Arctic-Atlantic Climate Variability and Predictability in Observations and in a Dynamical Prediction System (PhD thesis)

Goncalves Dos Passos, Leilane (2023-11-03): Arctic-Atlantic Climate Variability and Predictability in Observations and in a Dynamical Prediction System. PhD thesis, University of Bergen, Bergen, Norway. https://bora.uib.no/bora-xmlui/handle/11250/3099594

Summary: The major focus of this thesis is on understanding decadal climate predictability to improve climate models and their predictions. Climate predictions show promising results but are still facing challenges, especially in connecting the ocean and atmosphere. The ocean is the main source of predictability. The ocean’s capacity to store and release heat over long periods of time makes it a thermal memory of the climate system. In the Arctic-Atlantic region, ocean currents transport heat to polar areas, and along this path, the ocean releases the heat to the atmosphere through surface fluxes. From this interaction, both the ocean and the atmosphere change. On the one hand, as the ocean releases heat into the atmosphere, it cools down, increasing its density. The denser water eventually flows southward as part of the Atlantic Meridional Overturning Circulation (AMOC). On the other hand, the atmosphere being warmed by the ocean affects nearby land areas through the winds, influencing the climate variability of Western Europe.
This dynamic ocean-atmosphere interaction is a source of predictability in the Arctic-Atlantic region and is investigated here using observations and a dynamical prediction system, the Norwegian Climate Prediction Model (NorCPM). Dynamical prediction systems are useful tools for investigating and predicting climate variability on decadal timescales. Beginning their development in the early 2000s, these systems are currently the focus of significant efforts by the scientific community to provide operational decadal forecasts with reliable and accurate information. The research of this thesis is aligned with the development of NorCPM while also focusing on investigating key mechanisms that give rise to predictability in the Arctic-Atlantic region.
Climate predictions are initialized in different ways, which affects their performance. The first study of the thesis investigates the best initialization method for the Arctic-Atlantic region using NorCPM. Paper I finds that employing a more complex data assimilation method leads to the improved predictive skill of temperature and salinity in the Subpolar North Atlantic (SPNA) but not in the Norwegian Sea. The loss of skill in the Norwegian Sea is found in regions characterized by intense surface heat fluxes and eddy activity, such as the Norwegian and Lofoten Basins. The warm Atlantic water moving northwards from the SPNA to the Norwegian Sea carries thermohaline anomalies, and it is transformed from light-to-dense waters by surface forcing along the path. These two mechanisms are investigated in observation-based data in Paper II. Their relationship is analyzed, focusing on the decadal timescale in the eastern SPNA. Paper II finds that warm anomalies are associated with surface-forced water mass transformation in the light-density classes, while during cold anomalies, more transformation happens in denser classes. This relationship was disrupted during the Great Salinity Anomaly events of the 70s and 90s. Furthermore, the study highlights a faster propagation of thermohaline anomalies in the SPNA compared to the Norwegian Sea, particularly regarding temperature.
The influence of the ocean on the climate of Europe is investigated in Paper III. This study advances the understanding of how constrained ocean variability impacts the atmosphere of NorCPM. The results show a more realistic thermodynamic component of surface air temperature (SAT) over the ocean and some European regions. Paper III shows that there is potential to improve multi-annual to decadal predictions over Europe, which is currently challenging in prediction systems. The research presented in this Thesis enhances the understanding of climate predictability in the Arctic-Atlantic region. It provides insights into the interactions between the atmosphere and ocean and adds to the development of the Norwegian Climate Prediction Model, contributing to making this prediction system operational in the coming years. Following similar approaches as presented in this thesis for other dynamical prediction systems would be highly recommended.

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Forced and internal components of observed Arctic sea-ice changes

Dörr, J.S., Bonan, D.B., Årthun, M., Svendsen, L., Wills, R.C.J. 2023: Forced and internal components of observed Arctic sea-ice changes. The Cryosphere. https://doi.org/10.5194/tc-17-4133-2023

