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At least 361 records · Page 20

A Novel Framework to Project the Permafrost Fate With Explicit Quantification of Soil Property and Future Climate Uncertainties

This study develops a novel general framework to project the permafrost fate with rigorous uncertainty quantification to assess dominant sources. Borehole temperature records from three sites in the Russian western Arctic are used to constrain the uncertainty of a high‐fidelity freeze‐thaw model. Projections from 9 Global Climate Models (GCM) are stochastically downscaled to generate future trajectories of surface ground heat flux. Under the two emission scenarios SSP2‐4.5 and SSP5‐8.5, the projected average thawing depths by 2100 vary from 0.4 to 14.4 m or 2.1 to 17.7 m, and the increase in the top 10 m average temperature from 2015 to 2100 is 1.2–2.7°C or 1.9–3.0°C. The results show that the freeze‐thaw model uncertainty can sometimes dominate over that of GCM outputs, calling for site‐specific information to improve model accuracy. The framework is applicable for understanding permafrost degradation and related uncertainties at larger scales.

Bayesian downscaling↗

On the Dependence of Simulated Convection on Domain Size in CRMs

Abstract We present a heuristic model to explain the suppression of deep convection in convection‐resolving models (CRMs) with a small number of grid columns, such as those used in super‐parameterized or multi‐scale modeling framework (MMF) general circulation models (GCM) of the atmosphere. Domains with few grid columns require greater instability to sustain convection because they force a large convective fraction, driving strong compensating subsidence warming. Updraft dilution, which is stronger for reduced horizontal grid spacing, enhances this effect. Thus, suppression of deep convection in CRMs with few grid columns can be reduced by increasing grid spacing. Radiative‐convective equilibrium simulations using standalone CRM simulations with the System for Atmospheric Modeling (SAM) and using GCM‐coupled CRM simulations with the Energy Exascale Earth System Model (E3SM)‐MMF confirm the heuristic model results.

CRM↗

An Integrated Hydroclimatic Assessment of Future Reservoir and Hydropower Operations in the U.S.

The engineering of rivers by dams is a formative feature of human-nature systems and the interconnectivity of water, energy, and the climate. Sufficient and broad-based representations of dams in large-scale hydrological models prove essential to mapping their extensive regulation of river flow and biogeochemistry and gauging climate-linked provisions, including freshwater supply and hydropower. We present an integrated modeling framework to investigate future streamflow and hydropower generation in the Contiguous U.S. (1990–2075), leveraging an ensemble of six downscaled and bias-corrected General Circulation Models (GCMs) from the high-end SSP585 scenario of the CMIP6. To achieve this, we develop a reservoir operations and parameterization scheme for 1,384 dams in a high-resolution river network, including simulated hydropower generation for 326 dams. For the GCM ensemble mean, we simulate a widespread increase in regulated streamflow into the late-century (11% annual and 17% in winter for the dam median) with region-specific changes in summer streamflow that feature prominent declines in the Northwest (−7%). Mediation by reservoirs is shown to dampen intra-annual streamflow changes, delivering additional summer releases that partially mitigate declining flows. Total hydropower generation is projected to increase modestly (+3%), with boosted generation in the winter (+9%) and spring (+5%) offsetting declined summer generation (−3.4%), suggesting strong adaptation potential for hydropower in the future energy portfolio. Further analysis reveals that the choice of GCM, particularly in western regions, has significant bearing on projected streamflow and hydropower changes.

13 HYDRO ENERGY↗

Examining the Robustness of Weakened Orographic Influence on Precipitation in Downscaled Climate Projections Over the Western US

Assessing local climate change impacts often requires downscaling coarse global climate model (GCM) output to finer resolution. Two main approaches exist: dynamical downscaling using high-resolution regional climate models, and statistical downscaling based on historical relationships between large-scale and local variables. In a recent analysis of five dynamically downscaled simulations over the western United States, Koszuta et al. (2024, https://doi.org/10.1029/2023gl107298) found that warming weakens orographic influence on winter precipitation, damping increases on windward slopes and amplifying them in rain-shadowed regions. Here we show that this effect is robust across seasons and multiple dynamically downscaled ensembles, and is more pronounced at higher model resolutions. However, it is absent in projections from a widely used statistical model (LOCA2), even when trained on high-resolution future simulations (LOCA2-Hybrid). This highlights a key limitation of many statistical downscaling methods: their preservation of parent GCM trends, which usually fail to capture emergent changes in orographic precipitation patterns.

54 ENVIRONMENTAL SCIENCES↗

Scientific data from precipitation driver response model intercomparison project

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth’s radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.

