We compare several statistical routines that may be used to calculate d 18 O sw and SSS from paired coral Sr/Ca and d 18 O measurements. Typically, the d 18 O coral -SST relationship is estimated by linear regression of coral d 18 O vs. SST. If this method is applied, evidence should be given that at a particular site SST and SSS do not co-vary. In the tropical oceans, SST and d 18 O sw (SSS) often co-vary, and this will bias the estimate of the regression slope of d 18 O coral -SST. Using a stochastic model, we show that covariance leads to a bias in the coefficients of the univariate regression equations. As the slope of the d 18 O coral -SST relationship has known, we propose to insert this value for c 1 in the regression models. This requires that the constants of the regression equations are removed. To omit the constants, we propose to center the regression equations (i.e., to remove the mean values from the variables). The statistical error propagation is calculated to assess our ability to resolve past variations in d 18 O sw (SSS). At Tahiti, we find that the combined analytical uncertainties of coral d 18 O and Sr/Ca equal the amplitude of the seasonal cycle of d 18 O sw (SSS). Therefore, we cannot resolve the seasonal cycle of SSS at Tahiti. At Timor, the error of reconstructed d 18 O sw (SSS) is lower than the magnitude of seasonal variations of d 18 O sw (SSS), and the seasonal cycle of d 18 O sw (SSS) can be resolved.

The last interglaciation (-130 to 116 ka) is a time period with a strong astronomically induced seasonal forcing of insolation compared to the present. Proxy records indicate a significantly different climate to that of the modern, in particular Arctic summer warming and higher eustatic sea level. Because the forcings are relatively well constrained, it provides an opportunity to test numerical models which are used for future climate prediction. In this paper we compile a set of climate model simulations of the early last interglaciation (130 to 125 ka), encompassing a range of model complexities. We compare the simulations to each other and to a recently published compilation of last interglacial temperature estimates.We show that the annual mean response of the models is rather small, with no clear signal in many regions. However, the seasonal response is more robust, and there is significant agreement amongst models as to the regions of warming vs cooling. However, the quantitative agreement of the model simulations with data is poor, with the models in general underestimating the magnitude of response seen in the proxies. Taking possible seasonal biases in the proxies into account improves the agreement, but only marginally. However, a lack of uncertainty estimates in the data does not allow us to draw firm conclusions. Instead, this paper points to several ways in which both modelling and data could be improved, to allow a more robust model-data comparison. © Author(s) 2013

Abstract. We compare the ocean temperature evolution of the Holocene as simulated by climate models and reconstructed from marine temperature proxies. We use transient simulations from a coupled atmosphere–ocean general circulation model, as well as an ensemble of time slice simulations from the Paleoclimate Modelling Intercomparison Project. The general pattern of sea surface temperature (SST) in the models shows a high-latitude cooling and a low-latitude warming. The proxy dataset comprises a global compilation of marine alkenone- and Mg/Ca-derived SST estimates. Independently of the choice of the climate model, we observe significant mismatches between modelled and estimated SST amplitudes in the trends for the last 6000 yr. Alkenone-based SST records show a similar pattern as the simulated annual mean SSTs, but the simulated SST trends underestimate the alkenone-based SST trends by a factor of two to five. For Mg/Ca, no significant relationship between model simulations and proxy reconstructions can be detected. We test if such discrepancies can be caused by too simplistic interpretations of the proxy data. We explore whether consideration of different growing seasons and depth habitats of the planktonic organisms used for temperature reconstruction could lead to a better agreement of model results with proxy data on a regional scale. The extent to which temporal shifts in growing season or vertical shifts in depth habitat can reduce model–data misfits is determined. We find that invoking shifts in the living season and habitat depth can remove some of the model–data discrepancies in SST trends. Regardless whether such adjustments in the environmental parameters during the Holocene are realistic, they indicate that when modelled temperature trends are set up to allow drastic shifts in the ecological behaviour of planktonic organisms, they do not capture the full range of reconstructed SST trends. Results indicate that modelled and reconstructed temperature trends are to a large degree only qualitatively comparable, thus providing a challenge for the interpretation of proxy data as well as the model sensitivity to orbital forcing.

The Chagos Archipelago was designated a no-take marine protected area (MPA) in 2010; it covers 550 000 km2, with more than 60 000 km2 shallow limestone platform and reefs. This has doubled the global cover of such MPAs.It contains 25–50% of the Indian Ocean reef area remaining in excellent condition, as well as the world’s largest contiguous undamaged reef area. It has suffered from warming episodes, but after the most severe mortality event of 1998, coral cover was restored after 10 years.Coral reef fishes are orders of magnitude more abundant than in other Indian Ocean locations, regardless of whether the latter are fished or protected.Coral diseases are extremely low, and no invasive marine species are known.Genetically, Chagos marine species are part of the Western Indian Ocean, and Chagos serves as a ‘stepping-stone’ in the ocean.The no-take MPA extends to the 200 nm boundary, and. includes 86 unfished seamounts and 243 deep knolls as well as encompassing important pelagic species.On the larger islands, native plants, coconut crabs, bird and turtle colonies were largely destroyed in plantation times, but several smaller islands are in relatively undamaged state.There are now 10 ‘important bird areas’, coconut crab density is high and numbers of green and hawksbill turtles are recovering.Diego Garcia atoll contains a military facility; this atoll contains one Ramsar site and several ‘strict nature reserves’. Pollutant monitoring shows it to be the least polluted inhabited atoll in the world. Today, strict environmental regulations are enforced.Shoreline erosion is significant in many places. Its economic cost in the inhabited part of Diego Garcia is very high, but all islands are vulnerable.Chagos is ideally situated for several monitoring programmes, and use is increasingly being made of the archipelago for this purpose.

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[1] This study provides the first monthly resolved, 41-year record of geochemical variations (d 18 O and Sr/Ca) in a fast-growing Diploria strigosa brain coral from Guadeloupe, Caribbean Sea. Linear regression yields a significant correlation of coral Sr/Ca (d O; p < 0.0001) demonstrates the applicability of geochemical proxies measured from Diploria strigosa corals as reliable recorders for interannual temperature variability. Both coral proxies are highly correlated with annual and seasonal mean time series of major SST indices in the northern tropical Atlantic (e.g., r = À0.71 for correlation between the index of North Tropical Atlantic SST anomaly and Sr/Ca, and r = À0.70 for d 18 O; mean annual scale, p < 0.001). Furthermore, the coral proxies capture the impact of the El Niño-Southern Oscillation on the northern tropical Atlantic during boreal spring. Thus fast-growing Diploria strigosa corals are a promising new archive for the Atlantic Ocean.

The end of the last interglacial period, ~118 kyr ago, was characterized by substantial ocean circulation and climate perturbations resulting from instabilities of polar ice sheets. These perturbations are crucial for a better understanding of future climate change. The seasonal temperature changes of the tropical ocean, however, which play an important role in seasonal climate extremes such as hurricanes, floods and droughts at the present day, are not well known for this period that led into the last glacial. Here we present a monthly resolved snapshot of reconstructed sea surface temperature in the tropical North Atlantic Ocean for 117.7±0.8 kyr ago, using coral Sr/Ca and δ18O records. We find that temperature seasonality was similar to today, which is consistent with the orbital insolation forcing. Our coral and climate model results suggest that temperature seasonality of the tropical surface ocean is controlled mainly by orbital insolation changes during interglacials.