Thermohaline patterns of intrinsic Atlantic Multidecadal Variability

Zanchettin, D., Fang, S.-W., Khodri, M., Omrani, N.-E., Rubinetti, S., Rubino, A., Timmreck, C., Jungclaus, J.-H. 2023: Thermohaline patterns of intrinsic Atlantic Multidecadal Variability. Clim Dyn. https://link.springer.com/article/10.1007/s00382-023-06679-w

Summary: A vivid scientific debate exists on the nature of the Atlantic Multidecadal Variability (AMV) as an intrinsic rather than predominantly forced climatic phenomenon, and on the role of ocean circulation. Here, we use a multi-millennial unperturbed control simulation and a Holocene simulation with slow-varying greenhouse gas and orbital forcing performed with the low-resolution version of the Max Planck Institute Earth System Model to illustrate thermohaline conditions associated with twelve events of strong AMV that are comparable, in the surface anomalies, to observations in their amplitudes (~ 0.3 °C) and periods (~ 80 years). The events are associated with recurrent yet spatially diverse same-sign anomalous sea-surface temperature and salinity fields that are substantially symmetric in the warm-to-cold and following cold-to-warm transitions and only partly superpose with the long-term spatial AMV pattern. Subpolar cold-fresh anomalies develop in the deep layers during the peak cold phase of strong AMV events, often in association with subtropical warm-salty anomalies yielding a meridional dipole pattern. The Atlantic meridional overturning circulation (AMOC) robustly weakens during the warm-to-cold transition of a strong AMV event and recovers thereafter, with surface salinity anomalies being potential precursors of such overturning changes. A Holocene simulation with the same model including volcanic forcing can disrupt the intrinsic AMV–AMOC connection as post-eruption periods often feature an AMOC strengthening forced by the volcanically induced surface cooling. Overall, our results support the AMV as a potential intrinsic feature of climate, whose episodic strong anomalous events can display different shades of spatial patterns and timings for the warm-to-cold and subsequent cold-to-warm transitions. Attribution of historical AMV fluctuations thus requires full consideration of the associated surface and subsurface thermohaline conditions and assessing the AMOC–AMV relation.

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Latitudinally distinct stocks of Atlantic cod face fundamentally different biophysical challenges under on-going climate change

Kjesbu, O.S., Alix, M., Sandø, A.B., Strand, E., Wright, P.J., Johns, D.G., Thorsen, A., Marshall, C.T., Bakkeplass, K.G., Vikebø, F.B., Myksvoll, M.S., Ottersen, G., Allan, B.J.M., Fossheim, M., Stiansen, J.E., Huse, G., Sundby, S. 2023: Latitudinally distinct stocks of Atlantic cod face fundamentally different biophysical challenges under on-going climate change. Fish and Fisheries. https://doi.org/10.1111/faf.12728

Summary: Observed and future winter Arctic sea ice loss is strongest in the Barents Sea. However, the anthropogenic signal of the sea ice decline is superimposed by pronounced internal variability that represents a large source of uncertainty in future climate projections. A notable manifestation of internal variability is rapid ice change events (RICEs) that greatly exceed the anthropogenic trend. These RICEs are associated with large displacements of the sea ice edge which could potentially have both local and remote impacts on the climate system. In this study we present the first investigation of the frequency and drivers of RICEs in the future Barents Sea, using multi-member ensemble simulations from CMIP5 and CMIP6. A majority of RICEs are triggered by trends in ocean heat transport or surface heat fluxes. Ice loss events are associated with increasing trends in ocean heat transport and decreasing trends in surface heat loss. RICEs are a common feature of the future Barents Sea until the region becomes close to ice-free. As their evolution over time is closely tied to the average sea ice conditions, rapid ice changes in the Barents Sea may serve as a precursor for future changes in adjacent seas.

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Riverine impact on future projections of marine primary production and carbon uptake

Gao, S., Schwinger, J., Tjiputra, J., Bethke, I., Hartmann, J., Mayorga, E., Heinze, C. 2023: Riverine impact on future projections of marine primary production and carbon uptake. Biogeosciences. https://doi.org/10.5194/bg-20-93-2023