54 ENVIRONMENTAL SCIENCES↗

Prototype hardware design and testing of the global common module for the global trigger subsystem of the ATLAS phase-II upgrade

We report the High-Luminosity Large Hadron Collider (HL-LHC) will deliver more than ten times the integrated luminosity of the previous runs combined. Meeting its stricter throughput requirements poses new challenges to the Trigger and Data Acquisition (TDAQ) systems of the LHC experiments. Introduced in the framework of the ATLAS experiment’s HL upgrade, the Global Trigger (GT) is a new subsystem which will perform offline-like algorithms on full-granularity calorimeter data. The implementation of the GT’s functionality is firmware-focused and is composed of three layers: multiplexing (or data aggregating), global event processing, and demultiplexing interface to the central trigger processor. Each layer will be composed of several, similar nodes, hosted on replicas of identical hardware, the Global Common Module (GCM), an ATCA front board which is designed to be adopted throughout the entire GT subsystem. This article proceeds from the TWEPP 2021 conference and presents the GCM hardware design, performed in 2020, and focuses on some key results of its extensive testing performed in 2021.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Role of momentum in the generator-coordinate method applied to barrier penetration

Nuclear fission at barrier-top energies is conventionally modeled by a one-dimensional Schrödinger equation applied to internal fission channels, but that treatment is hard to justify in the configuration-interaction approach to nuclear Hamiltonians. Here we show that inclusion of states of finite momentum by the generator coordinate method (GCM) considerably extends the range of energies at which GCM-based Hamiltonians could reproduce the Schrödinger treatment. Furthermore, the transmission probabilities for crossing the barrier are calculated by a discrete version of Kohn's variational method, which may also be useful for other systems of interacting fermions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Differential credibility assessment for statistical downscaling

Climate science is increasingly using (i) ensembles of climate projections from multiple models derived using different assumptions and/or scenarios and (ii) process-oriented diagnostics of model fidelity. Efforts to assign differential credibility to projections and/or models are also rapidly advancing. A framework to quantify and depict the credibility of statistically downscaled model output is presented and demonstrated. Here, the approach employs transfer functions in the form of robust and resilient generalized linear models applied to downscale daily minimum and maximum temperature anomalies at 10 locations using predictors drawn from ERA-Interim reanalysis and two global climate models (GCM; GFDL-ESM2M and MPI-ESM-LR). The downscaled time series are used to derive several impact relevant CLIMDEX temperature indices that are assigned credibility based on (1) the reproduction of relevant large-scale predictors by the GCMs (i.e. fraction of regression beta-weights derived from predictors that are well-reproduced) and (2) the degree of variance in the observations reproduced in the downscaled series following application of a new variance inflation technique. Credibility of the downscaled predictands varies across locations, between the two GCM and is generally higher for minimum temperature than maximum temperature. The differential credibility assessment framework demonstrated here is easy to use and flexible. It can be applied as is to inform decision makers regarding projection confidence, and/or extended to include other components of the transfer functions, and/or used to weight members of a statistically downscaled ensemble.

54 ENVIRONMENTAL SCIENCES↗

The Role of Radiative Interactions in Tropical Cyclone Development under Realistic Boundary Conditions

Abstract The impact of radiative interactions on tropical cyclone (TC) climatology is investigated using a global, TC-permitting general circulation model (GCM) with realistic boundary conditions. In this model, synoptic-scale radiative interactions are suppressed by overwriting the model-generated atmospheric radiative cooling rates with their monthly varying climatological values. When radiative interactions are suppressed, the global TC frequency is significantly reduced, indicating that radiative interactions are a critical component of TC development even in the presence of spatially varying boundary conditions. The reduced TC activity is primarily due to a decrease in the frequency of pre-TC synoptic disturbances (“seeds”), whereas the likelihood that the seeds undergo cyclogenesis is less affected. When radiative interactions are suppressed, TC genesis shifts toward coastal regions, whereas TC lysis locations stay almost unchanged; together the distance between genesis and lysis is shortened, reducing TC duration. In a warmer climate, the magnitude of TC reduction from suppressing radiative interactions is diminished due to the larger contribution from latent heat release with increased sea surface temperatures. These results highlight the importance of radiative interactions in modulating the frequency and duration of TCs.

