Sea-surface temperature and salinity reconstruction for sediment core GeoB5844-2

We present high-resolution paleoceanographic records of surface and deep water conditions within the northern Red Sea covering the last glacial maximum and termination I using alkenone paleothermometry, stable oxygen isotopes, and sediment compositional data. Paleoceanographic records in the restricted desert-surrounded northern Red Sea are strongly affected by the stepwise sea level rise and appear to record and amplify well-known millennial-scale climate events from the North Atlantic realm. During the last glacial maximum (LGM), sea surface temperatures were about 4°C cooler than the late Holocene. Pronounced coolings associated with Heinrich event 1 (~2°C below the LGM level) and the Younger Dryas imply strong atmospheric teleconnections to the North Atlantic. Owing to the restricted exchange with the Indian Ocean, Red Sea salinity is particularly sensitive to changes in global sea level. Paleosalinities exceeded 50 psu during the LGM. A pronounced freshening of the surface waters is associated with the meltwater peaks MWP1a and MWP1b owing to an increased surface-near inflow of "normal" saline water from the Indian Ocean. Vertical delta18O gradients are also increased during these phases, indicating stronger surface water stratification. The combined effect of deglacial changes in sea surface temperature and salinity on water column stratification initiated the formation of two sapropel layers, which were deposited under almost anoxic condition in a stagnant water body.

Exploring the potential of clumped isotope thermometry on coccolith-rich sediments as a sea surface temperature proxy

Understanding past changes in sea surface temperatures (SSTs) is crucial; however, existing proxies for reconstructing past SSTs are hindered by unknown ancient seawater composition (foraminiferal Mg/Ca and d18O), or reflect subsurface temperatures (TEX86) or have a limited applicable temperature range (Uk'37). We examine clumped isotope (D47) thermometry to fossil coccolith-rich material as an SST proxy, as clumped isotopes are independent of original seawater composition and applicable to a wide temperature range and coccolithophores are widespread and dissolution resistant. The D47-derived temperatures from <63, <20, <10 and 2-5 µm size fractions of two equatorial Pacific late Miocene-early Pliocene sediment samples (c1; c2) range between ~18-29 {degree sign}C, with c1 temperatures consistently above c2. Removing the >63 µm fraction removes most non-mixed layer components; however, the D47-derived temperatures display an unexpected slight decreasing trend with decreasing size fraction. This unexpected trend could partly arise because larger coccoliths (5-12 µm) are removed during the size fraction separation process. The c1 and <63 µm c2 D47-derived temperatures are comparable to concurrent Uk'37 SSTs. The <20, <10 and 2-5 µm c2 D47-derived temperatures are consistently cooler than expected. The D47-Uk'37 temperature offset is probably caused by abiotic/diagenetic calcite present in the c2 2-5 µm fraction (~53% by area), which potentially precipitated at bottom water temperatures of ~6 {degree sign}C . Our results indicate that clumped isotopes on coccolith-rich sediment fractions have potential as an SST proxy, particularly in tropical regions, providing that careful investigation of the appropriate size fraction for the region and timescale is undertaken.

Sea-surface temperature reconstruction and calibration-function of sediment cores from the Southern Ocean

We provide a new multivariate calibration-function based on South Atlantic modern assemblages of planktonic foraminifera and atlas water column parameters from the Antarctic Circumpolar Current to the Subtropical Gyre and tropical warm waters (i.e., 60°S to 0°S). Therefore, we used a dataset with the abundance pattern of 35 taxonomic groups of planktonic foraminifera in 141 surface sediment samples. Five factors were taken into consideration for the analysis, which account for 93% of the total variance of the original data representing the regional main oceanographic fronts. The new calibration-function F141-35-5 enables the reconstruction of Late Quaternary summer and winter sea-surface temperatures with a statistical error of ~0.5°C. Our function was verified by its application to a sediment core extracted from the western South Atlantic. The downcore reconstruction shows negative anomalies in sea-surface temperatures during the early-mid Holocene and temperatures within the range of modern values during the late Holocene. This pattern is consistent with available reconstructions.

