ENSO teleconnections in terms of non-NAO and NAO atmospheric variability

The validity of the long-held understanding or assumption that El Niño-Southern Oscillation (ENSO) has a remote influence on the North Atlantic Oscillation (NAO) in the January–February–March (JFM) months has been questioned recently. We examine this claim further using atmospheric data filtered to separate the variability orthogonal and parallel to NAO. This decomposition of the atmospheric fields is based on the Principal Component/Empirical Orthogonal Function method whereby the leading mode of the sea-level pressure in the North Atlantic sector is recognised as the NAO, while the remaining variability is orthogonal (unrelated) to NAO. Composite analyses indicate that ENSO has statistically significant links with both the non-NAO and NAO variability at various atmospheric levels. Additional bootstrap tests carried out to quantify the uncertainty and statistical significance confirm these relationships. Consistent with previous studies, we find that an ENSO teleconnection in the NAO-related variability is characterised by lower-stratospheric eddy heat flux anomalies (related to the vertical propagation of planetary waves) which appear in November–December and strengthen through JFM. Under El Niño (La Niña), there is constructive (destructive) interference of anomalous eddy heat flux with the climatological pattern, enhancing (reducing) fluxes over the northern Pacific and Barents Sea areas. We further show that the teleconnection of extreme El Niño is essentially a non-NAO phenomenon. Some non-linearity of the teleconnections is suggested, with El Niño including more NAO-related variability than La Niña, but the statistical significance is degraded due to weaker signals and smaller sample sizes after the partitioning. Our findings have implications for the general understanding of the nature of ENSO teleconnections over the North Atlantic, as well as for refining methods to characterise and evaluate them in models.publishedVersio

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

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.publishedVersio

Impact of the Agulhas Current on Southern Africa Precipitation: A Modeling Study

Postponed access: the file will be available after 2022-05-22The Agulhas Current (AC) creates a sharp temperature gradient with the surrounding ocean, leading to a large turbulent flux of moisture from ocean to atmosphere. We use two simulations of the Weather Research and Forecasting (WRF) Model to show the seasonal impact of the warm core of the AC on southern Africa precipitation. In one simulation the sea surface temperature (SST) of the AC is similar to satellite observations, while the second uses satellite SST observations spatially smoothed to reduce the temperature of the core of the AC by ~1.5°C. We show that decreasing the SST of the AC reduces the precipitation of the wettest seasons (austral summer and autumn) inland. Over the ocean, reducing the SST reduces precipitation, low-level wind convergence, SST, and SLP Laplacians above the AC in all seasons, consistent with the pressure adjustment mechanism. Moreover, winter precipitation above the AC may also be related to increased latent flux. In summer and autumn, the AC SST reduction is also associated with decreased precipitation farther inland (more than 1.5 mm day−1), caused by an atmospheric circulation that decreases the horizontal moisture flux from the AC to South Africa. The reduction is also associated with higher geopotential height extending from the surface east and over the AC to the midtroposphere over southeastern Africa. The westward tilted geopotential height is consistent with the linear response to shallow diabatic heating in midlatitudes. An identical mechanism occurs in spring but is weaker. Winter rainfall response is confined above the AC.publishedVersio

Southern Ocean Control of 2°C Global Warming in Climate Models

Global warming will soon reach the Paris Agreement targets of 1.5°C/2°C temperature increase above pre-industrial levels. Under a business-as-usual scenario, the time to reach these targets varies widely among climate models. Using Coupled Model Intercomparison Project Phase 5 and 6, we show that a 2°C global warming is determined by Southern Ocean (SO) state closely tied with a low-level cloud (LLC) amount feedback strength during reference (1861–1900) period; climate models with cold SO tend to accompany more low-level cloudiness and Antarctic sea ice concentration due to a strong LLC amount feedback. Consequently, initially cold SO models tend to simulate a fast global warming by absorbing more downward shortwave radiation compared to initially warm SO models because more LLC disappears due to a strong LLC amount feedback during the 2°C rise. Our results demonstrate that climate models that correctly simulate initial SO state can improve 2°C warming projections with reduced uncertainties.publishedVersio

