U.S. State-level Projections of the Spatial Distribution of Population Consistent with Shared Socioeconomic Pathways

Zoraghein, Hamidreza; O’Neill, Brian C.

doi:10.3390/su12083374

Cited by 27 publications

(16 citation statements)

References 34 publications

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“…We also note that population and average income of each state increase over time following central estimates in existing literature [37, 55,56]. These trajectories are equal for the three analyzed scenarios.…”

Section: Egalitariansupporting

confidence: 66%

Implications of different income distributions for future residential energy demand in the U.S.

Sampedro

Msangi

Waldhoff

et al. 2022

Environ. Res. Lett.

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Future income distribution will affect energy demand and its interactions with various societal priorities. Most future model simulations assume a single average consumer and thus miss this important demand determinant. We quantify long-term implications of alternative future income distributions for state-level residential energy demand, investment, greenhouse gas (GHG), and pollutant emission patterns in the United States (U.S.) by incorporating income quintiles into the residential energy sector of the Global Change Analysis Model with 50-state disaggregation (GCAM-USA). We find that if the income distribution within each U.S. state becomes more egalitarian than present, what means that the difference on income between the richest and poorest decreases over time, residential energy demand could be 10% (4-14% across states) higher in 2100. This increase of residential energy demand will directly reduce energy poverty, with a very modest increment on economywide CO2 emissions (1-2%). On the other hand, if U.S. states transition to a less equitable income distribution than present, with the difference between richest and poorest increasing over time, residential energy demand could be 19% (12-26% across states) lower. While this study focuses on a single sector, we conclude that to improve understanding of synergies and tradeoffs across multiple societal goals such as energy access, emissions, and investments, future model simulations should explicitly consider subregional income distribution impacts.

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Section: Egalitariansupporting

confidence: 66%

Implications of different income distributions for future residential energy demand in the U.S.

Sampedro

Msangi

Waldhoff

et al. 2022

Environ. Res. Lett.

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“…Zoraghein and O’Neill ( 2020a , 2020b ) also created small area population forecasts for the USA, though for 1 km 2 grid squares and for population totals only. Existing State population forecasts were downscaled to grid squares using a gravity-type model, specified separately for urban and rural areas.…”

Section: Small Area Population Forecasting Methods 2001–2020mentioning

confidence: 99%

Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs

Wilson

Grossman

Alexander

et al. 2021

Popul Res Policy Rev

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Small area population forecasts are widely used by government and business for a variety of planning, research and policy purposes, and often influence major investment decisions. Yet, the toolbox of small area population forecasting methods and techniques is modest relative to that for national and large subnational regional forecasting. In this paper, we assess the current state of small area population forecasting, and suggest areas for further research. The paper provides a review of the literature on small area population forecasting methods published over the period 2001–2020. The key themes covered by the review are extrapolative and comparative methods, simplified cohort-component methods, model averaging and combining, incorporating socioeconomic variables and spatial relationships, ‘downscaling’ and disaggregation approaches, linking population with housing, estimating and projecting small area component input data, microsimulation, machine learning, and forecast uncertainty. Several avenues for further research are then suggested, including more work on model averaging and combining, developing new forecasting methods for situations which current models cannot handle, quantifying uncertainty, exploring methodologies such as machine learning and spatial statistics, creating user-friendly tools for practitioners, and understanding more about how forecasts are used. Supplementary Information The online version contains supplementary material available at 10.1007/s11113-021-09671-6.

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“…Compound events, windstorms which exhibit a cooccurrence of extreme precipitation and/or freezing rain with high winds, are associated with amplified risk (Zscheischler et al, 2018;Sadegh et al, 2018). Precipitation intensity and hydrometeor class from ERA5 are used to identify to what degree each of the 10 windstorms identified here are compound events.…”

Section: Era5 Reanalysismentioning

confidence: 99%

Intense windstorms in the northeastern United States

Letson

Barthelmie

Hodges

et al. 2021

Nat. Hazards Earth Syst. Sci.

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Abstract. Windstorms are a major natural hazard in many countries. The objective of this study is to identify and characterize intense windstorms during the last 4 decades in the US Northeast and determine both the sources of cyclones responsible for these events and the manner in which those cyclones differ from the cyclone climatology. The windstorm detection is based on the spatial extent of locally extreme wind speeds at 100 m height from the ERA5 reanalysis database. During the top 10 windstorms, wind speeds exceed their local 99.9th percentile over at least one-third of land-based ERA5 grid cells in this high-population-density region of the USA. Maximum sustained wind speeds at 100 m during these windstorms range from 26 to over 43 ms−1, with wind speed return periods exceeding 6.5 to 106 years (considering the top 5 % of grid cells during each storm). Property damage associated with these storms, with inflation adjusted to January 2020, ranges from USD 24 million to over USD 29 billion. Two of these windstorms are linked to decaying tropical cyclones, three are Alberta clippers, and the remaining storms are Colorado lows. Two of the 10 re-intensified off the east coast, leading to development of nor'easters. These windstorms followed frequently observed cyclone tracks but exhibit maximum intensities as measured using 700 hPa relative vorticity and mean sea level pressure that is 5–10 times the mean values for cyclones that followed similar tracks over this 40-year period. The time evolution of wind speeds and concurrent precipitation for those windstorms that occurred after the year 2000 exhibit good agreement with in situ ground-based and remote sensing observations, plus storm damage reports, indicating that the ERA5 reanalysis data have a high degree of fidelity for large, damaging windstorms such as these. A larger pool of the top 50 largest windstorms exhibit evidence of only weak serial clustering, which is in contrast to the relatively strong serial clustering of windstorms in Europe.

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U.S. State-level Projections of the Spatial Distribution of Population Consistent with Shared Socioeconomic Pathways

Cited by 27 publications

References 34 publications

Implications of different income distributions for future residential energy demand in the U.S.

Implications of different income distributions for future residential energy demand in the U.S.

Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs

Intense windstorms in the northeastern United States

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