Extralimital Senegalese species during Marine Isotope Stages 5.5 and 11 in the Canary Islands (29 degrees N): Sea surface temperature estimates

[EN] The presence of Harpa doris Röding, 1798 in marine deposits of the last interglacial period, ~. 130-120. ka (marine isotope stage or MIS 5.5) in the Canary Islands (Gran Canaria, Lanzarote and Fuerteventura) enabled us to compare this occurrence with its present habitat in the Gulf of Guinea and the Cape Verde Islands, well to the south. This comparison leads to the conclusion that sea surface temperatures (SSTs) in the waters around the Canary Islands during the last interglacial period were at least 3.3. °C higher than today. H. doris is found in association with the large gastropod Persististrombus latus (Gmelin, 1791) as well as the coral Siderastrea radians (Pallas, 1766).

Daily MODIS composites of thin-ice thickness and ice-surface temperatures for the Southern Weddell Sea

Based upon high-resolution thermal-infrared Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite imagery in combination with ERA-Interim atmospheric reanalysis data, we derived long-term polynya parameters such as polynya area, thin-ice thickness distribution and ice-production rates from daily cloud-cover corrected thin-ice thickness composites. Our study is based on a thirteen year investigation period (2002-2014) for the austral winter (1 April to 30 September) in the Antarctic Southern Weddell Sea. The focus lies on coastal polynyas which are important hot spots for new-ice formation, bottom-water formation and heat/moisture release into the atmosphere. MODIS has the capability to resolve even very narrow coastal polynyas. Its major disadvantage is the sensor limitation due to cloud cover. We make use of a newly developed and adapted spatial feature reconstruction scheme to account for cloud-covered areas. We find the sea-ice areas in front of Ronne and Brunt Ice Shelf to be the most active with an annual average polynya area of 3018 ± 1298 and 3516 ± 1420 km2 as well as an accumulated volume ice production of 31 ± 13 and 31 ± 12 km**3, respectively. For the remaining four regions, estimates amount to 421 ± 294 km**2 and 4 ± 3 km**3 (Antarctic Peninsula), 1148 ± 432 km**2 and 12 ± 5 km**3 (Iceberg A23A), 901 ± 703 km**2 and 10 ± 8 km**3 (Filchner Ice Shelf) as well as 499 ± 277 km**2 and 5 ± 2 km**3 (Coats Land). Our findings are discussed in comparison to recent studies based on coupled sea-ice/ocean models and passive-microwave satellite imagery, each investigating different parts of the Southern Weddell Sea.

Addressing Sea Surface Salinity retrieval at different spatial resolution. Feasibility study using OCCAM data within SEPS simulator and L2 processor tools

Projecte de recerca elaborat a partir d’una estada a la National Oceanography Centre of Southampton (NOCS), Gran Bretanya, entre maig i juliol del 2006. La possibilitat d’obtenir una estimació precissa de la salinitat marina (SSS) és important per a investigar i predir l’extensió del fenòmen del canvi climàtic. La missió Soil Moisture and Ocean Salinity (SMOS) va ser seleccionada per l’Agència Espacial Europea (ESA) per a obtenir mapes de salinitat de la superfície marina a escala global i amb un temps de revisita petit. Abans del llençament de SMOS es preveu l’anàlisi de la variabilitat horitzontal de la SSS i del potencial de les dades recuperades a partir de mesures de SMOS per a reproduir comportaments oceanogràfics coneguts. L’objectiu de tot plegat és emplenar el buit existent entre les fonts de dades d’entrada/auxiliars fiables i les eines desenvolupades per a simular i processar les dades adquirides segons la configuració de SMOS. El SMOS End-to-end Performance Simulator (SEPS) és un simulador adhoc desenvolupat per la Universitat Politècnica de Catalunya (UPC) per a generar dades segons la configuració de SMOS. Es va utilitzar dades d’entrada a SEPS procedents del projecte Ocean Circulation and Climate Advanced Modeling (OCCAM), utilitzat al NOCS, a diferents resolucions espacials. Modificant SEPS per a poder fer servir com a entrada les dades OCCAM es van obtenir dades de temperatura de brillantor simulades durant un mes amb diferents observacions ascendents que cobrien la zona seleccionada. Les tasques realitzades durant l’estada a NOCS tenien la finalitat de proporcionar una tècnica fiable per a realitzar la calibració externa i per tant cancel•lar el bias, una metodologia per a promitjar temporalment les diferents adquisicions durant les observacions ascendents, i determinar la millor configuració de la funció de cost abans d’explotar i investigar les posibiltats de les dades SEPS/OCCAM per a derivar la SSS recuperada amb patrons d’alta resolució.

