The effect of vertical ocean mixing on the tropical Atlantic in a coupled global climate model

Sea surface temperature (SST) biases in the tropical Atlantic are a long-standing problem among coupled global climate models (CGCMs). They occur in equilibrated state, as well as in initialised seasonal to decadal simulations. The bias is typically characterised by too high SST in upwelling regions and associated errors of wind and precipitation. We examine the SST bias in the state-of-the-art CGCM EC-Earth by means of an upper ocean heat budget analysis. Horizontal advection processes affect the SST bias development only to a small extent, and surface heat fluxes mostly dampen the warm bias. Subgrid-scale upper ocean vertical mixing is too low in EC-Earth when compared to estimates from reanalysis data, potentially giving rise to the warm bias. We perform sensitivity experiments to examine the effect of enhanced vertical mixing on the SST bias in quasi equilibrium present day climate and its impact on projected climate change. Enhanced mixing in historical simulation mode (MixUp pr) reduces the SST bias in the tropical Atlantic compared to the control experiment (Control pr). Associated atmospheric biases of precipitation and surface winds are also reduced in MixUp pr. We further perform climate projections under the RCP8.5 emission scenario (Control fu and MixUp fu). Under increasing greenhouse gas forcing, the tropical Atlantic warms by up to 4.5∘C locally, and maritime precipitation increases in boreal winter and spring. We show that the vertical mixing parameterisation influences future climate. In MixUp fu, SSTs remain 0.5∘C colder in boreal winter and spring, but increase with the same amplitude in summer and fall. The strength and location of the projected intertropical convergence zone also depends on the ocean vertical mixing efficiency. The rain band moves southward in summer, and its strength increases in winter in MixUp fu as compared to Control fu.</p

An EC-Earth coupled atmosphere–ocean single-column model (AOSCM.v1_EC-Earth3) for studying coupled marine and polar processes

Single-column models (SCMs) have been used as tools to help develop numerical weather prediction and global climate models for several decades. SCMs decouple small-scale processes from large-scale forcing, which allows the testing of physical parameterisations in a controlled environment with reduced computational cost. Typically, either the ocean, sea ice or atmosphere is fully modelled and assumptions have to be made regarding the boundary conditions from other subsystems, adding a potential source of error. Here, we present a fully coupled atmosphere–ocean SCM (AOSCM), which is based on the global climate model EC-Earth3. The initial configuration of the AOSCM consists of the Nucleus for European Modelling of the Ocean (NEMO3.6) (ocean), the Louvain-la-Neuve Sea Ice Model (LIM3) (sea ice), the Open Integrated Forecasting System (OpenIFS) cycle 40r1 (atmosphere), and OASIS3-MCT (coupler). Results from the AOSCM are presented at three locations: the tropical Atlantic, the midlatitude Pacific and the Arctic. At all three locations, in situ observations are available for comparison. We find that the coupled AOSCM can capture the observed atmospheric and oceanic evolution based on comparisons with buoy data, soundings and ship-based observations. The model evolution is sensitive to the initial conditions and forcing data imposed on the column. Comparing coupled and uncoupled configurations of the model can help disentangle model feedbacks. We demonstrate that the AOSCM in the current set-up is a valuable tool to advance our understanding in marine and polar boundary layer processes and the interactions between the individual components of the system (atmosphere, sea ice and ocean)

Role of wind stress in driving SST biases in the tropical Atlantic

Coupled climate models used for long-term future climate projections and seasonal or decadal predictions share a systematic and persistent warm sea surface temperature (SST) bias in the tropical Atlantic. This study attempts to better understand the physical mechanisms responsible for the development of systematic biases in the tropical Atlantic using the so-called Transpose-CMIP protocol in a multi-model context. Six global climate models have been used to perform seasonal forecasts starting both in May and February over the period 2000-2009. In all models, the growth of SST biases is rapid. Significant biases are seen in the first month of forecast and, by six months, the root-mean-square SST bias is 80% of the climatological bias. These control experiments show that the equatorial warm SST bias is not driven by surface heat flux biases in all models, whereas in the south-eastern Atlantic the solar heat flux could explain the setup of an initial warm bias in the first few days. A set of sensitivity experiments with prescribed wind stress confirm the leading role of wind stress biases in driving the equatorial SST bias, even if the amplitude of the SST bias is model dependent. A reduced SST bias leads to a reduced precipitation bias locally, but there is no robust remote effect on West African Monsoon rainfall. Over the south-eastern part of the basin, local wind biases tend to have an impact on the local SST bias (except in the high resolution model). However, there is also a non-local effect of equatorial wind correction in two models. This can be explained by sub-surface advection of water from the equator, which is colder when the bias in equatorial wind stress is corrected. In terms of variability, it is also shown that improving the mean state in the equatorial Atlantic leads to a beneficial intensification of the Bjerknes feedback loop. In conclusion, we show a robust effect of wind stress biases on tropical mean climate and variability in multiple climate models

Air-sea interaction in the tropical Atlantic

Sea surface temperatures (SST) in the tropical Atlantic ocean influence weather and climate patterns on the bordering continents and beyond. SST patterns are related to the West African Monsoon, and rainfall and drought over South America. Accurate simulation of oceanic processes with state-of-the-art coupled general circulation models (CGCMs) could enable prediction of societally relevant events, such as drought seasons. However, CGCMs are limited by long-standing biases in the tropical Atlantic, specifically by excessively warm SST in the south-east. In this thesis we investigate sources of variability in the tropical Atlantic, and how their representation in CGCMs lead to biases. We investigate basin wide air-sea interaction pathways as well as local mechanism, which contribute to the build-up of warm SST biases. Our results point to the importance of correct parameterisation of upper ocean vertical mixing for accurate climate model simulations.</p

