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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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NASA NTRS2017

Extratropical Weather Systems on Mars: Radiatively-Active Water Ice Effects

Extratropical, large-scale weather disturbances, namely transient, synoptic-period,baroclinic barotropic eddies - or - low- (high-) pressure cyclones (anticyclones), are components fundamental to global circulation patterns for rapidly rotating, differentially heated, shallow atmospheres such as Earth and Mars. Such "wave-like" disturbances that arise via (geophysical) fluid shear instability develop, mature and decay, and travel west-to-east in the middle and high latitudes within terrestrial-like planetary atmospheres. These disturbances serve as critical agents in the transport of heat and momentum between low and high latitudes of the planet. Moreover, they transport trace species within the atmosphere (e.g., water vapor/ice, other aerosols (dust), chemical species, etc). Between early autumn through early spring, middle and high latitudes on Mars exhibit strong equator-to-pole mean temperature contrasts (i.e., "baroclinicity"). Data collected during the Viking era and observations from both the Mars Global Surveyor (MGS) and Mars Reconnaissance Orbiter (MRO) indicate that such strong baroclinicity supports vigorous, large-scale eastward traveling weather systems [Banfield et al., 2004; Barnes et al., 1993]. A good example of traveling weather systems, frontal wave activity and sequestered dust activity from MGS/MOC image analyses is provided in Figure 1 (cf. Wang et al. [2005]). Utilizing an upgraded and evolving version of the NASA Ames Research Center (ARC) Mars global climate model, investigated here are key dynamical and physical aspects of simulated northern hemisphere (NH) large-scale extratropica lweather systems,with and without radiatively-active water ice clouds. Mars Climate Model:

cyclones↗

NASA NTRS2022

NASA Global Daily Downscale Projections, CMIP6

We describe the latest version of the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). The archive contains downscaled historical and future projections for 1950–2100 based on output from Phase 6 of the Climate Model Intercomparison Project (CMIP6). The downscaled products were produced using a daily variant of the monthly bias correction/spatial disaggregation (BCSD) method and are at 1/4-degree horizontal resolution. Currently, eight variables from five CMIP6 experiments (historical, SSP126, SSP245, SSP370, and SSP585) are provided as procurable from thirty-five global climate models.

Climate↗

DOE OSTI2023

Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)

The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios. Sup3rCC is downscaled Global Climate Model (GCM) data. The downscaling process was performed using a generative machine learning approach called sup3r: Super-Resolution for Renewable Energy Resource Data (linked below as "Sup3r GitHub Repo"). The data includes both historical and future weather years, although the historical years represent the historical climate, not the actual historical weather that we experienced. You cannot use Sup3rCC data to study historical weather events, although other sup3r datasets may be intended for this. The Sup3rCC data is intended to help researchers study the impact of climate change on energy systems with high levels of wind and solar capacity. Please note that all climate change data is only a representation of the possible future climate and contains significant uncertainty. Analysis of multiple climate change scenarios and multiple climate models can help quantify this uncertainty.

Array↗

NASA NTRS1988

Modelling the slow climatic attractor

Attempts to model the evolution of the slow-response parts of the climatic system such as the global ice mass are reviewed, and the fundamental laws governing the complete complex multidomain slow system, called the slow climatic attractor, are analyzed. The uses of paleoclimatic records are discussed, and a low-order model for the late Quaternary variations that constitutes a credible global representation of the slow climatic attractor is presented. It is shown that although according to the model the climatic system is centered on an unstable equilibrium, the points of the limit cycle attractor are quite stable and robust. It is also noted that one major deficiency of the model is its inability to portray the geographic spatial variability of climatic mean states. However, at least with regard to atmospheric CO2, estimates of the geographic fields of all significant atmospheric and surface boundary layer climate variables are deducible.

