Professor Myles Allen CBE FRS

Abstract:

Abstract Record-breaking extreme rainfall events, such as those observed in Southeast Africa (SEAF) in February 2023, underscore the urgent need to quantify anthropogenic impacts on extreme weather risks. This study presents an attribution and projection analysis of February extreme rainfall in SEAF by evaluating probabilistic risk changes across multiple Earth System Model (ESM) ensembles and Numerical Weather Prediction (NWP) experiments. While NWP models reliably capture the magnitude and frequency of these extremes, ESMs generally exhibit a wet bias, necessitating the use of relative thresholds. Our attribution analysis reveals that greenhouse gas (GHG) forcing significantly increases the risk of extreme events (e.g., once-in-70-year and once-in-150-year events, comparable to the precipitation intensities of 2000 and 2023). However, this risk increase remains less certain under all-forcing simulations, as ESMs show substantial disagreement regarding aerosol (AER) influences. Future projections under various Shared Socioeconomic Pathways (SSPs) indicate that a higher GHG emission exacerbates these risks, highlighting the critical importance of aggressive mitigation efforts. Furthermore, shifts in Generalized Extreme Value (GEV) parameters demonstrate how forcing-driven climate changes may deform the risk probability distribution, with a higher emission of GHG potentially altering both the climatological mean and interannual variability of SEAF extreme rainfall. Our findings are supported by both ESM and NWP results (particularly short-lead forecasts), with the latter exhibiting lower uncertainty due to constraints on synoptic systems and internal oceanic variability. We conclude that GHG forcing likely elevates the risk of 2023-like extreme events in SEAF and discuss the remaining sources of uncertainty in these projections.

Abstract:

Abstract. In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. We track twelve key sets of indicators of the state of the climate system, closely following Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment report (AR6) methods, to produce our fourth annual publication. One of the indicators, the Earth's energy imbalance (EEI) provides a crucial integrative measure of the overall heating of the planet and the pace of climate change – this has more than doubled since the 1976–1995 period. A newly added indicator of temperature extremes, the number of days experiencing marine heatwaves, has more than tripled between 1991 and 2025. For the 2016–2025 decade average, observed warming relative to 1850–1900 was 1.26 [1.13 to 1.36] °C, of which 1.24 [1.0 to 1.5] °C was human-induced. Human-induced warming reached 1.37 °C relative to 1850–1900 in the year 2025, increasing at a rate of 0.27 [0.2–0.4] °C per decade over 2016–2025. This high rate of warming, which matches the all-time high seen last year in the instrumental record, was caused by a combination of greenhouse gas emissions being at an all-time high of 54.6 ± 5.5 GtCO2e yr−1 over the last decade (2015–2024), as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that CO2 emission growth is slowing. The continuation of these annual updates could track decreases or increases in the rate of human influence and climatic changes presented here, reflecting the outcomes of societal choices during the critical 2020s decade. The data presented herein can provide a useful reference point for the drafting of the IPCC seventh assessment report. In total, we employ analysis from over 40 global datasets (https://doi.org/10.5281/zenodo.20499280, Smith et al., 2026a). Future monitoring of these indicators, such as ocean and satellite measurements of the Earth's energy imbalance, are threatened by geopolitical and public funding decisions. Our ability to consistently track many of the indicators requires the continuity of observation programs and coordination mechanisms, including the Global Climate Observing System (GCOS) program, that enable their effective integration and use.

Abstract:

Greenhouse gas emission metrics are widely used for comparing climate impacts of different gases and for guiding mitigation policy. Conventional metrics such as GWP100 perform well for representing the warming effects of long-lived gases which behave like CO₂ but poorly for short-lived climate pollutants (SLCPs). Methane (CH4) is the most important SLCP and has been the main focus of alternative metrics. GWP* was developed to more accurately capture impact on global warming, particularly from stable and declining CH4 emissions which are not well served by GWP100. This means that GWP* better connects emissions pathways to long-term temperature targets (Cain et al., 2022). Previous studies optimised GWP* for CH4 for a limited range of scenarios up to 2100. However, future mitigation pathways involve a wider range of gases and transition speeds, overshoot behaviour, and long-term stabilization beyond this period. In addition, highly radiatively efficient fluorinated gases are increasingly important in mitigation strategies yet have not been demonstrated with the GWP* framework. In this study, we systematically test the performance of GWP* across an expanded set of emissions scenarios, including rapid mitigation, delayed action, and prolonged temperature overshoot pathways, and extend the analysis to multi-century time horizons with an optimisation of the flow term of GWP* (Mastropierro et al., 2025). We further develop and evaluate a generalized formulation of GWP* for fluorinated gases with diverse atmospheric lifetimes. The outcomes examine the performance of GWP* under realistic transition pathways and its representation of temperature responses for fluorinated gases. This work supports the development of more physically consistent multi-gas emission metrics for climate targets, carbon budgeting, and policy design, as it is a simple tool to calculate how much global warming is added or avoided by increasing or cutting SLCPs such as F-gases.Cain, M., Jenkins, S., Allen, M.R., Lynch, J., Frame, D.J., Macey, A.H., Peters, G.P. Methane and the Paris Agreement temperature goals. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 380 (2022). https://doi.org/10.1098/rsta.2020.0456Mastropierro, M., Tanaka, K., Melnikova, I. et al. Testing GWP* to quantify non-CO2contributions in the carbon budget framework in overshoot scenarios. npj Clim Atmos Sci 8, 101 (2025). https://doi.org/10.1038/s41612-025-00980-7

