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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Micro2Macro: Origins of Climate Change Uncertainty

Where we are: Global Earth system models (ESMs) are essential tools for seasonal-to decadal environmental predictions, which decision-makers across government and industry require. However, uncertainties originating at the microphysical scale, i.e., in processes occurring on scales smaller than typical ESM grid boxes, remain a major challenge. While resolution continues to improve in our predictive models, we will need to parameterize microphysical processes that contribute the bulk of prediction uncertainty for the foreseeable future. Microphysical uncertainties contribute broadly to remaining limitations on Earth system predictability on seasonal and decadal time scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Understanding the Shift of Drivers of Soil Erosion and Sedimentation Based on Regional Process-Based Modeling in the Mississippi River Basin During the Past Century

Soil erosion and sedimentation problems remain a major water quality concern for making watershed management policies in the Mississippi River Basin (MRB). It is unclear whether the observed decreasing trend of stream suspended sediment loading to the mouth of the MRB over the last eight decades truly reflects a decline in upland soil erosion in this large basin. Here, for this work, we improved a distributed regional land surface model, the Dynamic Land Ecosystem Model, to evaluate how climate and land use changes have impacted soil erosion and sediment yield over the entire MRB during the past century. Model results indicate that total sediment yield significantly increased during 1980–2018, despite no significant increase in annual precipitation and runoff. The increased soil erosion and sediment yield are mainly driven by intensified extreme precipitation (EP). Spatially, we found notable intensified EP events in the cropland-dominated Midwest region, resulting in a substantial increase in soil erosion and sediment yield. Land use change played a critical role in determining sediment yield from the 1910s to the 1930s, thereafter, climate variability increasingly became the dominant driver of soil erosion, which peaked in the 2010s. This study highlights the increasing influences of extreme climate in affecting soil erosion and sedimentation, thus, water quality. Therefore, existing forest and cropland Best Management Practices should be revisited to confront the impacts of climate change on water quality in the MRB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics

Abstract. African and South American (ASA) wildfires account for more than 70 % of global burned areas and have strong connection to local climate for sub-seasonal to seasonal wildfire dynamics. However, representation of the wildfire–climate relationship remains challenging due to spatiotemporally heterogenous responses of wildfires to climate variability and human influences. Here, we developed an interpretable machine learning (ML) fire model (AttentionFire_v1.0) to resolve the complex controls of climate and human activities on burned areas and to better predict burned areas over ASA regions. Our ML fire model substantially improved predictability of burned areas for both spatial and temporal dynamics compared with five commonly used machine learning models. More importantly, the model revealed strong time-lagged control from climate wetness on the burned areas. The model also predicted that, under a high-emission future climate scenario, the recently observed declines in burned area will reverse in South America in the near future due to climate changes. Our study provides a reliable and interpretable fire model and highlights the importance of lagged wildfire–climate relationships in historical and future predictions.

58 GEOSCIENCES↗
DOE OSTI2022

Reactive transport modeling for supporting climate resilience at groundwater contamination sites

Abstract. Climate resilience is an emerging issue at contaminated sites and hazardous waste sites, since projected climate shifts (e.g., increased/decreased precipitation) and extreme events (e.g., flooding, drought) could affect ongoing remediation or closure strategies. In this study, we develop a reactive transport model (Amanzi) for radionuclides (uranium, tritium, and others) and evaluate how different scenarios under climate change will influence the contaminant plume conditions and groundwater well concentrations. We demonstrate our approach using a two-dimensional (2D) reactive transport model for the Savannah River Site F-Area, including mineral reaction and sorption processes. Different recharge scenarios are considered by perturbing the infiltration rate from the base case as well as considering cap-failure and climate projection scenarios. We also evaluate the uranium and nitrate concentration ratios between scenarios and the base case to isolate the sorption effects with changing recharge rates. The modeling results indicate that the competing effects of dilution and remobilization significantly influence pH, thus changing the sorption of uranium. At the maximum concentration on the breakthrough curve, higher aqueous uranium concentration implies that sorption is reduced with lower pH due to remobilization. To better evaluate the climate change impacts in the future, we develop the workflow to include the downscaled CMIP5 (Coupled Model Intercomparison Project) climate projection data in the reactive transport model and evaluate how residual contamination evolves through 2100 under four climate Representative Concentration Pathway (RCP) scenarios. The integration of climate modeling data and hydrogeochemistry models enables us to quantify the climate change impacts, assess which impacts need to be planned for, and therefore assist climate resiliency efforts and help guide site management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Demography, dynamics and data: building confidence for simulating changes in the world's forests

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm-2 yr-1 for boreal, temperate and tropical sites, respectively), influenced by each model's initial forest state. Models captured mature forest carbon content but showed compensating effects between overestimated growth and underestimated mortality rates. This first multi-model benchmarking identifies growth and mortality rates as critical calibration targets and highlights the need to refine postdisturbance establishment conditions for model development. We outline specific benchmarking variables needed to improve predictions of forest responses to environmental change.