Sea state effect on the sea surface emissivity at L-band

In May 1999, the European Space Agency (ESA) selected the Earth Explorer Opportunity Soil Moisture and Ocean Salinity (SMOS) mission to obtain global and frequent soil moisture and ocean salinity maps. SMOS' single payload is the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS), an L-band two-dimensional aperture synthesis radiometer with multiangular observation capabilities. At L-band, the brightness temperature sensitivity to the sea surface salinity (SSS) is low, approximately 0.5 K/psu at 20/spl deg/C, decreasing to 0.25 K/psu at 0/spl deg/C, comparable to that to the wind speed /spl sim/0.2 K/(m/s) at nadir. However, at a given time, the sea state does not depend only on local winds, but on the local wind history and the presence of waves traveling from far distances. The Wind and Salinity Experiment (WISE) 2000 and 2001 campaigns were sponsored by ESA to determine the impact of oceanographic and atmospheric variables on the L-band brightness temperature at vertical and horizontal polarizations. This paper presents the results of the analysis of three nonstationary sea state conditions: growing and decreasing sea, and the presence of swell. Measured sea surface spectra are compared with the theoretical ones, computed using the instantaneous wind speed. Differences can be minimized using an "effective wind speed" that makes the theoretical spectrum best match the measured one. The impact on the predicted brightness temperatures is then assessed using the small slope approximation/small perturbation method (SSA/SPM).

Systematic winter sea-surface temperature biases in the northern Arabian Sea in HiGEM and the CMIP3 models

Analysis of 20th century simulations of the High resolution Global Environment Model (HiGEM) and the Third Coupled Model Intercomparison Project (CMIP3) models shows that most have a cold sea-surface temperature (SST) bias in the northern Arabian Sea during boreal winter. The association between Arabian Sea SST and the South Asian monsoon has been widely studied in observations and models, with winter cold biases known to be detrimental to rainfall simulation during the subsequent monsoon in coupled general circulation models (GCMs). However, the causes of these SST biases are not well understood. Indeed this is one of the first papers to address causes of the cold biases. The models show anomalously strong north-easterly winter monsoon winds and cold air temperatures in north-west India, Pakistan and beyond. This leads to the anomalous advection of cold, dry air over the Arabian Sea. The cold land region is also associated with an anomalously strong meridional surface temperature gradient during winter, contributing to the enhanced low-level convergence and excessive precipitation over the western equatorial Indian Ocean seen in many models.

Extended optimal estimation techniques for sea surface temperature from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI)

Sea surface temperature (SST) can be estimated from day and night observations of the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) by optimal estimation (OE). We show that exploiting the 8.7 μm channel, in addition to the “traditional” wavelengths of 10.8 and 12.0 μm, improves OE SST retrieval statistics in validation. However, the main benefit is an improvement in the sensitivity of the SST estimate to variability in true SST. In a fair, single-pixel comparison, the 3-channel OE gives better results than the SST estimation technique presently operational within the Ocean and Sea Ice Satellite Application Facility. This operational technique is to use SST retrieval coefficients, followed by a bias-correction step informed by radiative transfer simulation. However, the operational technique has an additional “atmospheric correction smoothing”, which improves its noise performance, and hitherto had no analogue within the OE framework. Here, we propose an analogue to atmospheric correction smoothing, based on the expectation that atmospheric total column water vapour has a longer spatial correlation length scale than SST features. The approach extends the observations input to the OE to include the averaged brightness temperatures (BTs) of nearby clear-sky pixels, in addition to the BTs of the pixel for which SST is being retrieved. The retrieved quantities are then the single-pixel SST and the clear-sky total column water vapour averaged over the vicinity of the pixel. This reduces the noise in the retrieved SST significantly. The robust standard deviation of the new OE SST compared to matched drifting buoys becomes 0.39 K for all data. The smoothed OE gives SST sensitivity of 98% on average. This means that diurnal temperature variability and ocean frontal gradients are more faithfully estimated, and that the influence of the prior SST used is minimal (2%). This benefit is not available using traditional atmospheric correction smoothing.

