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At least 19 records

Wake Effects in Lower Carbon Future Scenarios

In August 2022, the U.S. Congress passed the Inflation Reduction Act (IRA), which intended to accelerate U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. The National Renewable Energy Laboratory has examined possible scenarios for growth by 2050 resulting from the IRA and other emissions reduction drivers and defined several possible scenarios for large-scale wind deployment. These scenarios incorporate large clusters of turbines operating as wind farms grouped around existing or likely transmission lines which will result in wind farm wakes. Using a numerical weather prediction (NWP) model, we assess these wake effects in a domain in the U. S. Southern Great Plains for a representative year with four scenarios in order to validate the simulations, estimate the internal wake impact, and quantify the cluster wake effect. Herein, we present a validation of the ”no wind farm” scenario and quantify the internal waking effect for the ”ONE” wind farm scenario. Future work will use the “MID” scenario (more than 8000 turbines) and the “HI” scenario (more than 16,000 turbines) to quantify the effect of cluster wakes or inter-farm wakes on power production.

17 WIND ENERGY↗

Spatially explicit land-energy-water future scenarios for cities: Guiding infrastructure transitions for urban sustainability

Cities control the majority of global human resource consumption and serve as hubs of major infrastructural networks. To offset their resource demands, cities derive goods and resources from regions well outside urban boundaries inducing stress and impacts on distal ecosystems. As cities grow, these stressors are likely to increase, depending on choices about how resource demands will be addressed through new infrastructures; hence, city governance is extremely important to future global sustainability. Yet, to support effective decision-making and infrastructure transitions, developing tangible city-scale alternative future scenarios is needed. We present a methodology for developing plausible spatially explicit alternative futures for city infrastructures and discuss the tradeoffs in land, energy, carbon, and water resources among alternative future pathways. We first estimate future city populations and urban boundaries and characterize future land cover scenarios. Future population along with residential housing and commercial characteristics are used to estimate current and future electricity and water demand. We characterize the energysheds of cities, which then become the spatial template for designing future electricity production scenarios. Future electricity mixes and spatial distributions of powerplants provide wide-ranging tradeoffs in carbon reduction, water use reduction, and land usage. Additionally, we explore future alternatives for meeting water supply demands. With this work, we emphasize the importance of translating scenarios into physical on-the-ground relevance in order to ensure transparent communication among city- and utility-governance. Unless spatially explicit future infrastructure scenarios are provided, we believe city-level goals will become difficult to implement, or even worse, result in unintended consequences on regional natural resources.

54 ENVIRONMENTAL SCIENCES↗

Urban Expansion and Climate Change: Investigating the Impact of Future Scenarios on Child Health

Cities in the poorest countries of the world are rapidly urbanizing. In fact, some of the fastest growing cities on the planet are found in sub-Saharan Africa. Many people benefit from economic, educational, and health opportunities that exist in cities and, as a result, city-dwellers often face less risk of poverty and disease in the context of climate change than their rural-dwelling counterparts. However, rapid urbanization, resulting from a large and constant influx of migrants from rural areas, can put pressure on existing social, economic, and health systems. For poor cities, they face a challenge to support existing residents while also expanding to support the needs of migrants, many of whom are deeply impoverished. Additionally, in a climate change, linked to heat waves, floods, droughts, and other related events, can add stress to complex urban food, health, hygiene, and housing systems. In this project we investigate urban expansion, climate change, and health in four major African cities – Ouagadougou, Addis Ababa, Nairobi, and Kigali. We consider different scenarios of urban expansion using historic and contemporary maps of urban extent, combined with climate (temperature, rainfall, and vegetation) and land cover combined with spatially referenced health information from the Demographic and Health Surveys (DHS) to investigate the relationships between urban dwelling, climate change and health. Temperature and rainfall scenarios are developed under different urban land use futures (expanding agricultural areas versus reducing agricultural areas) to examine the ways that individual health outcomes related to malnutrition vary under different potential future conditions. Preliminary results of the research highlight the importance of temperature for health, in particular, and suggest that while urban conditions related to urban infrastructure (e.g., educational attainment, electricity access, and improved hygiene) cannot reduce health risks to counter the impacts of high temperatures and reduced agricultural land. As cities in poor countries urbanize, city-dwellers face unique risks when droughts, heat waves, and other extreme weather events occur. In this project we explore urban land use conditions, climate conditions and health using future scenarios. Specifically we evaluate health outcomes in the future while considering different land use practices, urban expansion, temperature, and rainfall conditions to identify individual-level risk and protective factors. We compare results across four major cities in sub Saharan Africa.

