (CAM) in the UK Met Office Unified Model (UM), allowing us to compare, for the first time, the impact of key features of the host climate model on contrail cirrus ERF. We find that differences in background humidity between the models result in the UM-simulated contrail fractions being 2 to 3 times larger than in CAM. Additionally, the models show contrasting responses in overall global cloud fraction, with contrails increasing the total cloud fraction in the UM and decreasing it in CAM. Differences in the complexity of the cloud microphysics schemes lead to significant differences in simulated changes to cloud ice water content due to aviation. After compensating for the unrealistically low contrail optical depth in the UM, we estimate the 2018 contrail cirrus ERF to be 40.8 mW m−2 in the UM, compared to 60.1 mW m−2 in CAM. These values highlight the substantial uncertainty in contrail cirrus ERF due to differences in microphysics and radiation schemes between the two models. We also find a factor-of-8 uncertainty in contrail cirrus ERF due to existing uncertainty in contrail cirrus optical depth. Future research should focus on better representing microphysical and radiative contrail characteristics in climate models and on improved observational constraints.

Zhang, Weiyu [University of Leeds (United Kingdom)↗

United States Multi-Sector Dynamics land use and land cover base maps to support Human-Earth System Modeling

Datasets are land use and land cover (LULC) rasterized base maps at 30-m resolution for the conterminous United States (CONUS) for the years 2008, 2011, 2016, and 2019. Separate base maps are provided where LULC classifications are thematically congruent with Community Land Model (CLM), Land Use Harmonization (LUH2), and Global Change Analysis Model (GCAM), and a detailed decomposition of all combined land classes into a Multisector Dynamics (MSD) LULC product. Base maps were developed using empirically derived satellite (National Land Cover Dataset, MODIS) and combined observation datasets (Crop Data Layer, Protected Areas Database) and represent the most up-to-date accurate information on LULC in the CONUS. The four datasets encompass four different landcover classification systems: MSD Layers - The raw landcover classes obtained from reclassifying NLCD and USDA Crop data layers into a respective landcover class GCAM Layers - The MSD classes mosaiced, reclassified, and combined into the respective GCAM landcover classes CLM Layers - Similar process to GCAM layers, but mosaiced, reclassified, and combined MSD layers to their respective PFT classes LUH2 Layers - Similar process to both GCAM and CLM Layers, but mosaiced, reclassified and combined the MSD layers to align with the respective states

Food↗

Orographic Cirrus and Its Radiative Forcing in NCAR CAM6

Cirrus clouds play an important role in the Earth's radiative energy budget, thereby affecting the climate state and climate change. Orographic gravity wave (OGW)-induced sub-grid scale vertical velocity (i.e., cooling rate) is not resolved by large-scale models and its impact on ice formation in cirrus clouds is not well quantified. In this study, one sub-grid scale OGW scheme (e.g., McFarlane) is used in the Community Atmosphere Model version 6 (CAM6) to generate vertical velocity variance (σw) for cirrus formation. Results from the default model and simulations with the OGW-induced σw are evaluated against the DOE ARM Small Particles in Cirrus (SPARTICUS) campaign observations. The OGW based on the McFarlane scheme increases the sub-grid scale σw over mountains compared to the default model and improves the model agreement with the SPARTICUS observations. Larger σ w due to OGWs can trigger more frequent homogeneous nucleation in orographic cirrus and generates a higher number concentration of ice crystals observed during the SPARTICUS campaign. Moreover, our evaluation of the model simulations against satellite observations indicates that the McFarlane scheme generates high in-cloud ice number concentrations (>200 L -1 ) in the upper troposphere over mountains and high plateaus at mid- and high-latitudes of the winter hemisphere as shown in the observations. More ice crystals with smaller sizes absorb more infrared radiation (+0.523 ± 0.125 W m -2 ). The net radiative cloud forcing change at the top of the atmosphere is +0.330 W m -2 due to the orographic cirrus.

54 ENVIRONMENTAL SCIENCES↗

Response of Global SSTs and ENSO to the Atlantic and Pacific Meridional Overturning Circulations

Consequences from a slowdown or collapse of the Atlantic meridional overturning circulation (AMOC) could include modulations to El Niño–Southern Oscillation (ENSO) and development of the Pacific meridional overturning circulation (PMOC). Despite potential ramifications to the global climate, our understanding of the influence of various AMOC and PMOC states on ENSO and global sea surface temperatures (SSTs) remains limited. Five multicentennial, fully coupled model simulations created with the Community Earth System Model were used to explore the influence of AMOC and PMOC on global SSTs and ENSO. We found that the amplitude of annual cycle SSTs across the tropical Pacific decreases and ENSO amplitude increases as a result of an AMOC shutdown, irrespective of PMOC development. However, active deep overturning circulations in both the Atlantic and Pacific basins reduce ENSO amplitude and variance of monthly SSTs globally. Furthermore, the underlying physical reasons for changes to global SSTs and ENSO are also discussed, with the atmospheric and oceanic mechanisms that drive changes to ENSO amplitude differing based on PMOC state. These results suggest that if climate simulations projecting AMOC weakening are realized, compounding climate impacts could occur given the far-reaching ENSO teleconnections to extreme weather and climate events. More broadly, these results provide us with insight into past geologic era climate states, when PMOC was active.

