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NASA NTRS2014

A Deglacial and Holocene Record of Climate Variability in South-Central Alaska from Stable Oxygen Isotopes and Plant Macrofossils in Peat

We used stable oxygen isotopes derived from bulk peat (delta-O-18(sub TOM) in conjunction with plant macrofossils and previously published carbon accumulation records, in a approximately14,500 cal yr BP peat core (HT Fen) from the Kenai lowlands in south-central Alaska to reconstruct the climate history of the area. We find that patterns are broadly consistent with those from lacustrine records across the region, and agree with the interpretation that major shifts in delta-O-18(sub TOM) values indicate changes in strength and position of the Aleutian Low (AL), a semi-permanent low-pressure cell that delivers winter moisture to the region. We find decreased strength or a more westerly position of the AL (relatively higher delta-O-18(sub TOM) values) during the Bolling-Allerod, Holocene Thermal Maximum (HTM), and late Holocene, which also correspond to warmer climate regimes. These intervals coincide with greater peat preservation and enhanced carbon (C) accumulation rates at the HT Fen and with peatland expansion across Alaska. The HTM in particular may have experienced greater summer precipitation as a result of an enhanced Pacific subtropical high, a pattern consistent with modern delta-O-18 values for summer precipitation. The combined warm summer temperatures and greater summer precipitation helped promote the observed rapid peat accumulation. A strengthened AL (relatively lower delta-O-18(sub TOM) values) is most evident during the Younger Dryas, Neoglaciation, and the Little Ice Age, consistent with lower peat preservation and C accumulation at the HT Fen, suggesting less precipitation reaches the leeward side of the Kenai Mountains during periods of enhanced AL strength. The peatlands on the Kenai Peninsula thrive when the AL is weak and the contribution of summer precipitation is higher, highlighting the importance of precipitation seasonality in promoting peat accumulation. This study demonstrates that delta-O-18(sub TOM) values in peat can be applied toward understand large-scale shifts in atmospheric circulation over millennial timescales.

Holocene↗

NASA NTRS1999

Can El Nino Amplify the Solar Forcing of Climate?

ENSO (El Nino and the Southern Oscillation) is considered as a stochastic driver that excites the atmospheric anomaly states, such as Pacific North American pattern. This can make the 11 year solar activity forcing feasible to climate through stochastic resonance -- a phenomenon that amplifies a weak input to a nonlinear bistable system by the assistance of noise.

ENSO El Nino Oscillation climate stochastic resona↗

NASA NTRS2013

Emerging and Reemeriging Human Bunyavirus Infections and Climate Change

The Bunyaviridae family includes a growing number of viruses that have contributed to the burden of emerging and reemerging infectious diseases around the globe. Many of these viruses cause severe clinical outcomes in human and animal populations, the results of which can be detrimental to public health and the economies of affected communities. The threat to endemic and non-native regions is particularly high, and national and international public health agencies are often on alert. Many of the bunyaviruses cause severe clinical disease including hemorrhage, organ failure, and death leading to their high-risk classification. Hantaviruses and Rift Valley fever virus (RVFV) (genus Phlebovirus) are National Institute of Allergy and Infectious Diseases Category A priority pathogens in the United States. Viral hemorrhagic fevers, a classification that includes many bunyaviruses, are immediately notifiable in the European Union. The emergence of new and reemerging bunyaviruses has resulted in numerous human and animal fatalities. Outbreaks of Rift Valley fever (RVF) in East Africa (1997/1998, 2006/2007), Sudan (2007), Southern Africa (2008-2010), Kenya (1997/1998, 2006/2007) (Anyamba et al., 2009, 2010; Breiman et al., 2010; Grobbelaar et al., 2011; Woods et al., 2002) and Saudi Arabia & Yemen (2000, 2010) (Food and Agriculture Organization, 2000; Hjelle and Glass, 2000; Madani et al., 2003) and the emergence of Sin Nombre virus (1993) (Hjelle and Glass, 2000) and most recently Schmallenberg virus (2011) (DEFRA, 2012) are prime examples of the devastating and worldwide toll bunyaviruses have on health and economies. Climate variability (precipitation and temperature in particular) greatly influence the ecological conditions that drive arboviral disease outbreaks across the globe. Several human and animal disease outbreaks have been influenced by changes in climate associated with the El Niño Southern Oscillation (ENSO) phenomenon including the bunyaviruses RVFV and Sin Nombre (an etiologic agent of hantavirus pulmonary syndrome (HPS)), as well as Murray Valley encephalitis, chikungunya, and malaria to name but a few (Anyamba et al., 2009; Bouma and Dye, 1997; Chretien et al., 2007; Engelthaler et al., 1999; Kovats et al., 2003; Linthicum et al., 1999; Nicholls, 1986). Most bunyaviruses exhibit episodic outbreak patterns with seasonal or annual trends dependent upon climate conditions, vector abundance, and the proximity of a susceptible population. The implications for continued climate change are dire, especially with regard to vector-borne diseases, many of which can cause severe morbidity, sequelae, and death. Increased rainfall and widening endemicity as a result of climate change, compounded by the emergence of new viruses, poses a serious threat to a greater geographic range beyond the regions of endemicity.