Saltzman, Barry↗

DOE OSTI2017

The G4Foam Experiment: Global climate impacts of regional ocean albedo modification

Reducing insolation has been proposed as a geoengineering response to global warming. Here we present the results of climate model simulations of a unique Geoengineering Model Intercomparison Project Testbed experiment to investigate the benefits and risks of a scheme that would brighten certain oceanic regions. The National Center for Atmospheric Research CESM CAM4-Chem global climate model was modified to simulate a scheme in which the albedo of the ocean surface is increased over the subtropical ocean gyres in the Southern Hemisphere. In theory, this could be accomplished using a stable, nondispersive foam, comprised of tiny, highly reflective microbubbles. Such a foam has been developed under idealized conditions, although deployment at a large scale is presently infeasible. We conducted three ensemble members of a simulation (G4Foam) from 2020 through to 2069 in which the albedo of the ocean surface is set to 0.15 (an increase of 150%) over the three subtropical ocean gyres in the Southern Hemisphere, against a background of the RCP6.0 (representative concentration pathway resulting in +6Wm -2 radiative forcing by 2100) scenario. After 2069, geoengineering is ceased, and the simulation is run for an additional 20 years. Global mean surface temperature in G4Foam is 0.6 K lower than RCP6.0, with statistically significant cooling relative to RCP6.0 south of 30°N. There is an increase in rainfall over land, most pronouncedly in the tropics during the June–July–August season, relative to both G4SSA (specified stratospheric aerosols) and RCP6.0. Heavily populated and highly cultivated regions throughout the tropics, including the Sahel, southern Asia, the Maritime Continent, Central America, and much of the Amazon experience a statistically significant increase in precipitation minus evaporation. The temperature response to the relatively modest global average forcing of -1.5 W m -2 is amplified through a series of positive cloud feedbacks, in which more shortwave radiation is reflected. Finally, the precipitation response is primarily the result of the intensification of the southern Hadley cell, as its mean position migrates northward and away from the Equator in response to the asymmetric cooling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Timescale Dependence of the Precipitation Response to CO 2 ‐Induced Warming in Millennial‐Length Climate Simulations

Abstract Previous work has shown that estimates of climate sensitivity vary over time in response to abrupt CO 2 forcing in climate model simulations. The energy fluxes that drive warming in response to increasing CO 2 also influence precipitation, which prompts the question: Does the precipitation response therefore also vary over time? We investigate by examining the response of precipitation to warming forced by greenhouse gases—the hydrological sensitivity—in a set of millennial‐length climate simulations with multiple climate models, Long Run Model Intercomparison Project (LongRunMIP). We compare hydrological sensitivity calculated from three different timescales of the simulations: years 1–20, 21–150, and 151–1000. We show that the hydrological sensitivity lacks a consistent dependence on timescale, in contrast to climate sensitivity. Decomposition of the surface energy budget reveals that the relative muting of the multi‐model mean hydrological sensitivity is driven by surface downwelling shortwave flux.

Him (Kinen) Kao, Wing↗

DOE OSTI2016

Impact of horizontal resolution on simulation of precipitation extremes in an aqua-planet version of Community Atmospheric Model (CAM3)

One key question regarding current climate models is whether the projection of climate extremes converges to a realistic representation as the spatial and temporal resolutions of the model are increased. Ideally the model extreme statistics should approach a fixed distribution once the resolutions are commensurate with the characteristic length and time scales of the processes governing the formation of the extreme phenomena of interest. In this study, a series of AGCM runs with idealized 'aquaplanet-steady-state' boundary conditions have been performed with the Community Atmosphere Model CAM3 to investigate the effect of horizontal resolution on climate extreme simulations. The use of the aquaplanet framework highlights the roles of model physics and dynamics and removes any apparent convergence in extreme statistics due to better resolution of surface boundary conditions and other external inputs. Assessed at a same large spatial scale, the results show that the horizontal resolution and time step have strong effects on the simulations of precipitation extremes. The horizontal resolution has a much stronger impact on precipitation extremes than on mean precipitation. Updrafts are strongly correlated with extreme precipitation at tropics at all the resolutions, while positive low-tropospheric temperature anomalies are associated with extreme precipitation at mid-latitudes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2019

