scholarly journals Correction to: Weakened SST variability in the tropical Atlantic Ocean since 2000

2021 ◽  
Author(s):  
Arthur Prigent ◽  
Joke F. Lübbecke ◽  
Tobias Bayr ◽  
Mojib Latif ◽  
Christian Wengel
Keyword(s):  
Atlantic Ocean ◽  
Tropical Atlantic ◽  
Tropical Atlantic Ocean ◽  
Sst Variability

Decadal and Interannual SST Variability in the Tropical Atlantic Ocean

1996 ◽  
Vol 26 (7) ◽  
pp. 1165-1175 ◽  
Author(s):  
James A. Carton ◽  
Xianhe Cao ◽  
Benjamin S. Giese ◽  
Arlindo M. Da Silva
Keyword(s):  
Atlantic Ocean ◽  
Tropical Atlantic ◽  
Tropical Atlantic Ocean ◽  
Sst Variability

scholarly journals Weakened SST variability in the tropical Atlantic Ocean since 2000

2020 ◽  
Vol 54 (5-6) ◽  
pp. 2731-2744 ◽  
Author(s):  
Arthur Prigent ◽  
Joke F. Lübbecke ◽  
Tobias Bayr ◽  
Mojib Latif ◽  
Christian Wengel
Keyword(s):  
Atlantic Ocean ◽  
Tropical Atlantic ◽  
Tropical Atlantic Ocean ◽  
Sst Variability

Mean and Variability of the Tropical Atlantic Ocean in the CCSM4*

2012 ◽  
Vol 25 (14) ◽  
pp. 4860-4882 ◽  
Author(s):  
Ernesto Muñoz ◽  
Wilbert Weijer ◽  
Semyon A. Grodsky ◽  
Susan C. Bates ◽  
Ilana Wainer
Keyword(s):  
Atlantic Ocean ◽  
Wind Stress ◽  
Heat Budget ◽  
South Atlantic ◽  
Tropical Atlantic ◽  
Climate System Model ◽  
Tropical Atlantic Ocean ◽  
Modes Of Variability ◽  
Sst Variability ◽  
Budget Analysis

Abstract This study analyzes important aspects of the tropical Atlantic Ocean from simulations of the fourth version of the Community Climate System Model (CCSM4): the mean sea surface temperature (SST) and wind stress, the Atlantic warm pools, the principal modes of SST variability, and the heat budget in the Benguela region. The main goal was to assess the similarities and differences between the CCSM4 simulations and observations. The results indicate that the tropical Atlantic overall is realistic in CCSM4. However, there are still significant biases in the CCSM4 Atlantic SSTs, with a colder tropical North Atlantic and a hotter tropical South Atlantic, that are related to biases in the wind stress. These are also reflected in the Atlantic warm pools in April and September, with its volume greater than in observations in April and smaller than in observations in September. The variability of SSTs in the tropical Atlantic is well represented in CCSM4. However, in the equatorial and tropical South Atlantic regions, CCSM4 has two distinct modes of variability, in contrast to observed behavior. A model heat budget analysis of the Benguela region indicates that the variability of the upper-ocean temperature is dominated by vertical advection, followed by meridional advection.

scholarly journals Role of Net Surface Heat Flux in Seasonal Variations of Sea Surface Temperature in the Tropical Atlantic Ocean

2006 ◽  
Vol 19 (23) ◽  
pp. 6153-6169 ◽  
Author(s):  
Lisan Yu ◽  
Xiangze Jin ◽  
Robert A. Weller
Keyword(s):  
Heat Flux ◽  
Atlantic Ocean ◽  
Surface Heat Flux ◽  
Surface Heat ◽  
The Other ◽  
Sea Surface ◽  
Tropical Atlantic ◽  
Atlantic Sector ◽  
Tropical Atlantic Ocean ◽  
Sst Variability