The Bjerknes feedback in the tropical Atlantic in CMIP5 models

Coupled state-of-the-art general circulation models still perform relatively poorly in simulating tropical Atlantic (TA) climate. To investigate whether lack of air–sea interaction might be responsible for their biases, we investigate the Bjerknes feedback (BF) in the TA, the driver of the dominant interannual variability in that region. First, we analyse this mechanism from reanalysis data. Then, we compare our findings to model output from the Coupled Model Intercomparison Project Phase 5. The feedback is subdivided into three components. The first one consists of the influence of eastern equatorial sea surface temperature anomalies (SST’) on zonal wind stress anomalies ((Formula presented.)’) in the western basin. The second component is the influence of wind stress anomalies in the western TA on eastern equatorial oceanic heat content anomalies (HC’). The third component is the local response of overlying SST’ to HC’ in the eastern TA. All three components are shown to be present in ERA-Interim and ORAS4 reanalysis by correlating the two variables of each component with each other. The obtained patterns are compared to the ones from model output via pattern correlation per component. While the models display errors in the annual cycles of SST, (Formula presented.), and HC, as well as in the seasonality of the feedback, the impact of SST’ on wind stress and the impact of wind stress on HC’ are simulated relatively well by most of the models. This is especially the case when correcting for the error in seasonality. The third component of the BF, the impact of HC’ on SST’ in the eastern part of the basin, deviates from what we find in reanalysis. We find an influence of HC anomalies on overlying SSTs in the eastern equatorial TA, but it is weaker than in the reanalysis and it is not strongly confined to the equator. Longitude–depth cross sections of equatorial temperature variance and correlation between subsurface temperature anomalies and SST’ in the cold tongue region show that flawed simulation and slow adjustment of the subsurface ocean are responsible for this.</p

Climate change adaptation and the role of fuel subsidies: An empirical bio-economic modeling study for an artisanal open-access fishery

Climate change can severely impact artisanal fisheries and affect the role they play in food security. We study climate change effects on the triple bottom line of ecological productivity, fishers’ incomes, and fish consumption for an artisanal open-access fishery. We develop and apply an empirical, stochastic bio-economic model for the Senegalese artisanal purse seine fishery on small pelagic fish and compare the simulated fishery’s development using four climate projections and two policy scenarios. We find that economic processes of adaptation may amplify the effects of climate variations. The regions’ catch potential increases with climate change, induced by stock distribution changes. However, this outcome escalates over-fishing, whose effects outpace the incipiently favorable climate change effects under three of the four climate projections. Without policy action, the fishery is estimated to collapse in 2030–2035 on average over 1000 runs. We propose an easily implementable and overall welfare-increasing intervention: reduction of fuel subsidies. If fuel subsidies were abolished, ecological sustainability as well as the fishery’s welfare contribution would increase regardless of the climate projection

The southeastern tropical atlantic sst bias investigated with a coupled atmosphere-ocean single-column model at a pirata mooring site

Warm sea surface temperature (SST) biases in the tropical Atlantic Ocean form a longstanding problem in coupled general circulation models (CGCMs). Considerable efforts to understand the origins of these biases and alleviate them have been undertaken, but state-of-the-art CGCMs still suffer from biases that are very similar to those of the generation of models before. In this study, we use a powerful combination of in situ moored buoy observations and a new coupled ocean-atmosphere single-column model (SCM) with parameterization that is identical to that of a three-dimensional CGCM to investigate the SST bias. We place the SCM at the location of a Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) mooring in the southeastern tropical Atlantic, where large SST biases occur in CGCMs. The SCM version of the EC-Earth state-of-the-art coupled GCM performs well for the first five days of the simulation. Then, it develops an SST bias that is very similar to that of its three-dimensional counterpart. Through a series of sensitivity experiments we demonstrate that the SST bias can be reduced by 70%. We achieve this result by enhancing the turbulent vertical ocean mixing efficiency in the ocean parameterization scheme. The under-representation of vertical mixing in three-dimensional CGCMs is a candidate for causing the warm SST bias. We further show that surface shortwave radiation does not cause the SST bias at the location of the PIRATA mooring. Rather, a warm atmospheric near-surface temperature bias and a wet moisture bias contribute to it. Strongly nudging the atmosphere to profiles from reanalysis data reduces the SST bias by 40%.</p

Correction: Strong enhancement of parity violation effects in chiral uranium compounds

International audienceCorrection for ‘Strong enhancement of parity violation effects in chiral uranium compounds’ by Michael Wormit et al., Phys. Chem. Chem. Phys., 2014, 16, 17043–1705

Strong enhancement of parity violation effects in chiral uranium compounds

International audienceThe effects of parity violation (PV) on the vibrational transitions of chiral uranium compounds of the type N≡UXYZ and N≡UHXY (X, Y, Z = F, Cl, Br, I) are analysed by means of exact two-component relativistic (X2C) Hartree-Fock and density functional calculations using NUFClI and NUHFI as representative examples. The PV contributions to the vibrational transitions were found to be in the Hz range, larger than for any of the earlier proposed chiral molecules. Thus, these systems are very promising candidates for future experimental PV measurements. A detailed comparison of the N≡UHFI and the N≡WHFI homologues reveals that subtle electronic structure effects, rather than exclusively a simple Z(5) scaling law, are the cause of the strong enhancement in PV contributions of the chiral uranium molecules