Summary: Riverine transport of nutrients and carbon from inland waters to the coastal and finally the open ocean alters marine primary production (PP) and carbon (C) uptake regionally and globally. So far, this process has not been fully represented and evaluated in the state-of-the-art Earth system models. Here we assess changes in marine PP and C uptake projected under the Representative Concentration Pathway 4.5 climate scenario using the Norwegian Earth system model, with four riverine transport configurations for nutrients (nitrogen, phosphorus, silicon, and iron), carbon, and total alkalinity: deactivated, fixed at a recent-past level, coupled to simulated freshwater runoff, and following four plausible future scenarios. The inclusion of riverine nutrients and carbon at the 1970 level improves the simulated contemporary spatial distribution of annual mean PP and air–sea CO2 fluxes relative to observations, especially on the continental margins (5.4 % reduction in root mean square error (RMSE) for PP) and in the North Atlantic region (7.4 % reduction in RMSE for C uptake). While the riverine nutrients and C input is kept constant, its impact on projected PP and C uptake is expressed differently in the future period from the historical period. Riverine nutrient inputs lessen nutrient limitation under future warmer conditions as stratification increases and thus lessen the projected decline in PP by up to 0.66 ± 0.02 Pg C yr−1 (29.5 %) globally, when comparing the 1950–1999 with the 2050–2099 period. The riverine impact on projected C uptake depends on the balance between the net effect of riverine-nutrient-induced C uptake and riverine-C-induced CO2 outgassing. In the two idealized riverine configurations the riverine inputs result in a weak net C sink of 0.03–0.04 ± 0.01 Pg C yr−1, while in the more plausible riverine configurations the riverine inputs cause a net C source of 0.11 ± 0.03 Pg C yr−1. It implies that the effect of increased riverine C may be larger than the effect of nutrient inputs in the future on the projections of ocean C uptake, while in the historical period increased nutrient inputs are considered the largest driver. The results are subject to model limitations related to resolution and process representations that potentially cause underestimation of impacts. High-resolution global or regional models with an adequate representation of physical and biogeochemical shelf processes should be used to assess the impact of future riverine scenarios more accurately.

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Benefit of vertical localization for sea surface temperature assimilation in isopycnal coordinate model

Wang, Y., Counillon, F., Barthélémy, S., Barth, A. 2022: Benefit of vertical localization for sea surface temperature assimilation in isopycnal coordinate model. Front Clim. https://doi.org/10.3389/fclim.2022.918572

Summary: Sea surface temperature (SST) observations are a critical data set for long-term climate reconstruction. However, their assimilation with an ensemble-based data assimilation method can degrade performance in the ocean interior due to spurious covariances. Assimilation in isopycnal coordinates can delay the degradation, but it remains problematic for long reanalysis. We introduce vertical localization for SST assimilation in the isopycnal coordinate. The tapering functions are formulated empirically from a large pre-industrial ensemble. We propose three schemes: 1) a step function with a small localization radius that updates layers from the surface down to the first layer for which insignificant correlation with SST is found, 2) a step function with a large localization radius that updates layers down to the last layer for which significant correlation with SST is found, and 3) a flattop smooth tapering function. These tapering functions vary spatially and with the calendar month and are applied to isopycnal temperature and salinity. The impact of vertical localization on reanalysis performance is tested in identical twin experiments within the Norwegian Climate Prediction Model (NorCPM) with SST assimilation over the period 1980–2010. The SST assimilation without vertical localization greatly enhances performance in the whole water column but introduces a weak degradation at intermediate depths (e.g., 2,000–4,000 m). Vertical localization greatly reduces the degradation and improves the overall accuracy of the reanalysis, in particular in the North Pacific and the North Atlantic. A weak degradation remains in some regions below 2,000 m in the Southern Ocean. Among the three schemes, scheme 2) outperforms schemes 1) and 3) for temperature and salinity.

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Multidisciplinary perspectives on living marine resources in the Arctic

Kvamsdal, S.F., Dankel, D., Ekerhovd, N.-A., Hoel, A.H., Renner, A., Sandø, A.B., Steinshamn, S.I. 2022: Multidisciplinary perspectives on living marine resources in the Arctic. Polar Research. https://doi.org/10.33265/polar.v41.7766

Summary: Many areas in the Arctic are vulnerable to the impacts of climate change. We observe large-scale effects on physical, biological, economic and social parameters, including ice cover, species distributions, economic activity and regional governance frameworks. Arctic living marine resources are affected in various ways. A holistic understanding of these effects requires a multidisciplinary enterprise. We synthesize relevant research, from oceanography and ecology, via economics, to political science and international law. We find that multidisciplinary research can enhance our understanding and promote new questions and issues relating to impacts and outcomes of climate change in the Arctic. Such issues include recent insights on changing spawning migrations of the North-east Arctic cod stock that necessitates revisions of socioeconomic estimates of ecosystem wealth in the Barents Sea, better integrated prediction systems that require increased cooperation between experts on climate prediction and ecosystem modelling, and institutional complexities of Arctic governance that require enhanced coordination.

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Upcoming workshop: External versus internal variability on decadal and longer time scales

On Wednesday 14th September, the CLIVAR Climate Dynamics Panel (CDP) will launch the first of an intended series of annual CDP workshops. This year’s workshop will target our understanding of internal and externally forced variability in the climate system, their interaction on decadal timescales and longer, and the effects of variability on extreme events. To foster discussion that will stimulate focused research on this important topic, the workshop aims to tackle the following overarching questions:

  • How to isolate the relative contributions of external and internal variability to observed decadal and longer variability?
  • How do the various external forcings modulate internal variability?
  • How to progress in narrowing observational and modeling uncertainties in external and internal variability?
  • What are the effects of external and internal variability on extreme events?

