scholarly journals Post-Bomb Radiocarbon Records of Surface Corals from the Tropical Atlantic Ocean

Radiocarbon ◽  
1996 ◽  
Vol 38 (3) ◽  
pp. 563-572 ◽  
Author(s):  
Ellen R. M. Druffel

Δ14C records are reported for post-bomb corals from three sites in the tropical Atlantic Ocean. In corals from 18°S in the Brazil Current, Δ14C values increased from ca. −58% in the early 1950s to +138% by 1974, then decreased to 110‰ by 1982. Shorter records from 8ºS off Brazil and from the Cape Verde Islands (17°N) showed initially higher Δ14C values before 1965 than those at 18ºS, but showed lower rates of increase of Δ14C during the early 1960s. There is general agreement between the coral results and Δ14C of dissolved inorganic carbon (DIC) measured in seawater previously for locations in the tropical Atlantic Ocean. Δ14C values at our tropical ocean sites increased at a slower rate than those observed previously in the temperate North Atlantic (Florida and Bermuda), owing to the latter's proximity to the bomb 14C input source in the northern, hemisphere. Model results show that from 1960–1980 the Cape Verde coral and selected DIG Δ14C values from the North Equatorial Current agree with that calculated for the North Atlantic based on an isopycnal mixing model with a constant water mass renewal rate between surface and subsurface waters. This is in contrast to Δ14C values in Bermuda corals that showed higher post-bomb values than those predicted using a constant water mass renewal rate, hence indicating that ventilation in the western north Atlantic Ocean had decreased by a factor of 3 during the 1960s and 1970s (Druffel 1989).

2020 ◽  
Author(s):  
Brady Ferster ◽  
Alexey Fedorov ◽  
Juliette Mignot ◽  
Eric Guilyardi

<p>The Arctic and North Atlantic Ocean play a fundamental role in Earth’s water cycle, distribution of energy (i.e. heat), and the formation of cold, dense waters. Through the Atlantic meridional overturning circulation (AMOC), heat is transported to the high-latitudes. Classically, the climate impact of AMOC variations has been investigated through hosing experiments, where anomalous freshwater is artificially added or removed from the North Atlantic to modulate deep water formation. However, such a protocol introduces artificial changes in the subpolar area, possibly masking the effect of the AMOC modulation. Here, we develope a protocol where AMOC intensity is modulated remotely through the teleconnection of the tropical Indian Ocean (TIO), so as to investigate more robustly the impact of the AMOC on climate. Warming in the TIO has recently been shown to strengthen the Walker circulation in the Atlantic through the propagation of Kelvin and Rossby waves, increasing and stabilizing the AMOC on longer timescales. Using the latest coupled-model from Insitut Pierre Simon Laplace (IPSL-CM6), we have designed a three-member ensemble experiment nudging the surface temperatures of the TIO by -2°C, +1°C, and +2°C for 100 years. The objectives are to better quantify the timescales of AMOC variability outside the use of hosing experiments and the TIO-AMOC relationship.  In each ensemble member, there are two distinct features compared to the control run. The initial changes in AMOC (≤20 years) are largely atmospherically driven, while on longer timescales is largely driven by the TIO teleconnection to the tropical Atlantic. In the northern North Atlantic, changes in sensible heat fluxes range from 15 to 20 W m<sup>-2 </sup>in all three members compared to the control run, larger than the natural variability. On the longer timescales, AMOC variability is strongly influenced from anomalies in the tropical Atlantic Ocean. The TIO teleconnection supports decreased precipitation in the tropical Atlantic Ocean during warming (opposite during TIO cooling) events, as well as positive salinity anomalies and negative temperature anomalies. Using lagged correlations, there are the strongest correlations on scales within one year and a delayed response of 30 years (in the -2°C ensembles). In comparing the last 20 years, nudging the TIO induces a 3.3 Sv response per 1°C change. In summary, we have designed an experiment to investigate the AMOC variability without directly changing the North Atlantic through hosing, making way for a more unbiased approach to analysing the AMOC variability in climate models.</p>