Meteorology & Atmospheric Sciences↗

CYPminer: an automated cytochrome P450 identification, classification, and data analysis tool for genome data sets across kingdoms

Background: Cytochrome P450 monooxygenases (termed CYPs or P450s) are hemoproteins ubiquitously found across all kingdoms, playing a central role in intracellular metabolism, especially in metabolism of drugs and xenobiotics. The explosive growth of genome sequencing brings a new set of challenges and issues for researchers, such as a systematic investigation of CYPs across all kingdoms in terms of identification, classification, and pan-CYPome analyses. Such investigation requires an automated tool that can handle an enormous amount of sequencing data in a timely manner. Results: CYPminer was developed in the Python language to facilitate rapid, comprehensive analysis of CYPs from genomes of all kingdoms. CYPminer consists of two procedures i) to generate the Genome-CYP Matrix (GCM) that lists all occurrences of CYPs across the genomes, and ii) to perform analyses and visualization of the GCM, including pan-CYPomes (pan- and core-CYPome), CYP co-occurrence networks, CYP clouds, and genome clustering data. The performance of CYPminer was evaluated with three datasets from fungal and bacterial genome sequences. Conclusions: CYPminer completes CYP analyses for large-scale genomes from all kingdoms, which allows systematic genome annotation and comparative insights for CYPs. CYPminer also can be extended and adapted easily for broader usage.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of oceanic post-cold frontal clouds and their model representation. Final report

Low-level clouds are ubiquitous over the oceans, and their impact on the Earth’ radiative budget is important. However, general circulation models (GCMs) that are used to represent our climate and its evolution still experience problems to represent their correct amount and radiative impact. In the extratropical latitudes (~30-60 N/S), cloud properties are strongly modulated by the occurrence of anti-cyclones (high pressure systems) and cyclones (low pressure systems). While deep clouds dominate in cyclones near the center and along the cold and warm fronts, low-level clouds populate the colder regions of the cyclones, and more specifically the region in the wake of the cold fronts, the post-cold frontal region (PCF). The GCMs mentioned above were found to underestimate the amount of these PCF clouds, and this caused errors in their representation of the amount of solar radiation at the surface of the southern hemisphere oceans, causing an excess in absorption and errors in long-term predictions. To better understand which processes are ill-represented in the GCMs to cause such issues, we used ground-based observations from the Eastern North Atlantic (ENA) ARM site and a high resolution regional model (called WRF) to examine the properties of PCF clouds. With the WRF model, we simulated the passage of a cold front at the ENA site using theoretically distinct representations of convection and the physics of the boundary layer. While these physical representations had little impact on the timing, structure and circulation of the cold front, we found a high sensitivity to how the large scale information was fed into the model. Errors rapidly developed if the incoming flow information was injected too far from the site, but 1000 km was found to be an optimal distance between the outer boundary and the ENA site for a realistic cold front passage. With this model, we then conducted a series of experiment where convection and boundary layer schemes were changed, and revealed that 1) the clouds were more sensitive to the convection than boundary layer schemes and 2) the interaction between the two has a large impact. Furthermore, changing the representation of the physics in the model had greater impacts on PCF clouds than changing the initial conditions. As large-scale models increase their spatial resolution, convection will eventually be resolved but it remains that their representation of the physics of the boundary layer will matter for the correct representation of shallow (low-level) clouds. Observations were used to find which large-scale information had a clear relationship with PCF cloud and precipitation properties, in view of helping with GCM parameterizations and evaluation. Both lower troposphere stability and surface forcing were found to be important for PCF clouds that experience more vigorous dynamics than their tropical or subtropical counterparts. For cloud base and top heights, a simple measure of the change in potential temperature between the surface and the 800 hPa was found to be a good predictor. This relationship was found to hold as well when using data from campaigns recently conducted in the southern ocean south of Tasmania. A recent GCM was found to succeed in representing similar relations. For cloud depth, water content, and different characteristics of precipitation both the temperature contrast between the surface and near-air and the near-surface wind speed had a strong relationship. To summarize, through observational constraints and regional model experiments, the project has provided guidance to evaluate GCMs and tools to improve their representation of low-level clouds in the extratropics. It has also highlighted differences in behavior between these clouds and those typically found in the subtropics, thus opening new avenues of research for shallow clouds in general.