Public Health↗

Evaluating Contemporary and Future-Scenario Substantial-Precipitation Events in the Missouri River Basin Using Object-Oriented Analysis

The Missouri River Basin is the largest single river basin in the United States, and, as such, it plays an important role in natural ecosystems as well as the country’s economy, through agriculture, hydroelectric power generation, and transportation. Episodes of heavy precipitation can have a substantial negative impact on all these aspects of the basin, so understanding how well these episodes are simulated and projected to change in the future climate is important. We analyzed contemporary and projected mid-century behavior of heavy-precipitation episodes using an object-oriented analysis to diagnose short-term (≥5-day) and extended-period (≥30-day) events with substantial precipitation, using PRISM gridded, observed precipitation and RegCM4 regional-climate simulations that used outputs from two different GCMs for boundary conditions. The simulations were produced for the North American portion of the CORDEX program. A 25 km grid was used for the simulations and for aggregated PRISM precipitation. Overall, the simulated contemporary-climate events compared favorably with the PRISM events’ frequency and duration. The simulated event areas tended to be larger than the areas in the PRISM events, suggesting that the effective resolution of the simulations is greater than 25 km. Event areas and durations change little going from contemporary to scenario climate. The short-term events increase in frequency by an amount commensurate with the increase in mean precipitation simulated for the basis. However, the extended-term events showed little change in frequency, despite the average precipitation increase. Roughly half the extended-period events overlapped with at least one short-term event in both the observations and the simulations. Extended-period events that overlap a short-term event generally have larger areas and longer durations compared to their counterparts with no overlapping short-term events. Understanding the climate dynamics yielding the two types of extended-period events could be useful for assessing future changes in the Missouri River Basin’s heavy precipitation events and their impact.

Fisel, Brandon J.↗

Pathways of bio-jet adoption in the US aviation industry with implications for the overall transportation and energy sectors: an integrated, multi-sectoral analysis of future scenarios

Bio-jet adoption has emerged as an attractive option to complement and supplement the use of refined fossil liquid fuels in the aviation industry in the US. However, there are significant uncertainties surrounding the costs of bio-jet including but not limited to costs of feedstock, transformation costs and the competition with co-products of bio-jet that may be demanded elsewhere in the transportation or energy sectors. This study models alternative trajectories of bio-jet adoption in the US aviation industry by 2050 through the use of a global integrated multi sector dynamics model. Three bio-jet production and consumption pathways are presented- soybean oil to jet, corn ethanol to jet (ETJ) and Fisher–Tropsch-based bio-jet, with each pathway explicitly considering the co-production of renewable diesel and renewable gasoline alongside the bio-jet. Without explicit actions or technology changes to offset the technology cost of bio-jet, scenarios where bio-jet displaces refined liquids result in higher aviation fuel prices (ranging from a 25% increase to 120% increase by mid-century) and lower demand (ranging from −14% to −43%). Corn ethanol will play an important role in the US if large scale amounts of bio-jet are to be produced with smaller effects on demand and prices. While scenarios with high levels of bio-jet availability without the availability of ETJ in the US can significantly reduce emissions in the aviation sector, these reductions are achieved more through the reduction in overall aviation fuel demand rather than technology adoption.

