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- Bustamante, Mercedes, et al.
(författare)
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Ten new insights in climate science 2023
- 2023
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Ingår i: Global Sustainability. - : CAMBRIDGE UNIV PRESS. - 2059-4798. ; 7
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Forskningsöversikt (refereegranskat)abstract
- Non-technical summary We identify a set of essential recent advances in climate change research with high policy relevance, across natural and social sciences: (1) looming inevitability and implications of overshooting the 1.5 degrees C warming limit, (2) urgent need for a rapid and managed fossil fuel phase-out, (3) challenges for scaling carbon dioxide removal, (4) uncertainties regarding the future contribution of natural carbon sinks, (5) intertwinedness of the crises of biodiversity loss and climate change, (6) compound events, (7) mountain glacier loss, (8) human immobility in the face of climate risks, (9) adaptation justice, and (10) just transitions in food systems.Technical summary The Intergovernmental Panel on Climate Change Assessment Reports provides the scientific foundation for international climate negotiations and constitutes an unmatched resource for researchers. However, the assessment cycles take multiple years. As a contribution to cross- and interdisciplinary understanding of climate change across diverse research communities, we have streamlined an annual process to identify and synthesize significant research advances. We collected input from experts on various fields using an online questionnaire and prioritized a set of 10 key research insights with high policy relevance. This year, we focus on: (1) the looming overshoot of the 1.5 degrees C warming limit, (2) the urgency of fossil fuel phase-out, (3) challenges to scale-up carbon dioxide removal, (4) uncertainties regarding future natural carbon sinks, (5) the need for joint governance of biodiversity loss and climate change, (6) advances in understanding compound events, (7) accelerated mountain glacier loss, (8) human immobility amidst climate risks, (9) adaptation justice, and (10) just transitions in food systems. We present a succinct account of these insights, reflect on their policy implications, and offer an integrated set of policy-relevant messages. This science synthesis and science communication effort is also the basis for a policy report contributing to elevate climate science every year in time for the United Nations Climate Change Conference.Social media summary We highlight recent and policy-relevant advances in climate change research - with input from more than 200 experts.
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| 2. |
- Chang, Kuang Yu, et al.
(författare)
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Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates
- 2023
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Ingår i: Global Change Biology. - 1354-1013. ; 29:15, s. 4298-4312
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Tidskriftsartikel (refereegranskat)abstract
- The recent rise in atmospheric methane (CH4) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year−1) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.
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| 3. |
- Petrescu, Ana Maria Roxana, et al.
(författare)
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The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990-2019
- 2023
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Ingår i: Earth System Science Data. - : COPERNICUS GESELLSCHAFT MBH. - 1866-3508 .- 1866-3516. ; 15:3, s. 1197-1268
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990-2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015-2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 TgCH(4) yr(-1) (EDGARv6.0, last year 2018) and 18.4 TgCH(4) yr(-1) (GAINS, last year 2015), close to the NGHGI estimates of 17 :5 +/- 2 :1 TgCH(4) yr(-1). TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 TgCH(4) yr(-1). Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 TgCH(4) yr(-1) inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH-HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 TgCH(4) yr(-1). For N2O emissions, over the 2015-2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 TgN(2)Oyr(-1), close to the NGHGI data (0 :8 +/- 55% TgN(2)Oyr(-1)). Over the same period, the mean of TD global and regional inversions was 1.4 TgN(2)Oyr(-1) (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 C UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. The referenced dataset srelated to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).
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