demographic vegetation model benchmarking↗
DOE OSTI2017

The Response of Atlantic Tropical Cyclones to Suppression of African Easterly Waves

Atlantic tropical cyclone (TC) genesis is strongly linked with African easterly waves (AEWs) on the synoptic time scale. However, the TC–AEW relationship is unclear on interannual to climate time scales, and it is unknown whether AEWs are necessary to maintain climatological TC frequency, that is, whether TCs are limited by AEWs. We investigated the impact of AEW suppression on seasonal Atlantic TC activity using a 10–member ensemble of regional climate model simulations in which AEWs were either prescribed or removed through the lateral boundary condition. The climate model experiments produced no significant change in seasonal Atlantic TC number, indicating that AEWs are not necessary to maintain climatological basin–wide TC frequency even though TCs readily originate from these types of disturbances. This suggests that the specific type of “seedling” disturbance is unimportant for determining basin–wide seasonal Atlantic TC number and that in the absence of AEWs, TCs will generate by other mechanisms. Furthermore, the results imply that changes in the presence of AEWs may not be reliable predictors of seasonal variability and future change in Atlantic TC frequency.

58 GEOSCIENCES↗
NASA NTRS2015

An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations

Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.

Stackhouse, Paul W., Jr.↗
DOE OSTI2018

Combined effects of warming and acidification on accumulation and elimination dynamics of paralytic shellfish toxins in mussels Mytilus galloprovincialis

Highlights: • Impact of warming and acidification on the accumulation/elimination dynamics of HAB-toxins in shellfish. • High toxicity levels were found under current conditions. • Climate change scenarios may lead to lower but prolonged PST contamination. Harmful algal blooms (HAB) have been increasing in frequency and intensity most likely due to changes on global conditions, which constitute a significant threat to wild shellfish and its commercial farming. This study evaluated the impact of increasing seawater temperature and acidification on the accumulation/elimination dynamics of HAB-toxins in shellfish. Mytilus galloprovincialis were acclimated to four environmental conditions simulating different climate change scenarios: i) current conditions, ii) warming, iii) acidification and iv) interaction of warming with acidification. Once acclimated, mussels were exposed to the paralytic shellfish toxins (PSTs) producing dinoflagellate Gymnodinium catenatum for 5 days and to non-toxic diet during the subsequent 10 days. High toxicity levels (1493 µg STX eq. kg{sup −1}) exceeding the safety limits were determined under current conditions at the end of the uptake period. Significantly lower PSP toxicity levels were registered for warming- and acidification-acclimated mussels (661 and 761 µg STX eq. kg{sup −1}). The combined effect of both warming and acidification resulted in PSP toxicity values slightly higher (856 μg STX eq. kg{sup −1}). A rapid decrease of toxicity was observed in mussels at the current conditions after shifting to a non-toxic diet, which was not noticed under the predicted climate change scenarios. Variability of each PST analogue, measured throughout the experiment, highlighted different mechanisms are associated with changes of each environmental factor, although both resulting in lower toxicity. Warming-acclimated mussels showed lower accumulation/elimination rates, while acidification-acclimated mussels showed higher capability to accumulate toxins, but also a higher elimination rate preventing high toxicity levels. As different mechanisms are triggered by warming and acidification, their combined effect not leads to a synergism of their individual effects. The present work is the first assessing the combined effect of climate change drivers on accumulation/elimination of PSTs, in mussels, indicating that warming and acidification may lead to lower toxicity values but longer toxic episodes. PSTs are responsible for the food poisoning syndrome, paralytic shellfish poisoning (PSP) in humans. This study can be considered as the first step to build models for predicting shellfish toxicity under climate change scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)

Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. Thus, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth system models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth system models challenge validation and parameterization of hydrothermal models. A recently developed surface–subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to achieve the goals of constructing a process-rich model based on plausible parameters and to identify fine-scale controls of ALT in ice-wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze–thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g., troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)

Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Urbanization exacerbates continental- to regional-scale warming

Urbanization is usually ignored when estimating past changes in large-scale climate and for future climate projections since cities historically covered a small fraction of the Earth’s surface. Here, by combining global land surface temperature observations with historical estimates of urban area, we demonstrate that the urban contribution to continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions and countries in Asia. Consequently, expected urban expansion over the next century suggests further increased urban influence on large-scale surface climate in the future (approximately 0.16 K for North America and Europe for high-emission scenario in 2100). Based on these results, also seen for air temperature, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in climate change assessments. This requires incorporation of dynamic urban extent and biophysics in current-generation Earth system models to quantify potential urban feedback on the climate system across scales.

