The methodological framework for DRIP: Drought representation index for CMIP model performance
This paper presents a methodological framework designed to evaluate the ability of CMIP climate models to simulate drought characteristics. The approach is based on the Drought Representation Index for CMIP Model Performance (DRIP), which assesses models using three key drought parameters—average du...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | MethodsX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016125000950 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1839650399572721664 |
|---|---|
| author | Lucas Pereira de Almeida Ályson Brayner Sousa Estácio Rosa Maria Formiga-Johnsson Francisco de Assis de Souza Filho Victor Costa Porto Alexandra Nauditt Lars Ribbe Alfredo Akira Ohnuma Júnior |
| author_facet | Lucas Pereira de Almeida Ályson Brayner Sousa Estácio Rosa Maria Formiga-Johnsson Francisco de Assis de Souza Filho Victor Costa Porto Alexandra Nauditt Lars Ribbe Alfredo Akira Ohnuma Júnior |
| author_sort | Lucas Pereira de Almeida |
| collection | DOAJ |
| description | This paper presents a methodological framework designed to evaluate the ability of CMIP climate models to simulate drought characteristics. The approach is based on the Drought Representation Index for CMIP Model Performance (DRIP), which assesses models using three key drought parameters—average duration, severity, and return period—by comparing simulated outputs with historical observations. The methodology encompasses four main stages: data acquisition and preparation, drought characterization, DRIP calculation, and model ensemble generation (E-DRIP). This approach provides a systematic method to identify models that best represent regional drought dynamics and reduce uncertainty in climate projections. By leveraging DRIP as a selection criterion, E-DRIP ensembles outperform traditional CMIP ensembles in both reliability and precision. The method's flexibility allows adaptation to various drought indices and temporal scales, making it applicable across diverse climatic contexts. Validation in a climatically uncertain area, the Paraíba do Sul River Basin in Southeast Brazil, demonstrates DRIP's effectiveness in enhancing model performance assessment and improving drought scenario projections. This study contributes a replicable tool for climate modelling, supporting water resources management strategies amid increasing climate variability. • DRIP index assesses CMIP models' performance in representing drought characteristics. • E-DRIP ensembles reduced drought projections uncertainties by up to 63 % in the validation study area. • DRIP enhances decision-making in climate model selection, improving its reliability for regional water planning. |
| format | Article |
| id | doaj-art-c76b2c0c7ddb4247830e2d50fbfe0d98 |
| institution | Matheson Library |
| issn | 2215-0161 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | MethodsX |
| spelling | doaj-art-c76b2c0c7ddb4247830e2d50fbfe0d982025-06-27T05:51:08ZengElsevierMethodsX2215-01612025-06-0114103249The methodological framework for DRIP: Drought representation index for CMIP model performanceLucas Pereira de Almeida0Ályson Brayner Sousa Estácio1Rosa Maria Formiga-Johnsson2Francisco de Assis de Souza Filho3Victor Costa Porto4Alexandra Nauditt5Lars Ribbe6Alfredo Akira Ohnuma Júnior7Postgraduate Program in Environmental Engineering (DEAMB), State University of Rio de Janeiro, Rio de Janeiro, BrazilResearch Institute for Meteorology and Water Resources (FUNCEME), Fortaleza, Ceará, BrazilCorresponding author at: Associate Professor, State University of Rio de Janeiro (UERJ), Brazil.; Department of Environmental and Sanitary Engineering, State University of Rio de Janeiro, Rio de Janeiro, BrazilDepartment of Environmental and Hydraulic Engineering, Federal University of Ceará, Fortaleza, BrazilDepartment of Environmental and Hydraulic Engineering, Federal University of Ceará, Fortaleza, BrazilInstitute for Technology and Resources Management in the Tropics and Subtropics, Cologne University of Applied Sciences, Cologne, GermanyInstitute for Technology and Resources Management in the Tropics and Subtropics, Cologne University of Applied Sciences, Cologne, GermanyDepartment of Environmental and Sanitary Engineering, State University of Rio de Janeiro, Rio de Janeiro, BrazilThis paper presents a methodological framework designed to evaluate the ability of CMIP climate models to simulate drought characteristics. The approach is based on the Drought Representation Index for CMIP Model Performance (DRIP), which assesses models using three key drought parameters—average duration, severity, and return period—by comparing simulated outputs with historical observations. The methodology encompasses four main stages: data acquisition and preparation, drought characterization, DRIP calculation, and model ensemble generation (E-DRIP). This approach provides a systematic method to identify models that best represent regional drought dynamics and reduce uncertainty in climate projections. By leveraging DRIP as a selection criterion, E-DRIP ensembles outperform traditional CMIP ensembles in both reliability and precision. The method's flexibility allows adaptation to various drought indices and temporal scales, making it applicable across diverse climatic contexts. Validation in a climatically uncertain area, the Paraíba do Sul River Basin in Southeast Brazil, demonstrates DRIP's effectiveness in enhancing model performance assessment and improving drought scenario projections. This study contributes a replicable tool for climate modelling, supporting water resources management strategies amid increasing climate variability. • DRIP index assesses CMIP models' performance in representing drought characteristics. • E-DRIP ensembles reduced drought projections uncertainties by up to 63 % in the validation study area. • DRIP enhances decision-making in climate model selection, improving its reliability for regional water planning.http://www.sciencedirect.com/science/article/pii/S2215016125000950Drought Representation Index for CMIP Climate Model Performance (DRIP) |
| spellingShingle | Lucas Pereira de Almeida Ályson Brayner Sousa Estácio Rosa Maria Formiga-Johnsson Francisco de Assis de Souza Filho Victor Costa Porto Alexandra Nauditt Lars Ribbe Alfredo Akira Ohnuma Júnior The methodological framework for DRIP: Drought representation index for CMIP model performance MethodsX Drought Representation Index for CMIP Climate Model Performance (DRIP) |
| title | The methodological framework for DRIP: Drought representation index for CMIP model performance |
| title_full | The methodological framework for DRIP: Drought representation index for CMIP model performance |
| title_fullStr | The methodological framework for DRIP: Drought representation index for CMIP model performance |
| title_full_unstemmed | The methodological framework for DRIP: Drought representation index for CMIP model performance |
| title_short | The methodological framework for DRIP: Drought representation index for CMIP model performance |
| title_sort | methodological framework for drip drought representation index for cmip model performance |
| topic | Drought Representation Index for CMIP Climate Model Performance (DRIP) |
| url | http://www.sciencedirect.com/science/article/pii/S2215016125000950 |
| work_keys_str_mv | AT lucaspereiradealmeida themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT alysonbraynersousaestacio themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT rosamariaformigajohnsson themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT franciscodeassisdesouzafilho themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT victorcostaporto themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT alexandranauditt themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT larsribbe themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT alfredoakiraohnumajunior themethodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT lucaspereiradealmeida methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT alysonbraynersousaestacio methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT rosamariaformigajohnsson methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT franciscodeassisdesouzafilho methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT victorcostaporto methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT alexandranauditt methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT larsribbe methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance AT alfredoakiraohnumajunior methodologicalframeworkfordripdroughtrepresentationindexforcmipmodelperformance |