Stellar Activity Effects on Moist Habitable Terrestrial Atmospheres Around M Dwarfs

Transit spectroscopy of terrestrial planets around nearby M dwarfs will be a primary goal of space missions in coming decades. Three-dimensional climate modeling has shown that slow-synchronous rotating terrestrial planets may develop thick clouds at the substellar point, increasing the albedo. For M dwarfs with T(eff)>3000 K, such planets at the inner habitable zone (IHZ) have been shown to retain moist greenhouse conditions, with enhanced stratospheric water vapor ( fH2O>10(exp −3)) and low Earth-like surface temperatures. However, M dwarfs also possess strong UV activity, which may effectively photolyze stratospheric H2O. Prior modeling efforts have not included the impact of high stellar UV activity on the H2O. Here, we employ a 1D photochemical model with varied stellar UV, to assess whether H2O destruction driven by high stellar UV would affect its detectability in transmission spectroscopy. Temperature and water vapor profiles are taken from published 3D climate model simulations for an IHZ Earth-sized planet around a 3300 K M dwarf with an N2–H2O atmosphere; they serve as self-consistent input profiles for the 1D model. We explore additional chemical complexity within the 1D model by introducing other species into the atmosphere. We find that as long as the atmosphere is well-mixed up to 1 mbar, UV activity appears to not impact detectability of H2O in the transmission spectrum. The strongest H2O features occur in the James Webb Space Telescope MIRI instrument wavelength range and are comparable to the estimated systematic noise floor of ∼50 ppm.

Badhan, Mahmuda Afrin↗

DOE OSTI2025

Cloud radiative effects significantly increase wintertime atmospheric blocking in the Euro-Atlantic sector

Reliable simulation, prediction, and complete theoretical understanding of atmospheric blocking remain challenging despite its significant socio-economic impacts. Generations of climate models have notoriously underestimated blocking frequency, particularly over the Euro-Atlantic sector. Identifying factors controlling blocking frequency and dynamics is therefore essential for improving its simulation. Here, using a cloud-locking experiment, we show that cloud radiative effects (CREs) significantly increase the frequency of Euro-Atlantic blocking. CREs enhance upstream diabatic source of wave activity, both directly through longwave heating and indirectly through their feedback on latent heating, with the latter playing the dominant role. The resulting increase in the upstream diabatic source feeds into local wave activity downstream and promotes blocking formation. Qualitatively similar results are shown by multi-model experiments with radiatively inactive clouds to longwave radiation, albeit with a larger impact from mean-state changes. The results underscore the necessity of accurately representing cloud-radiation interactions in weather and climate models for improved prediction of blocking events.

Atmospheric dynamics↗

DOE OSTI2019

Monitoring the Urban Heat Island Effect and the Efficacy of Future Countermeasures

To relate fine-scale spatial air-temperature variations in local urban heat islands and urban cool islands—increases and decreases in outside air temperature—within a large urban-climate archipelago to variations in land-use and land-cover properties in the Los Angeles Basin, the research team sought to (a) use fine-resolution meso-urban climate models to identify areas of urban heat and cool islands, select sites for fixed weather monitoring, and choose routes for mobile observations; (b) relate observed intraurban temperature variations to land use and land cover and surface physical properties; and (c) calibrate/validate the climate models. The research team assessed urban temperature variations via simulations and observations, including mobile transects, mesonet, dense networks of personal weather stations, and sparse but more accurate research-grade monitors. To identify the causative factors of the urban heat and cool islands at the neighborhood scale, the research team collected detailed urban morphometric and land use and land cover datasets, such as 1-meter (3.3 foot) resolution roof albedo (solar reflectance) and tree canopy cover. The research team used the observationvalidated model to finalize the transect routes and site the stationary monitors. This study provides the first observational evidence from analysis of high-spatial-density weather stations that increases in roof albedo at neighborhood scale are associated with reductions in near-surface air temperature. This finding was corroborated with the analysis from mobile transect measurements and correlation of observed air temperature with neighborhood-scale albedo and vegetation. This correlation revealed a cooling effect from areawide increase in albedo or canopy cover or both. The calibrated meteorological model accurately identified the localized urban heat and cool islands observed in this study. Interested stakeholders/researchers can use the same models and calibration/validation methodology to characterize within-city microclimate variations elsewhere in California, and can apply them to analyze the benefits from using urban heat island countermeasures. This project report is an extended and more detailed version of a related report prepared for California’s Fourth Climate Change Assessment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Preliminary Science Plan

