Tag: keenlyside

WMO Global Annual to Decadal Climate Update: A Prediction for 2021–25

Hermanson, L., Smith, D., Seabrook, M., Bilbao, R., Doblas-Reyes, F., Tourigny, E., Lapin, V., Kharin, V.V., Merryfield, W.J., Sospedra-Alfonso, R., Athanasiadis, P., Nicoli, D., Gualdi, S., Dunstone, N., Eade, R., Scaife, A., Collier, M., O’Kane, T., Kitsios, V., Sandery, P., Pankatz, K., Früh, B., Pohlmann, H., Müller, W., Kataoka, T., Tatebe, H., Ishii M., Imada, Y., Kruschke, T., Koenigk, T., Pasha Karami, M., Yang, S., Tian, T., Zhang, L., Delworth, T., Yang, X., Zeng, F., Wang, Y., Counillon, F., Keenlyside, N.S., Bethke, I., Lean, J., Luterbacher, J., Kumar Kolli, R., Kumar, A. 2022: WMO Global Annual to Decadal Climate Update: A Prediction for 2021–25. BAMS https://doi.org/10.1175/BAMS-D-20-0311.1 .

Summary: As climate change accelerates, societies and climate-sensitive socioeconomic sectors cannot continue to rely on the past as a guide to possible future climate hazards. Operational decadal predictions offer the potential to inform current adaptation and increase resilience by filling the important gap between seasonal forecasts and climate projections. The World Meteorological Organization (WMO) has recognized this and in 2017 established the WMO Lead Centre for Annual to Decadal Climate Predictions (shortened to “Lead Centre” below), which annually provides a large multimodel ensemble of predictions covering the next 5 years. This international collaboration produces a prediction that is more skillful and useful than any single center can achieve. One of the main outputs of the Lead Centre is the Global Annual to Decadal Climate Update (GADCU), a consensus forecast based on these predictions. This update includes maps showing key variables, discussion on forecast skill, and predictions of climate indices such as the global mean near-surface temperature and Atlantic multidecadal variability. it also estimates the probability of the global mean temperature exceeding 1.5°C above preindustrial levels for at least 1 year in the next 5 years, which helps policy-makers understand how closely the world is approaching this goal of the Paris Agreement. This paper, written by the authors of the GADCU, introduces the GADCU, presents its key outputs, and briefly discusses its role in providing vital climate information for society now and in the future..

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Propagation of Thermohaline Anomalies and Their Predictive Potential along the Atlantic Water Pathway

Langehaug, H. R., Ortega, P., Counillon, F., Matei, D., Maroon, E., Keenlyside, N., Mignot, J., Wang, Y., Swingedouw, D., Bethke, I., Yang, S., Danabasoglu, G., Bellucci, A., Ruggieri, P., Nicolì, D., Årthun, M. 2022: Propagation of Thermohaline Anomalies and Their Predictive Potential along the Atlantic Water Pathway. J Clim. https://doi.org/10.1007/s10236-022-01523-x

Summary: In this study, we find that dynamical prediction systems and their respective climate models struggle to realistically represent ocean surface temperature variability in the eastern subpolar North Atlantic and Nordic seas on interannual-to-decadal time scales. In previous studies, ocean advection is proposed as a key mechanism in propagating temperature anomalies along the Atlantic water pathway toward the Arctic Ocean. Our analysis suggests that the predicted temperature anomalies are not properly circulated to the north; this is a result of model errors that seems to be exacerbated by the effect of initialization shocks and forecast drift. Better climate predictions in the study region will thus require improving the initialization step, as well as enhancing process representation in the climate models.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Assessing the influence of sea surface temperature and arctic sea ice cover on the uncertainty in the boreal winter future climate projections

Cheung, HN., Keenlyside, N., Koenigk, T., Yang, S., Tian, T., Xu, Z., Gao, Y., Ogawa, F., Omrani, N.-E., Qiao, S., Zhou, W. 2022: Assessing the influence of sea surface temperature and arctic sea ice cover on the uncertainty in the boreal winter future climate projections. Clim. Dyn. https://doi.org/10.1007/s00382-022-06136-0