09 BIOMASS FUELS↗

Exploring Building Retrofit Strategies Using AutoBEM Under Future Weather Scenarios

This study evaluates the long-term effectiveness of energy conservation measures (ECMs) on building energy consumption using AutoBEM, a scalable modeling framework driven by the high-resolution Model America dataset. We simulated 18,951 buildings in Flagstaff, Arizona under four climate scenarios using Future Typical Meteorological Year (fTMY) weather files for six time periods spanning from 1980 to 2099. Six ECMs were analyzed across electricity and gas usage, including HVAC fuel-switching, insulation upgrades, and infiltration control. While some measures, such as reducing space infiltration by percentage, showed minimal or even negative impact on total energy savings at the aggregate level, they proved highly effective for specific building types. Conversely, HVAC electrification offers high gas reduction but shifts demand to electricity, highlighting critical trade-offs under different climate trajectories. Building-type-specific analysis under SSP5-RCP8.5 (2080–2099) revealed significant variation in ECM performance, underscoring the need for targeted retrofit strategies. This study demonstrates the power of combining fTMY projections with large-scale simulations to inform data-driven retrofit planning.

Chowdhury, Shovan [ORNL]↗

Analysis of Hybrid Electric Aircraft Operations in the National Airspace System

This paper investigates the fuel burn and flight time impacts of hybrid electric aircraft operating in the National Airspace System. Future scenarios with hybrid electric flights and the same passenger travel capacity between city pairs as a baseline scenario, taken from historical data, were created. Aircraft that serviced select flights in the baseline scenario were replaced with hybrid electric aircraft based on the flight’s range and seat capacity. Additional hybrid electric flights were added to future scenarios when necessary to keep the future scenario passenger capacity equal or greater to that of the baseline scenario. The baseline and future scenarios were simulated in the NAS Digital Twin, a live, virtual, and constructive environment for building and executing simulations of the Nation Airspace System. Results showed that the future scenarios with hybrid electric flights saved fuel burn, but increased flight time. In the future scenarios, the additional hybrid electric flights did not cause any airports to exceed their operational capacity.

Simulation↗

Operating Hybrid Electric Aircraft in the National Airspace System

This paper investigates the fuel burn and flight time impacts of hybrid electric aircraft operating in the National Airspace System. Future scenarios with hybrid electric flights and the same passenger travel capacity between city pairs as a baseline scenario, taken from historical data, were created. Aircraft that serviced select flights in the baseline scenario were replaced with hybrid electric aircraft based on the flight’s range and seat capacity. Additional hybrid electric flights were added to future scenarios when necessary to keep the future scenario passenger capacity equal or greater to that of the baseline scenario. The baseline and future scenarios were simulated in the NAS Digital Twin, a live, virtual, and constructive environment for building and executing simulations of the Nation Airspace System. Results showed that the future scenarios with hybrid electric flights saved fuel burn, but increased flight time. In the future scenarios, the additional hybrid electric flights did not cause any airports to exceed their operational capacity.

hybrid electric aircraft↗

When Do Different Scenarios of Future Electricity Demand Start to Meaningfully Diverge?

Climate and population change are known to influence electricity demand, but what is the impact of uncertainty in climate and population projections on electricity demand in the United States (U.S.) over the next 30 years? This question has important implications for investment decisions in the energy sector, which are typically made using a 15- to 30-year time horizon. Simply put, if future climate and population scenarios do not lead to meteorological conditions and subsequent energy demands that are distinctly different within the first 30 years then, for the purposes of investment decisions, it may not matter which potential pathway we are most likely on. The Integrated, Multisector, Multiscale Modeling (IM3) project has generated a wide, yet plausible range of 21st century high-resolution climate and population scenarios for the U.S. The IM3 projections span two climate scenarios (Representative Concentration Pathways 4.5 and 8.5) and two population scenarios (Shared Socioeconomic Pathways 3 and 5). For each of the climate scenarios, we reflect a range of climate model uncertainty by using boundary conditions from a set of climate models that are hotter and colder than the multi-model mean. In total there are eight (2 x 2 x 2) IM3 scenarios. This work explores a basic question: When do future climate and energy outcomes start to meaningfully diverge across the eight scenarios? The analysis is done on both the raw meteorology time-series from each scenario as well as a time-series of projected total electricity demand generated using IM3's Total ELectricity Loads (TELL) model. We also explore the spatial heterogeneity of the divergence signal to identify regions of the country that may be more or less path dependent.