General circulation models and downscaled regional models exhibit persistent biases in deep convective initiation location and timing, cloud top height, stratiform area and precipitation fraction, and anvil coverage. Despite important impacts on the distribution of atmospheric heating, moistening, and momentum, nearly all climate models fail to represent convective organization, while system evolution is not represented at all. Improving representation of convective systems in models requires characterization of their predictability as a function of environmental conditions, and this characterization depends on observing many cases of convective initiation, non-initiation, organization, and non-organization. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) experiment in the Sierras de Córdoba mountain range of north-central Argentina is designed to improve understanding of cloud life cycle and organization in relation to environmental conditions so that cumulus, microphysics, and aerosol parameterizations in multi-scale models can be improved. The Sierras de Córdoba range has a high frequency of orographic boundary-layer clouds, many reaching congestus depths, many initiating into deep convection, and some organizing into mesoscale systems uniquely observable from a single fixed site. Some systems even grow upscale to become among the deepest, largest, and longest-lived in the world. These systems likely contribute to an observed regional trend of increasing extreme rainfall, and poor prediction of them likely contributes to a warm, dry bias in climate models downstream of the Sierras de Córdoba range in a key agricultural region. Many environmental factors influence the convective lifecycle in this region including orographic, low-level jet, and frontal circulations, surface fluxes, synoptic vertical motions influenced by the Andes, cloud detrainment, and aerosol properties. Local and long-range transport of smoke resulting from biomass burning as well as blowing dust are common in the austral spring, while changes in land surface properties as the wet season progresses impact surface fluxes and boundary layer evolution on daily and seasonal time scales that feed back to cloud and rainfall generation. This range of environmental conditions and cloud properties coupled with a high frequency of events makes this an ideal location for improving our understanding of cloud-environment interactions. The following primary science questions will be addressed through coordinated first ARM Mobile Facility (AMF1), mobile C-band Scanning ARM Precipitation Radar (C-SAPR2), guest instrumentation, and potential ARM Aerial Facility (AAF) Gulfstream-1 (G-1) observations: 1. How are the properties and lifecycles of orographically generated cumulus humulis, mediocris, and congestus clouds affected by environmental kinematics, thermodynamics, aerosols, and surface properties? How do these cloud types alter these environmental conditions? 2. How do environmental kinematics, thermodynamics, and aerosols impact deep convective initiation, upscale growth, and mesoscale organization? How are soil moisture, surface fluxes, and aerosol properties altered by deep convective precipitation events and seasonal accumulation of precipitation? This multi-faceted experiment involves a long term 8.5-month Extended Observing Period (EOP, 15 August, 2018-30 April, 2019) as well as a 6-week Intensive Observation Period (IOP, 1 November-15 December) that will coincide with the international multi-agency RELAMPAGO field campaign.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Science Plan