Summary: We investigate the uncertainty (i.e., inter-model spread) in future projections of the boreal winter climate, based on the forced response of ten models from the CMIP5 following the RCP8.5 scenario. The uncertainty in the forced response of sea level pressure (SLP) is large in the North Pacific, the North Atlantic, and the Arctic. A major part of these uncertainties (31%) is marked by a pattern with a center in the northeastern Pacific and a dipole over the northeastern Atlantic that we label as the Pacific–Atlantic SLP uncertainty pattern (PA∆SLP). The PA∆SLP is associated with distinct global sea surface temperature (SST) and Arctic sea ice cover (SIC) perturbation patterns. To better understand the nature of the PA∆SLP, these SST and SIC perturbation patterns are prescribed in experiments with two atmospheric models (AGCMs): CAM4 and IFS. The AGCM responses suggest that the SST uncertainty contributes to the North Pacific SLP uncertainty in CMIP5 models, through tropical–midlatitude interactions and a forced Rossby wavetrain. The North Atlantic SLP uncertainty in CMIP5 models is better explained by the combined effect of SST and SIC uncertainties, partly related to a Rossby wavetrain from the Pacific and air-sea interaction over the North Atlantic. Major discrepancies between the CMIP5 and AGCM forced responses over northern high-latitudes and continental regions are indicative of uncertainties arising from the AGCMs. We analyze the possible dynamic mechanisms of these responses, and discuss the limitations of this work.

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NorCPM1 and its contribution to CMIP6 DCPP

Bethke, I., Wang, Y., Counillon, F., Keenlyside, N., Kimmritz, M., Fransner, F., Samuelsen, A., Langehaug, H., Svendsen, L., Chiu, P.-G., Passos, L., Bentsen, M., Guo, C., Gupta, A., Tjiputra, J., Kirkevåg, A., Olivié, D., Seland, Ø., Solsvik Vågane, J., Fan, Y., Eldevik, T. 2021: NorCPM1 and its contribution to CMIP6 DCPP. Geosci Model Dev. https://doi.org/10.5194/gmd-14-7073-2021 .

For an easy-to-understand overview, we recommend starting with this neat article written by the Climate Futures team, a project connected to BCPU: “New Study: Decadal Climate Forecasts From The Norwegian Climate Prediction Model” (les heller på norsk).

Summary: The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It combines the Norwegian Earth System Model version 1 (NorESM1) – which features interactive aerosol–cloud schemes and an isopycnic-coordinate ocean component with biogeochemistry – with anomaly assimilation of sea surface temperature (SST) and -profile observations using the ensemble Kalman filter (EnKF).

We describe the Earth system component and the data assimilation (DA) scheme, highlighting implementation of new forcings, bug fixes, retuning and DA innovations. Notably, NorCPM1 uses two anomaly assimilation variants to assess the impact of sea ice initialization and climatological reference period: the first (i1) uses a 1980–2010 reference climatology for computing anomalies and the DA only updates the physical ocean state; the second (i2) uses a 1950–2010 reference climatology and additionally updates the sea ice state via strongly coupled DA of ocean observations.

