A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses
A large number of historical simulations and future climate projections are available from Global Climate Models, but these are typically of coarse resolution, which limits their effectiveness for assessing local scale changes in climate and attendant impacts. Here, we use a novel statistical downsc...
| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer Nature
2023
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| _version_ | 1797111258527301632 |
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| author | Gebrechorkos, S Leyland, J Slater, L Wortmann, M Ashworth, PJ Bennett, GL Boothroyd, R Cloke, H Delorme, P Griffith, H Hardy, R Hawker, L McLelland, S Neal, J Nicholas, A Tatem, AJ Vahidi, E Parsons, DR Darby, SE |
| author_facet | Gebrechorkos, S Leyland, J Slater, L Wortmann, M Ashworth, PJ Bennett, GL Boothroyd, R Cloke, H Delorme, P Griffith, H Hardy, R Hawker, L McLelland, S Neal, J Nicholas, A Tatem, AJ Vahidi, E Parsons, DR Darby, SE |
| author_sort | Gebrechorkos, S |
| collection | OXFORD |
| description | A large number of historical simulations and future climate projections are available from Global Climate Models, but these are typically of coarse resolution, which limits their effectiveness for assessing local scale changes in climate and attendant impacts. Here, we use a novel statistical downscaling model capable of replicating extreme events, the Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ), to downscale daily precipitation, air-temperature, maximum and minimum temperature, wind speed, air pressure, and relative humidity from 18 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). BCCAQ is calibrated using high-resolution reference datasets and showed a good performance in removing bias from GCMs and reproducing extreme events. The globally downscaled data are available at the Centre for Environmental Data Analysis ( https://doi.org/10.5285/c107618f1db34801bb88a1e927b82317 ) for the historical (1981-2014) and future (2015-2100) periods at 0.25° resolution and at daily time step across three Shared Socioeconomic Pathways (SSP2-4.5, SSP5-3.4-OS and SSP5-8.5). This new climate dataset will be useful for assessing future changes and variability in climate and for driving high-resolution impact assessment models. |
| first_indexed | 2024-03-07T08:06:12Z |
| format | Journal article |
| id | oxford-uuid:2e5615f4-a79f-413a-8494-770dc8552ee3 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T08:06:12Z |
| publishDate | 2023 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:2e5615f4-a79f-413a-8494-770dc8552ee32023-11-06T06:09:35ZA high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analysesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:2e5615f4-a79f-413a-8494-770dc8552ee3EnglishSymplectic ElementsSpringer Nature2023Gebrechorkos, SLeyland, JSlater, LWortmann, MAshworth, PJBennett, GLBoothroyd, RCloke, HDelorme, PGriffith, HHardy, RHawker, LMcLelland, SNeal, JNicholas, ATatem, AJVahidi, EParsons, DRDarby, SEA large number of historical simulations and future climate projections are available from Global Climate Models, but these are typically of coarse resolution, which limits their effectiveness for assessing local scale changes in climate and attendant impacts. Here, we use a novel statistical downscaling model capable of replicating extreme events, the Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ), to downscale daily precipitation, air-temperature, maximum and minimum temperature, wind speed, air pressure, and relative humidity from 18 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). BCCAQ is calibrated using high-resolution reference datasets and showed a good performance in removing bias from GCMs and reproducing extreme events. The globally downscaled data are available at the Centre for Environmental Data Analysis ( https://doi.org/10.5285/c107618f1db34801bb88a1e927b82317 ) for the historical (1981-2014) and future (2015-2100) periods at 0.25° resolution and at daily time step across three Shared Socioeconomic Pathways (SSP2-4.5, SSP5-3.4-OS and SSP5-8.5). This new climate dataset will be useful for assessing future changes and variability in climate and for driving high-resolution impact assessment models. |
| spellingShingle | Gebrechorkos, S Leyland, J Slater, L Wortmann, M Ashworth, PJ Bennett, GL Boothroyd, R Cloke, H Delorme, P Griffith, H Hardy, R Hawker, L McLelland, S Neal, J Nicholas, A Tatem, AJ Vahidi, E Parsons, DR Darby, SE A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses |
| title | A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses |
| title_full | A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses |
| title_fullStr | A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses |
| title_full_unstemmed | A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses |
| title_short | A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses |
| title_sort | high resolution daily global dataset of statistically downscaled cmip6 models for climate impact analyses |
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