Uncertainty maps for model-based global climate classification systems
Abstract Climate classification systems (CCSs) are emerging as essential tools in climate change science for mitigation and adaptation. However, their limitations are often misunderstood by non-specialists. This situation is especially acute when the CCSs are derived from Global Climate Model output...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04387-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841544980317863936 |
|---|---|
| author | Andrés Navarro Andrés Merino Eduardo García-Ortega Francisco J. Tapiador |
| author_facet | Andrés Navarro Andrés Merino Eduardo García-Ortega Francisco J. Tapiador |
| author_sort | Andrés Navarro |
| collection | DOAJ |
| description | Abstract Climate classification systems (CCSs) are emerging as essential tools in climate change science for mitigation and adaptation. However, their limitations are often misunderstood by non-specialists. This situation is especially acute when the CCSs are derived from Global Climate Model outputs (GCMs). We present a set of uncertainty maps of four widely used schemes -Whittaker-Ricklefs, Holdridge, Thornthwaite-Feddema and Köppen- for present (1980–2014) and future (2015–2100) climate based on 52 models from the Coupled Intercomparison Model Project Phase six (CMIP6). Together with the classification maps, the uncertainty maps provide essential guidance on where the models perform within limits, and where sources of error lie. We share a digital resource that can be readily and freely integrated into mitigation and adaptation studies and which is helpful for scientists and practitioners using climate classifications, minimizing the risk of pitfalls or unsubstantiated conclusions. |
| format | Article |
| id | doaj-art-7548bfb9e8f04127a07e520227ff4afe |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-7548bfb9e8f04127a07e520227ff4afe2025-01-12T12:07:42ZengNature PortfolioScientific Data2052-44632025-01-0112111010.1038/s41597-025-04387-0Uncertainty maps for model-based global climate classification systemsAndrés Navarro0Andrés Merino1Eduardo García-Ortega2Francisco J. Tapiador3Earth and Space Sciences (ESS) Group, Institute of Environmental Sciences, University of Castilla-La Mancha (UCLM)Atmospheric Physics Group (GFA), Environmental Institute, Universidad de León (ULE)Atmospheric Physics Group (GFA), Environmental Institute, Universidad de León (ULE)Earth and Space Sciences (ESS) Group, Institute of Environmental Sciences, University of Castilla-La Mancha (UCLM)Abstract Climate classification systems (CCSs) are emerging as essential tools in climate change science for mitigation and adaptation. However, their limitations are often misunderstood by non-specialists. This situation is especially acute when the CCSs are derived from Global Climate Model outputs (GCMs). We present a set of uncertainty maps of four widely used schemes -Whittaker-Ricklefs, Holdridge, Thornthwaite-Feddema and Köppen- for present (1980–2014) and future (2015–2100) climate based on 52 models from the Coupled Intercomparison Model Project Phase six (CMIP6). Together with the classification maps, the uncertainty maps provide essential guidance on where the models perform within limits, and where sources of error lie. We share a digital resource that can be readily and freely integrated into mitigation and adaptation studies and which is helpful for scientists and practitioners using climate classifications, minimizing the risk of pitfalls or unsubstantiated conclusions.https://doi.org/10.1038/s41597-025-04387-0 |
| spellingShingle | Andrés Navarro Andrés Merino Eduardo García-Ortega Francisco J. Tapiador Uncertainty maps for model-based global climate classification systems Scientific Data |
| title | Uncertainty maps for model-based global climate classification systems |
| title_full | Uncertainty maps for model-based global climate classification systems |
| title_fullStr | Uncertainty maps for model-based global climate classification systems |
| title_full_unstemmed | Uncertainty maps for model-based global climate classification systems |
| title_short | Uncertainty maps for model-based global climate classification systems |
| title_sort | uncertainty maps for model based global climate classification systems |
| url | https://doi.org/10.1038/s41597-025-04387-0 |
| work_keys_str_mv | AT andresnavarro uncertaintymapsformodelbasedglobalclimateclassificationsystems AT andresmerino uncertaintymapsformodelbasedglobalclimateclassificationsystems AT eduardogarciaortega uncertaintymapsformodelbasedglobalclimateclassificationsystems AT franciscojtapiador uncertaintymapsformodelbasedglobalclimateclassificationsystems |