We assess the baseline, reanalysis and prediction performance with output contributed to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). The NorESM1 simulations exhibit a moderate historical global surface temperature evolution and tropical climate variability characteristics that compare favourably with observations. The climate biases of NorESM1 using CMIP6 external forcings are comparable to, or slightly larger than those of, the original NorESM1 CMIP5 model, with positive biases in Atlantic meridional overturning circulation (AMOC) strength and Arctic sea ice thickness, too-cold subtropical oceans and northern continents, and a too-warm North Atlantic and Southern Ocean. The biases in the assimilation experiments are mostly unchanged, except for a reduced sea ice thickness bias in i2 caused by the assimilation update of sea ice, generally confirming that the anomaly assimilation synchronizes variability without changing the climatology. The i1 and i2 reanalysis/hindcast products overall show comparable performance. The benefits of DA-assisted initialization are seen globally in the first year of the prediction over a range of variables, also in the atmosphere and over land. External forcings are the primary source of multiyear skills, while added benefit from initialization is demonstrated for the subpolar North Atlantic (SPNA) and its extension to the Arctic, and also for temperature over land if the forced signal is removed. Both products show limited success in constraining and predicting unforced surface ocean biogeochemistry variability. However, observational uncertainties and short temporal coverage make biogeochemistry evaluation uncertain, and potential predictability is found to be high. For physical climate prediction, i2 performs marginally better than i1 for a range of variables, especially in the SPNA and in the vicinity of sea ice, with notably improved sea level variability of the Southern Ocean. Despite similar skills, i1 and i2 feature very different drift behaviours, mainly due to their use of different climatologies in DA; i2 exhibits an anomalously strong AMOC that leads to forecast drift with unrealistic warming in the SPNA, whereas i1 exhibits a weaker AMOC that leads to unrealistic cooling. In polar regions, the reduction in climatological ice thickness in i2 causes additional forecast drift as the ice grows back. Posteriori lead-dependent drift correction removes most hindcast differences; applications should therefore benefit from combining the two products.

The results confirm that the large-scale ocean circulation exerts strong control on North Atlantic temperature variability, implying predictive potential from better synchronization of circulation variability. Future development will therefore focus on improving the representation of mean state and variability of AMOC and its initialization, in addition to upgrades of the atmospheric component. Other efforts will be directed to refining the anomaly assimilation scheme – to better separate internal and forced signals, to include land and atmosphere initialization and new observational types – and improving biogeochemistry prediction capability. Combined with other systems, NorCPM1 may already contribute to skilful multiyear climate prediction that benefits society.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Twenty-one years of phytoplankton bloom phenology in the Barents, Norwegian and North seas

Silva, E.F.F., Counillon, F., Brajard, J., Korosov, A., Pettersson, L., Samuelsen, A., Keenlyside, N. 2021: Twenty-one years of phytoplankton bloom phenology in the Barents, Norwegian and North seas. Front Mar Sci.  https://doi.org/10.3389/fmars.2021.746327 .

For en flott oppsummering på norsk, les denne artikkelen av vår samarbeidspartner, Climate Futures.

Summary: Phytoplankton blooms provide biomass to the marine trophic web, contribute to the carbon removal from the atmosphere and can be deadly when associated with harmful species. This points to the need to understand the phenology of the blooms in the Barents, Norwegian, and North seas. We use satellite chlorophyll-a from 2000 to 2020 to assess robust climatological and the interannual trends of spring and summer blooms onset, peak day, duration and intensity. Further, we also correlate the interannual variability of the blooms with mixed layer depth (MLD), sea surface temperature (SST), wind speed and suspended particulate matter (SPM) retrieved from models and remote sensing. The climatological spring blooms start on March 10th and end on June 19th. The climatological summer blooms begin on July 13th and end on September 17th. In the Barents Sea, years of shallower mixed layer (ML) driven by both calm waters and higher freshwaters input keeps the phytoplankton in the euphotic zone, causing the spring bloom to start earlier and reach higher biomass but end sooner due to the lack of nutrients upwelling from the deep. In the Norwegian Sea, a correlation between SST and the spring blooms is found. Here, warmer waters are correlated to earlier and stronger blooms in most regions but with later and weaker blooms in the eastern Norwegian Sea. In the North Sea, years of shallower ML reduces the phytoplankton sinking below the euphotic zone and limits the SPM increase from the bed shear stress, creating an ideal environment of stratified and clear waters to develop stronger spring blooms. Last, the summer blooms onset, peak day and duration have been rapidly delaying at a rate of 1.25-day year–1, but with inconclusive causes based on the parameters assessed in this study.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

Professor Noel Keenlyside speaks at COP26 side event

Ocean connections from the Arctic across the globe. With Prof. Noel Keenlyside, University of Bergen and the Bjerknes Centre. 04:00 PM – 05:00 PM GMT (17.00-18.00 UTC+1)

This workshop will explore the importance of the ocean in the global and north west European climate, the need to ensure we are measuring the strength of ocean currents and the ocean’s properties, and how this information can be incorporated into climate models, climate services and decision-making at national and international levels.