The workshop will be online, and consist of six, weekly 2-hour sessions, from September 14th to October 19th, 2022. The sessions will be on Wednesdays with the timings varying to accommodate participation from different time zones.

Workshop program and further event information: https://www.clivar.org/events/clivar-climate-dynamics-panel-cdp-annual-workshop-external-versus-internal-variability

 

Weakening of the Atlantic Niño variability under global warming

Crespo, L.R., Prigent, A., Keenlyside, N., Koseki, S., Svendsen, L., Richter, I., Sánchez-Gómez, E. 2022: Weakening of the Atlantic Niño variability under global warming. Nat. Clim. Chang. https://doi.org/10.1038/s41558-022-01453-y

Summary: The Atlantic Niño is one of the most important patterns of interannual tropical climate variability, but how climate change will influence this pattern is not well known due to large climate model biases. Here we show that state-of-the-art climate models robustly predict a weakening of Atlantic Niños in response to global warming, mainly due to a decoupling of subsurface and surface temperature variations as the upper equatorial Atlantic Ocean warms. This weakening is predicted by most (>80%) models in the Coupled Model Intercomparison Project Phases 5 and 6 under the highest emission scenarios. Our results indicate a reduction in variability by the end of the century by 14%, and as much as 24–48% when accounting for model errors using a simple emergent constraint analysis. Such a weakening of Atlantic Niño variability will potentially impact climate conditions and the skill of seasonal predictions in many regions.

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Super-resolution data assimilation

Barthélémy, S., Brajard, J., Bertino, L., Counillon, F. 2022: Super-resolution data assimilation. Ocean Dyn. https://doi.org/10.1007/s10236-022-01523-x

Summary: Increasing model resolution can improve the performance of a data assimilation system because it reduces model error, the system can more optimally use high-resolution observations, and with an ensemble data assimilation method the forecast error covariances are improved. However, increasing the resolution scales with a cubical increase of the computational costs. A method that can more effectively improve performance is introduced here. The novel approach called “Super-resolution data assimilation” (SRDA) is inspired from super-resolution image processing techniques and brought to the data assimilation context. Starting from a low-resolution forecast, a neural network (NN) emulates the fields to high-resolution, assimilates high-resolution observations, and scales it back up to the original resolution for running the next model step. The SRDA is tested with a quasi-geostrophic model in an idealized twin experiment for configurations where the model resolution is twice and four times lower than the reference solution from which pseudo-observations are extracted. The assimilation is performed with an Ensemble Kalman Filter. We show that SRDA outperforms both the low-resolution data assimilation approach and a version of SRDA with cubic spline interpolation instead of NN. The NN’s ability to anticipate the systematic differences between low- and high-resolution model dynamics explains the enhanced performance, in particular by correcting the difference of propagation speed of eddies. With a 25-member ensemble at low resolution, the SRDA computational overhead is 55 percent and the errors reduce by 40 percent, making the performance very close to that of the high-resolution system (52 percent of error reduction) that increases the cost by 800 percent. The reliability of the ensemble system is not degraded by SRDA.

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Impact of initialization methods on the predictive skill in NorCPM: an Arctic–Atlantic case study

Passos, L., Langehaug, HR., Årthun, M., Eldevik, T., Bethke, I., Kimmritz, M. 2022: Impact of initialization methods on the predictive skill in NorCPM: an Arctic–Atlantic case study. Clim Dyn. https://doi.org/10.1007/s00382-022-06437-4

Summary: The skilful prediction of climatic conditions on a forecast horizon of months to decades into the future remains a main scientific challenge of large societal benefit. Here we assess the hindcast skill of the Norwegian Climate Prediction Model (NorCPM) for sea surface temperature (SST) and sea surface salinity (SSS) in the Arctic–Atlantic region focusing on the impact of different initialization methods. We find the skill to be distinctly larger for the Subpolar North Atlantic than for the Norwegian Sea, and generally for all lead years analyzed. For the Subpolar North Atlantic, there is furthermore consistent benefit in increasing the amount of data assimilated, and also in updating the sea ice based on SST with strongly coupled data assimilation. The predictive skill is furthermore significant for at least two model versions up to 8–10 lead years with the exception for SSS at the longer lead years. For the Norwegian Sea, significant predictive skill is more rare; there is relatively higher skill with respect to SSS than for SST. A systematic benefit from more complex data assimilation approach can not be identified for this region. Somewhat surprisingly, skill deteriorates quite consistently for both the Subpolar North Atlantic and the Norwegian Sea when going from CMIP5 to corresponding CMIP6 versions. We find this to relate to change in the regional performance of the underlying physical model that dominates the benefit from initialization.

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