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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Predicting Future Disease Burden in a Rapidly Changing Climate

The interplay of a rapidly changing climate and infectious disease occurrence is emerging as a critical topic, requiring investigation of possible direct, as well as indirect, connections between disease processes and climate-related variation and phenomena. First, we introduce and overview three infectious disease exemplars (dengue, influenza, valley fever) representing different transmission classes (insect-vectored, human-to-human, environmentally-transmitted) to illuminate the complex and significant interplay between climate disease processes, as well as to motivate discussion of how Sandia can transform the field, and change our understanding of climate-driven infectious disease spread. We also review state-of-the-art epidemiological and climate modeling approaches, together with data analytics and machine learning methods, potentially relevant to climate and infectious disease studies. We synthesize the modeling and disease exemplars information, suggesting initial avenues for research and development (R&D) in this area, and propose potential sponsors for this work. Whether directly or indirectly, it is certain that a rapidly changing climate will alter global disease burden. The trajectory of climate change is an important control on this burden, from local, to regional and global scales. The efforts proposed herein respond to the National Research Councils call for the creation of a multidisciplinary institute that would address critical aspects of these interlocking, cascading crises.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Baseline Climate Variables for Earth System Modelling

The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 135 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most frequently used elements of the Coupled Model Intercomparison Project Phase 6 (CMIP6) archive. Successive phases of CMIP have supported strong results in science and substantially influence international climate policy formulation. This paper responds to both interest in exploiting CMIP data standards in a broader range of climate modelling activities and a need to achieve greater clarity about the significance and intention of variables in the CMIP Data Request. As Earth system modelling archives grow in scale and complexity, there are emerging problems associated with weak standardisation at the variable collection level. That is, there are good standards covering how specific variables should be archived, but this paper fills a gap in the standardisation of which variables should be archived. The ESM-BCV list is intended as a resource for ESM intercomparison projects (MIPs) developing requests to enable greater consistency among MIPs and as a reference for modelling centres to enhance consistency within MIPs. Provisional planning for the CMIP7 Data Request exploits the ESM-BCVs as a core element. The baseline variable list includes 98 variables which have modest or minor data volume footprints and could be generated systematically when simulations are produced and archived for exploitation by the World Climate Research Programme (WCRP) community. A further 35 variables are classed as “high volume” and are only suitable for production when the resource implications are justified.

Juckes, Martin [University of Oxford (United Kingd↗
DOE OSTI2018

WebGIobe - A cloud-based geospatial analysis framework for interacting with climate data

While climate models have evolved over time to produce high fidelity and high resolution climate forecasts, visualization and analysis of the output of the model simulations has been limited, typically constrained to single dimensional charts for visualization and basic aggregate statistics for analytics. Same is true for the large troves of observational data available from meteorological stations all over the world. For richer understanding of climate and the impact of climate change, one needs computational tools that allow researchers, policymakers, and general public, to interact with the climate data. In this paper, we describe, webGlobe, a browser based GIS framework for interacting with climate data, and other datasets available in similar format. webGlobe is a unique resource that allows unprecedented access to climate data through a browser. The framework also allows for deploying machine learning based analytical applications on the climate data without putting computational burden on the client. Instead, webGlobe uses a client-server framework, where the server, deployed on a cloud infrastructure, allows for dynamic allocation of resources for running compute-intensive applications. The capabilities of the framework will be discussed in context of a use case: identifying extreme events from real and simulated climate data using a Gaussian process based change detection algorithm.

Sharma, Arun↗
DOE OSTI2026

Unprecedented Shifts in Hydrology Are Emerging Across California's Critical Basins: An Evaluation From 0.5 to 3.5°C

With advances in climate models and downscaling techniques, stakeholders anticipate high-resolution analysis to inform regional to local changes in water management. Here, we produce hydrologic projections from an ensemble of Earth System Models (ESMs) that were selected and downscaled to support California's 5th Climate Assessment. An ensemble of 19 ESMs was downscaled to a 3-km resolution across California using a statistical-dynamical downscaling approach and subsequently run through two calibrated hydrology models. Although California has been extensively studied in the context of climate change, we provide the first evaluation of the warming thresholds at which hydroclimate metrics demonstrate statistically significant shifts. We show that present-day to near-term warming levels in Klamath and Northern Sierra Nevada basins, which serve as a critical source of water for California, show statistically significant decreases in snowfall and peak snowpack and associated decreases in summer snowmelt and runoff. More generally, shifts in these hydroclimate metrics occur for intermediate elevation basins ranging from 1,315 to 1,455 m (4,314.3–4,773.6 ft), while the warming level of emergence is delayed for lower and higher elevation basins. We also find that several basins already demonstrate significant increases in 5- to 100-year runoff intensities, primarily due to the increasing influence of precipitation falling as rain. Hydroclimate metrics with trends that demonstrate near-term warming levels of emergence are reflected in reanalysis-based observations, suggesting California is entering a fundamentally different hydroclimate regime. While this will likely stress California's water management, the research provided can support when to implement adaptation efforts.

