Bias-correction in the CCAFS-Climate Portal: A description of methodologies
Global Climate Models (GCMs) have been the primary source of information for constructing climate scenarios, and they provide the basis for climate change impacts assessments of climate change at all scales, from local to global. However, impact studies rarely use GCM outputs directly because errors...
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| Format: | Informe técnico |
| Language: | Inglés |
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CGIAR Research Program on Climate Change, Agriculture and Food Security
2015
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| Online Access: | https://hdl.handle.net/10568/76609 |
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| author | Navarro Racines, Carlos Eduardo Tarapues Montenegro, Jaime Eduardo |
| author_browse | Navarro Racines, Carlos Eduardo Tarapues Montenegro, Jaime Eduardo |
| author_facet | Navarro Racines, Carlos Eduardo Tarapues Montenegro, Jaime Eduardo |
| author_sort | Navarro Racines, Carlos Eduardo |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Global Climate Models (GCMs) have been the primary source of information for constructing climate scenarios, and they provide the basis for climate change impacts assessments of climate change at all scales, from local to global. However, impact studies rarely use GCM outputs directly because errors in GCM simulations relative to historical observations are large (Ramirez-Villegas et al. 2013), and because the spatial resolution is generally too coarse to satisfy the requirements for finer-scale impact studies. More specifically, the typical GCM spatial resolution (50 km or even more) is not practical for assessing agricultural landscapes, particularly in the tropics, where orographic and climatic conditions vary significantly across relatively small distances (Tabor & Williams, 2010). Hence, it is important to bias-correct and downscale the raw climate model outputs in order to produce climate projections that are better fit for agricultural modeling. Here we describe three different calibration approaches to produce reliable daily climate for future periods, employed in a new interface in CCAFS-Climate portal (www.ccafs-climate.org/data_bias_corrected/), as follows: (a) bias correction (or nudging) (Hawkins et al., 2013), (b) change factor (Hawkins et al., 2013) and (c) Quantile Mapping (Gudmundsson et al., 2012). In addition, briefly describe some observational datasets relevant to agricultural modeling and employed as the historical observations for the calibration methods mentioned here. |
| format | Informe técnico |
| id | CGSpace76609 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| publisherStr | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| record_format | dspace |
| spelling | CGSpace766092025-12-10T12:47:19Z Bias-correction in the CCAFS-Climate Portal: A description of methodologies Navarro Racines, Carlos Eduardo Tarapues Montenegro, Jaime Eduardo climate change agriculture food security biodiversity certification evaluation evidence-based conservation monitoring voluntary sustainability standards biodiversidad certificación conservación con base en evidencias evaluación monitoreo normas voluntarias de sostenibilidad Global Climate Models (GCMs) have been the primary source of information for constructing climate scenarios, and they provide the basis for climate change impacts assessments of climate change at all scales, from local to global. However, impact studies rarely use GCM outputs directly because errors in GCM simulations relative to historical observations are large (Ramirez-Villegas et al. 2013), and because the spatial resolution is generally too coarse to satisfy the requirements for finer-scale impact studies. More specifically, the typical GCM spatial resolution (50 km or even more) is not practical for assessing agricultural landscapes, particularly in the tropics, where orographic and climatic conditions vary significantly across relatively small distances (Tabor & Williams, 2010). Hence, it is important to bias-correct and downscale the raw climate model outputs in order to produce climate projections that are better fit for agricultural modeling. Here we describe three different calibration approaches to produce reliable daily climate for future periods, employed in a new interface in CCAFS-Climate portal (www.ccafs-climate.org/data_bias_corrected/), as follows: (a) bias correction (or nudging) (Hawkins et al., 2013), (b) change factor (Hawkins et al., 2013) and (c) Quantile Mapping (Gudmundsson et al., 2012). In addition, briefly describe some observational datasets relevant to agricultural modeling and employed as the historical observations for the calibration methods mentioned here. 2015-08-25 2016-08-25T11:55:43Z 2016-08-25T11:55:43Z Report https://hdl.handle.net/10568/76609 en Open Access application/pdf CGIAR Research Program on Climate Change, Agriculture and Food Security Navarro CE, Tarapues JE. 2015. Bias-correction in the CCAFS-Climate Portal: A description of methodologies. Decision and Policy Analysis (DAPA) Research Area. Cali, Colombia: International Center for Tropical Agriculture (CIAT). |
| spellingShingle | climate change agriculture food security biodiversity certification evaluation evidence-based conservation monitoring voluntary sustainability standards biodiversidad certificación conservación con base en evidencias evaluación monitoreo normas voluntarias de sostenibilidad Navarro Racines, Carlos Eduardo Tarapues Montenegro, Jaime Eduardo Bias-correction in the CCAFS-Climate Portal: A description of methodologies |
| title | Bias-correction in the CCAFS-Climate Portal: A description of methodologies |
| title_full | Bias-correction in the CCAFS-Climate Portal: A description of methodologies |
| title_fullStr | Bias-correction in the CCAFS-Climate Portal: A description of methodologies |
| title_full_unstemmed | Bias-correction in the CCAFS-Climate Portal: A description of methodologies |
| title_short | Bias-correction in the CCAFS-Climate Portal: A description of methodologies |
| title_sort | bias correction in the ccafs climate portal a description of methodologies |
| topic | climate change agriculture food security biodiversity certification evaluation evidence-based conservation monitoring voluntary sustainability standards biodiversidad certificación conservación con base en evidencias evaluación monitoreo normas voluntarias de sostenibilidad |
| url | https://hdl.handle.net/10568/76609 |
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