Population projections for US states under the Shared Socioeconomic Pathways based on global gridded population projections
Population projections across scales are essential for integrated assessment of global environmental changes. Currently, projections at the aggregate national scale, and at the grid-cell scale, are available globally and for many individual countries. However few projections exist at intermediate scales, such as US states, which are important for capturing broad-scale redistribution of population through internal migration. We are currently developing explicit US state-level projections, from which we will create consistent gridded outcomes. Here we present a placeholder set of projections that could be used in analyses while waiting on explicit state projections. These placeholder projections are based on an existing set of global gridded projections, which we aggregate (upscale) to the state level to produce a set of projections numerically consistent at the grid cell, state and national level. We test alternative aggregation methods and geographic resolutions of the gridded population to derive the aggregate state-level projections for all 50 states (and Puerto Rico), for rural and urban areas. Results show that with high resolution gridded population data for the present population, the upscaling outcomes match reasonably well total population at the national and state levels. Comparison of the state-level projections aggregated from the grid cell level to explicit state projections from the US Census Bureau through 2030 show that results are reasonable for many states, but are much less reliable for states experiencing population dynamics differing from national overall patterns. Results therefore also demonstrate the need for a new set of alternative, state-level population projections with consistent gridded outcomes.
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http://n2t.net/ark:/85065/d7cv4mc2
eng
geoscientificInformation
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2016-01-01T00:00:00Z
EARTH SCIENCE > HUMAN DIMENSIONS > SOCIOECONOMICS
EARTH SCIENCE > HUMAN DIMENSIONS > POPULATION
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2021-09-17
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2018-01-09T00:00:00Z
Copyright Author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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