Bass, B. [Univ. of California, Los Angeles, CA (Un↗
DOE OSTI2025

A Decadal Hybrid GCM Simulation Using Deep‐Learning‐Based Cloud and Convection Parameterization Generalized to a Warm Climate

A critical challenge for machine‐learning (ML) parameterization in global climate models (GCMs) is to achieve stable, accurate simulations under climates not seen during training. Previous studies have demonstrated promising offline performance and year‐long online stability in aquaplanet simulations but have encountered difficulties in real geography and under climate warming. Here we report that a GCM with real geography configuration using neural‐network‐based cloud and convection parameterization, trained exclusively with present‐day climate data, successfully performs a stable, decade‐long simulation of a warm climate with +4 K sea surface temperature (SST). The neural network (NN) is based on Han et al. (2023, https://doi.org/10.1029/2022ms003508 ) with additional inputs. The simulation captures the global precipitation distribution, surface temperatures, vertical atmospheric structures, and extreme precipitation very well, closely matching simulations from both the superparameterized CAM (SPCAM) and the conventional CAM5 in the warm climate without accuracy degradation compared to those in the baseline climate. Moreover, it produces a climate response to +4 K SST in atmospheric thermodynamic states and circulations similar to those from SPCAM and CAM5. Prognostic ablation tests on NN input variables show that the NN without convective memory as input suffers from numerical instability, and the NN without considering radiative variables and land fraction as input, or with reduced training samples produce less accurate results. To our knowledge, this is the first time an ML parameterization successfully achieves online extrapolation to a warm climate without using additional warm‐climate data for training. It demonstrates the potential of ML‐driven parameterizations for credible long‐term climate projections.

Atmosphere model↗
DOE OSTI2012

THERMAL PHASES OF EARTH-LIKE PLANETS: ESTIMATING THERMAL INERTIA FROM ECCENTRICITY, OBLIQUITY, AND DIURNAL FORCING

In order to understand the climate on terrestrial planets orbiting nearby Sun-like stars, one would like to know their thermal inertia. We use a global climate model to simulate the thermal phase variations of Earth analogs and test whether these data could distinguish between planets with different heat storage and heat transport characteristics. In particular, we consider a temperate climate with polar ice caps (like the modern Earth) and a snowball state where the oceans are globally covered in ice. We first quantitatively study the periodic radiative forcing from, and climatic response to, rotation, obliquity, and eccentricity. Orbital eccentricity and seasonal changes in albedo cause variations in the global-mean absorbed flux. The responses of the two climates to these global seasons indicate that the temperate planet has 3 Multiplication-Sign the bulk heat capacity of the snowball planet due to the presence of liquid water oceans. The obliquity seasons in the temperate simulation are weaker than one would expect based on thermal inertia alone; this is due to cross-equatorial oceanic and atmospheric energy transport. Thermal inertia and cross-equatorial heat transport have qualitatively different effects on obliquity seasons, insofar as heat transport tends to reduce seasonal amplitude without inducing a phase lag. For an Earth-like planet, however, this effect is masked by the mixing of signals from low thermal inertia regions (sea ice and land) with that from high thermal inertia regions (oceans), which also produces a damped response with small phase lag. We then simulate thermal light curves as they would appear to a high-contrast imaging mission (TPF-I/Darwin). In order of importance to the present simulations, which use modern-Earth orbital parameters, the three drivers of thermal phase variations are (1) obliquity seasons, (2) diurnal cycle, and (3) global seasons. Obliquity seasons are the dominant source of phase variations for most viewing angles. A pole-on observer would measure peak-to-trough amplitudes of 13% and 47% for the temperate and snowball climates, respectively. Diurnal heating is important for equatorial observers ({approx}5% phase variations), because the obliquity effects cancel to first order from that vantage. Finally, we compare the prospects of optical versus thermal direct imaging missions for constraining the climate on exoplanets and conclude that while zero- and one-dimensional models are best served by thermal measurements, second-order models accounting for seasons and planetary thermal inertia would require both optical and thermal observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Future Drying in Central America and Northern South America Linked With Atlantic Meridional Overturning Circulation