54 ENVIRONMENTAL SCIENCES↗

Enhancing Convection Parameterization for Next Generation E3SM (Final Technical Report)

This technical report summarizes the achievements during the project period. The general goal of the project is to enhance the representation of atmospheric deep convection in the DOE global climate model E3SM. By implementing a stochastic convection scheme into E3SM, we improved the simulation of precipitation intensity and frequency. As a result, it has a profound impact on the simulation of other fields in the model, including aerosol scavenging by precipitation and aerosol radiative effects. We also implemented a convective cloud microphysics scheme into E3SMv2 to represent more accurately the interaction between convection and grid-scale clouds. An extensive analysis of model simulations as part of the Next Generation Development (NGD) convection scheme assessment project found that including the convective microphysics scheme improved the simulation of Madden-Julian oscillations (MJO) in the model. To make convective parameterization schemes more scale-aware as the GCM resolution increases, we analyzed the output from cloud-resolving model (CRM) simulations of both organized and unorganized convection by coarse-graining the CRM data to different GCM resolutions. Using a novel approach to modify the convective closure, we demonstrated that the convection scheme used in E3SM (ZM scheme) can be made scale-aware.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of Global Climate Models for Use in Energy Analysis

The interplay between energy, climate, and weather is becoming more complex due to increasing contributions of renewable energy generation, energy storage, electrified end uses, and the increasing frequency of extreme weather events. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and subjective process. In this work, we assess datasets from various global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We present evaluations of their skills with respect to the historical climate and comparisons of their future projections of climate change for two climate change scenarios. We present the results for different climatic and energy system regions and include interactive figures in the accompanying software repository. Previous work has presented similar GCM evaluations, but none have presented variables and metrics specifically intended for comprehensive energy systems analysis including impacts on energy demand, thermal cooling, hydropower, water availability, solar energy generation, and wind energy generation. We focus on GCM output meteorological variables that directly affect these energy system components including the representation of extreme values that can drive grid resilience events. The objective of this work is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and scenarios in subsequent work.

14 SOLAR ENERGY↗

Pluminate: Quantifying aerosol injection behavior from simulation, experimentation and observations

Marine aerosol injections are a key component in further understanding of both the potentials of deliberate injection for marine cloud brightening (MCB), a potential climate intervention (CI) strategy, and key aerosol-cloud interaction behaviors that currently form the largest uncertainty in global climate model (GCM) predictions of our climate. Since the rate of spread of aerosols in a marine environment directly translates to the effectiveness and ability of aerosol injections in impacting cloud radiative forcing, it is crucial to understand the spatial and temporal extent of injected-aerosol effects following direct injection into marine environments. The ubiquity of ship-injected aerosol tracks from satellite imagery renders observational validation of new parameterizations possible in 2D, however, 3D compatible data is more scarce, and necessary for the development of subgrid scale parameterizations of aerosol-cloud interactions in GCMs. This report introduces two novel parameterizations of atmospheric aerosol injection behavior suitable for both 3D (GCM-compatible) and 2D (observation-related) modeling. Their applicability is highlighted using a wealth of different observational data: small and larger scale salt-aerosol injection experiments conducted at SNL, 3D large eddy simulations of ship-injected aerosol tracks and 2D satellite images of ship tracks. The power of experimental data in enhancing knowledge of aerosol-cloud interactions is in particular emphasized by studying key aerosol microphysical and optical properties as observed through their mixing in cloud-like environments.

54 ENVIRONMENTAL SCIENCES↗

Using MARCUS, MICRE, and COMBLE data to improve understanding and modeling of cloud, aerosol, and boundary layer processes at high-latitudes

Because it is believed general circulation (GCM) and numerical weather prediction (NWP) models underestimate shortwave radiation over the Southern Ocean (SO) due to inadequate representations of boundary layer (BL) and cloud processes, it is critical to improve our understanding of key aerosol, cloud, precipitation, and BL processes. Over the north Atlantic Ocean (NA), cold-air outbreaks are common, yet few studies of the aerosol and environmental controls of the associated convective BL clouds exist as needed to develop and evaluate GCM representations. Although processes cannot be observed, cloud and aerosol properties can be measured in-situ or remotely retrieved, which when combined with numerical simulations enable process level understanding required to improve model representations.