General circulation models and downscaled regional models exhibit persistent biases in deep convective initiation location and timing, cloud top height, stratiform area and precipitation fraction, and anvil coverage. Despite important impacts on the distribution of atmospheric heating, moistening, and momentum, nearly all climate models fail to represent convective organization, while system evolution is not represented at all. Improving representation of convective systems in models requires characterization of their predictability as a function of environmental conditions, and this characterization depends on observing many cases of convective initiation, non-initiation, organization, and non-organization. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) experiment in the Sierras de Córdoba mountain range of north-central Argentina is designed to improve understanding of cloud life cycle and organization in relation to environmental conditions so that cumulus, microphysics, and aerosol parameterizations in multiscale models can be improved. The Sierras de Córdoba range has a high frequency of orographic boundary-layer clouds, many reaching congestus depths, many initiating into deep convection, and some organizing into mesoscale systems uniquely observable from a single fixed site. Some systems even grow upscale to become among the deepest, largest, and longest-lived in the world. These systems likely contribute to an observed regional trend of increasing extreme rainfall, and poor prediction of them likely contributes to a warm, dry bias in climate models downstream of the Sierras de Córdoba range in a key agricultural region. Many environmental factors influence the convective life cycle in this region, including orographic, low-level jet, and frontal circulations, surface fluxes, synoptic vertical motions influenced by the Andes, cloud detrainment, and aerosol properties. Local and long-range transport of smoke resulting from biomass burning as well as blowing dust are common in the austral spring, while changes in land surface properties as the wet season progresses impact surface fluxes and boundary-layer evolution on daily and seasonal time scales that feed back to cloud and rainfall generation. This range of environmental conditions and cloud properties coupled with a high frequency of events makes this an ideal location for improving our understanding of cloud-environment interactions. The following primary science questions will be addressed through coordinated first U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF1), mobile C-band Scanning ARM Precipitation Radar (C-SAPR2), ARM Aerial Facility (AAF) Gulfstream-1 (G-1), and guest instrument observations: How are the properties and life cycles of orographically generated cumulus humulis, mediocris, and congestus clouds affected by environmental kinematics, thermodynamics, aerosols, and surface properties? How do these cloud types alter these environmental conditions? How do environmental kinematics, thermodynamics, and aerosols impact deep convective initiation, upscale growth, and mesoscale organization? How are soil moisture, surface fluxes, and aerosol properties altered by deep convective precipitation events and seasonal accumulation of precipitation? This multi-faceted experiment involves a long-term 7-month extended operational period (EOP, 1 October, 2018–30 April, 2019) as well as a 1.5-month intensive operational period (IOP, 30 October–13 December) that will include G-1 observations coinciding with the international multi-agency Remote Sensing of Electrification, Lightning, and Meso-scale/Micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign.

Convection, Andes, Argentina, cloud life cycle, cl↗

NASA NTRS1982

The influence of ground moisture conditions in North America on summer climate as modeled in the GISS GCM

A new general circulation model, developed to run on a coarse grid (8 x 10 deg resolution) at the Goddard institute for Space Studies is employed to investigate the potential use of ground moisture anomalies for seasonal climate prediction. For three different summertime simulations, the ground moisture on 1 June over the United States is reduced to 1/4 of its value in the control run. The results show that the subsequent surface air temperature is significantly higher throughout most of the summer, while the precipitation decreases, especially in June and July. Knowledge of late spring ground moisture anomalies should thus be an aid in predicting summertime climate.

Rind, D.↗

NASA NTRS2019

Stellar Activity Effects on Moist Habitable Terrestrial Atmospheres Around M Dwarfs

