Frontogenesis of the Angola-Benguela Frontal Zone

A diagnostic analysis of the climatological annual mean and seasonal cycle of the Angola–Benguela Frontal Zone (ABFZ) is performed by applying an ocean frontogenetic function (OFGF) to the ocean mixing layer (OML). The OFGF reveals that the meridional confluence and vertical tilting terms are the most dominant contributors to the frontogenesis of the ABFZ. The ABFZ shows a well-pronounced semiannual cycle with two maximum (minimum) peaks in April–May and November–December (February–March and July–August). The development of the two maxima of frontogenesis is due to two different physical processes: enhanced tilting from March to April and meridional confluence from September to October. The strong meridional confluence in September to October is closely related to the seasonal southward intrusion of tropical warm water to the ABFZ that seems to be associated with the development of the Angola Dome northwest of the ABFZ. The strong tilting effect from March to April is attributed to the meridional gradient of vertical velocities, whose effect is amplified in this period due to increasing stratification and shallow OML depth. The proposed OFGF can be viewed as a tool to diagnose the performance of coupled general circulation models (CGCMs) that generally fail at realistically simulating the position of the ABFZ, which leading to huge warm biases in the southeastern Atlantic.publishedVersio

The role of the sea surface temperature in the atmospheric seasonal cycle of the equatorial Atlantic

We investigate the role of sea surface temperature (SST) and land surface temperature (LST) in driving the seasonal cycle of the atmosphere (surface winds and precipitation) in the tropical Atlantic. For this we compare three atmospheric general circulation model (AGCM) experiments for the historical period 1982–2013 forced by different SST: (1) observed daily-climatological SST, (2) globally annual-mean SST, and (3) annual-mean SST in the equatorial Atlantic and daily-climatological SST elsewhere. Seasonal variations in SST strongly influence the seasonal evolution of the West African Monsoon (WAM) and ITCZ over the equatorial Atlantic Ocean. Forcing the model with annual mean SST (globally and in the equatorial Atlantic) considerably reduces the seasonal variance in the atmosphere, except for the zonal winds in the eastern equatorial Atlantic. Equatorial Atlantic SST contributes to the seasonal cycle in precipitation and meridional winds over the entire equatorial Atlantic, but only strongly influences zonal winds in the western equatorial Atlantic and has little influence on the northward penetration of the WAM. The leading modes of coupled SST–LST-atmosphere co-variability are identified by multivariate analysis. The analysis shows that both LST and SST drive seasonal variations in precipitation over equatorial Atlantic, with the LST being a larger contributor to the continental rainfall in West Africa. The coupling between ocean and atmosphere is stronger in the western than in the eastern equatorial Atlantic. The pressure adjustment mechanism is the main driver of the surface meridional wind convergence in the eastern tropical Atlantic.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

Seasonality of coastal upwelling trends in the Mauritania-Senegalese region under RCP8.5 climate change scenario

The Mauritania-Senegalese upwelling region (MSUR), the southernmost region of the Canary current upwelling system, is well-known for its coastal productivity and the key role it plays in enriching the oligotrophic open ocean through the offshore transport of the upwelled coastal waters. The great ecological and socio-economic importance makes it necessary to evaluate the impact of climate change on this region. Hence, our main objective is to examine the climate change signal over the MSUR with a high resolution regional climate system model (RCSM) forced by the Earth system model MPI-ESM-LR under RCP8.5 scenario. This RCSM has a regional atmosphere model (REMO) coupled to a global ocean model (MPIOM) with high-resolution in the MSUR, which allows us to evaluate the wind pattern, the ocean stratification, as well as the upwelling source water depth, while maintaining an ocean global domain. Under RCP8.5 scenario, our results show that the upwelling favourable winds of the northern MSUR are year-round intensified, while the southern MSUR presents a strengthening in winter and a weakening in March–April. Along with changes in the wind pattern, we found increased ocean stratification in the spring months. In those months southern MSUR presents a shallowing of the upwelling source water depth associated to changes in both mechanisms. However, in winter the whole MSUR shows a deepening of the upwelling source water depth due to the intensification of the upwelling favourable winds, with the increased ocean stratification playing a secondary role. Our results demonstrate the need to evaluate the future evolution of coastal upwelling systems taking into account their latitudinal and seasonal variability and the joint contribution of both mechanisms.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

Causes of the large warm bias in the Angola–Benguela Frontal Zone in the Norwegian Earth System Model

We have investigated the causes of the sea surface temperature (SST) bias in the Angola–Benguela Frontal Zone (ABFZ) of the southeastern Atlantic Ocean simulated by the Norwegian Earth System Model (NorESM). Similar to other coupled-models, NorESM has a warm SST bias in the ABFZ of up to 8 °C in the annual mean. Our analysis of NorESM reveals that a cyclonic surface wind bias over the ABFZ drives a locally excessively strong southward (0.05 m/s (relative to observation)) Angola Current displacing the ABFZ southward. A series of uncoupled stand-alone atmosphere and ocean model simulations are performed to investigate the cause of the coupled model bias. The stand-alone atmosphere model driven with observed SST exhibits a similar cyclonic surface circulation bias; while the stand-alone ocean model forced with the reanalysis data produces a warm SST in the ABFZ with a magnitude approximately half of that in the coupled NorESM simulation. An additional uncoupled sensitivity experiment shows that the atmospheric model’s local negative surface wind curl generates anomalously strong Angola Current at the ocean surface. Consequently, this contributes to the warm SST bias in the ABFZ by 2 °C (compared to the reanalysis forced simulation). There is no evidence that local air-sea feedbacks among wind stress curl, SST, and sea level pressure (SLP) affect the ABFZ SST bias. Turbulent surface heat flux differences between coupled and uncoupled experiments explain the remaining 2 °C warm SST bias in NorESM. Ocean circulation, upwelling and turbulent heat flux errors all modulate the intensity and the seasonality of the ABFZ errors.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

On the impact of atmospheric vs oceanic resolutions on the representation of the sea surface temperature in the South Eastern Tropical Atlantic

Despite the efforts of the modelling community to improve the representation of the sea surface temperature (SST) over the South Eastern Tropical Atlantic, warm biases still persist. In this work we use four different configurations of the fully-coupled AWI Climate Model (AWI-CM) which allow us to gain physics-based insight into the role of the oceanic and atmospheric resolutions of the model in the regional distribution of the SST. Our results show that a sole refinement of the oceanic resolution reduces warm biases further than a single increase of the atmospheric component. An increased oceanic resolution is required (i) to simulate properly the Agulhas Current and its associated rings; (ii) to reinforce the northward-flowing Benguela Current and (iii) to intensify coastal upwelling. The best results are obtained when both resolutions are refined. However, even in that case, warm biases persist, reflecting that some processes and feedbacks are still not optimally resolved. Our results indicate that overheating is not due to insufficient upwelling, but rather due to upwelling of waters which are warmer than observations as a result of an erroneous representation of the vertical distribution of temperature. Errors in the representation of the vertical temperature profile are the consequence of a warm bias in the simulated climate state

Weakening of the Atlantic Niño variability under global warming

The Atlantic Nino 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 Ninos 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 Nino variability will potentially impact climate conditions and the skill of seasonal predictions in many regions. The Atlantic Nino is an important mode of tropical climate variability, but how it reacts to climate change is not well known due to model biases. Here the authors show a robust weakening of the Atlantic Nino of up to 24-48% under high emissions until the end of the century

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