Summary: The Arctic sea-ice cover is strongly influenced by internal variability on decadal timescales, affecting both short-term trends and the timing of the first ice-free summer. Several mechanisms of variability have been proposed, but how these mechanisms manifest both spatially and temporally remains unclear. The relative contribution of internal variability to observed Arctic sea-ice changes also remains poorly quantified. Here, we use a novel technique called low-frequency component analysis to identify the dominant patterns of winter and summer decadal Arctic sea-ice variability in the satellite record. The identified patterns account for most of the observed regional sea-ice variability and trends, and they thus help to disentangle the role of forced and internal sea-ice changes over the satellite record. In particular, we identify a mode of decadal ocean–atmosphere–sea-ice variability, characterized by an anomalous atmospheric circulation over the central Arctic, that accounts for approximately 30 % of the accelerated decline in pan-Arctic summer sea-ice area between 2000 and 2012 but accounts for at most 10 % of the decline since 1979. For winter sea ice, we find that internal variability has dominated decadal trends in the Bering Sea but has contributed less to trends in the Barents and Kara seas. These results, which detail the first purely observation-based estimate of the contribution of internal variability to Arctic sea-ice trends, suggest a lower estimate of the contribution from internal variability than most model-based assessments.

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Supermodeling: improving predictions with an ensemble of interacting models

Schevenhoven , F., Keenlyside, N., Counillon, F., Carrassi, A., Chapman, W.E., Devilliers, M., Gupta, A., Koseki, S., Selten, F., Shen, M.L., Wang, S. 2023: Supermodeling: improving predictions with an ensemble of interacting models. BAMS. https://doi.org/10.1175/BAMS-D-22-0070.1

Summary: The modeling of weather and climate has been a success story. The skill of forecasts continues to improve and model biases continue to decrease. Combining the output of multiple models has further improved forecast skill and reduced biases. But are we exploiting the full capacity of state-of-the-art models in making forecasts and projections? Supermodeling is a recent step forward in the multimodel ensemble approach. Instead of combining model output after the simulations are completed, in a supermodel individual models exchange state information as they run, influencing each other’s behavior. By learning the optimal parameters that determine how models influence each other based on past observations, model errors are reduced at an early stage before they propagate into larger scales and affect other regions and variables. The models synchronize on a common solution that through learning remains closer to the observed evolution. Effectively a new dynamical system has been created, a supermodel, that optimally combines the strengths of the constituent models. The supermodel approach has the potential to rapidly improve current state-of-the-art weather forecasts and climate predictions. In this paper we introduce supermodeling, demonstrate its potential in examples of various complexity, and discuss learning strategies. We conclude with a discussion of remaining challenges for a successful application of supermodeling in the context of state-of-the-art models. The supermodeling approach is not limited to the modeling of weather and climate, but can be applied to improve the prediction capabilities of any complex system, for which a set of different models exists.

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Climate and marine-ecosystem intelligence for a green and competitive Nordic region (policy brief)

Keenlyside, N., Ogilvie A., Yang, S. Koening, T., Counilon F. 2023: Climate and marine-ecosystem intelligence for a green and competitive Nordic region. Nordic Region Fast Track to Vision 2030, NordForsk Policy Brief. https://norden.diva-portal.org/smash/get/diva2:1789341/FULLTEXT03

Summary: Operational climate and marine ecosystem services are urgently needed at the Nordic level. These services are crucial for combating the climate and marine ecosystem emergencies currently threatening the region. They are also needed to manage climate risks and to increase resilience in transport, construction, and food sectors, as well as to develop a renewable energy sector to achieve carbon neutrality. They are important for managing human activities to ensure a healthy marine ecosystem and sustainable fisheries.
We identify two priorities for developing climate and marine-ecosystem services that capitalise on world-leading Nordic research. First, fully integrated climate and marine ecosystems models need to be developed to predict changes on seasonal-to-decadal timescales. Second, services need to be co-developed with a fundamental understanding of societal needs. This requires trans-disciplinary collaboration among climate and ecosystem
researchers, computational scientists, and social scientists, with the active participation of all users.
Cooperation is needed at the Nordic level to address the common challenges that we face. Combining expertise and infrastructure will have major synergistic benefits. The shared cultural and societal values will facilitate the co-development of solutions to achieve a green and more competitive Nordic Region.

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Surface-Forced Variability in the Nordic Seas Overturning Circulation and Overflows

Årthun, M. 2023: Surface-Forced Variability in the Nordic Seas Overturning Circulation and Overflows. Geophys Res Lett. https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GL104158

Summary: Water mass transformation in the Nordic Seas and the associated overflow of dense waters across the Greenland-Scotland Ridge (GSR) acts to maintain the lower limb of the Atlantic meridional overturning circulation. Here, we use ocean and atmospheric reanalysis to assess the temporal variability in the Nordic Seas overturning circulation between 1950 and 2020 and its relation to surface buoyancy forcing. We find that variable surface-forced transformation of Atlantic waters in the eastern Nordic Seas can explain variations in overflow transport across the GSR. The production of dense water masses in the Greenland and Iceland Seas is of minor importance to overflow variability. The Nordic Seas overturning circulation shows pronounced multidecadal variability that is in phase with the Atlantic Multidecadal Variability (AMV) index, but no long-term trend. As the AMV is currently transitioning into its negative phase, the next decades could see a decreased overflow from the Nordic Seas.