54 ENVIRONMENTAL SCIENCES↗

A More La Niña–Like Response to Radiative Forcing after Flux Adjustment in CESM2

Abstract In response to greenhouse gas forcing, most coupled global climate models project the tropical Pacific SST trend toward an “El Niño–like” state, with a reduced zonal SST gradient and a weakened Walker circulation. However, observations over the last five decades reveal a trend toward a more “La Niña–like” state with a strengthening zonal SST gradient. Recent research indicates that the identified trend differences are unlikely to be entirely due to internal variability and probably result, at least in part, from systematic model biases. In this study, Community Earth System Model, version 2 (CESM2), is used to explore how mean-state biases within the model may influence its forced response to radiative forcing in the tropical Pacific. The results show that using flux adjustment to reduce the mean-state bias in CESM2 over the tropical regions results in a more La Niña–like trend pattern in the tropical Pacific, with a strengthening of the tropical Pacific zonal SST gradient and a relatively enhanced Walker circulation, as hypothesized to occur if the ocean thermostat mechanism is stronger than the atmospheric mechanisms which by themselves would weaken the Walker circulation. We also find that the historical strengthening of the tropical Pacific zonal gradient is transient but persists into the near term in a high-emissions future warming scenario. These results suggest the potential of flux adjustment as a method for developing alternative projections that represent a wider range of possible future tropical Pacific warming scenarios, especially for a better understanding of regional patterns of climate risk in the near term.

Zhuo, Jing-Yi [Lamont-Doherty Earth Observatory, C↗

Agricultural Impacts on Nitrogen Cycling: Climate and Air Pollution (Final Technical Report)

We have successfully added a parameterization of ammonia emissions from synthetic fertilizer and manure from agriculture to Earth System Models. We have evaluated how emissions change in the future and the processes driving these changes. We have examined the impact of agricultural ammonia emissions on present-day air quality and have evaluated the impact of resolving the emissions with high temporal resolution. We have also examined the impact of how Earth System Models treat the cycling of emissions in soils. Our code, the Flows of Agricultural Nitrogen – version 2 – model (FANv2) has been run in both the CLM framework and the ELM framework. To my knowledge the code has not yet been fully implemented into ELM. Volatilization of ammonia (NH3) from fertilizers and livestock wastes forms a significant pathway of nitrogen losses in agricultural ecosystems and constitutes the largest source of atmospheric emissions of NH3. We have provided a major update to the process model FAN (Flow of Agricultural Nitrogen), which evaluates NH3 emissions interactively within an Earth system model; in this work, the Community Earth System Model (CESM) is used. The updated version (FANv2) includes a more detailed treatment of both physical and agricultural processes, which allows the model to differentiate between the volatilization losses from animal housings, manure storage, grazed pastures, and the application of manure and different types of mineral fertilizers. The modeled ammonia emissions are first evaluated at a local scale against experimental data for various types of fertilizers and manure, and they are subsequently run globally to evaluate NH3 emissions for 2010–2015 based on gridded datasets of fertilizer use and livestock populations. Comparison of regional emissions shows that FANv2 agrees with previous inventories for North America and Europe and is within the range of previous inventories for China. However, due to higher NH3 emissions in Africa, India, and Latin America, the global emissions simulated by FANv2(48 Tg N) are 30 %–40 % higher than in the existing inventories.

54 ENVIRONMENTAL SCIENCES↗

LA100 Equity Strategies. Chapter 6: Universal Access to Safe and Comfortable Home Temperatures

The LA100 Equity Strategies project integrates community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. This chapter focuses on housing weatherization and cooling technologies as means to increase access to safe and comfortable home temperatures. Lack of cooling access and use can have severe health impacts on building occupants during heat waves. Specifically, NREL developed and used a residential building stock model to simulate the energy use of 50,000 dwellings representing the diversity of housing types, appliances, climate zones, and household incomes across Los Angeles. We compared a baseline scenario with seven upgrade scenarios. Five scenarios cooled the entire household and featured cooling systems at varying efficiency levels with various improvements to the envelope, roof, and shading, and two scenarios cooled a single room in a household with no prior cooling using either a room air-conditioning or a heat pump system. For each scenario, we evaluated impacts on utility bills, payback periods, and changes in energy burdens, as well as ability to achieve safe and comfortable temperatures. We also examined the effects of building types (multifamily vs. single-family) on indoor air temperatures. Based on the results of modeling, analysis, and community guidance, we identified six short-term and two long-term strategies for improving access to building envelope upgrades and cooling strategies that could save lives and maintain safe home temperatures for Los Angeles' low-income households during heat waves. Research was guided by input from the community engagement process, and associated equity strategies are presented in alignment with that guidance.

air conditioning↗

An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen version 2 (FANv2)

Abstract. Volatilization of ammonia (NH 3 ) from fertilizers and livestock wastes forms a significant pathway of nitrogen losses in agricultural ecosystems and constitutes the largest source of atmospheric emissions of NH 3 . This paper describes a major update to the process model FAN (Flow of Agricultural Nitrogen), which evaluates NH 3 emissions interactively within an Earth system model; in this work, the Community Earth System Model (CESM) is used. The updated version (FANv2) includes a more detailed treatment of both physical and agricultural processes, which allows the model to differentiate between the volatilization losses from animal housings, manure storage, grazed pastures, and the application of manure and different types of mineral fertilizers. The modeled ammonia emissions are first evaluated at a local scale against experimental data for various types of fertilizers and manure, and they are subsequently run globally to evaluate NH3 emissions for 2010–2015 based on gridded datasets of fertilizer use and livestock populations. Comparison of regional emissions shows that FANv2 agrees with previous inventories for North America and Europe and is within the range of previous inventories for China. However, due to higher NH 3 emissions in Africa, India, and Latin America, the global emissions simulated by FANv2 (48 Tg N) are 30 %–40 % higher than in the existing inventories.

Vira, Julius↗

A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

54 ENVIRONMENTAL SCIENCES↗