Transit spectroscopy of terrestrial planets around nearby M dwarfs is a primary goal of space missions in coming decades. 3-D climate modeling has shown that slow-synchronous rotating terrestrial planets may develop thick clouds at the substellar point, increasing the albedo. For M dwarfs with T(eff) > 3000 K, such planets at the inner habitable zone (IHZ) have been shown to retain moist greenhouse conditions, with enhanced stratospheric water vapor (fH2O > 10(exp -3)) and low Earth-like surface temperatures. However, M dwarfs also possess strong UV activity, which may effectively photolyze stratospheric H2O. Prior modeling efforts have not included the impact of high stellar UV activity on the H2O. Here, we employ a 1-D photochemical model with varied stellar UV, to assess whether H2O destruction driven by high stellar UV would affect its detectability in transmission spectroscopy. Temperature and water vapor profiles are taken from published 3-D climate model simulations for an IHZ Earth-sized planet around a 3300 K M dwarf with an N2-H2O atmosphere; they serve as self-consistent input profiles for the 1-D model. We explore additional chemical complexity within the 1-D model by introducing other species into the atmosphere. We find that as long as the atmosphere is well-mixed up to 1 mbar, UV activity appears to not impact detectability of H2O in the transmission spectrum. The strongest H2O features occur in the JWST MIRI instrument wavelength range and are comparable to the estimated systematic noise floor of ~50 ppm.

Mahmuda Afrin Badhan↗

NASA NTRS2015

Role of Longwave Cloud-Radiation Feedback in the Simulation of the Madden-Julian Oscillation

The role of the cloud-radiation interaction in the simulation of the Madden-Julian oscillation (MJO) is investigated. A special focus is on the enhancement of column-integrated diabatic heating due to the greenhouse effects of clouds and moisture in the region of anomalous convection. The degree of this enhancement, the greenhouse enhancement factor (GEF), is measured at different precipitation anomaly regimes as the negative ratio of anomalous outgoing longwave radiation to anomalous precipitation. Observations show that the GEF varies significantly with precipitation anomaly and with the MJO cycle. The greenhouse enhancement is greater in weak precipitation anomaly regimes and its effectiveness decreases monotonically with increasing precipitation anomaly. The GEF also amplifies locally when convection is strengthened in association with the MJO, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). A robust statistical relationship is found among CMIP5 climate model simulations between the GEF and the MJO simulation fidelity. Models that simulate a stronger MJO also simulate a greater GEF, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). Models with a greater GEF in the strong precipitation anomaly regime (greater than 30 mm day(-1)) represent a slightly slower MJO propagation speed. Many models that lack the MJO underestimate the GEF in general and in particular in the weak precipitation anomaly regime. The results herein highlight that the cloud-radiation interaction is a crucial process for climate models to correctly represent the MJO.

Clouds↗

DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗

DOE OSTI2016

Large differences in regional precipitation change between a first and second 2 K of global warming

For adaptation and mitigation planning, stakeholders need reliable information about regional precipitation changes under different emissions scenarios and for different time periods. A significant amount of current planning effort assumes that each K of global warming produces roughly the same regional climate change. By using 25 climate models, we compare precipitation responses with three 2 K intervals of global ensemble mean warming: a fast and a slower route to a first 2 K above pre-industrial levels, and the end-of-century difference between high-emission and mitigation scenarios. Here, we show that, although the two routes to a first 2 K give very similar precipitation changes, a second 2 K produces quite a different response. In particular, the balance of physical mechanisms responsible for climate model uncertainty is different for a first and a second 2 K of warming. Our results are consistent with a significant influence from nonlinear physical mechanisms, but aerosol and land-use effects may be important regionally.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

A Regional Model of Climate Change and Human Migration

As climate change and human migration accelerate globally, decision-makers are seeking tools that can deepen their understanding of the complex nexus between climate change and human migration. These tools can help to identify populations under pressure to migrate, and to explore proactive policy options and adaptive measures. Given the complexity of factors influencing migration, this article presents a system dynamics-based model that couples migration decision making and behavior with the interacting dynamics of economy, labor, population, violence, governance, water, food, and disease. The regional model is applied here to the test case of migration within and beyond Mali. As a result the study explores potential systems impacts of a range of proactive policy solutions and shows that improving the effectiveness of governance and increasing foreign aid to urban areas have the highest potential of those investigated to reduce the necessity to migrate in the face of climate change.

54 ENVIRONMENTAL SCIENCES↗