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Coral reefs are facing severe threats and are at risk of accelerated decline due to climate change‐induced changes in their environment. Ongoing efforts to understand the mechanisms of coral response to warming rely on multiple sources of temperature data. Yet, it remains uncertain whether the Sea Surface Temperature (SST) data used for coral reef studies are consistent among different data products, despite potential implications for conservation. A better understanding of the consistency among the different SST data applied to coral reefs may facilitate the fusion of data into a standard product. This will improve monitoring and understanding of the impact of global warming on coral reefs. Four types of SST data across North‐Western and South‐Western Australia are compared to assess their differences and ability to observe high thermal stress during historical coral bleaching events. The four SST data sources included those derived from Global Circulation Models, NOAA CoralTemp SST product, ESA CCI SST product, and coral core derived SST. Coral bleaching risk indicators, Degree Heating Week (DHW), and Degree Heating Month (DHM) were calculated using these sources and compared for consistency. DHW and DHM were inconsistent among data sets and did not accurately reflect high thermal stress metrics during moderate and severe bleaching events. Some reefs did not experience bleaching in spite of high DHWs and DHMs, suggesting a mismatch in data scales, or perhaps other oceanographic factors and coral adaptation. By exploring the differences and similarities among these four data sources, this study highlights the need to compare existing indicators of thermal stress from different data sets. Plain Language Summary: Climate change and warming have resulted in global coral bleaching events, severely compromising our environment's health. Monitoring the changes in ocean temperatures around them is essential to maximizing our efforts to protect them. Different ocean temperature data products exist and are being used without understanding their differences. To highlight these differences, the present study compares historical warming from climate models and remote and in situ sensors and known bleaching events on five reefs across Western Australia. Key Points: Temperature data sources did not provide consistent risk indicators for coral bleachingAcross five reefs, coral bleaching risk indicators differed in their ability to predict the observed coral bleaching eventsTemperature data in daily and monthly temporal resolutions differed in the accuracy of coral bleaching risk indicators [ABSTRACT FROM AUTHOR]

Abstract: Lack of reliable observational metadata represents a key barrier to understanding sea surface temperature (SST) measurement biases, a large contributor to uncertainty in the global surface record. We present a method to identify SST measurement practice by comparing the observed SST diurnal cycle from individual ships with a reference from drifting buoys under similar conditions of wind and solar radiation. Compared to existing estimates, we found a larger number of engine room‐intake (ERI) reports post–World War II and in the period 1960–1980. Differences in the inferred mixture of observations lead to a systematic warmer shift of the bias adjusted SST anomalies from 1980 compared to previous estimates, while reducing the ensemble spread. Changes in mean field differences between bucket and ERI SST anomalies in the Northern Hemisphere over the period 1955–1995 could be as large as 0.5°C and are not well reproduced by current bias adjustment models. [ABSTRACT FROM AUTHOR]

Transfusion-related acute lung injury (TRALI) is a life-threatening complication of blood product transfusion characterized by sudden onset hypoxemic respiratory failure with bilateral lung infiltrates and non-cardiogenic pulmonary edema developing within 6 hours of transfusion. It is believed to be under-recognized, particularly among preterm neonates in whom co-existing developmental lung disease adds diagnostic complexity. Here we report the case of a preterm neonate who developed TRALI during a blood transfusion following PDA ligation. [ABSTRACT FROM AUTHOR]

Uncertainty in the bias adjustments applied to historical sea-surface temperature (SST) measurements made using buckets are thought to make the largest contribution to uncertainty in global surface temperature trends. Measurements of the change in temperature of water samples in wooden and canvas buckets are compared with the predictions of models that have been used to estimate bias adjustments applied in widely used gridded analyses of SST. The results show that the models are broadly able to predict the dependence of the temperature change of the water over time on the thermal forcing and the bucket characteristics: volume and geometry; structure and material. Both the models and the observations indicate that the most important environmental parameter driving temperature biases in historical bucket measurements is the difference between the water and wet-bulb temperatures. However, assumptions inherent in the derivation of the models are likely to affect their applicability. We observed that the water sample needed to be vigorously stirred to agree with results from the model, which assumes well-mixed conditions. There were inconsistencies between the model results and previous measurements made in a wind tunnel in 1951. The model assumes non-turbulent incident flow and consequently predicts an approximately square-root dependence on airflow speed. The wind tunnel measurements, taken over a wide range of airflows, showed a much stronger dependence. In the presence of turbulence the heat transfer will increase with the turbulent intensity; for measurements made on ships the incident airflow is likely to be turbulent and the intensity of the turbulence is always unknown. Taken together, uncertainties due to the effects of turbulence and the assumption of well-mixed water samples are expected to be substantial and may represent the limiting factor for the direct application of these models to adjust historical SST observations. [ABSTRACT FROM AUTHOR]

