Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ...

We updated this global GDP projections based on Version 5 at https://zenodo.org/record/5880037#.Yyx4lsi5fRQ, which makes the following changes: a) the population projections were replaced by: Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways...

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Bibliographic Details
Main Authors: Wang, Tingting, Sun, Fubao
Format: Dataset
Language:unknown
Published: Zenodo 2022
Subjects:
GDP
SSP
Online Access:https://dx.doi.org/10.5281/zenodo.7100721
https://zenodo.org/record/7100721
id ftdatacite:10.5281/zenodo.7100721
record_format openpolar
spelling ftdatacite:10.5281/zenodo.7100721 2023-06-11T04:04:11+02:00 Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ... Wang, Tingting Sun, Fubao 2022 https://dx.doi.org/10.5281/zenodo.7100721 https://zenodo.org/record/7100721 unknown Zenodo https://dx.doi.org/10.1038/s41597-022-01300-x https://dx.doi.org/10.5281/zenodo.4350026 Closed Access info:eu-repo/semantics/closedAccess GDP SSP downscaling Dataset dataset 2022 ftdatacite https://doi.org/10.5281/zenodo.710072110.1038/s41597-022-01300-x10.5281/zenodo.4350026 2023-06-01T11:16:58Z We updated this global GDP projections based on Version 5 at https://zenodo.org/record/5880037#.Yyx4lsi5fRQ, which makes the following changes: a) the population projections were replaced by: Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways by Wang et al (2022), which implements random forest (RF) algorithm. b) provides GDP projections from 2025 to 2100 at a five-year interval for five SSPs. For more details, please refer to the article: Global gridded GDP data set consistent with the shared socioeconomic pathways that is consistent with Version 5. There are 81 tif files (2005 and 2020 - 2100 at a five-year interval for five SSPs) for each spatial resolution. The gridded GDP are distributed over land with value of zero filled in the Antarctica, oceans and some desert or wilderness areas (non-illuminated and depopulated zones). The spatial extents are 72S - 84N and 180E - 180W in standard WGS84 coordinate system. ... : {"references": ["Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850\u20132005) harmonized with future projections according to the Shared Socio-economic Pathways (2006\u20132100), Earth System Science Data, 10, 847\u2013856, 2018.", "Dellink, R., Chateau, J., Lanzi, E., and Magn\u00e9, B.: Long-term economic growth projections in the Shared Socioeconomic Pathways, Global Environmental Change, 42. 200-214, 2015.", "Wang, X., Meng, X., Long, Y. (2022) Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways. Scientific data 9, 1-13."]} ... Dataset Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) Chateau ENVELOPE(-55.898,-55.898,51.983,51.983) Geiger ENVELOPE(-62.900,-62.900,-64.300,-64.300)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic GDP
SSP
downscaling
spellingShingle GDP
SSP
downscaling
Wang, Tingting
Sun, Fubao
Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ...
topic_facet GDP
SSP
downscaling
description We updated this global GDP projections based on Version 5 at https://zenodo.org/record/5880037#.Yyx4lsi5fRQ, which makes the following changes: a) the population projections were replaced by: Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways by Wang et al (2022), which implements random forest (RF) algorithm. b) provides GDP projections from 2025 to 2100 at a five-year interval for five SSPs. For more details, please refer to the article: Global gridded GDP data set consistent with the shared socioeconomic pathways that is consistent with Version 5. There are 81 tif files (2005 and 2020 - 2100 at a five-year interval for five SSPs) for each spatial resolution. The gridded GDP are distributed over land with value of zero filled in the Antarctica, oceans and some desert or wilderness areas (non-illuminated and depopulated zones). The spatial extents are 72S - 84N and 180E - 180W in standard WGS84 coordinate system. ... : {"references": ["Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850\u20132005) harmonized with future projections according to the Shared Socio-economic Pathways (2006\u20132100), Earth System Science Data, 10, 847\u2013856, 2018.", "Dellink, R., Chateau, J., Lanzi, E., and Magn\u00e9, B.: Long-term economic growth projections in the Shared Socioeconomic Pathways, Global Environmental Change, 42. 200-214, 2015.", "Wang, X., Meng, X., Long, Y. (2022) Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways. Scientific data 9, 1-13."]} ...
format Dataset
author Wang, Tingting
Sun, Fubao
author_facet Wang, Tingting
Sun, Fubao
author_sort Wang, Tingting
title Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ...
title_short Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ...
title_full Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ...
title_fullStr Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ...
title_full_unstemmed Gross domestic product (GDP) downscaling: a global gridded dataset consistent with the Shared Socioeconomic Pathways ...
title_sort gross domestic product (gdp) downscaling: a global gridded dataset consistent with the shared socioeconomic pathways ...
publisher Zenodo
publishDate 2022
url https://dx.doi.org/10.5281/zenodo.7100721
https://zenodo.org/record/7100721
long_lat ENVELOPE(-55.898,-55.898,51.983,51.983)
ENVELOPE(-62.900,-62.900,-64.300,-64.300)
geographic Chateau
Geiger
geographic_facet Chateau
Geiger
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_relation https://dx.doi.org/10.1038/s41597-022-01300-x
https://dx.doi.org/10.5281/zenodo.4350026
op_rights Closed Access
info:eu-repo/semantics/closedAccess
op_doi https://doi.org/10.5281/zenodo.710072110.1038/s41597-022-01300-x10.5281/zenodo.4350026
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