Bunyavirus↗

DOE OSTI2025

Exploring the role of clouds in offshore wind potential off the US West Coast in a changing climate

To meet US goals of deploying additional wind energy as part of the decarbonization strategy, wind plants are being planned for the deep water offshore the western US. The wind flow in that region is complex due to the proximity to the coast, cold water upwelling, and persistent stratiform clouds that interact with radiation in ways that have the potential to destabilize the atmosphere. That flow has the potential to change with a changing climate. To address these issues, we assess the flow and the clouds in that region using downscaled climate model data, under both historic climate (1975–2005) and projected future (2025–2055) conditions. We note that the climate simulations agree fairly well with the cloud patterns observed by satellite data in the nearshore and offshore regions. We then assess the projected changes in clouds, wind speed, and other important variables, noting that our simulations project that the predominant north/northwesterly low-level jet is expected to strengthen and clouds are likely to be commensurately enhanced, although projected changes are within about 10% of current conditions. Our examination of the dynamics associated with the changes in the climate simulations provides confidence in the dynamical consistency of these projected changes.

17 WIND ENERGY↗

DOE OSTI2023

Seasonal and Geographical Variations in Fundamental Weather Patterns during Extreme Precipitation as Identified from Omega Equation Forcing

Abstract We investigate the large-scale weather patterns during extreme precipitation (PEx) events over the conterminous United States (CONUS) by applying a version of the quasigeostrophic (QG) omega equation. This work aims to develop a climatology of the weather patterns most related to PEx events during current climate. Extreme events are examined for each of seven regions defined by consistent annual cycles of precipitation and spanning the CONUS. For the CONUS we train several self-organizing maps (SOM) on a pressure–time series of vertical velocity from each of the advective forcing terms in the QG omega equation for each extreme event. The unsupervised learning of the SOM allows us to identify the most descriptive set of nine patterns in vertical velocity associated with precipitation extremes. This method finds multiple frontal- and cyclone-driven patterns while grouping primarily convective events into one pattern. Frontal events include a synoptic pattern consistent with West Coast atmospheric river events as well as pattern groups linked to developing and to mature (“occluded”) frontal cyclones. The primary patterns found during PEx events vary seasonally and geographically. Frontal cyclone patterns are most common during PEx events during summer in the part of the Great Plains and during winter for the Northeast, Southeast, Pacific Northwest, and Southwest. Convection is the most common pattern during summer in all regions. Except in the Southeast, the annual cycles of monthly number of PEx events and average precipitation match well, partially validating our choice of regions to aggregate PEx events.

Meteorology & Atmospheric Sciences↗

NASA NTRS2015

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Simulation↗

NASA NTRS2014

Northern Late Winter Planetary Waves: MRO/MARCI Observations and Mars Climate Model Simulations