Abstract Many climate models from the fifth phase of the Coupled Model Intercomparison Project predict decreases in precipitation in Central America and northern South America by the year 2100 for the Representative Concentration Pathway 8.5 scenario. Here we show that the fifth phase of the Coupled Model Intercomparison Project models able to more accurately simulate warm North Atlantic sea surface temperatures (SSTs) for the present climate (strong Atlantic meridional overturning circulation models) are more likely to project a larger precipitation decrease. Drought amplification from the slowdown of Atlantic meridional overturning circulation is more significant during the wet season in the Northern Hemisphere, with an SST‐constrained model estimate yielding a 73% larger decrease in precipitation (−1.11 mm/day) than the multimodel mean (−0.64 mm/day). Since most Earth system models underestimate contemporary SSTs in the North Atlantic, the use of the multimodel mean for impact analysis likely underestimates drought stress and the vulnerability of neotropical forests to increasing drought from climate change.

Chen, Y.↗
DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗
DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗
DOE OSTI2021

Climatology and Evolution of the Antarctic Peninsula Föhn Wind-Induced Melt Regime From 1979–2018

Warm and dry föhn winds on the Antarctic Peninsula (AP) cause surface melt that can destabilize vulnerable ice shelves. Topographic funneling of these downslope winds through mountain passes and canyons can produce localized wind-induced melt that is difficult to quantify without direct measurements. Our Föhn Detection Algorithm (FöhnDA) identifies the surface föhn signature that causes melt from measurement by 12 Automatic Weather Stations on the AP, that train a machine learning model to detect föhn in 5 km Regional Atmospheric Climate Model 2 (RACMO2.3p2) simulations and in the ERA5 reanalysis model. We estimate the fraction of AP surface melt attributed to föhn and possibly katabatic winds and identify the drivers of melt, temporal variability, and long-term trends and evolution from 1979–2018. We find that föhn wind-induced melt accounts for 3.1% of the total melt on the AP and can be as high at 18% close to the mountains where the winds funnel through mountain canyons. Föhn-induced surface melt does not significantly increase from 1979–2018, despite a warmer atmosphere and more positive Southern Annular Mode. However, a significant increase (+0.1 Gt y-1) and subsequent decrease/stabilization occur in 1979–1998 and 1999–2018, consistent with the AP warming and cooling trends during the same time periods. Föhn occurrence, more than föhn strength, drives the annual variability in föhn-induced melt. Long-term föhn-induced melt trends and evolution are attributable to seasonal changes in föhn occurrence, with increased occurrence in summer, and decreased occurrence in fall, winter, and early spring over the past 20 years.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sequential Abiotic-Biotic Processes Drive Organic Carbon Transformation in Peat Bogs

Peatlands, which store one-third of the terrestrial carbon (C), are subject to large disturbances under a changing climate. It is crucial to understand how microbial and physiochemical factors affect the vulnerability of these large C stores to predict climate induced greenhouse gas fluxes. Here, we used a combination of mass spectrometry and spectroscopy techniques, to understand sequential biotic and abiotic degradation pathways of Sphagnum fallax leachate in an anaerobic incubation experiment, in the presence and absence of microorganisms. Removal of microorganisms was carried out by passing aqueous samples through 0.2 µm filters. In this work, our results revealed that Sphagnum fallax leachate degradation by abiotic reactions is a significant contributor to CO 2 production. Further, abiotic factors, such as low pH, are responsible for partial dissolved organic carbon (DOC) degradation that produces bioavailable compounds that shift microbial metabolic pathways and stimulate respiration in peat bogs. Acid-catalyzed hydrolysis of Sphagnum-produced glycosides can provide the microbial communities with glucose and stimulate microbial respiration of DOC to CO 2 . These results, while unique to peatlands, demonstrate the importance and underscore the complexity of sequential abiotic and biotic processes on C cycling in peat bogs. It is therefore crucial to incorporate abiotic degradation and sequential below-ground biotic and abiotic interactions into climate models for a better prediction of the influence of climate change on DOC stability in peatlands. These findings might not be representative of other ecosystems with different environmental conditions including mineral-rich peatlands and plant matter in surface peat horizons that comprise discrete microbial populations, and DOC composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Enhanced Volatile Organic Compounds emissions and organic aerosol mass increase the oligomer content of atmospheric aerosols