 

Speakers:

  • Bee Berx (Scottish Government)
  • Mark Payne (Danish Meteorological Institute)
  • Jacob Høyer (Danish Meteorological Institute, GHRSST Group for High Resolution Sea Surface Temperature)
  • Noel Keenlyside (Bjerknes Centre for Climate Research, University of Bergen)
  • Marit Reigstad (UiT the Arctic University of Norway)
  • Siân Henley (University of Edinburgh)
  • Finlo Cottier (Scottish Association for Marine Science)

Organizer: Scottish Government with the Danish Meteorological Institute, Bjerknes Centre for Climate Research, UiT the Arctic University of Norway, University of Edinburgh, Scottish Association for Marine Science

Online access to all events

No accreditation to COP26? Don’t worry. All events will be streamed by our media partner, We Don’t Have Time. Follow this event live on their COP26 streaming hub:

We Don’t Have Time – A Virtual Backdoor To COP26

Understanding the dynamics of recent Norwegian extreme weather events and their influence on energy production (Master’s thesis)

Pecnjak, Martin (2021-08-05). Understanding the dynamics of recent Norwegian extreme weather events and their influence on energy production (Master’s thesis, University of Bergen, Bergen, Norway). https://bora.uib.no/bora-xmlui/handle/11250/2778409 .

Summary: The growing frequency and severity of extreme weather events in the Northern Hemisphere has prompted a lot of research being done on their origin and physical mechanisms. Both simplified and complex approaches have been introduced in defining and understanding these events, where they look into high-amplitude quasi-stationary Rossby waves and their quasi-resonant amplification. However, different approaches exist to investigating extreme events and these were just a motivation for this thesis. Since the resonance method is suit- able mostly for summer events and the events discussed in this thesis have happened in all seasons, a different approach was needed. The events in question were a winter drought, two summer and autumn floods, a winter snowfall and a spring/summer heatwave in the areas of south and southwestern Norway. In order to detect certain features which would help solve this issue, we look into anomalies of different meteorological variables such as geopoten- tial height, surface temperature, precipitation and snowfall rate and zonal and meridional winds. Deep and thorough statistical and dynamical analyses are applied to define the out- comes and the physical origins which would help us obtain a clear picture on the whole case. The finite-amplitude local wave activity (LWA) diagnostic, as a measure of the meandering of the jet stream, has helped to give a clear picture along with the large-scale circulation. This method can be used as a proxy for the strength of the eddy-driven jet and the storm track. It has proven to be the key factor in defining what has exactly caused the events in ques- tion. The results and findings have shown that the LWA is a conclusive tool in determining whether an extreme event was related to a blocking pattern or not, while the LWA budget equation components have shed light on the so far poorly understood dynamical aspects which led to the events. The zonal LWA flux has proven to be a good predictor of blocking with its onset in the early stages of the events, similar to the traffic jam concept introduced by (Nakamura and Huang, 2018). The jet stream has a capacity for the LWA flux similar to how a highway has a capacity for the number of vehicles on it. If the capacity is exceeded, blocking occurs, and this is readily shown in the results and findings of this work. As for the budget equation components, the zonal LWA flux convergence has proven to be the key in maintaining the increase of the LWA as well as also having an early onset in each blocking event in agreement with the LWA flux. On the other hand, the residual in the LWA budget, which represents the non-conservative small-scale processes (diabatic sources and sinks of LWA), dampens the LWA. The LWA method has also proven to be useful in all seasons. The motivation for the thesis also came from the influence of the events on the meteorological variables related to the Norwegian energy production. The results show us clues into possible ways of improving forecasting of such events and minimizing their harmful impacts. They also show possibilities in improving energy management, infrastructure, allocation of resources and preparedness of the society for damages and hazards caused by the events. This was not fully investigated in this thesis and is the next step in the research of this topic.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.