As does Earth, Mars presents pronounced global atmospheric circulation patterns. Solar differential heating drives mean meridional overturning (Hadley) circulations which are deep and intense, are hemispherically asymmetric, and where a cross-equatorial single cell dominates. Within middle and high latitudes, thermally indirect eddy-driven (Ferrel) circulation cells have been indicated. Differently, however, large-amplitude orography on planetary and continental scales on Mars can force very non-Earth-like hemispheric circulation patterns. Recent observations from the Mars Reconnaissance Orbiter, "Mars Color Imager" (MARCI) instrument are utilized that emphasize water ice clouds in ultra-violet (UV) wavelengths, and these measurements have been binned into "daily global maps" (DGMs) of water-ice cloud optical depth. The presence of large-scale, extratropical quasi-stationary atmospheric wave disturbances in middle and late winter of the northern hemisphere have been found to be present in such DGMs. In combination with such observations, a full-physics Mars global climate model (NASA ARC marsgcm 2.1) is applied to place the observations into context. During late northern winter, it is found that strong, forced Rossby modes (i.e., planetary waves) exist, and with direct correlation to columnintegrated cloud opacity undulating spatial patterns. At this season, zonal wavenumber s = 2 dominates (in contrast to wavenumber s = 1), consistent with MGS/TES analyses at this particular season (Banfield et al., 2003). Large-scale, planetary waves dictate the "coherence" of the northern polar vortex. Fundamentally, such forced planetary waves influence the polar vortex's impermeability (wave-induced) to tracer transport (e.g., dust and water-ice aerosol) and temporal mean water vapor spatial variations. The large-scale dynamical features of such planetary waves will be highlighted and discussed.

Northern polar vortex↗

DOE OSTI2022

Functional Redundancy in Soil Microbial Community Based on Metagenomics Across the Globe

Understanding the contribution of soil microbial communities to ecosystem processes is critical for predicting terrestrial ecosystem feedbacks under changing climate. Our current understanding lacks a consistent strategy to formulate the linkage between microbial systems and ecosystem processes due to the presumption of functional redundancy in soil microbes. Here we present a global soil microbial metagenomic analysis to generalize patterns of microbial taxonomic compositions and functional potentials across climate and geochemical gradient. Our analyses show that soil microbial taxonomic composition varies widely in response to climate and soil physicochemical gradients, while microbial functional attributes based on metagenomic gene abundances are redundant. Among 17 climate zones, microbial taxonomic compositions were more distinct than functional potentials, as climate and edaphic properties showed more significant influence on microbial taxonomic compositions than on functional potentials. Microbial taxonomies formed a larger and more complex co-occurrence network with more module structures than functional potentials. Functional network was strongly inter-connected among different categories, whereas taxonomic network was more positively interactive in the same taxonomic groups. This study provides strong evidence to support the hypothesis of functional redundancy in soil microbes, as microbial taxonomic compositions vary to a larger extent than functional potentials based on metagenomic gene abundances in terrestrial ecosystems across the globe.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1999

Climate-Rotation Feedback on Mars

A new model is presented for the coupled evolution of climate and rotation, as applied to Mars. It has long been appreciated that changes in the orbital and rotational geometry of Mars will influence the seasonal and latitudinal pattern of insolation [1-5], and this will likely dominate climatic fluctuations on time scales of 10(exp 5) to 10(exp 7) years [6-9]. Equally important, but less widely appreciated, is the influence climatic change can have on rotational dynamics. The primary means by which climate influences rotation is via its influence on transport of mass (volatiles and dust) into and out of the polar regions. Many important issues remain unresolved: What are the ages of the polar caps? What climatic periods are recorded in the polar layered deposits? What is the long term obliquity history?

Bills, Bruce G.↗

NASA NTRS2022

Midwest Water Resources: Developing an Evapotranspiration Climatology to Analyze Spatiotemporal Water Budget Patterns for Agriculture and Natural Resources Managers in the Midwest

Evapotranspiration (ET) is a climatic variable critical to the hydrologic cycle and is used to evaluate spatiotemporal trends in drought conditions. Although in-situ observations provide accurate ET information, these records are spatially sparse. The United States Department of Agriculture (USDA) Midwest Climate Hub, National Integrated Drought Information System, Minnesota Department of Agriculture, Michigan State University, and the USDA Foreign Agricultural Service have partnered with DEVELOP to gain new insights on spatiotemporal patterns of ET with NASA satellite data. This project evaluates the feasibility of using remotely sensed ET data products to understand trends from 2001 through 2020. Actual ET (aET) data were sourced from NASA’s Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and reference ET (refET) and precipitation data were sourced from the Gridded Surface Meteorological Dataset (gridMET). Spatial and temporal differences in the MODIS and gridMET data sets were resolved such that gridded data could be compared. These data sets were then used to produce monthly Normals maps of mm/8-day of precipitation, aET, and refET. Using precipitation and ET Normals maps, hydrologic state maps were produced by subtracting either refET or aET from precipitation. These hydrologic state maps provide a proxy water balance by summarizing the difference between water entering and leaving the ground surface. Additionally, the ET products were compared in timeseries plots. The ET products from this project provided partners with comparable datasets to assess potential drought and flooding conditions to support Midwest agricultural and natural resource managers in decision-making.