Abstract The present study used a new net surface heat flux (Qnet) product obtained from the Objective Analyzed Air–Sea Fluxes (OAFlux) project and the International Satellite Cloud Climatology Project (ISCCP) to examine two specific issues—one is to which degree Qnet controls seasonal variations of sea surface temperature (SST) in the tropical Atlantic Ocean (20°S–20°N, east of 60°W), and the other is whether the physical relation can serve as a measure to evaluate the physical representation of a heat flux product. To better address the two issues, the study included the analysis of three additional heat flux products: the Southampton Oceanographic Centre (SOC) heat flux analysis based on ship reports, and the model fluxes from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). The study also uses the monthly subsurface temperature fields from the World Ocean Atlas to help analyze the seasonal changes of the mixed layer depth (hMLD). The study showed that the tropical Atlantic sector could be divided into two regimes based on the influence level of Qnet. SST variability poleward of 5°S and 10°N is dominated by the annual cycle of Qnet. In these regions the warming (cooling) of the sea surface is highly correlated with the increased (decreased) Qnet confined in a relatively shallow (deep) hMLD. The seasonal evolution of SST variability is well predicted by simply relating the local Qnet with a variable hMLD. On the other hand, the influence of Qnet diminishes in the deep Tropics within 5°S and 10°N and ocean dynamic processes play a dominant role. The dynamics-induced changes in SST are most evident along the two belts, one of which is located on the equator and the other off the equator at about 3°N in the west, which tilts to about 10°N near the northwestern African coast. The study also showed that if the degree of consistency between the correlation relationships of Qnet, hMLD, and SST variability serves as a measure of the quality of the Qnet product, then the Qnet from OAFlux + ISCCP and ERA-40 are most physically representative, followed by SOC. The NCEP–NCAR Qnet is least representative. It should be noted that the Qnet from OAFlux + ISCCP and ERA-40 have a quite different annual mean pattern. OAFlux + ISCCP agrees with SOC in that the tropical Atlantic sector gains heat from the atmosphere on the annual mean basis, where the ERA-40 and the NCEP–NCAR model reanalyses indicate that positive Qnet occurs only in the narrow equatorial band and in the eastern portion of the tropical basin. Nevertheless, seasonal variances of the Qnet from OAFlux + ISCCP and ERA-40 are very similar once the respective mean is removed, which explains why the two agree with each other in accounting for the seasonal variability of SST. In summary, the study suggests that an accurate estimation of surface heat flux is crucially important for understanding and predicting SST fluctuations in the tropical Atlantic Ocean. It also suggests that future emphasis on improving the surface heat flux estimation should be placed more on reducing the mean bias.

scholarly journals Simulated Dust Aerosol Impacts on Western Sahelian Rainfall: Importance of Ocean Coupling

2018 ◽  
Vol 31 (22) ◽  
pp. 9107-9124 ◽  
Author(s):  
Asha K. Jordan ◽  
Anand Gnanadesikan ◽  
Benjamin Zaitchik
Keyword(s):  
Atlantic Ocean ◽  
North Africa ◽  
Negative Impact ◽  
Positive Impact ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Tropical Atlantic ◽  
Tropical Atlantic Ocean ◽  
Ocean Atmosphere ◽  
Sahel Region ◽  
Dust Precipitation

North Africa is the world’s largest source of mineral dust, and this dust has potentially significant impacts on precipitation. Yet there is no consensus in published studies regarding the sign or magnitude of dust impacts on rainfall in either the highly climate-sensitive Sahel region of North Africa or the neighboring tropical Atlantic Ocean. Here the Geophysical Fluid Dynamics Laboratory (GFDL) Climate Model 2 (GFDL CM2.0) with Modular Ocean Model, version 4.1 (MOM4.1), run at coarse resolution (CM2Mc) is applied to investigate one poorly characterized aspect of dust–precipitation dynamics: the importance of sea surface temperature (SST) changes in mediating the atmospheric response to dust. Two model experiments were performed: one comparing Dust-On to Dust-Off simulations in the absence of ocean–atmosphere coupling, and the second comparing Dust-On to Dust-Off with the ocean fully coupled. Results indicate that SST changes in the coupled experiment reduce the magnitude of dust impacts on Sahel rainfall and flip the sign of the precipitation response over the nearby ocean. Over the Sahel, CM2Mc simulates a net positive impact of dust on monsoon season rainfall, but ocean–atmosphere coupling in the presence of dust decreases the inflow of water vapor, reducing the amount by which dust enhances rainfall. Over the tropical Atlantic Ocean, dust leads to SST cooling in the coupled experiment, resulting in increased static stability that overrides the warming-induced increase in convection observed in the uncoupled experiment and yields a net negative impact of dust on precipitation. These model results highlight the potential importance of SST changes in dust–precipitation dynamics in North Africa and neighboring regions.

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