Climate Change↗

GCAP 2.0: A Global 3-D Chemical-Transport Model Framework for Past, Present, and Future Climate Scenarios

This manuscript describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the preindustrial and recent past. In addition, meteorology is available for the near future and end-of-the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) product and with observational constraints.

Global Change and Air Pollution (GCAP 2.0) model↗

GCAP 2.0: A Global 3-D Chemical-Transport Model Framework for Past, Present, and Future Climate Scenarios

This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.

Global Change and Air Pollution (GCAP 2.0) model↗

The Transportation Energy and Mobility Pathway Options (TEMPO) Model: Overview and Validation of V1.0 [Slides]

This presentation documents the approaches and methods used in the Transportation Energy & Mobility Pathway Options™ (TEMPO) model to evaluate passenger and freight demand for transportation and mobility services, project vehicle ownership and technology adoption decisions, and determine transport mode choices to derive scenarios of future energy use and emissions. TEMPO is an all-inclusive transportation demand model that covers the entire United States, with an implicit spatial resolution and an hourly temporal resolution that allows for generating time-resolved energy use profiles to assess multisectoral integration aspects. Key features of the TEMPO model include the ability to perform endogenous out-of-sample forecasting to extrapolate recent emerging trends and analyze impacts of disruptive technological breakthroughs and behavioral changes. TEMPO employs an innovative representation of passenger mobility demand stemming from household-level decisions that determine vehicle adoption, ownership, and use based on sociodemographics (e.g., income, household composition), technology attributes (e.g., travel cost, time), geography (e.g., urban, suburban, rural) and population-specific multiday mobility and travel requirements. This representation enables a more forward-looking perspective on the use of new mobility options and the adoption of alternative fuel vehicles, as well as a more accurate representation of their energy usage profiles than previous modeling approaches. A comparison with the U.S. Energy Information Administration’s Annual Energy Outlook showcases the ability of TEMPO to accurately replicate widely accepted projections by representing the key elements of the entire transportation sector at the appropriate level of resolution. TEMPO is intended to generate future scenarios of technology adoption, energy use, and emissions in the transportation sector to compare alternatives, inform decision makers, and assess integration with energy infrastructure and supply systems at an appropriate spatiotemporal resolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem

NASA is preparing for the retirement of the ISS and transition of LEO activities to one or more Commercial LEO Destinations (CLDs) by 2030. This transition necessitates new models for connecting NASA and other government-funded users of the LEO environment to platforms and opportunities. This paper describes for consideration six models for facilitating government-funded activities in the post-ISS LEO ecosystem. These six models are illustrative and represent a wide trade space of potential options, each relying on unique mechanisms for facilitating activities on one or more commercial LEO platforms or vehicles. We assessed each model across three possible future scenarios varying in number and diversity of LEO activities and commercial offerings, and across five stakeholder-driven model evaluation criteria. We present the highlights of the analysis, including ways to modify and strengthen each model. The Government Research Broker model performs best across all future scenarios, followed by Innovation Campus, Anchor Tenant, and Fee for Service. While Matchmaker and Institute Network exhibit positive aspects, these models perform most favorably in future scenarios with well-established communities and markets. While each model has strengths and weaknesses, no single model in its current form performs well across all criteria in all three future scenarios. NASA leadership can adjust models as desired to align closer to their priorities using combinations of unique model mechanisms. A model that meets leadership priorities is likely a combination of features from multiple models.

