Bjerknes Climate Prediction Unit

Cai, W., Reason, C., Mohino, E., …. , N.S. Keenlyside et al.  2025: Climate impacts of the El Niño–Southern Oscillation in Africa. Nat Rev Earth Environ. https://doi.org/10.1038/s43017-025-00705-7 Summary: The El Niño–Southern Oscillation (ENSO) — describing shifts between warm El Niño and cold La Niña phases — has a substantial effect on the global climate. In this Review, we outline the mechanisms and climate impacts of ENSO in Africa, focusing on rainfall. ENSO’s influence varies strongly by season, region, phase, event and decade, highlighting complex dynamics and asymmetries. Although difficult to generalize, key characteristics include: anomalies across the Sahel in July–September, related to the tropospheric temperature mechanism; a strong dipole in anomalies between eastern and southern Africa during October–December (the short rain reason) and December–February, linked to interactions with the Indian Ocean Dipole and Indian Ocean Basin mode, respectively; and anomalies over southern Africa (with possible indications of opposite anomalies over East Africa) during March–May (the long rain season), associated with continuation of the Indian Ocean Basin mode. These teleconnections tend to be most pronounced for East Pacific El Niño and Central Pacific La Niña events, as well as during decades when interbasin interactions are strongest. Although challenging to simulate, climate models suggest that these impacts will strengthen in the future, manifesting as an increased frequency of ENSO-related dry and wet extremes. Given the reliance of much of Africa on rain-fed agriculture, resolving these relationships is vital, necessitating realistic simulation of regional circulations, ENSO and its interbasin interactions. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Hu, A., I. Richter, Y. Okumura, N. Burls, N. Keenlyside, R. Parfitt, K. Bellomo, A. Bellucci, R. Farneti, A. Fedorov, B. S. Ferster, C. He, Q. Li, D. Matei 2025: Unraveling the Complexity of Global Climate Dynamics: Interactions among El Niño–Southern Oscillation, Atlantic Meridional Overturning Circulation, and Tropical Basins Across Different Timescales. Ocean-Land-Atmos Res.. https://spj.science.org/doi/10.34133/olar.0096 Summary: Tropical basin interactions and the climatic linkages between mid-to-high latitudes and the tropics are active research areas. These interactions include the influence of El Niño–Southern Oscillation (ENSO) on the tropical Indian and Atlantic oceans, the feedback from these basins on ENSO, the influence of the tropics on mid-to-high-latitude climates, and the feedback from higher latitudes on tropical climate variability. This review summarizes the current understanding of these relationships and key underlying physical processes. In particular, we assessed the current knowledge of tropical variability and the interactions between the tropics and extratropics, including ENSO variability and diversity, the influence of ENSO on the tropical Atlantic and Indian Oceans, interactions among tropical basins on different timescales, variability in the Atlantic meridional overturning circulation (AMOC), the effect of tropical basins on the AMOC, the relationship between the AMOC and Atlantic multidecadal variability, the influence of the AMOC on ENSO and tropical variability, and the impact of other mid-to-high-latitude processes on tropical variability. Although ENSO is the dominant mode of variability on interannual timescales, its characteristics are not stationary and can be influenced by processes from other tropical basins and mid-to-high latitudes. The strength and variations of these interactions among different tropical basins and latitudes can be modulated by changes in external forcing, whether of natural or anthropogenic origin, and may also be shaped by nonlinear interactions between different modes of internal variability. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Chafik, L., Årthun, M., Langehaug, H.R., Nilsson, J., Rossby, T. 2025: The Nordic Seas overturning is modulated by northward-propagating thermohaline anomalies. Commun Earth Environ. https://doi.org/10.1038/s43247-025-02557-x Summary: The inflow of warm waters into the Nordic Seas, crucial for sustaining the climate-regulating Atlantic overturning circulation, can be reconstructed from hydrography using a north-south dynamic height gradient across the Greenland-Scotland Ridge. Variations in this influx are herein linked to northward-propagating thermohaline anomalies, initially observed at the intergyre boundary and likely driven by changes in ocean heat transport. As these anomalies reach the eastern subpolar North Atlantic, they modulate the cross-ridge dynamic height difference, thereby influencing both the Atlantic inflow and the Nordic Seas overflows on multi-year to decadal scales. Thus, these thermohaline anomalies play a dynamically active role in modulating the watermass exchanges across the ridge and downstream along the Atlantic Water path, rather than being a simple passive train of signals. This explains why these thermohaline signals are a key source of climate predictability and provides fresh insights into the functioning of the Nordic Seas overturning circulation from observations. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Richter, I., Chang, P., Chiu, P.-G., Danabasoglu, G., Doi, T., Dommenget, D., Gastineau, G., Gillett, Z. E., Hu, A., Kataoka, T., Keenlyside, N. S., Kucharski, F., Okumura, Y. M., Park, W., Stuecker, M. F., Taschetto, A. S., Wang, C., Yeager, S. G., and Yeh, S.