Emma Myrick↗

NASA NTRS2013

Impacts of Climate Change on Surface Ozone and Intercontinental Ozone Pollution: A Multi-Model Study

The impact of climate change between 2000 and 2095 SRES A2 climates on surface ozone (O)3 and on O3 source-receptor (S-R) relationships is quantified using three coupled climate-chemistry models (CCMs). The CCMs exhibit considerable variability in the spatial extent and location of surface O3 increases that occur within parts of high NOx emission source regions (up to 6 ppbv in the annual average and up to 14 ppbv in the season of maximum O3). In these source regions, all three CCMs show a positive relationship between surface O3 change and temperature change. Sensitivity simulations show that a combination of three individual chemical processes-(i) enhanced PAN decomposition, (ii) higher water vapor concentrations, and (iii) enhanced isoprene emission-largely reproduces the global spatial pattern of annual-mean surface O3 response due to climate change (R2 = 0.52). Changes in climate are found to exert a stronger control on the annual-mean surface O3 response through changes in climate-sensitive O3 chemistry than through changes in transport as evaluated from idealized CO-like tracer concentrations. All three CCMs exhibit a similar spatial pattern of annual-mean surface O3 change to 20% regional O3 precursor emission reductions under future climate compared to the same emission reductions applied under present-day climate. The surface O3 response to emission reductions is larger over the source region and smaller downwind in the future than under present-day conditions. All three CCMs show areas within Europe where regional emission reductions larger than 20% are required to compensate climate change impacts on annual-mean surface O3.

Troposphere: constituent transport and chemistry↗

NASA NTRS2007

Spectral Retrieval of Latent Heating Profiles from TRMM PR data: Moistening Estimates over Tropical Ocean Regions - Part 3

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of precipitation formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the tropics with the associated latent heating (LH) accounting for threefourths of the total heat energy available to the Earth's atmosphere. In the last decade, it has been established that standard products of LH from satellite measurements, particularly TRMM measurements, would be a valuable resource for scientific research and applications. Such products would enable new insights and investigations concerning the complexities of convection system life cycles, the diabatic heating controls and feedbacks related to rne-sosynoptic circulations and their forecasting, the relationship of tropical patterns of LH to the global circulation and climate, and strategies for improving cloud parameterizations In environmental prediction models. However, the LH and water vapor profile or budget (called the apparent moisture sink, or Q2) is closely related. This paper presented the development of an algorithm for retrieving Q2 using 'TRMM precipitation radar. Since there is no direct measurement of LH and Q2, the validation of algorithm usually applies a method called consistency check. Consistency checking involving Cloud Resolving Model (CRM)-generated LH and 42 profiles and algorithm-reconstructed is a useful step in evaluating the performance of a given algorithm. In this process, the CRM simulation of a time-dependent precipitation process (multiple-day time series) is used to obtain the required input parameters for a given algorithm. The algorithm is then used to "~econsti-LKt~h"e heating and moisture profiles that the CRM simulation originally produced, and finally both sets of conformal estimates (model and algorithm) are compared each other. The results indicate that discrepancies between the reconstructed and CM-simulated profiles for Q2, especially at low levels, are larger than those for latent heat. Larger discrepancies in Q2 at low levels are due to moistening for non-precipitating region that algorithm cannot reconstruct. Nevertheless, the algorithm-reconstructed total Q2 profiles are in good agreement with the CRM-simulated ones.

