Simulation of global sea surface temperature maps using Pix2Pix GAN
Simulated data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) has been very important for climate science research, as they can provide wide spatio-temporal coverage to address data deficiencies in both present and future scenarios. However, these physics-based models require a huge...
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Cambridge University Press
2025-01-01
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| Series: | Environmental Data Science |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S2634460224000384/type/journal_article |
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| author | Deepayan Chakraborty Adway Mitra |
| author_facet | Deepayan Chakraborty Adway Mitra |
| author_sort | Deepayan Chakraborty |
| collection | DOAJ |
| description | Simulated data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) has been very important for climate science research, as they can provide wide spatio-temporal coverage to address data deficiencies in both present and future scenarios. However, these physics-based models require a huge amount of high-performance computing (HPC) resources. As an alternative approach, researchers are exploring if such simulated data can be generated by Generative Machine Learning models. In this work, we develop a model based on Pix2Pix conditional Generative Adversarial Network (cGAN), which can generate high-resolution spatial maps of global sea surface temperature (SST) using comparatively less computing power and time. We have shown that the maps generated by these models have similar statistical characteristics as the CMIP6 model simulations. Notably, we trained and validated our cGAN model on completely distinct time periods across all ensemble members of the EC-Earth3-CC and CMCC-CM2-SR5 CMIP6 models, demonstrating satisfactory results and confirming the generalizability of our proposed model. |
| format | Article |
| id | doaj-art-13fa8f40f0524affa63f321d8aaabb72 |
| institution | Kabale University |
| issn | 2634-4602 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Environmental Data Science |
| spelling | doaj-art-13fa8f40f0524affa63f321d8aaabb722025-02-12T07:42:22ZengCambridge University PressEnvironmental Data Science2634-46022025-01-01410.1017/eds.2024.38Simulation of global sea surface temperature maps using Pix2Pix GANDeepayan Chakraborty0https://orcid.org/0000-0002-8163-0244Adway Mitra1Department of Artificial Intelligence, Indian Institute of Technology, Kharagpur, IndiaDepartment of Artificial Intelligence, Indian Institute of Technology, Kharagpur, IndiaSimulated data from the Coupled Model Intercomparison Project Phase 6 (CMIP6) has been very important for climate science research, as they can provide wide spatio-temporal coverage to address data deficiencies in both present and future scenarios. However, these physics-based models require a huge amount of high-performance computing (HPC) resources. As an alternative approach, researchers are exploring if such simulated data can be generated by Generative Machine Learning models. In this work, we develop a model based on Pix2Pix conditional Generative Adversarial Network (cGAN), which can generate high-resolution spatial maps of global sea surface temperature (SST) using comparatively less computing power and time. We have shown that the maps generated by these models have similar statistical characteristics as the CMIP6 model simulations. Notably, we trained and validated our cGAN model on completely distinct time periods across all ensemble members of the EC-Earth3-CC and CMCC-CM2-SR5 CMIP6 models, demonstrating satisfactory results and confirming the generalizability of our proposed model.https://www.cambridge.org/core/product/identifier/S2634460224000384/type/journal_articleCMIP6generative adversarial networkglobal climate modelsea surface temperature |
| spellingShingle | Deepayan Chakraborty Adway Mitra Simulation of global sea surface temperature maps using Pix2Pix GAN Environmental Data Science CMIP6 generative adversarial network global climate model sea surface temperature |
| title | Simulation of global sea surface temperature maps using Pix2Pix GAN |
| title_full | Simulation of global sea surface temperature maps using Pix2Pix GAN |
| title_fullStr | Simulation of global sea surface temperature maps using Pix2Pix GAN |
| title_full_unstemmed | Simulation of global sea surface temperature maps using Pix2Pix GAN |
| title_short | Simulation of global sea surface temperature maps using Pix2Pix GAN |
| title_sort | simulation of global sea surface temperature maps using pix2pix gan |
| topic | CMIP6 generative adversarial network global climate model sea surface temperature |
| url | https://www.cambridge.org/core/product/identifier/S2634460224000384/type/journal_article |
| work_keys_str_mv | AT deepayanchakraborty simulationofglobalseasurfacetemperaturemapsusingpix2pixgan AT adwaymitra simulationofglobalseasurfacetemperaturemapsusingpix2pixgan |