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Enhancing Seasonal Forecast Skills by Optimally Weighting the Ensemble from Fresh Data

Brajard, J., Counillon, F., Wang, Y., Kimmritz, M. 2023: Enhancing Seasonal Forecast Skills by Optimally Weighting the Ensemble from Fresh Data. Weather and Forecasting. https://doi.org/10.1175/WAF-D-22-0166.1

Summary: Dynamical climate predictions are produced by assimilating observations and running ensemble simulations of Earth system models. This process is time consuming and by the time the forecast is delivered, new observations are already available, making it obsolete from the release date. Moreover, producing such predictions is computationally demanding, and their production frequency is restricted. We tested the potential of a computationally cheap weighting average technique that can continuously adjust such probabilistic forecasts—in between production intervals—using newly available data. The method estimates local positive weights computed with a Bayesian framework, favoring members closer to observations. We tested the approach with the Norwegian Climate Prediction Model (NorCPM), which assimilates monthly sea surface temperature (SST) and hydrographic profiles with the ensemble Kalman filter. By the time the NorCPM forecast is delivered operationally, a week of unused SST data are available. We demonstrate the benefit of our weighting method on retrospective hindcasts. The weighting method greatly enhanced the NorCPM hindcast skill compared to the standard equal weight approach up to a 2-month lead time (global correlation of 0.71 vs 0.55 at a 1-month lead time and 0.51 vs 0.45 at a 2-month lead time). The skill at a 1-month lead time is comparable to the accuracy of the EnKF analysis. We also show that weights determined using SST data can be used to improve the skill of other quantities, such as the sea ice extent. Our approach can provide a continuous forecast between the intermittent forecast production cycle and be extended to other independent datasets.

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Key physical processes and their model representation for projecting climate impacts on subarctic Atlantic net primary production: A synthesis

Myksvoll, M. S., Sandø, A. B., Tjiputra, J., Samuelsen, A., Çağlar Yumruktepe, V., Li, C., Mousing, E. A., Bettencourt, J.P.H., Ottersen, G. 2023: Key physical processes and their model representation for projecting climate impacts on subarctic atlantic net primary production: A synthesis. Progress in Oceanography. https://doi.org/10.1016/j.pocean.2023.103084

Summary: Oceanic net primary production forms the foundation of marine ecosystems. Understanding the impact of climate change on primary production is therefore critical and we rely on Earth System Models to project future changes. Stemming from their use of different physical dynamics and biogeochemical processes, these models yield a large spread in long-term projections of change on both the global and regional scale. Here we review the key physical processes and biogeochemical parameterizations that influence the estimation of primary production in Earth System Models and synthesize the available projections of productivity in the subarctic regions of the North Atlantic. The key processes and modelling issues we focus on are mixed layer depth dynamics, model resolution and the complexity and parameterization of biogeochemistry. From the model mean of five CMIP6 models, we found a large increase in PP in areas where the sea ice retreats throughout the 21st century. Stronger stratification and declining MLD in the Nordic Seas, caused by sea ice loss and regional freshening, reduce the vertical flux of nutrients into the photic zone. Following the synthesis of the primary production among the CMIP6 models, we recommend a number of measures: constraining model hindcasts through the assimilation of high-quality long-term observational records to improve physical and biogeochemical parameterizations in models, developing better parameterizations for the sub-grid scale processes, enhancing the model resolution, downscaling and multi-model comparison exercises for improved regional projections of primary production.

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On dynamical downscaling of ENSO-induced oceanic anomalies off Baja California Peninsula, Mexico: role of the air-sea heat flux

Rivas, D., Counillon, F., Keenlyside, N. 2023: On dynamical downscaling of ENSO-induced oceanic anomalies off Baja California Peninsula, Mexico: role of the air-sea heat flux. Front Mar Sci. https://doi.org/10.3389/fmars.2023.1179649