Estimation of sea surface temperature from the Spinning Enhanced Visible and Infra Red Imager, improved using numerical weather prediction

Most of the operational Sea Surface Temperature (SST) products derived from satellite infrared radiometry use multi-spectral algorithms. They show, in general, reasonable performances with root mean square (RMS) residuals around 0.5 K when validated against buoy measurements, but have limitations, particularly a component of the retrieval error that relates to such algorithms' limited ability to cope with the full variability of atmospheric absorption and emission. We propose to use forecast atmospheric profiles and a radiative transfer model to simulate the algorithmic errors of multi-spectral algorithms. In the practical case of SST derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG), we demonstrate that simulated algorithmic errors do explain a significant component of the actual errors observed for the non linear (NL) split window algorithm in operational use at the Centre de Météorologie Spatiale (CMS). The simulated errors, used as correction terms, reduce significantly the regional biases of the NL algorithm as well as the standard deviation of the differences with drifting buoy measurements. The availability of atmospheric profiles associated with observed satellite-buoy differences allows us to analyze the origins of the main algorithmic errors observed in the SEVIRI field of view: a negative bias in the inter-tropical zone, and a mid-latitude positive bias. We demonstrate how these errors are explained by the sensitivity of observed brightness temperatures to the vertical distribution of water vapour, propagated through the SST retrieval algorithm.

Sea surface temperature estimation from the Geostationary Operational Environmental Satellite 12 (GOES-12)

This paper describes the techniques used to obtain sea surface temperature (SST) retrievals from the Geostationary Operational Environmental Satellite 12 (GOES-12) at the National Oceanic and Atmospheric Administration’s Office of Satellite Data Processing and Distribution. Previous SST retrieval techniques relying on channels at 11 and 12 μm are not applicable because GOES-12 lacks the latter channel. Cloud detection is performed using a Bayesian method exploiting fast-forward modeling of prior clear-sky radiances using numerical weather predictions. The basic retrieval algorithm used at nighttime is based on a linear combination of brightness temperatures at 3.9 and 11 μm. In comparison with traditional split window SSTs (using 11- and 12-μm channels), simulations show that this combination has maximum scatter when observing drier colder scenes, with a comparable overall performance. For daytime retrieval, the same algorithm is applied after estimating and removing the contribution to brightness temperature in the 3.9-μm channel from solar irradiance. The correction is based on radiative transfer simulations and comprises a parameterization for atmospheric scattering and a calculation of ocean surface reflected radiance. Potential use of the 13-μm channel for SST is shown in a simulation study: in conjunction with the 3.9-μm channel, it can reduce the retrieval error by 30%. Some validation results are shown while a companion paper by Maturi et al. shows a detailed analysis of the validation results for the operational algorithms described in this present article.

Sea surface temperature from a geostationary satellite by optimal estimation

Optimal estimation (OE) is applied as a technique for retrieving sea surface temperature (SST) from thermal imagery obtained by the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on Meteosat 9. OE requires simulation of observations as part of the retrieval process, and this is done here using numerical weather prediction fields and a fast radiative transfer model. Bias correction of the simulated brightness temperatures (BTs) is found to be a necessary step before retrieval, and is achieved by filtered averaging of simulations minus observations over a time period of 20 days and spatial scale of 2.5° in latitude and longitude. Throughout this study, BT observations are clear-sky averages over cells of size 0.5° in latitude and longitude. Results for the OE SST are compared to results using a traditional non-linear retrieval algorithm (“NLSST”), both validated against a set of 30108 night-time matches with drifting buoy observations. For the OE SST the mean difference with respect to drifter SSTs is − 0.01 K and the standard deviation is 0.47 K, compared to − 0.38 K and 0.70 K respectively for the NLSST algorithm. Perhaps more importantly, systematic biases in NLSST with respect to geographical location, atmospheric water vapour and satellite zenith angle are greatly reduced for the OE SST. However, the OE SST is calculated to have a lower sensitivity of retrieved SST to true SST variations than the NLSST. This feature would be a disadvantage for observing SST fronts and diurnal variability, and raises questions as to how best to exploit OE techniques at SEVIRI's full spatial resolution.