We analyse the regional variability in observed sea surface height (SSH), sea surface temperature (SST) and ocean colour (OC) from the ESA Climate Change Initiative datasets over the period 1993-2011. The analysis focuses on the signature of the ocean large-scale climate fluctuations driven by the atmospheric forcing and do not address the mesoscale variability. We use the ECCO version 4 ocean reanalysis to unravel the role of ocean transport and surface buoyancy fluxes in the observed SSH, SST and OC variability. We show that the SSH regional variability is dominated by the steric effect (except at high latitude) and is mainly shaped by ocean heat transport divergences with some contributions from the surface heat fluxes forcing that can be significant regionally (confirming earlier results). This is in contrast with the SST regional variability, which is the result of the compensation of surface heat fluxes by ocean heat transport in the mixed layer and arises from small departures around this background balance. Bringing together the results of SSH and SST analyses, we show that SSH and SST bear some common variability. This is because both SSH and SST variability show significant contributions from the surface heat fluxes forcing. It is evidenced by the high correlation between SST and buoyancy-forced SSH almost everywhere in the ocean except at high latitude. OC, which is determined by phytoplankton biomass, is governed by the availability of light and nutrients that essentially depend on climate fluctuations. For this reason, OC shows significant correlation with SST and SSH. We show that the correlation with SST displays the same pattern as the correlation with SSH with a negative correlation in the tropics and subtropics and a positive correlation at high latitude. We discuss the reasons for this pattern. [ABSTRACT FROM AUTHOR]

A statistical model is derived relating the diurnal variation of sea surface temperature (SST) to the net surface heat flux and surface wind speed from a numerical weather prediction (NWP) model. The model is derived using fluxes and winds from the European Centre for Medium-Range Weather Forecasting (ECMWF) NWP model and SSTs from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In the model, diurnal warming has a linear dependence on the net surface heat flux integrated since (approximately) dawn and an inverse quadratic dependence on the maximum of the surface wind speed in the same period. The model coefficients are found by matching, for a given integrated heat flux, the frequency distributions of the maximum wind speed and the observed warming. Diurnal cooling, where it occurs, is modelled as proportional to the integrated heat flux divided by the heat capacity of the seasonal mixed layer. The model reproduces the statistics (mean, standard deviation, and 95-percentile) of the diurnal variation of SST seen by SEVIRI and reproduces the geographical pattern of mean warming seen by the Advanced Microwave Scanning Radiometer (AMSR-E). We use the functional dependencies in the statistical model to test the behaviour of two physical model of diurnal warming that display contrasting systematic errors. [ABSTRACT FROM AUTHOR]

The sensitivity of the biological parameters in a nutrient-phytoplankton-zooplankton-detritus (NPZD) model in the calculation of the air-sea CO2 flux, primary production and detrital export is analysed. We explore the effect on these outputs of variation in the values of the twenty parameters that control ocean ecosystem growth in a 1-D formulation of the UK Met Office HadOCC NPZD model used in GCMs. We use and compare the results from one-at-a-time and all-at-a-time perturbations performed at three sites in the EuroSITES European Ocean Observatory Network: the Central Irminger Sea (60° N 40° W), the Porcupine Abyssal Plain (49° N 16° W) and the European Station for Time series in the Ocean Canary Islands (29° N 15° W). Reasonable changes to the values of key parameters are shown to have a large effect on the calculation of the air-sea CO2 flux, primary production, and export of biological detritus to the deep ocean. Changes in the values of key parameters have a greater effect in more productive regions than in less productive areas. The most sensitive parameters are generally found to be those controlling well-established ocean ecosystem parameterisations widely used in many NPZD-type models. The air-sea CO2 flux is most influenced by variation in the parameters that control phytoplankton growth, detrital sinking and carbonate production by phytoplankton (the rain ratio). Primary production is most sensitive to the parameters that define the shape of the photosynthesis-irradiance curve. Export production is most sensitive to the parameters that control the rate of detrital sinking and the remineralisation of detritus. [ABSTRACT FROM AUTHOR]

