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Abstract:

We assess near-surface temperature and sea surface temperature trends in 8 seasonal forecast systems in the Copernicus Climate Change Service archive, over the common hindcast period (1993–2016). All but one of the systems show a faster warming of the global-mean, relative to observations in both boreal summer and winter seasons. On average, systems warm at 0.21K/decade and 0.22K/decade for winter and summer, respectively, compared to 0.17K/decade and 0.19K/decade for ERA5. In summer, forecast systems tend to show an excessive warming of the tropical Pacific, tropical Atlantic and southern mid-latitudes, which contributes to the difference in global warming rates compared to observations. In contrast, greater warming in the northern mid-latitudes contributes most to trend differences for winter. The faster warming of models over this period has important implications for seasonal forecasts of future global and regional temperature and suggests further work is required to understand this bias.

Abstract:

While it is widely believed that the intense rainfall in summer 2022 over Pakistan was substantially exacerbated by anthropogenic climate change1, 2, climate models struggled to confirm this3, 4. Using a high-resolution operational seasonal forecasting system that successfully predicted the extreme wet conditions, we perform counterfactual experiments simulating pre-industrial and future conditions. Both experiments also exhibit strong anomalous rainfall, indicating a limited role of CO2-induced forcing. We attribute 10% of the total rainfall to historical increases in CO2 and ocean temperature. However, further increases in the future suggest a weak mean precipitation reduction but with increased variability. By decomposing rainfall and large-scale circulation into CO2 and SST-related signals, we illustrate a tendency for these signals to compensate each other in future scenarios. This suggests that historical CO2 impacts may not reliably predict future responses. Accurately capturing local dynamics is therefore essential for regional climate adaptation planning and for informing loss and damage discussions.