New EASAC report: “A Sea of Change”

Translated from the Norwegian press release at the Bjerknes Centre for Climate Research

Tor Eldevik leads EASAC report, “A sea of change: Europe’s future in the Atlantic realm”.

In the report an international panel of experts goes through the changes seen until now in the Atlantic Ocean, and what we can expect of climate change. But there is also a potential in being the closest neighbour to our western ocean.

The report is published by EASAC, the European science academy advisory council. The panel of experts is led by Tor Eldevik, Professor at the University of Bergen and the Bjerknes Centre for Climate Research, and Deputy Leader in the BCPU.

A potential in climate prediction

The report shows how fluctuations and trends in the Atlantic Ocean affects the climate in Europe and both the environment and resources in the ocean and on land.

“The report is very clear about future climatic risks, but equally focuses on the future benefits we can harvest from better understanding of the relations between the state of the Atlantic and climatic conditions over Europe that affects everything from the supply of renewable energy to fisheries,” says Tor Eldevik.

He emphasises how this knowledge can be used far better than it is now. Climate predictions developed today have the potential to predict cod movements between years, including movements out of Norwegian fisheries sectors.

To power companies the knowledge of how westerlies in the Atlantic Ocean (NAO index) affect Norwegian hydro power production can also be useful.

Figurtekst: Norsk vasskraftproduksjon svinger saman med vestavindsbeltet i Atlanterhavet, slik tidlegare vist av Helene Asbjørnsen og Noel Keenlyside UiB og Bjerknessenteret. Vasskraftdata frå SSB, styrke på vestavind vinterstid (NAO-indeks) frå climatedataguide.ucar.edu
Figure 4.1 Norwegian hydropower production swings with the westerly winds (wintertime NAO; variance explained 40%). (Source: H. Asbjørnsen and N. Keenlyside, University of Bergen / Bjerknes Climate Prediction Unit; power production and NAO data from https://www.ssb.no/en/statbank/table/08307 and https://climatedataguide.ucar.edu/climate-data/hurrell-north-atlanticoscillation-nao-index-station-based, respectively.)

Climate risk

Tor Eldevik points out how future changes in the ocean are connected to how successful we are at mitigating global warming.

“If we succeed in keeping the average warming to 1.5°C, then Antarctica may continue melting at current rates; but overshooting the 2 °C Paris Agreement target towards 3°C may lead to Antarctic melt alone add 0.5 cm a year by 2100,” he says.

Sea level rise have regional differences, but to the many million people living by the North Sea Basin, accounting for a meter rise in sea level.

Cities along the coast of the Netherlands, Germany, Denmark and Great Britain will be affected greatly.

Figure 2.5 The North Sea coastline with +1 m of global SLR with the flooded areas in blue. Major population centres are marked in circles. (Source: https://sealevel.climatecentral.org/maps/.)
Figure 2.5 The North Sea coastline with +1 m of global SLR with the flooded areas in blue. Major population centres are marked in circles. (Source: https://sealevel.climatecentral.org/maps/.)

