Quantifying Contributions of External Forcing and Internal Variability to Arctic Warming During 1900–2021

Earth s Future, Journal Year: 2024, Volume and Issue: 12(5)

Published: May 1, 2024

Abstract Arctic warming has significant environmental and social impacts. long‐term trend is modulated by decadal‐to‐multidecadal variations. Improved understanding of how different external forcings internal variability affect surface air temperature (SAT) crucial for explaining predicting climate changes. We analyze multiple observational data sets large ensembles model simulations to quantify the contributions specific various modes SAT changes during 1900–2021. find that total variance in Arctic‐mean since 1900 are largely forced responses, including due greenhouse gases natural cooling anthropogenic aerosols. In contrast, dominates early 20th century mid‐20th cooling. Internal also explains ∼40% recent from 1979 2021. Unforced attributed two leading modes. The first pan‐Arctic with stronger loading over Eurasian sector, accounting 70% unforced closely related positive phase Atlantic Multidecadal Oscillation (AMO). second mode exhibits relatively weak averaged entire North American‐Pacific sector 10% likely caused Interdecadal Pacific (IPO). AMO‐related dominate 1979, while IPO‐related contribute decadal Arctic.

Language: Английский

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Using regional warming levels to describe future climate change for services and adaptation: Application to the French reference trajectory for adaptation

Climate Services, Journal Year: 2025, Volume and Issue: 38, P. 100553 - 100553

Published: March 14, 2025

Language: Английский

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A transformer-based method for correcting daily SST numerical forecasting products

Frontiers in Earth Science, Journal Year: 2025, Volume and Issue: 13

Published: March 28, 2025

This study introduces applies a Transformer-based method to correct daily Sea Surface Temperature (SST) numerical forecasting products, addressing persistent challenges in short-term SST prediction. The proposed approach utilizes Transformer model architecture capture complex spatiotemporal dependencies error fields, enabling efficient prediction of forecast errors across multiple time scales. was applied hindcast data from the First Institute Oceanography (FIO-COM) ocean system, focusing on northwestern Pacific region. Results demonstrate significant improvements accuracy, with Root Mean Square Error (RMSE) reductions ranging 38.8% for day 2 forecasts 17.6% 5 forecasts. Spatial analysis reveals method’s robust performance diverse oceanographic regimes, including coastal and shelf regions where traditional models often struggle. showed ability reproduce patterns, effectively both large-scale systematic biases smaller-scale regional variations. consistent different horizons suggests potential extending reliable range predictions. findings have important implications applications requiring precise forecasts, operational oceanography, marine weather forecasting, coupled ocean-atmosphere modeling.

Language: Английский

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How does the CMIP6 ensemble change the picture for European climate projections?

Environmental Research Letters, Journal Year: 2021, Volume and Issue: 16(9), P. 094042 - 094042

Published: Aug. 18, 2021

Abstract We compare Coupled Model Intercomparison Project (CMIP) ensemble (CMIP6) projections for seasonal mean temperature and precipitation to CMIP5 northern Europe, central Europe the Mediterranean. The CMIP6 shows increased projected summer warming compared CMIP5, which was found be statistically significant in Precipitation Central were have a stronger drying trend months, there also substantially narrower projection range. Spatial comparisons indicate that this extends into large part Europe. show warmer temperatures Mediterranean are largely driven by higher global climate sensitivities models, while regional changes broadly similar. In difference responses these cases picture can said changed. find sensitivity is important where it accounts roughly 40 % of differences between ensembles temperature.

Language: Английский

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Enhanced simulated early 21st century Arctic sea ice loss due to CMIP6 biomass burning emissions

Science Advances, Journal Year: 2022, Volume and Issue: 8(30)

Published: July 27, 2022

The mechanisms underlying decadal variability in Arctic sea ice remain actively debated. Here, we show that boreal biomass burning (BB) emissions strongly influences simulated on multidecadal time scales. In particular, find a strong acceleration decline the early 21st century Community Earth System Model version 2 (CESM2) is related to increased prescribed BB sixth phase of Coupled Intercomparison Project (CMIP6) through summertime aerosol-cloud interactions. Furthermore, more than half reported improvement sensitivity CO2 and global warming from CMIP5 CMIP6 can be attributed variability, at least CESM. These results highlight new kind uncertainty needs considered when incorporating observational data into model forcing while also raising questions about role observed loss.

Language: Английский

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