Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments
Quantifying climate change impact on water resources systems at regional or catchment scales is important in water resources planning and management. General circulation models (GCMs) represent our main source of knowledge about future climate change. However, several key limitations restrict the di...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2023-07-01
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| Series: | Journal of Water and Climate Change |
| Subjects: | |
| Online Access: | http://jwcc.iwaponline.com/content/14/7/2085 |
| _version_ | 1797202765765672960 |
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| author | Ashish Sharma Rajeshwar Mehrotra Cilcia Kusumastuti |
| author_facet | Ashish Sharma Rajeshwar Mehrotra Cilcia Kusumastuti |
| author_sort | Ashish Sharma |
| collection | DOAJ |
| description | Quantifying climate change impact on water resources systems at regional or catchment scales is important in water resources planning and management. General circulation models (GCMs) represent our main source of knowledge about future climate change. However, several key limitations restrict the direct use of GCM simulations for water resource assessments. In particular, the presence of systematic bias and the need for its correction is an essential pre-processing step that improves the quality of GCM simulations, making climate change impact assessments more robust and believable. What exactly is systematic bias? Can systematic bias be quantified if the model is asynchronous with observations or other model simulations? Should model bias be sub-categorized to focus on individual attributes of interest or aggregated to focus on lower moments alone? How would one address bias in multiple attributes without making the correction model complex? How could one be confident that corrected simulations for the yet-to-be-seen future bear a closer resemblance to the truth? How can one meaningfully extrapolate correction to multiple dimensions, without being impacted by the ‘Curse of Dimensionality’? These are some of the questions we attempt to address in the paper.
HIGHLIGHTS
Importance of procedures for correcting systematic biases is discussed.;
Extensive literature is presented on bias correction and its use.;
The importance of correcting specific attributes for water resources applications is illustrated.;
Challenges in formulating a bias correction alternative are highlighted.;
Added information on how correcting these biases is critical before any dynamical or statistical downscaling application.; |
| first_indexed | 2024-03-12T15:25:00Z |
| format | Article |
| id | doaj.art-ba8b0efd51414971be2b7d76d2f95be4 |
| institution | Directory Open Access Journal |
| issn | 2040-2244 2408-9354 |
| language | English |
| last_indexed | 2024-04-24T08:08:39Z |
| publishDate | 2023-07-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Journal of Water and Climate Change |
| spelling | doaj.art-ba8b0efd51414971be2b7d76d2f95be42024-04-17T08:30:13ZengIWA PublishingJournal of Water and Climate Change2040-22442408-93542023-07-011472085210210.2166/wcc.2023.230230Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessmentsAshish Sharma0Rajeshwar Mehrotra1Cilcia Kusumastuti2 Water Research Centre, School of Civil and Environmental Engineering, The University of New South Wales, Sydney, NSW 2052, Australia Water Research Centre, School of Civil and Environmental Engineering, The University of New South Wales, Sydney, NSW 2052, Australia Water Research Centre, School of Civil and Environmental Engineering, The University of New South Wales, Sydney, NSW 2052, Australia Quantifying climate change impact on water resources systems at regional or catchment scales is important in water resources planning and management. General circulation models (GCMs) represent our main source of knowledge about future climate change. However, several key limitations restrict the direct use of GCM simulations for water resource assessments. In particular, the presence of systematic bias and the need for its correction is an essential pre-processing step that improves the quality of GCM simulations, making climate change impact assessments more robust and believable. What exactly is systematic bias? Can systematic bias be quantified if the model is asynchronous with observations or other model simulations? Should model bias be sub-categorized to focus on individual attributes of interest or aggregated to focus on lower moments alone? How would one address bias in multiple attributes without making the correction model complex? How could one be confident that corrected simulations for the yet-to-be-seen future bear a closer resemblance to the truth? How can one meaningfully extrapolate correction to multiple dimensions, without being impacted by the ‘Curse of Dimensionality’? These are some of the questions we attempt to address in the paper. HIGHLIGHTS Importance of procedures for correcting systematic biases is discussed.; Extensive literature is presented on bias correction and its use.; The importance of correcting specific attributes for water resources applications is illustrated.; Challenges in formulating a bias correction alternative are highlighted.; Added information on how correcting these biases is critical before any dynamical or statistical downscaling application.;http://jwcc.iwaponline.com/content/14/7/2085climate changefuture climategeneral circulation modelssystematic biaswater resources systems |
| spellingShingle | Ashish Sharma Rajeshwar Mehrotra Cilcia Kusumastuti Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments Journal of Water and Climate Change climate change future climate general circulation models systematic bias water resources systems |
| title | Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments |
| title_full | Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments |
| title_fullStr | Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments |
| title_full_unstemmed | Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments |
| title_short | Correcting systematic bias in derived hydrologic simulations – Implications for climate change assessments |
| title_sort | correcting systematic bias in derived hydrologic simulations implications for climate change assessments |
| topic | climate change future climate general circulation models systematic bias water resources systems |
| url | http://jwcc.iwaponline.com/content/14/7/2085 |
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