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Abstract:

Abstract We propose a new temporal merging method for seamless climate forecast information of climate extremes. In order to construct stable and seamless climate forecast information for user-oriented climate extremes, ensemble members are pooled across available start dates using relative weights, for a target season. Recently, vineyard farmers from Catalonia, Spain, reported frost risk during the spring months (March and April). The observations show high interannual variability of the frequency of frost days (FFD) over Catalonia for the period 1983–2022. Multi-annual to seasonal forecasts from the European Centre for Medium-Range Weather Forecasts show a varying level of FFD forecast skill for lead times 1 to 22 months. The temporally merged weighted forecast enhances forecast skill compared to individual start dates, by adding information from previous start dates, at no additional computational cost. For most start dates, the skill is primarily attributed to the warming trends, except for a few start dates, where remanent forecast skill is attributed to internal variability. The proposed anticipatory framework “Ready-Steady-Action/Go” shows that adopting seamless climate forecast information can bring about 20 to 30% potential economic value for vineyard farmers, with a maximum value noted for multi-annual forecasts.

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.

Abstract:

During early boreal winter, the extra-tropical atmospheric circulation is influenced by Rossby waves propagating from the Indian Ocean towards the North Atlantic-European (NAE) regions, resulting in a North Atlantic Oscillation (NAO)-like pattern. The mechanisms driving these teleconnections are not well understood and are crucial for improving model skills. This study investigates these mechanisms using the ERA5 dataset and tests the predictive capabilities of the ECMWF-SEAS5 hindcast, exploring potential reasons for a weak model response. Linear regression methods are employed to examine the extra-tropical links with the Indian Ocean dipole (IOD), both in isolation and in combination with the El Niño-Southern Oscillation (ENSO). Our findings demonstrate a connection between October IOD sea surface temperature anomalies and December Indian Ocean precipitation patterns. Furthermore, a correlation between the October IOD and December NAO time series suggests a link between the IOD and NAE circulation. The early winter European response to a positive IOD is characterized by a north-south precipitation dipole and a large positive surface air temperature anomaly. Positive feedback from transient eddy forcing reinforces the wavenumber-3-like propagation across extra-tropical regions, with ENSO playing a minor role compared to the IOD. This phenomenon is particularly evident in regions such as the North Pacific and North Atlantic, where wave energy propagation is intensified. Although SEAS5 replicates the NAO response, its magnitude is significantly weaker. The model struggles to simulate the delayed rainfall dipole response to the IOD accurately and shows structural discrepancies compared to reanalysis data.

Abstract:

We propose a new temporal merging method for seamless climate forecast information of climate extremes. In order to construct stable and seamless climate forecast information for user-oriented climate extremes, ensemble members are pooled across available start dates using relative weights, for a target season. Recently, vineyard farmers from Catalonia, Spain, reported frost risk during the spring months (March and April). The observations show high interannual variability of the frequency of frost days (FFD) over Catalonia for the period 1983–2022. Multi-annual to seasonal forecasts from the European Centre for Medium-Range Weather Forecasts show a varying level of FFD forecast skill for lead times 1 to 22 months. The temporally merged weighted forecast enhances forecast skill compared to individual start dates, by adding information from previous start dates, at no additional computational cost. For most start dates, the skill is primarily attributed to the warming trends, except for a few start dates, where remanent forecast skill is attributed to internal variability. The proposed anticipatory framework “Ready-Steady-Action/Go” shows that adopting seamless climate forecast information can bring about 20 to 30% potential economic value for vineyard farmers, with a maximum value noted for multi-annual forecasts.