Shige, S.↗

DOE OSTI2024

Reducing uncertainty of polar to midlatitude linkages using DOE’s E3SM in a coordinated model-experiment setting

This project brought DOE’s climate modeling effort with the Energy Exascale Earth System Model into the Polar Amplification Model Intercomparison Project (PAMIP), which is part of the sixth and latest Coupled Model Intercomparison Project, CMIP6. PAMIP examines the causes and consequences of polar amplification, when external forcing results in a larger temperature increase in high latitudes than the global average, in a coordinated set of model experiments with a common modeling protocol. Our teams from UC Irvine and the University of Toronto have designed, carried out, analyzed, and disseminated PAMIP output from the Energy Exascale Earth System Model (E3SM) and the Community Earth System Model (CESM). PAMIP’s ongoing stream of significant new results have advanced progress in the community’s understanding and led to new outstanding research questions that have motivated further work. PAMIP has led to improved consensus on the atmospheric response to sea ice loss. The important finding is that for a similar sea ice anomaly forcing, the simulated atmospheric response in the troposphere is remarkably consistent among the 16 models’ runs analyzed. The zonal-mean tropospheric response consists of a very robust equatorward shift of the westerly flow in mid-latitudes. However, while the multi-model mean response is robust, it has a weak amplitude relative to internal variability. We identified a weakness in the models (including E3SM) in terms of their response to sea-ice forcing that is related to eddy forcing (or nonlinear dynamical effects) at mid- to high latitudes. In fact, E3SM is an outlier in terms of the models participating, and in that sense, it turned out to be a vital participant model. We found that reductions in energy transport due sea-ice loss and involving dry air only are compensated by increases in moist energy transport from warmer sea surface temperature in midlatitudes. This leads to a large spread in energy transport into the Arctic and is a potential source of spread in Arctic amplification. We identified an important role that climate modes, including tropical modes of variability (El Nino and the Southern Oscillation (ENSO); the Quasi-biennial Oscillation (QBO)) play in the response to sea-ice anomalies, including in ocean coupled experiments. Similarly, we identified and quantified the contribution of sea-ice thickness to the atmospheric response compared to the response to sea-ice extent only. We found that it is important to run large ensembles and even with an ensemble size of 100 simulations the response is largely influenced by internal variability. We demonstrated convincingly that Ural blocking, not sea-ice loss, provides the weakening of the stratospheric polar vortex in fall/early winter and a negative phase of the North Atlantic Oscillation that can last for up to two months. However, sea-ice anomalies can influence the background flow so that the response to Ural blocking is more persistent under low sea-ice conditions in the Barents/Kara Sea than high sea ice Atmospheric model hierarchies that progressively add individual processes have a long history in providing dynamical insight for modeling the atmosphere. Similarly, coupled model hierarchies that progressively add individual ocean processes can provide insights into the workings of the coupled climate system, however such hierarchies have not been available except for a non-dynamical slab ocean model. Because of the missing processes, surface flux corrections must be added to produce a target climate. In this project, we managed to overcome this problem and develop a globally coupled ocean model hierarchy in CESM that can turn on and off the processes of mixed-layer entrainment and Ekman flow. We used the hierarchy to study the impact of Arctic sea-ice loss on the climate system. We find that the effect of mixed-layer entrainment on ocean heat uptake influences the atmospheric circulation by shifting the latitudinal positions of the mid-latitude westerly jet and the Intertropical Convergence Zone (ITCZ). In quadrupled CO 2 experiments, we studied how air-sea coupling affects the response of tropical rainfall under global warming. In order to identify the importance of individual ocean processes, we used the hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows, and frictional flows. We showed that including Ekman and frictional flows allows our simulation to produce the Pacific Ocean's enhanced equatorial warming pattern and equatorward ITCZ contraction noted in previous climate simulations. We also showed that the frictional flow, which has yet to receive much attention, is as important as the Ekman flow in generating equatorial heat convergence.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

Our Globally Changing Climate

Since the Third U.S. National Climate Assessment (NCA3) was published in May 2014, new observations along multiple lines of evidence have strengthened the conclusion that Earth's climate is changing at a pace and in a pattern not explainable by natural influences. While this report focuses especially on observed and projected future changes for the United States, it is important to understand those changes in the global context (this chapter). The world has warmed over the last 150 years, especially over the last six decades, and that warming has triggered many other changes to Earth's climate. Evidence for a changing climate abounds, from the top of the atmosphere to the depths of the oceans. Thousands of studies conducted by tens of thousands of scientists around the world have documented changes in surface, atmospheric, and oceanic temperatures; melting glaciers; disappearing snow cover; shrinking sea ice; rising sea level; and an increase in atmospheric water vapor. Rainfall patterns and storms are changing, and the occurrence of droughts is shifting.

