Predictability of weather and climate

Abstract:

Over the past 20 years, extreme event attribution has developed rapidly, providing a wide range of methods to attribute weather events - from unconditioned probabilistic to strongly conditioned storyline approaches. Advancing the field now requires combining results from multiple methods, allowing more robust conclusions drawing from various lines of evidence. Yet, doing so remains challenging. We call for closer interaction within the attribution field to develop approaches with method comparison in mind. We highlight the need to explicitly define the research questions answerable by specific methods, and to clearly outline the limitations of each method.

Abstract:

This study evaluates the performance of high-resolution (grid sizes of 9-28 km for the atmosphere; 5-13 km for the ocean) global simulations from the EERIE project in representing the persistence of the Southern Annular Mode (SAM), a leading mode of Southern Hemisphere climate variability. Using the decorrelation timescale of the SAM index (τ), we compare EERIE simulations with CMIP6 models and ERA5 reanalysis. EERIE simulations reduce long-standing biases in SAM persistence, especially in early summer, with τ values of 9-20 d compared to CMIP6's 9-32 d and ERA5's 11 d. This improvement correlates with a more accurate climatological jet latitude (λ0). EERIE atmosphere-only AMIP runs outperform the coupled simulations in both τ and λ0, showing smaller biases and ranges of variability, underscoring the critical role of sea surface temperature (SST) representation in shaping atmospheric circulation. In these AMIP experiments, the atmospheric eddy feedback strength, combined with the damping timescale estimated via friction, correlates more strongly with τ than λ0. We speculate that the well-captured jet position (biases < 1° relative to ERA5), due to prescribed SSTs, limits λ0's explanatory power for τ differences, allowing other processes to dominate. Using a finer model grid (9 km vs. 28 km) of the same AMIP model reduces τ, though the mechanism remains unclear. Finally, motivated by the importance of oceanic eddies in the Southern Ocean, we conducted sensitivity experiments that filter transient mesoscale features from the SST boundary conditions. The results suggest that oceanic eddies may enhance summertime SAM persistence (by g1/4 2 d), though this signal is not statistically significant and is absent in the single 9 km run, pointing to a subtle role of mesoscale ocean-Atmosphere interaction that remains to be explored.

Abstract:

Plain Language Summary: We investigate how the variability in the Indian Ocean Sea Surface Temperature in autumn, known as the Indian Ocean Dipole (IOD), influences the precipitation regime and storm activity in the North Atlantic, Europe, and Mediterranean regions during the winter season. Our results indicate that IOD variability triggers December shifts in atmospheric pressure over these regions and alters precipitation patterns, influencing the frequency and intensity of precipitation events. The strongest impacts are observed at mid‐latitudes, with storm activity decreasing over the Eastern Atlantic and Western Mediterranean. These storm changes are tied to stronger temperature contrasts between the north and south part of the domain, which produce significant changes in the vertical wind shear. Our study further supports the idea that Indian Ocean variability may influence the early winter weather in Europe and the Mediterranean—an important insight for improving sub‐seasonal to seasonal forecasts.

Abstract:

Abstract. We introduce Saudi Rainfall (SaRa), a gridded historical and near-real-time precipitation (P) product specifically designed for the Arabian Peninsula, one of the most arid, water-stressed, and data-sparse regions on Earth. The product has an hourly 0.1° resolution spanning 1979 to the present and is continuously updated with a latency of less than 2 h. The algorithm underpinning the product involves 18 machine learning model stacks trained for different combinations of satellite and (re)analysis P products along with several static predictors. As a training target, hourly and daily P observations from gauges in Saudi Arabia (n = 113) and globally (n = 14 256) are used. To evaluate the performance of SaRa, we carried out the most comprehensive evaluation of gridded P products in the region to date, using observations from independent gauges (randomly excluded from training) in Saudi Arabia as a reference (n = 119). Among the 20 evaluated P products, our new product, SaRa, consistently ranked first across all evaluation metrics, including the Kling–Gupta efficiency (KGE), correlation, bias, peak bias, wet-day bias, and critical success index. Notably, SaRa achieved a median KGE – a summary statistic combining correlation, bias, and variability – of 0.36, while widely used non-gauge-based products such as CHIRP, ERA5, GSMaP V8, and IMERG-L V07 achieved values of −0.07, 0.21, −0.13, and −0.39, respectively. SaRa also outperformed four gauge-based products such as CHIRPS V2, CPC Unified, IMERG-F V07, and MSWEP V2.8 which had median KGE values of 0.17, −0.03, 0.29, and 0.20, respectively. Our new P product – available at https://www.gloh2o.org/sara (last access: 24 September 2025) – addresses a crucial need in the Arabian Peninsula, providing a robust and reliable dataset to support hydrological modeling, water resource assessments, flood management, and climate research.

Abstract:

<jats:p>Abstract. The Atmospheric Processes And their Role in Climate (APARC) Quasi-Biennial Oscillation initiative (QBOi) has conducted new experiments to explore the modulation of the QBO by El Niño–Southern Oscillation (ENSO). This paper provides an overview of the experimental design and investigates the modulation of the QBO by ENSO using nine climate models used in QBOi. A key finding is a consistent lengthening of the QBO period during La Niña compared to El Niño across all models, aligning with observational evidence. Although several models simulate QBO periods that deviate from the observed mean of approximately 28 months, the relative difference between La Niña and El Niño remains interpretable within each model. The simulated QBO periods during La Niña tend to be longer than those during El Niño, although, in most models, the differences are small compared to that observed. However, the magnitude of this lengthening shows large inter-model differences. By contrast, even the sign of the ENSO effect on QBO amplitude varies among models. Models employing variable parameterized gravity wave sources generally exhibit greater sensitivity of the QBO amplitude to the presence of ENSO than those models using fixed sources. The models capture key observed ENSO-related characteristics, including a weaker Walker circulation and increased equatorial precipitation during El Niño compared to La Niña, as well as a characteristic response in zonal mean zonal wind and temperature. All models also simulate stronger equatorial tropical upwelling in El Niño compared to La Niña up to ∼ 10 hPa, consistent with ERA5 reanalysis. These modulations influence the propagation and filtering of gravity waves. Notably, models with variable parameterized gravity wave sources show stronger wave forcing during El Niño, potentially explaining the shorter QBO period modulation in these models. Further investigation into the complex interplay between ENSO, gravity waves, and the QBO can contribute to improved model formulations. </jats:p>