Disentangling the impact of Atlantic Niño on sea-air CO2 flux

Atlantic Niño is a major tropical interannual climate variability mode of the sea surface temperature (SST) that occurs during boreal summer and shares many similarities with the tropical Pacific El Niño. Although the tropical Atlantic is an important source of CO2 to the atmosphere, the impact of Atlantic Niño on the sea-air CO2 exchange is not well understood. Here we show that the Atlantic Niño enhances (weakens) CO2 outgassing in the central (western) tropical Atlantic. In the western basin, freshwater-induced changes in surface salinity, which considerably modulate the surface ocean CO2 partial pressure (pCO2), are the primary driver for the observed CO2 flux variations. In contrast, pCO2 anomalies in the central basin are dominated by the SST-driven solubility change. This multi-variable mechanism for pCO2 anomaly differs remarkably from the Pacific where the response is predominantly controlled by upwelling-induced dissolved inorganic carbon anomalies. The contrasting behavior is characterized by the high CO2 buffering capacity in the Atlantic, where the subsurface water mass contains higher alkalinity than in the Pacific.publishedVersio

Multidecadal variability of ENSO in a recharge oscillator framework

We use a conceptual recharge oscillator model to identify changes in El Niño and the Southern Oscillation (ENSO) statistics and dynamics during the observational record. The variability of ENSO has increased during the 20th century. The cross-correlation between sea surface temperature (SST) and warm water volume (WWV) has also changed during the observational record. From the 1970s onwards, the SST drives WWV anomalies with a lead-time of ten months and the WWV feedbacks onto the SST with a lead-time of eight months. This is reminiscent of a recharge-discharge mechanism of the upper ocean heat content. The full recharge-discharge mechanism is only observed from the 1970s onwards. This could be the result of the degradation of the quality of observations in the early part of the 20th century. However, it may also be a consequence of decadal changes in the coupling between WWV and SST. Additional analysis fitting the recharge oscillator model to the coupled state-of-the-art climate models indicates that ENSO properties show little decadal changes in the climate models. The disagreement in changes in ENSO properties between the reanalysis and the climate models can be due to errors in the available observational data or due to the models missing the low frequency variability and decadal wind trends. Longer and more reliable observational records would be required to validate our results.publishedVersio

The role of air–sea coupling on November–April intraseasonal rainfall variability over the South Pacific

We investigate the impact of resolving air-sea interaction on the simulation of the intraseasonal rainfall variability over the South Pacific using the ECHAM5 atmospheric general circulation model coupled with the Snow-Ice-Thermocline (SIT) ocean model. We compare the fully coupled simulation with two uncoupled ECHAM5 simulations, one forced with sea surface temperature (SST) climatology and one forced with daily SST from the coupled model. The intraseasonal rainfall variability over the South Pacific is reduced by 17% in the uncoupled model forced with SST climatology and increased by 8% in the uncoupled simulation forced with daily SST, suggesting the role of air–sea coupling and SST variability. The coupled model best simulates the key characteristics of the two dominant patterns (modes) of intraseasonal rainfall variability over the South Pacific with reasonable propagation and correct periodicity. The spatial structure of the two rainfall modes in all three simulations is very similar, suggesting the dynamics of the atmosphere primarily generate these modes. The southeastward propagation of rainfall anomalies associated with two leading rainfall modes in the South Pacific depends upon the eastward propagating Madden–Julian Oscillation (MJO) signals from the Indian Ocean and western Pacific. Air-sea interaction improves such propagation as both eastward and southeastward propagations are substantially reduced in the uncoupled model forced with SST climatology. The simulation of both eastward and southeastward propagations considerably improved in the uncoupled model forced with daily SST; however, the periodicity differs from the coupled model. Such discrepancy in the periodicity is attributed to the changes in the SST-rainfall relationship with weaker correlations and the nearly in-phase relationship, attributed to enhanced positive latent heat flux feedbacks.publishedVersio