Wuebbles, D. J.↗

NASA NTRS2008

Retrieved Latent Heating from TRMM

Tao, Wei-Kuo↗

DOE OSTI2022

Annual Herbaceous Plants Exhibit Altered Morphological Traits in Response to Altered Precipitation and Drought Patterns in Semiarid Sandy Grassland, Northern China

The frequency and intensity of extreme precipitation events and severe drought are predicted to increase in semiarid areas due to global climate change. Plant morphological traits can reflect plant responses to a changing environment, such as altered precipitation or drought patterns. In this study, we examined the response of morphological traits of root, stem, leaf and reproduction meristems of annual herbaceous species to altered precipitation and drought patterns in a semiarid sandy grassland. The study involved a control treatment (100% of background precipitation) and the following six altered precipitation treatments: (1) P(+): precipitation increased by 30%, (2) P(++): precipitation increased by 60%, (3) P(-): precipitation decreased by 30%, (4) P(--): precipitation decreased by 60%, (5) drought 1 (D1): 46-day drought from May 1st to June 15th, and (6) drought 2 (D2): 46-day drought from July 1st to August 15th. P(++) significantly increased root length, flower length-to-width ratio, both P(+) and P(++) significantly increased stem length and flower number in the plant growing seasons, while all of them decreased under P(-) and P(--). The annual herbaceous plants marginally increased the number of second-level stem branches and stem diameter in order to better resist the severe drought stress under P(--). P(+) and P(++) increased the root, stem, leaf, and flower dry weight, with the flower dry weight accounting for a larger proportion than the other aboveground parts. Under D2, the plants used the limited water resources more efficiently by increasing the root-to-shoot ratio compared with P(-), P(--) and D1, which reflects biomass allocation to belowground increased. The linear mixed-effects models and redundancy analysis showed that the root-to-shoot ratio and the dry weight of various plant components were significantly affected by morphological traits and altered precipitation magnitude. Our results showed that the herbaceous species have evolved morphological trait responses that allow them to adapt to climate change. Such differences in morphological traits may ultimately affect the growing patterns of annual herbaceous species, enhancing their drought-tolerant capacity in semiarid sandy grassland during the ongoing climate change.

Sun, Shan-Shan↗

DOE OSTI2025

Future Spatially Explicit Patterns of Land Transitions in the United States With Multiple Stressors

Climate change, income and population growth, and changing diets are major drivers of the global food system with implications for land use change. Land use in the U.S. will be affected directly by local and regional forces and indirectly through international trade. In order to investigate the effects of several potential forces on land use changes in the U.S., we advanced capabilities in representing the interactions between natural and human systems by linking a multisectoral and multiregional socio-economic model of the world economy to a model that downscales land use to a 0.5°grid scale. This enables us to translate regional projections of future land use into higher-resolution representations of time-evolving land cover (effectively spatially explicit land use transitions). We applied the framework over the U.S., with a particular interest in the Mississippi River Basin and its four sub-basins, to consider how a range of global drivers affect land use and cover in the target regions. Our results show that under scenarios of high pressure on the world food system a comparative advantage in livestock production amplifies the recent trend toward less cropland and more pastures in the U.S. Under low pressures on the world food system agricultural land is used less intensively. However, there can be key differences among the various land-use transitions at the sub- basin scale. Overall, these results highlighted the need for high resolution details to explicitly understand the implications of land use change on environmental impacts such as carbon storage, soil erosion, chemical use, hydrology, and water quality.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Convolutional Neural Networks Trained on Internal Variability Predict Forced Response of TOA Radiation by Learning the Pattern Effect

Abstract Predicting forced, long‐term radiative feedbacks from internal climate variability has been a decades‐long quest in climate science. We train a convolutional neural network (CNN) to predict annual‐ and global‐mean top of the atmosphere radiation anomalies from time‐varying maps of near‐surface temperature in climate models. Trained on internal variability alone, the nonlinear CNN can predict radiation under strong climate change, outperforms a regularized linear regression approach, and works within and across different climate models. We show with explainable artificial intelligence methods that the CNN draws predictive skill from physically meaningful regions but at much smaller spatial scales than currently assumed.

Rugenstein, Maria [Colorado State University Fort ↗