Chakraborty, TC↗
DOE OSTI2022

Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

Abstract. Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3

We analyze the atmospheric processes that explain the large changes in radiative feed-backs between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere-only climate-change simulations (amip and amip-p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme; and the development of a new mixed-phase cloud scheme. Both schemes reduce the strength of the pre-existing shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol-cloud interaction, and it also suppresses a negative clear-sky shortwave feedback. The mixed-phase scheme increases the amount of cloud liquid water path (LWP) in the present-day, thereby reducing the radiative effciency of the increase of LWP in the warmer climate. It also enhances a strong, pre-existing, positive cloud fraction feedback. We assess the realism of the changes by comparing present-day simulations against observations, and discuss avenues that could help constrain the relevant processes.

HadGEM3↗
DOE OSTI2013

The Impact of Abrupt Suspension of Solar Radiation Management (Termination Effect) in Experiment G2 of the Geoengineering Model Intercomparison Project (GeoMIP)

We have examined changes in climate which result from the sudden termination of geoengineering after 50 years of offsetting a 1% per annum increase in CO2 concentra- tions as simulated by 11 different climate models in experiment G2 of the Geoengineering Model Intercomparison Project. The models agree on a rapid rate of global-mean warming following termination, accompanied by increases in global-mean precipitation rate and in plant net primary productivity, and decreases in sea-ice cover. While there is a considerable degree of consensus for the geographical distribution of warming, there is much less of an agreement regarding the patterns of change in the other quantities.

experiment↗
DOE OSTI2016

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. Lastly, HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

58 GEOSCIENCES↗
NASA NTRS2015

Covariance Between Arctic Sea Ice and Clouds Within Atmospheric State Regimes at the Satellite Footprint Level

Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and mid-tropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.

Taylor, Patrick C.↗
DOE OSTI2013

Long-Term Performance of Uranium Tailings Disposal Cells - 13340

Recently, there has been interest in the performance and evolution of Uranium Mill Tailings Remedial Action (UMTRA) Project disposal cell covers because some sites are not compliant with groundwater standards. Field observations of UMTRA disposal cells indicate that rock covers tend to become vegetated and that saturated conductivities in the upper portion of radon barriers may increase due to freeze/thaw cycles and biointrusion. This paper describes the results of modeling that addresses whether these potential changes and transient drainage of moisture in the tailings affect overall performance of the disposal cells. A numerical unsaturated/saturated 3-dimensional flow model was used to simulate whether increases in saturated conductivities in radon barriers with rock covers affect the overall performance of the disposal cells using field data from the Shiprock, NM, UMTRA site. A unique modeling approach allowed simulation with daily climatic conditions to determine changes in moisture and moisture flux from the disposal cell. Modeling results indicated that increases in the saturated conductivity at the top of radon barrier do not influence flux from the tailings with time because the tailings behave similar hydraulically to the radon barrier. The presence of a thin layer of low conductivity material anywhere in the cover or tailings restricts flux in the worst case to the saturated conductivity of that material. Where materials are unsaturated at depth within the radon barrier of tailings slimes, conductivities are typically less than 10{sup -8} centimeters per second. If the low conductivity layer is deep within the disposal cell, its saturated properties are less likely to change with time. The significance of this modeling is that operation and maintenance of the disposal cells can be minimized if they are allowed to progress to a natural condition with some vegetation and soil genesis. Because the covers and underlying tailings have a very low saturated hydraulic conductivity after transient drainage, eventually the amount of moisture leaving the tailings has a negligible effect on groundwater quality. Although some of the UMTRA sites are not in compliance with the groundwater standards, the explanation may be legacy contamination from mining, or earlier higher fluxes from the tailings or unlined processing ponds. Investigation of other legacy sources at the UMTRA sites may help explain persistent groundwater contamination. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Understanding Recent Global Hydroclimate Change Using Multivariate Detection and Attribution Techniques and GCM Experiments

The observed slowdown in the rate of global average surface temperature (T) warming during the post-1998 decade (referred to at the time as the “global warming hiatus”) posed a challenge for climate researchers because it was not captured in global climate models projection. Observational and modeling evidence hinted that that leveling of the T trend was linked with the simultaneous appearance of cold surface temperature in the eastern equatorial Pacific that formed a protracted La Niña-like state, a phenomenon known as the Inter-decadal Pacific Oscillation (IPO). It was however not clear whether the concurrent equatorial Pacific cooling was a regional response to the rise in atmospheric greenhouse gas levels or anthropogenic aerosols that is not captured by the climate models or whether it was an unrelated, serendipitous manifestation of a natural phenomenon, internal to the climate system. To resolve this issue, we proposed in this project to develop and apply fingerprinting methods to differentiate between the observed climate response to various external forcing agents and the manifestations of internal climate variability. The project also sought to find out if climate models are able to reproduce the change signals detected in key observational phenomena and if they can be used to investigate the underlying processes. As such we examined changes in global hydroclimate variability and in an outstanding example of regional hydroclimate change, namely the multi-decadal 20 th century change in Sahel rainfall.

54 ENVIRONMENTAL SCIENCES↗