Framework for an Ocean-Connected Supermodel of the Earth System

A supermodel connects different models interactively so that their systematic errors compensate and achieve a model with superior performance. It differs from the standard non-interactive multi-model ensembles (NI), which combines model outputs a-posteriori. Supermodels with Earth system models (ESMs) has not been developed because it is technically challenging to combine models with different state space. Here, we formulate the first supermodel framework for ESMs and use data assimilation to synchronise models. The ocean of three ESMs is synchronised every month by assimilating pseudo sea surface temperature (SST) observations generated by them on a common grid to handle discrepancies in grid and resolution. We compare the performance of two supermodel approaches to that of the NI. In the first (EW), the models are connected to the equal-weight multi-model mean, while in the second (SINGLE), they are connected to a single model. Both versions achieve synchronisation in the ocean and in the atmosphere, where the ocean drives the variability. The time variability of the supermodel multi-model mean SST is reduced compared to observations, most where synchronisation is not achieved and is lower-bounded by NI. The damping is larger in EW, for which variability in the individual models is also damped. Hence, under partial synchronisation, the unsynchronized variability gets damped in the multi-model average pseudo-observations, causing a deflation during the assimilation. The SST bias in individual models of EW is reduced compared to that of NI, and so is its multi-model mean in the synchronised regions. A trained supermodel remains to be tested.publishedVersio

Phytoplankton abundance in the Barents Sea is predictable up to five years in advance

The Barents Sea is a highly biologically productive Arctic shelf sea with several commercially important fish stocks. Interannual-to-decadal predictions of its ecosystem would therefore be valuable for marine resource management. Here, we demonstrate that the abundance of phytoplankton, the base of the marine food web, can be predicted up to five years in advance in the Barents Sea with the Norwegian Climate Prediction Model. We identify two different mechanisms giving rise to this predictability; 1) in the southern ice-free Atlantic Domain, skillful prediction is a result of the advection of waters with anomalous nitrate concentrations from the Subpolar North Atlantic; 2) in the northern Polar Domain, phytoplankton predictability is a result of the skillful prediction of the summer ice concentration, which influences the light availability. The skillful prediction of the phytoplankton abundance is an important step forward in the development of numerical ecosystem predictions of the Barents Sea.publishedVersio

Propagation of Thermohaline Anomalies and their predictive potential along the Atlantic water pathway

We assess to what extent seven state-of-the-art dynamical prediction systems can retrospectively predict winter sea surface temperature (SST) in the subpolar North Atlantic and the Nordic seas in the period 1970–2005. We focus on the region where warm water flows poleward (i.e., the Atlantic water pathway to the Arctic) and on interannual-to-decadal time scales. Observational studies demonstrate predictability several years in advance in this region, but we find that SST skill is low with significant skill only at a lead time of 1–2 years. To better understand why the prediction systems have predictive skill or lack thereof, we assess the skill of the systems to reproduce a spatiotemporal SST pattern based on observations. The physical mechanism underlying this pattern is a propagation of oceanic anomalies from low to high latitudes along the major currents, the North Atlantic Current and the Norwegian Atlantic Current. We find that the prediction systems have difficulties in reproducing this pattern. To identify whether the misrepresentation is due to incorrect model physics, we assess the respective uninitialized historical simulations. These simulations also tend to misrepresent the spatiotemporal SST pattern, indicating that the physical mechanism is not properly simulated. However, the representation of the pattern is slightly degraded in the predictions compared to historical runs, which could be a result of initialization shocks and forecast drift effects. Ways to enhance predictions could include improved initialization and better simulation of poleward circulation of anomalies. This might require model resolutions in which flow over complex bathymetry and the physics of mesoscale ocean eddies and their interactions with the atmosphere are resolved.publishedVersio