Summary: The El Niño Southern Oscillation (ENSO) phenomenon is responsible for important physical and biogeochemical anomalies in the Northeastern Pacific Ocean. The event of 1997-98 has been one of the most intense in the last decades and it had large implications for the waters off Baja California (BC) Peninsula with a pronounced warm sea surface temperature (SST) anomaly adjacent to the coast. Downscaling of reanalysis products was carried out using a mesoscale-resolving numerical ocean model to reproduce the regional SST anomalies. The nested model has a 9 km horizontal resolution that extend from Cabo Corrientes to Point Conception. A downscaling experiment that computes surface fluxes online with bulk formulae achieves a better representation of the event than a version with prescribed surface fluxes. The nested system improves the representation of the large scale warming and the localized SST anomaly adjacent to BC Peninsula compared to the reanalysis product. A sensitivity analysis shows that air temperature and to a lesser extent wind stress anomalies are the primary drivers of the formation of BC temperature anomaly. The warm air-temperature anomalies advect from the near-equatorial regions and the central north Pacific and is associated with sea-level pressure anomalies in the synoptic-scale atmospheric circulation. This regional warm pool has a pronounced signature on sea level anomaly in agreement with observations, which may have implications for biogeochemistry.

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Pacific oceanic front amplifies the impact of Atlantic oceanic front on North Atlantic blocking

Cheung, HN., Omrani, NE., Ogawa, F., Keenlyside, N., Nakamura, H., Zhou, W. 2023: Pacific oceanic front amplifies the impact of Atlantic oceanic front on North Atlantic blocking. npj Clim Atmos Sci 6, 61. https://doi.org/10.1038/s41612-023-00370-x

Summary: Atmospheric blocking is a crucial driver of extreme weather events, but its climatological frequency is largely underestimated in state-of-the-art climate models, especially around the North Atlantic. While air-sea interaction along the North Atlantic oceanic frontal region is known to influence Atlantic blocking activity, remote effects from the Pacific have been less studied. Here we use semi-idealised experiments with an atmospheric general circulation model to demonstrate that the mid-latitude Pacific oceanic front is crucial for climatological Atlantic blocking activity. The front intensifies the Pacific eddy-driven jet that extends eastward towards the North Atlantic. The eastward-extended Pacific jet reinforces the North Atlantic circulation response to the Atlantic oceanic front, including the storm track activity and the eddy-driven jet. The strengthening of the eddy-driven jet reduces the Greenland blocking frequency. Moreover, the Pacific oceanic front greatly strengthens the stationary planetary-scale ridge in Europe. Together with a stronger northeastward extension of the Atlantic storm track, enhanced interaction between extratropical cyclones and the European ridge favours the occurrence of Euro-Atlantic blocking. Therefore, the North Atlantic circulation response amplified remotely by the Pacific oceanic front substantially increases Euro-Atlantic blocking frequency while decreasing Greenland blocking frequency.

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Trends and internal variability in Brazilian hydropower catchments (Master’s thesis)

Byermoen, Emilie. 2023: Trends and internal variability in Brazilian hydropower catchments. Master’s thesis, University of Bergen, Norway. https://bora.uib.no/bora-xmlui/handle/11250/3071878

Summary: Hydropower is a major energy source in Brazil, and long-term hydropower production planning is crucial both for maintaining energy and water security in the country. The amount of water that is available to electricity production in the reservoirs have changed in the recent years, and there is an urgent need to understand the cause(s) of these changes, and whether observed stream flow trends will persist, reverse or amplify in the future. In this thesis, I therefore separate externally forced precipitation and evaporation trends and variability from internal variations originating in the ocean for three hydrographic catchments in Brazil: Óbidos catchment in Amazon, Propria catchment in São Francisco and Porto Murtinho catchment in Paraguay. I compare an ocean anomaly assimilation experiment of Norwegian Climate Prediction Model (NorCPM) to an externally forced historical experiment and observed stream flow, precipitation and evaporation in the catchments. The results indicate that the multi-decadal increasing stream flow trend in Amazon is (partly) externally forced, and might therefore persist, but that the SON stream flow is tightly connected to JJA precipitation variation which is shown to be driven by ocean variation, and may therefore reverse in the future. The long-term decrease of precipitation in São francisco is likely to be caused by internal variability, and is therefore likely to (partly) restore in the future, but results indicate that decadal stream flow variations in the basin is substantially impacted by other factors than precipitation as well. São Francisco catchment is found to be strongly connected to DJF precipitation variations that the model is unable to replicate. In Paraguay, I find that the austral summer stream flow is tightly connected to inter-annual precipitation variability that originates in the ocean in austral winter and spring. The steep significant decrease in stream flow over the last decades in Paraguay catchment is likely to have additional causes than precipitation, according to the results. All the results have implications for hydropower and water management planning in the three catchments in Brazil.

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