Erica Rodgers↗

Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem

NASA is preparing for the retirement of the ISS and transition of LEO activities to one or more Commercial LEO Destinations (CLDs) by 2030. This transition necessitates new models for connecting NASA and other government-funded users of the LEO environment to platforms and opportunities. This paper describes for consideration six models for facilitating government-funded activities in the post-ISS LEO ecosystem. These six models are illustrative and represent a wide trade space of potential options, each relying on unique mechanisms for facilitating activities on one or more commercial LEO platforms or vehicles. We assessed each model across three possible future scenarios varying in number and diversity of LEO activities and commercial offerings, and across five stakeholder-driven model evaluation criteria. We present the highlights of the analysis, including ways to modify and strengthen each model. The Government Research Broker model performs best across all future scenarios, followed by Innovation Campus, Anchor Tenant, and Fee for Service. While Matchmaker and Institute Network exhibit positive aspects, these models perform most favorably in future scenarios with well-established communities and markets. While each model has strengths and weaknesses, no single model in its current form performs well across all criteria in all three future scenarios. NASA leadership can adjust models as desired to align closer to their priorities using combinations of unique model mechanisms. A model that meets leadership priorities is likely a combination of features from multiple models.

Erica Rodgers↗

Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem

NASA is preparing for the retirement of the ISS and transition of LEO activities to one or more Commercial LEO Destinations (CLDs) by 2030. This transition necessitates new models for connecting NASA and other government-funded users of the LEO environment to platforms and opportunities. This paper describes for consideration six models for facilitating government-funded activities in the post-ISS LEO ecosystem. These six models are illustrative and represent a wide trade space of potential options, each relying on unique mechanisms for facilitating activities on one or more commercial LEO platforms or vehicles. We assessed each model across three possible future scenarios varying in number and diversity of LEO activities and commercial offerings, and across five stakeholder-driven model evaluation criteria. We present the highlights of the analysis, including ways to modify and strengthen each model. The Government Research Broker model performs best across all future scenarios, followed by Innovation Campus, Anchor Tenant, and Fee for Service. While Matchmaker and Institute Network exhibit positive aspects, these models perform most favorably in future scenarios with well-established communities and markets. While each model has strengths and weaknesses, no single model in its current form performs well across all criteria in all three future scenarios. NASA leadership can adjust models as desired to align closer to their priorities using combinations of unique model mechanisms. A model that meets leadership priorities is likely a combination of features from multiple models.

Erica Rodgers↗

Aviation 2072: Scenario Planning for Wicked Problems

The world is changing rapidly. And with it, so are the potential futures for humanity. Many of these potential futures pose hidden threats, while others offer new opportunities for aviation and the broader aerospace community. To mitigate these risks and capitalize on opportunities, organizations must work to deeply understand these potential future scenarios and uncover any underlying drivers. Organizations will be more equipped and informed when making strategic investment decisions by better understanding these threats, opportunities, and drivers . The future scenarios and their threats and opportunities described in this paper were identified through a series of extensive brainstorming workshops, collectively titled MADNESS (Mapping for Aviation Driven by Needs Emergence and Satiating Society). These workshops engaged NASA civil servants and contractors with diverse backgrounds through a facilitated process of future scenario development and critique. The participants were led through exercises focused on a time horizon spanning from 2022 to 2072 and on problems that aviation might solve and or create during this period. From the broad results, two patterns of critical uncertainty emerged: “availability” (scarcity versus abundance) and “transparency” (openness versus security and privacy). The successful iteration and ideation across the MADNESS workshops also suggests a repeatable mechanism for strategic risk exploration across a variety of NASA and industry stakeholders.

Mapping↗

Food–energy–water implications of negative emissions technologies in a +1.5 °C future

Scenarios for meeting ambitious climate targets rely on large-scale deployment of negative emissions technologies (NETs), including direct air capture (DAC). However, the tradeoffs between food, water and energy created by deploying different NETs are unclear. Here we show that DAC could provide up to 3 GtCO 2 yr -1 of negative emissions by 2035—equivalent to 7% of 2019 global CO 2 emissions—based on current-day assumptions regarding price and performance. DAC in particular could exacerbate demand for energy and water, yet it would avoid the most severe market-mediated effects of land-use competition from bioenergy with carbon capture and storage and afforestation. This could result in staple food crop prices rising by approximately fivefold relative to 2010 levels in many parts of the Global South, raising equity concerns about the deployment of NETs. Overall, these results highlight that delays in aggressive global mitigation action greatly increase the requirement for DAC to meet climate targets, and correspondingly, energy and water impacts.