2007 ◽  
Vol 135 (5) ◽  
pp. 1786-1806 ◽  
Author(s):  
Zeng-Zhen Hu ◽  
Bohua Huang

Abstract This work investigates the predictive skill and most predictable pattern in the NCEP Climate Forecast System (CFS) in the tropical Atlantic Ocean. The skill is measured by the sea surface temperature (SST) anomaly correlation between the predictions and the corresponding analyses, and the most predictable patterns are isolated by an empirical orthogonal function analysis with a maximized signal-to-noise ratio. On average, for predictions with initial conditions (ICs) of all months, the predictability of SST is higher in the west than in the east. The highest skill is near the tropical Brazilian coast and in the Caribbean Sea, and the lowest skill occurs in the eastern coast. Seasonally, the skill is higher for predictions with ICs in summer or autumn and lower for those with ICs in spring. The CFS poorly predicts the meridional gradient in the tropical Atlantic Ocean. The superiority of the CFS predictions to the persistence forecasts depends on IC month, region, and lead time. The CFS prediction is generally better than the corresponding persistence forecast when the lead time is longer than 3 months. The most predictable pattern of SST in March has the same sign in almost the whole tropical Atlantic. The corresponding pattern in March is dominated by the same sign for geopotential height at 200 hPa in most of the domain and by significant opposite variation for precipitation between the northwestern tropical North Atlantic and the regions from tropical South America to the southwestern tropical North Atlantic. These predictable signals mainly result from the influence of the El Niño–Southern Oscillation (ENSO). The significant values in the most predictable pattern of precipitation in the regions from tropical South America to the southwestern tropical North Atlantic in March are associated with excessive divergence (convergence) at low (high) levels over these regions in the CFS. For the CFS, the predictive skill in the tropical Atlantic Ocean is largely determined by its ability to predict ENSO. This is due to the strong connection between ENSO and the most predictable patterns in the tropical Atlantic Ocean in the model. The higher predictive skill of tropical North Atlantic SST is consistent with the ability of the CFS to predict ENSO on interseasonal time scales, particularly for the ICs in warm months from March to October. In the southeastern ocean, the systematic warm bias is a crucial factor leading to the low skill in this region.


Ocean Science ◽  
2012 ◽  
Vol 8 (5) ◽  
pp. 797-811
Author(s):  
N. Freychet ◽  
E. Cosme ◽  
P. Brasseur ◽  
J.-M. Brankart ◽  
E. Kpemlie

Abstract. Most of oceanographic operational centers use three-dimensional data assimilation schemes to produce reanalyses. We investigate here the benefits of a smoother, i.e. a four-dimensional formulation of statistical assimilation. A square-root sequential smoother is implemented with a tropical Atlantic Ocean circulation model. A simple twin experiment is performed to investigate its benefits, compared to its corresponding filter. Despite model's non-linearities and the various approximations used for its implementation, the smoother leads to a better estimation of the ocean state, both on statistical (i.e. mean error level) and dynamical points of view, as expected from linear theory. Smoothed states are more in phase with the dynamics of the reference state, an aspect that is nicely illustrated with the chaotic dynamics of the North Brazil Current rings. We also show that the smoother efficiency is strongly related to the filter configuration. One of the main obstacles to implement the smoother is then to accurately estimate the error covariances of the filter. Considering this, benefits of the smoother are also investigated with a configuration close to situations that can be managed by operational center systems, where covariances matrices are fixed (optimal interpolation). We define here a simplified smoother scheme, called half-fixed basis smoother, that could be implemented with current reanalysis schemes. Its main assumption is to neglect the propagation of the error covariances matrix, what leads to strongly reduce the cost of assimilation. Results illustrate the ability of this smoother to provide a solution more consistent with the dynamics, compared to the filter. The smoother is also able to produce analyses independently of the observation frequency, so the smoothed solution appears more continuous in time, especially in case of a low frenquency observation network.


Tellus B ◽  
2000 ◽  
Vol 52 (2) ◽  
pp. 620-635 ◽  
Author(s):  
Thierry Elias ◽  
Claude Devaux ◽  
Philippe Goloub ◽  
Maurice Herman

Sign in / Sign up

Export Citation Format

Share Document