-W. 2025: The Tropical Basin Interaction Model Intercomparison Project (TBIMIP). Geosci. Model Dev.. https://doi.org/10.5194/gmd-18-2587-2025 Summary: Large-scale interaction between the three tropical ocean basins is an area of intense research that is often conducted through experimentation with numerical models. A common problem is that modeling groups use different experimental setups, which makes it difficult to compare results and delineate the role of model biases from differences in experimental setups. To address this issue, an experimental protocol for examining interaction between the tropical basins is introduced. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) consists of experiments in which sea surface temperatures (SSTs) are prescribed to follow observed values in selected basins. There are two types of experiments. One type, called standard pacemaker, consists of simulations in which SSTs are restored to observations in selected basins during a historical simulation. The other type, called pacemaker hindcast, consists of seasonal hindcast simulations in which SSTs are restored to observations during 12-month forecast periods. TBIMIP is coordinated by the Climate and Ocean – Variability, Predictability, and Change (CLIVAR) Research Focus on Tropical Basin Interaction. The datasets from the model simulations will be made available to the community to facilitate and stimulate research on tropical basin interaction and its role in seasonal-to-decadal variability and climate change. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Xiu, Y., Wang, Y., Luo, H., Garcia-Oliva, L., Yang, Q. 2025: Impact of ocean, sea ice or atmosphere initialization on seasonal prediction of regional Antarctic sea ice. JAMES. https://doi.org/10.1029/2024MS004382 Summary: This study investigates how the atmosphere, ocean, or sea ice observations affect the seasonal prediction of Antarctic sea ice. We analyze three sets of predictions from the Norwegian Climate Prediction Model, each integrating different data sets of the atmosphere, ocean, or sea ice. Initially, we assess the seasonal cycles, trends, and variability of Antarctic sea ice in these data sets. We found that including atmosphere observations gave the best seasonal cycle compared to the observed sea ice. However, the linear trend in sea ice when including atmospheric data is poorly reproduced in the western Southern Ocean. Regarding variability, including the combined ocean and sea ice data gave the best performance. Next, we assess the accuracy of regional Antarctic sea ice prediction. We found that the accuracy varies with region and season. Austral winter predictions in western Antarctic have some skill up to a year in advance, while those in the eastern Antarctic are less reliable. Predictions based on atmosphere data are generally more accurate than those based on ocean or ocean/sea-ice data, especially when predicting from July or October. Interestingly, once ocean data is used, involving additional sea ice data improves sea ice concentration in the reanalysis but not in the predictions. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Sospedra-Alfonso, R., Merryfield, W.J., Toohey, M., Timmreck, C., Vernier, J-P., Bethke, I., Wang, Y., Bilbao, R., Donat, M.G., Ortega, P., Cole, J., Lee, W.-S., Delworth, T.L., Paynter, D., Zeng, F., Zhang, L., Khodri, M., Mignot, J., Swingedouw, D., Torres, O., Hu, S., Man, W., Zuo, M., Hermanson, L., Smith, D., Kataoka, T., Tatebe, H. 2024: Decadal prediction centers prepare for a major volcanic eruption. Bulletin of the American Meteorological Society. https://doi.org/10.1175/BAMS-D-23-0111.1 Summary: The World Meteorological Organization’s Lead Centre for Annual-to-Decadal Climate prediction issues operational forecasts annually as guidance for regional climate centers, climate outlook forums and national meteorological and hydrological services. The occurrence of a large volcanic eruption such as that of Mount Pinatubo in 1991, however, would invalidate these forecasts and prompt producers to modify their predictions. To assist and prepare decadal prediction centers for this eventuality, the Volcanic Response activities under the World Climate Research Programme’s Stratosphere-troposphere Processes And their Role in Climate (SPARC) and the Decadal Climate Prediction Project (DCPP) organized a community exercise to respond to a hypothetical large eruption occurring in April 2022. As part of this exercise, the Easy Volcanic Aerosol forcing generator was used to provide stratospheric sulfate aerosol optical properties customized to the configurations of individual decadal prediction models. Participating centers then reran forecasts for 2022-2026 from their original initialization dates and in most cases also from just before the eruption at the beginning of April 2022, according to two candidate response protocols. This article describes various aspects of this SPARC/DCPP Volcanic Response Readiness Exercise (VolRes-RE), including the hypothesized volcanic event, the modified forecasts under the two protocols from the eight contributing centers, the lessons learned during the coordination and execution of this exercise, and the recommendations to the decadal prediction community for the response to an actual eruption. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Passos, L., Langehaug, H.R., Årthun M., Straneo, F. 2024: On the Relation between Thermohaline Anomalies and Water Mass Transformation in the Eastern Subpolar North Atlantic. Journal of Climate. https://doi.org/10.1175/JCLI-D-23-0379.1 Summary: Decadal thermohaline anomalies carried northward by the North Atlantic Current are an important source of predictability in the North Atlantic region. Here, we investigate whether these thermohaline anomalies influence surface-forced water mass transformation (SFWMT) in the eastern subpolar gyre using the reanalyses EN4.2.2 for the ocean and the ERA5 for the atmosphere. In addition, we follow the propagation of thermohaline anomalies along two paths: in the subpolar North Atlantic and the Norwegian Sea. We use observation-based datasets (HadISST, EN4.2.2, and Ishii) between 1947 and 2021 and apply complex empirical orthogonal functions. Our results show that when a warm anomaly enters the eastern subpolar gyre, more SFWMT occurs in light-density classes (27.0–27.2 kg m−3). In contrast, when a cold anomaly enters the eastern subpolar gyre, more SFWMT occurs in denser classes (27.4–27.5 kg m−3). Following the thermohaline anomalies in both paths, we find alternating warm–salty and cold–fresh subsurface anomalies, repeating throughout the 74-yr-long record with four warm–salty and cold–fresh periods after the 1950s. The cold–fresh anomaly periods happen simultaneously with the Great Salinity Anomaly events. Moreover, the propagation of thermohaline anomalies is faster in the subpolar North Atlantic (SPNA) than in the Norwegian Sea, especially for temperature anomalies. These findings might have implications for our understanding of the decadal variability of the lower limb of the Atlantic meridional overturning circulation and predictability in the North Atlantic region. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Bushuk, M., Ali, S., Bailey, D.A., Bao, Q., Batté, L., Bhatt, U.S., Blanchard-Wrigglesworth, E., Blockley, E., Cawley, G., Chi, J., Counillon, F., et al. 2024: Predicting September Arctic Sea Ice: A Multimodel Seasonal Skill Comparison. Bull. Amer. Meteor. Soc.. https://doi.org/10.1175/BAMS-D-23-0163.1 Summary: This study quantifies the state of the art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multimodel dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–20 for predictions of pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on 1 June, 1 July, 1 August, and 1 September. This diverse set of statistical and dynamical models can individually predict linearly detrended pan-Arctic SIE anomalies with skill, and a multimodel median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and central Arctic sectors. The skill of dynamical and statistical models is generally comparable for pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least 3 months in advance. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Richter, I., Ratnam, J.V., Martineau, P., Oettli, P., Doi, T., Ogata, T., Kataoka, T., Counillon, F. 2024: A simple statistical post-processing scheme for enhancing the skill of seasonal SST predictions in the tropics. Monthly Weather Review. https://doi.org/10.1175/MWR-D-23-0266.1 Summary: The prediction of year-to-year climate variability patterns, such as El Niño, offers potential benefits to society by aiding mitigation and adaptation efforts. Current prediction systems, however, may still have substantial room for improvement due to systematic model errors and due to imperfect initialization of the oceanic state at the start of predictions. Here we develop a statistical correction scheme to improve prediction skill after forecasts have been completed. The scheme shows some moderate success in improving the skill for predicting El Niño and similar climate patterns in seven prediction systems. Our results not only indicate a potential for improving prediction skill after the fact but also point to the importance of improving the way prediction systems are initialized. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Garcia-Oliva, L., Counillon, F., Bethke, I., Keenlyside, N. 2024: Intercomparison of initialization methods for Seasonal-to-Decadal Climate Predictions with the NorCPM. Clim Dyn. https://doi.org/10.1007/s00382-024-07170-w Summary: Initialization is essential for accurate seasonal-to-decadal (S2D) climate predictions. The initialization schemes used differ on the component initialized, the Data Assimilation method, or the technique. We compare five popular schemes within NorCPM following the same experimental protocol: reanalysis from 1980 to 2010 and seasonal and decadal predictions initialized from the reanalysis. We compare atmospheric initialization—Newtonian relaxation (nudging)—against ocean initialization—Ensemble Kalman Filter—(ODA). On the atmosphere, we explore the benefit of full-field (NudF-UVT) or anomaly (NudA-UVT) nudging of horizontal winds and temperature (U, V, and T) observations. The scheme NudA-UV nudges horizontal winds to disentangle the role of wind-driven variability. The ODA+NudA-UV scheme is a first attempt at joint initialization of ocean and atmospheric components in NorCPM. During the reanalysis, atmospheric nudging improves the synchronization of the atmosphere and land components with the observed data. Conversely, ODA is more effective at synchronizing the ocean component with observations. The atmospheric nudging schemes are better at reproducing specific events, such as the rapid North Atlantic subpolar gyre shift. An abrupt climatological change using the NudA-UV scheme demonstrates that energy conservation is crucial when only assimilating winds. ODA outperforms atmospheric-initialized versions for S2D global predictions, while atmospheric nudging is preferable for accurately initializing phenomena in specific regions, with the technique’s benefit depending on the prediction’s temporal scale. For instance, atmospheric full-field initialization benefits the tropical Atlantic Niño at 1-month lead time, and atmospheric anomaly initialization benefits longer lead times, reducing hindcast drift. Combining atmosphere and ocean initialization yields sub-optimal results, as sustaining the ensemble’s reliability—required for ODA’s performance—is challenging with atmospheric nudging. Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.