54 ENVIRONMENTAL SCIENCES↗

IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulation Datasets

Publication For a thorough description of the methods, see the peer-reviewed paper: Jones, A.D., Rastogi, D., Vahmani, P. et al. Continental United States climate projections based on thermodynamic modification of historical weather. Sci Data 10, 664 (2023). https://doi.org/10.1038/s41597-023-02485-5 Overview The IM3 / HyperFACETS climate simulations provide 40-year historical (1980-2019) as well as four 80-year future simulations (2020-2099) over the U.S. The future simulations are split into near (2020-2059) and far future (2060-2099) segments. The future scenarios span a range of plausible changes in future climate (both Global Circulation Model (GCM) and Representative Concentration Pathways/Shared Socioeconomic Pathway (RCP/SSP) dimensions). The simulations provide climate variables with high spatiotemporal resolution (25 hourly variables and 207 3-hourly variables at 12 km2). The datasets are generated using dynamical downscaling with the WRF (Weather Research and Forecasting) model (version 4.2.1) and therefore preserve physical consistency across variables. WRF is a state-of-the-art, fully compressible, non-hydrostatic, mesoscale numerical weather prediction model. WRF is coupled with an urban canopy model (UCM), which resolves urban surfaces. The future scenarios were developed using a thermodynamic global warming approach where past events are replayed under a range of future warming conditions. These scenarios therefore provide a perspective on potential increases in extreme event intensity, geographic scope, and duration, with previously non-extreme conditions potentially crossing new thresholds to be considered extreme by today's standards. This approach is not intended to estimate future changes in extreme event frequency that might result from changes in large-scale atmospheric dynamics. This dataset has NOT been bias corrected. A bias corrected version of selected variables is under development and will be released here when available. Scenarios Files Data for each scenario is provided in weekly NetCDF files. 25 variables are available at hourly resolution, and 207 variables are available at three-hourly resolution. Spatial resolution is 12km and spans the conterminous United States (CONUS), including some areas of Canada and Mexico, resulting in a grid of 424 by 299 cells. The spatial projection is a Lambert Conformal Conic with the following proj-string: "+proj=lcc +lat_0=40.0000076293945 +lon_0=-97 +lat_1=30 +lat_2=45 +x_0=0 +y_0=0 +R=6370000 +units=m +no_defs". The available scenarios and simulation periods are listed below: historical | 1980 - 2019 rcp45cooler | 2020 - 2059 rcp45cooler | 2060 - 2099 rcp45hotter | 2020 - 2059 rcp45hotter | 2060 - 2099 rcp85cooler | 2020 - 2059 rcp85cooler | 2060 - 2099 rcp85hotter | 2020 - 2059 rcp85hotter | 2060 - 2099 * The first year (1979, 2019, and 2059) of data within each scenario represents a model warmup period and should not be used. These are located in the `spinup_files` directory. Historical year 2020 is considered an extra year of data beyond the simulation period and can be found in the `additional_files` directory. For information on specific variables and a more in-depth discussion of methodology, please refer to the data landing page at https://tgw-data.msdlive.org. Delta Warming Files The global and CONUS warming deltas for each scenario are provided in degrees Celsius annually and monthly. Restart Files Yearly restart files are provided for each scenario which can be used to restart the WRF model at a particular point in time. Spinup Files The first year of data within each simulation period represents a model warmup period and should not be used. The files are provided here for the sake of reproducibility. Additional Files Additional years of data are provided as an extension of the historic simulation.

Jones, Andrew D.↗