Abstract:

Integrating physical, socio-economic, and technological perspectives is indispensable for addressing climate mitigation challenges. While directly coupling state-of-the-art Earth System Models (ESMs) and Integrated Assessment Models (IAMs) offers a way to explore feedbacks between these domains, doing so with full-complexity models remains computationally prohibitive. This is particularly true for cost-effective intertemporal optimization IAMs due to fundamental operational differences: while ESMs perform forward simulations, such IAMs optimize over time. Consequently, direct coupling would require numerous computationally intensive iterations to converge, a complication further compounded by the stochastic nature of ESMs.To overcome the barriers to coupling ESMs and IAMs, we employ their reduced-complexity representations (i.e., emulators). We couple an IAM emulator representing 9 distinct IAMs (Xiong et al. 2025) with an ESM emulator, FaIR, representing 66 ESM configurations (Smith et al. 2024a). Using this coupled ESM-IAM emulator framework in an optimization setting, we calculate cost-effective pathways that achieve the temperature targets of the Paris Agreement with and without overshoot.Our preliminary results indicate that the uncertainty ranges for such pathways are significantly larger than previously estimated. Our results also have implications for target setting; we show how pathways differ when IAMs optimize directly for a temperature target – a capability IAMs traditionally lack. Instead, IAMs typically rely on temperature proxies, such as carbon budgets (or their corresponding carbon price pathways), which do not necessarily provide an accurate representation of the temperature target. Furthermore, this study offers advanced insights into the dynamics of climate-economy interactions, providing a roadmap for future efforts to couple full-complexity models. ReferencesXiong, W., Tanaka, K., Ciais, P., Johansson, D. J. A., & Lehtveer, M. (2025). emIAM v1.0: an emulator for integrated assessment models using marginal abatement cost curves. Geosci. Model Dev., 18(5), 1575-1612. doi:10.5194/gmd-18-1575-2025Smith, C., Cummins, D. P., Fredriksen, H. B., Nicholls, Z., Meinshausen, M., Allen, M., . . . Partanen, A. I. (2024). fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections. Geosci. Model Dev., 17(23), 8569-8592. doi:10.5194/gmd-17-8569-2024

Abstract:

2025 has been the third warmest year on the observational record globally, while the past decade has been the warmest on record. Accelerating climate change is altering the hydrological cycle, with associated extreme events - including droughts, floods, and compound multivariate extremes - occurring with increasing frequency and intensity in many regions of the world.  The 2025 October–November-December (OND), short rains (Vuli/Deyr/Hageya) season largely disappointed across East Africa, with major drought hotspots involving highly vulnerable regions in Somalia, eastern Kenya, and southern Ethiopia. Many areas received well under 60% of climatological precipitation level, with patches even below 30%, and some locations ranking among the driest in the satellite-era record (roughly since 1979). This substantial rainfall deficit, amplified by unusually high near-surface air temperature, rapidly degraded rangelands and diminished water availability, driving livestock stress and low crop yields. Additionally, in Somalia, the OND drought contributed to population displacements and heightened need for humanitarian aid.  We analyse the dynamic and thermodynamic drivers of the 2025 OND, Vuli/Deyr/Hageya drought in East Africa. Using a multi-method attribution framework, we assess the influence of anthropogenic climate change on the development of these high-impact drought conditions, with the strongest signal magnitude in the eastern Horn of Africa. We combine multiple observational and reanalysis datasets with large ensembles of bias-corrected CMIP6 historical simulations and future projections under SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios. This enables us to evaluate the roles of climate-change indices and internal climate variability modes – most importantly ENSO and IOD - in shaping this extreme hydrological event on subseasonal to seasonal timescales.  Additionally, we use the Met Office HadGEM3-A attribution system to quantify the extent to which anthropogenic forcing has altered the probability and intensity of such class of meteorological drought in the region. We consider both unconditional and circulation-conditioned attribution perspectives. Preliminary results indicate a significant contribution of climate change to the likelihood and intensity of the 2025 Vuli/Deyr/Hageya drought over regions in Ethiopia, Kenya, and Somalia that would greatly benefit from adaptation measures.