54 ENVIRONMENTAL SCIENCES↗

A clustering-based approach to ocean model–data comparison around Antarctica

The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changing element of the Earth system. Analyses of global-scale general circulation model (GCM) simulations, including those available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6), can help reveal the origins of observed changes and predict the future evolution of the ACSS. However, an evaluation of ACSS hydrography in GCMs is vital: previous CMIP ensembles exhibit substantial mean-state biases (reflecting, for example, misplaced water masses) with a wide inter-model spread. Because the ACSS are also a sparely sampled region, grid-point-based model assessments are of limited value. Our goal is to demonstrate the utility of clustering tools for identifying hydrographic regimes that are common to different source fields (model or data), while allowing for biases in other metrics (e.g., water mass core properties) and shifts in region boundaries. We apply K-means clustering to hydrographic metrics based on the stratification from one GCM (Community Earth System Model version 2; CESM2) and one observation-based product (World Ocean Atlas 2018; WOA), focusing on the Amundsen, Bellingshausen and Ross seas. When applied to WOA temperature and salinity profiles, clustering identifies “primary” and “mixed” regimes that have physically interpretable bases. For example, meltwater-freshened coastal currents in the Amundsen Sea and a region of high-salinity shelf water formation in the southwestern Ross Sea emerge naturally from the algorithm. Both regions also exhibit clearly differentiated inner- and outer-shelf regimes. The same analysis applied to CESM2 demonstrates that, although mean-state model biases in water mass T–S characteristics can be substantial, using a clustering approach highlights that the relative differences between regimes and the locations where each regime dominates are well represented in the model. CESM2 is generally fresher and warmer than WOA and has a limited fresh-water-enriched coastal regimes. Given the sparsity of observations of the ACSS, this technique is a promising tool for the evaluation of a larger model ensemble (e.g., CMIP6) on a circum-Antarctic basis.

54 ENVIRONMENTAL SCIENCES↗

Xanthos Output Dataset Under ISIMIP3b Selected CMIP6 Scenarios: 1850 - 2100

Overview Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyze global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Analysis Model (GCAM). Details This dataset includes Xanthos outputs forced by the ISIMIP3b bias-adjusted CMIP6 climate forcing (1850 - 2100). There are 30 scenarios consists of 10 Coupled Model Intercomparison Project phase 6 (CMIP6) General Circulation Models (GCM) and 3 Shared Socioeconomic Pathways (SSP). Each folder is named as cmip6_{gcm}_{ensemble-member}_{ssp}. 10 CMIP6 GCMs: GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL, CanESM5, CNRM-CM6-1, CNRM-ESM2-1, EC-Earth3, and MIROC6 3 SSP-RCP Scenarios: SSP1-2.6, SSP3-7.0, and SSP5-8.5 The table below summarizes the details of output variables within each scenario folder. | Output Variable | File Short Name | Spatial Resolution | Unit | | ----------------------------------------------- | -------------------------------------- | -------------------------------- | --------------------- | | Runoff | q | 0.5x0.5 degree | km3/month | | Runoff | Basin_runoff | GCAM basin | km3/month | | Runoff | Country_runoff | Country | km3/month | | Runoff | GCAMRegion_runoff | GCAM region | km3/month | | Streamflow | avgchflow | 0.5x0.5 degree | m3/second | | Potential Evapotranspiration | pet | 0.5x0.5 degree | km3/month | | Actual Evapotranspiration | aet | 0.5x0.5 degree | km3/month | | Accessible Water | accessible_water | GCAM basin | km3/year | | Hydropower Generation | actual_hydro | GCAM region | EJ/year |

Climate Change↗

Xanthos Output Dataset Under ISIMIP3b Selected CMIP6 Scenarios: 1850 - 2100

Overview Xanthos is an open-source hydrologic model, written in Python, designed to quantify and analyze global water availability. Xanthos simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos was designed to be extensible and used by scientists that study global water supply and work with the Global Change Analysis Model (GCAM). Details This dataset includes Xanthos outputs forced by the ISIMIP3b bias-adjusted CMIP6 climate forcing (1850 - 2100). There are 30 scenarios consists of 10 Coupled Model Intercomparison Project phase 6 (CMIP6) General Circulation Models (GCM) and 3 Shared Socioeconomic Pathways (SSP). Each folder is named as cmip6_{gcm}_{ensemble-member}_{ssp}. 10 CMIP6 GCMs: GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL, CanESM5, CNRM-CM6-1, CNRM-ESM2-1, EC-Earth3, and MIROC6 3 SSP-RCP Scenarios: SSP1-2.6, SSP3-7.0, and SSP5-8.5 The table below summarizes the details of output variables within each scenario folder. | Output Variable | File Short Name | Spatial Resolution | Unit | | ----------------------------------------------- | -------------------------------------- | -------------------------------- | --------------------- | | Runoff | q | 0.5x0.5 degree | km3/month | | Runoff | Basin_runoff | GCAM basin | km3/month | | Runoff | Country_runoff | Country | km3/month | | Runoff | GCAMRegion_runoff | GCAM region | km3/month | | Streamflow | avgchflow | 0.5x0.5 degree | m3/second | | Potential Evapotranspiration | pet | 0.5x0.5 degree | km3/month | | Actual Evapotranspiration | aet | 0.5x0.5 degree | km3/month | | Accessible Water | accessible_water | GCAM basin | km3/year | | Hydropower Generation | actual_hydro | GCAM region | EJ/year |

Climate Change↗