Secondary organic aerosol (SOA) accounts for a dominant fraction of the submicron atmospheric particle mass, but knowledge of the formation, composition and climate effects of SOA is incomplete and limits our understanding of overall aerosol effects in the atmosphere. Organic oligomers were discovered as dominant components in SOA over a decade ago in laboratory experiments and have since been proposed to play a dominant role in many aerosol processes. However, it remains unclear whether oligomers are relevant under ambient atmospheric conditions because they are often not clearly observed in field samples. Here we resolve this long-standing discrepancy by showing that elevated SOA mass is one of the key drivers of oligomer formation in the ambient atmosphere and laboratory experiments. We show for the first time that a specific organic compound class in aerosols, oligomers, is strongly correlated with cloud condensation nuclei (CCN) activities of SOA particles. These findings might have important implications for future climate scenarios where increased temperatures cause higher biogenic volatile organic compound (VOC) emissions, which in turn lead to higher SOA mass formation and significant changes in SOA composition. Such processes would need to be considered in climate models for a realistic representation of future aerosol-climate-biosphere feedbacks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Holistic Algorithmic Approach to Improving Accuracy, Robustness, and Computational Efficiency for Atmospheric Dynamics

Atmospheric weather and climate models must perform simulations very quickly to be useful. Therefore, modelers have traditionally focused on reducing computations as much as possible. However, in our new era of increasingly compute-capable hardware, data movement is now the prohibiting expense. This study examines the computational benefits of a new algorithmic approach to modeling atmospheric dynamics on scales relevant to weather and climate simulation. Rather than minimizing computations, this new approach considers the larger problem more holistically, including spatial accuracy, temporal accuracy, robustness (i.e., oscillations), on-node efficiency, and internode data transfers together at once. Numerical experiments demonstrate how computations can be strategically increased to simultaneously address each of these constraints while reducing data movement to adapt to modern accelerated hardware. The new algorithm can achieve at times up to 80% peak floating point throughput in single precision on the Nvidia Tesla V100 GPU, where the traditional approach is shown to only achieve single-digit floating point efficiency. Further, the new algorithm is twice as fast as a standard Runge--Kutta time integrator, and high-order accuracy with Weighted Essentially Non-Oscillatory (WENO) limiting came at less than 30% additional runtime cost on a GPU, thus increasing the accuracy per degree of freedom.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Statistics of Storm Updraft Velocities from TWP-ICE Including Verification with Profiling Measurements

Comparisons between direct measurements and modeled values of vertical air motions in precipitating systems are complicated by differences in temporal and spatial scales. On one hand, vertically profiling radars more directly measure the vertical air motion but do not adequately capture full storm dynamics. On the other hand, vertical air motions retrieved from two or more scanning Doppler radars capture the full storm dynamics but require model constraints that may not capture all updraft features because of inadequate sampling, resolution, numerical constraints, and the fact that the storm is evolving as it is scanned by the radars. To investigate the veracity of radar-based retrievals, which can be used to verify numerically modeled vertical air motions, this article presents several case studies from storm events around Darwin, Northern Territory, Australia, in which measurements from a dual-frequency radar profiler system and volumetric radar-based wind retrievals are compared. While a direct comparison was not possible because of instrumentation location, an indirect comparison shows promising results, with volume retrievals comparing well to those obtained from the profiling system. This prompted a statistical analysis of an extended period of an active monsoon period during the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Results show less vigorous deep convective cores with maximum updraft velocities occurring at lower heights than some cloudresolving modeling studies suggest. 1. Introduction The regionalization of global climate models has been a driver of demand for more complex convective parameterization schemes. A key readjustment of the modeled atmosphere

Collis, Scott↗
DOE OSTI2017

Local Sensitivities of the Gulf Stream Separationa

Abstract Robust and accurate Gulf Stream separation remains an unsolved problem in general circulation modeling whose resolution will positively impact the ocean and climate modeling communities. Oceanographic literature does not face a shortage of plausible hypotheses that attempt to explain the dynamics of the Gulf Stream separation, yet a single theory that the community agrees on is missing. In this paper, the authors investigate the impact of the deep western boundary current (DWBC), coastline curvature, and continental shelf steepening on the Gulf Stream separation within regional configurations of the Massachusetts Institute of Technology General Circulation Model. Artificial modifications to the regional bathymetry are introduced to investigate the sensitivity of the separation to each of these factors. Metrics for subsurface separation detection confirm the direct link between flow separation and the surface expression of the Gulf Stream in the Mid-Atlantic Bight. It is shown that the Gulf Stream separation and mean surface position are most sensitive to the continental slope steepening, consistent with a theory proposed by Melvin Stern in 1998. In contrast, the Gulf Stream separation exhibits minimal sensitivity to the presence of the DWBC and coastline curvature. The implications of these results to the development of a “separation recipe” for ocean modeling are discussed. This study concludes adequate topographic resolution is a necessary, but not sufficient, condition for proper Gulf Stream separation.