Central points in the report

  • Sea level rise
    On average, the sea level has risen 11-16 centimeters in the twentieth century.
    Europe must prepare for up to one meter sea level rise by 2100. Storm surges on a level we now expect every 100 years, could be yearly by 2100 if CO2 emissions continues as today. Ice melts on Greenland and the Antarctic contributes to sea level rise, as well as glacial metling in warmer areas and sea water expanding with heat. There is uncertainty linked to melting on Greenland and the Antarctic which needs to be followed closely.
  • Renewable energy
    Wind, weather and precipitation over Europe, and especially the Norwegian coast, kan be linked to the ocean. The strength of the Gulf Stream and the westerlies over the Atlantic Ocean affects the severity of wind and precipication over Europe, including the Norwegian coast. This knowledge is critical to predict climate fluctuations for the coming years and seasons – which in Norway is especially useful to power companies, both wind and hydro energy production.
  • Ocean acidification
    Temperature increases leads to fish stocks moving, uptake of CO2 makes the ocean more acidic, which changes the living conditions for life in the ocean. If the current emissions of climate gases is kept up, we will reach a level in 2100 that is uninhabitable.
  • Ocean circulation, ocean streams and the Gulf Stream giving us a milder climate
    Speculations that the Gulf Stream will stop are excessive. But the Gulf Stream strength are connected to climate in Europe and Norway. A decline in heat transportation of 20% is expected further South in the Atlantic this century, but as far North as Norway we are likely to see an increase in the stream and a continued heating of the ocean.

Read the report with EASAC

 

 

The Future Atlantic Ocean: Forecasting ecosystem functioning from microbiomes to fisheries

Side event at the All Atlantic Conference 2021, where climate forecasting on a broad level was discussed. BCPU has contributing members in the EU Horizon 2020 projects TRIATLAS and Blue Action, who were organising the event with projects AtlantECO and Mission Atlantic.

Watch the presentations and following discussion on Youtube:

Training of supermodels in the context of weather and climate forecasting (PhD thesis)

Schevenhoven, Francine (2021-02-08). Training of supermodels in the context of weather and climate forecasting (PhD thesis, University of Bergen, Bergen, Norway). https://bora.uib.no/bora-xmlui/handle/11250/2727454 .

Summary: Given a set of imperfect weather or climate models, predictions can be improved by combining the models dynamically into a so called `supermodel’. The models are optimally combined to compensate their individual errors. This is different from the standard multi-model ensemble approach (MME), where the model output is statistically combined after the simulations. Instead, the supermodel can create a trajectory closer to observations than any of the imperfect models. By intervening during the forecast, errors can be reduced at an early stage and the ensemble can exhibit different dynamical behavior than any of the individual models. In this way, common errors between the models can be removed and new, physically correct behavior can appear.
In our simplified context of models sharing the same evolution function and phase space, we can define either a connected or a weighted supermodel. A connected supermodel uses nudging to bring the models closer together, while in a weighted supermodel all model states are replaced at regular time intervals (i.e., restarted) by the weighted average of the individual model states. To obtain optimal connection coefficients or weights, we need to train the supermodel on the basis of historical observations. A standard training approach such as minimization of a cost function requires many model simulations, which is computationally very expensive. This thesis has focused on developing two new methods to efficiently train supermodels. The first method is based on an idea called cross pollination in time, where models exchange states during the training. The second method is a synchronization-based learning rule, originally developed for parameter estimation.
The techniques are developed on low-order systems, such as Lorenz63, and later applied to different versions of the intermediate-complexity global coupled atmosphere-ocean-land model SPEEDO. Here the observations are from the same models, but with different parameters. The applicability of the method to real observations is tested using sensitivity to noisy and incomplete data. The characteristics the individual models should have in order to be combined together into a supermodel are identified, as well as which physical variables should be connected in a supermodel, and which ones should not. Both training methods result in supermodels that outperform both the individual models and the MME, for short term predictions as well as long term simulations. Furthermore, we show that the novel use of negative weights can improve predictions in cases where model errors do not cancel (for instance, all models are too warm with respect to the truth). A crucial advantage of the proposed training schemes is that in the present context relatively short training periods suffice to find good solutions. Although the validity of our conclusions in the context of real observations and model scenarios has yet to be proved, our results are very encouraging. In principle, the methods are suitable to train supermodels constructed using state-of-the art weather and climate models.

Link to publication. You are most welcome to contact us or the corresponding author(s) directly, if you have questions.