58 GEOSCIENCES↗
DOE OSTI2016

MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary

Cloud droplet size and optical depth are the most fundamental properties for understanding cloud formation, dissipation and interactions with aerosol and drizzle. They are also a crucial determinant of Earth’s radiative and water-energy balances. However, these properties are poorly predicted in climate models. As a result, the response of clouds to climate change is one of the major sources of uncertainty in climate prediction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

An unstructured C-grid type variational formulation for the sea ice dynamics

Historically, B-grid formulations of sea ice dynamics have been dominant because they have matched the grid type used by ocean models. The reason for the grid match is simple – it facilitates penetration of the curl of ice-ocean stress into the deep ocean with minimal numerical diffusivity because sea ice and ocean velocity are co-located. In recent years, as ocean models have increasingly progressed to C-grids, sea ice models have followed suit on quadrilateral meshes, but the implementation of an unstructured C-grid sea ice models is new. We present an unstructured C-grid discretization of the Elastic Viscous Plastic (EVP) rheology, where the velocity unknowns are discretized at the edges of the mesh cells with n-sides, where typically n is greater than or equal to four, rather than at the vertices, as in the B-grid. Our framework of choice is the Model for Prediction Across Scales (MPAS) within E3SM, the climate model of the U.S. Department of Energy, although our approach is general and could be applied to other models as well. While MPAS-Seaice is currently defined on a B-grid, MPAS-Ocean runs on a C-grid, hence interpolation operators are heavily used when coupled simulations are performed. In this work, we describe a mathematical formulation to transition the dynamics of MPAS-Seaice to a C-grid, in order to ultimately facilitate the coupling with MPAS-Ocean and reduce numerical errors associated with this communication. Numerical results are reported to highlight the features of the method.

58 GEOSCIENCES↗
DOE OSTI2020

Reaching 1.5 and 2.0 °C global surface temperature targets using stratospheric aerosol geoengineering

A new set of stratospheric aerosol geoengineering (SAG) model experiments has been performed with Community Earth System Model version 2 (CESM2) with the Whole Atmosphere Community Climate Model (WACCM6) that are based on the Coupled Model Intercomparison Project phase 6 (CMIP6) overshoot scenario (SSP5-34-OS) as a baseline scenario to limit global warming to 1.5 or 2.0 °C above 1850–1900 conditions. The overshoot scenario allows us to applying a peak-shaving scenario that reduces the needed duration and amount of SAG application compared to a high forcing scenario. In addition, a feedback algorithm identifies the needed amount of sulfur dioxide injections in the stratosphere at four pre-defined latitudes, 30 °N, 15 °N, 15 °S, and 30 °S, to reach three surface temperature targets: global mean temperature, and interhemispheric and pole-to-Equator temperature gradients. These targets further help to reduce side effects, including overcooling in the tropics, warming of high latitudes, and large shifts in precipitation patterns. These experiments are therefore relevant for investigating the impacts on society and ecosystems. Comparisons to SAG simulations based on a high emission pathway baseline scenario (SSP5-85) are also performed to investigate the dependency of impacts using different injection amounts to offset surface warming by SAG. We find that changes from present-day conditions around 2020 in some variables depend strongly on the defined temperature target (1.5 °C vs. 2.0 °C). These include surface air temperature and related impacts, the Atlantic Meridional Overturning Circulation, which impacts ocean net primary productivity, and changes in ice sheet surface mass balance, which impacts sea level rise. Others, including global precipitation changes and the recovery of the Antarctic ozone hole, depend strongly on the amount of SAG application. Furthermore, land net primary productivity as well as ocean acidification depend mostly on the global atmospheric CO 2 concentration and therefore the baseline scenario. Multi-model comparisons of experiments that include strong mitigation and carbon dioxide removal with some SAG application are proposed to assess the robustness of impacts on societies and ecosystems.

42 ENGINEERING↗