The sensitivity of the biological parameters in a nutrient-phytoplankton-zooplankton-detritus (NPZD) model in the calculation of the air-sea CO2 flux, primary production and detrital export is analysed. The NPZD model is the Hadley Centre Ocean Carbon Cycle model (HadOCC) from the UK Met Office, used in the Hadley Centre Coupled Model 3 (HadCM3) and FAst Met Office and Universities Simulator (FAMOUS) GCMs. Here, HadOCC is coupled to the 1-D General Ocean Turbulence Model (GOTM) and forced with European Centre for Medium-Range Weather Forecasting meteorology to undertake a sensitivity analysis of its twenty biological parameters. Analyses are performed at three sites in the EuroSITES European Ocean Observatory Network: the Central Irminger Sea (60° N 40° W), the Porcupine Abyssal Plain (49° N 16° W) and the European Station for Time series in the Ocean Canary Islands (29° N 15° W) to assess variability in parameter sensitivities at different locations in the North Atlantic Ocean. Reasonable changes to the values of key parameters are shown to have a large effect on the calculation of the air-sea CO2 flux, primary production, and export of biological detritus to the deep ocean. Changes in the values of key parameters have a greater effect in more productive regions than in less productive areas. We perform the analysis using one-at-a-time perturbations and using a statistical emulator, and compare results. The most sensitive parameters are generic to many NPZD ocean ecosystem models. The air-sea CO2 flux is most influenced by variation in the parameters that control phytoplankton growth, detrital sinking and carbonate production by phytoplankton (the rain ratio). Primary production is most sensitive to the parameters that define the shape of the photosythesis-irradiance curve. Export production is most sensitive to the parameters that control the rate of detrital sinking and the remineralisation of detritus. [ABSTRACT FROM AUTHOR]

A statistical model is derived relating the diurnal variation of sea surface temperature (SST) to the net surface heat flux and surface wind speed from a numerical weather prediction (NWP) model. The model is derived using fluxes and winds from the European Centre for Medium-Range Weather Forecasting (ECMWF) NWP model and SSTs from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In the model, diurnal warming has a linear dependence on the net surface heat flux integrated since (approximately) dawn and an inverse quadratic dependence on the maximum of the surface wind speed in the same period. The model coefficients are found by matching, for a given integrated heat flux, the frequency distributions of the maximum wind speed deceedance and the observed warming exceedance. Diurnal cooling, where it occurs, is modelled as proportional to the integrated heat efflux divided by the heat capacity of the seasonal mixed layer. The model reproduces the statistics (mean, standard deviation, and 95-percentile) of the diurnal variation of SST seen by SEVIRI and reproduces the geographical pattern of mean warming seen by the Advanced Microwave Scanning Radiometer (AMSR-E). We use the functional dependencies in the statistical model to test the behaviour of two physical model of diurnal warming that display contrasting systematic errors. [ABSTRACT FROM AUTHOR]

The effect of diurnal variations in sea surface temperature (SST) on the air-sea flux of CO2 over the central Atlantic ocean and Mediterranean Sea (60 S-60 N, 60W-45 E) is evaluated for 2005-2006. We use high spatial resolution hourly satellite ocean skin temperature data to determine the diurnal warming (ΔSST). The CO2 flux is then computed using three different temperature fields - a foundation temperature (Tf , measured at a depth where there is no diurnal variation), Tf plus the hourly ΔSST and Tf plus the monthly average of the ΔSSTs. This is done in conjunction with a physically-based parameterisation for the gas transfer velocity (NOAA-COARE). The differences between the fluxes evaluated for these three different temperature fields quantify the effects of both diurnal warming and diurnal covariations. We find that including diurnal warming increases the CO2 flux out of this region of the Atlantic for 2005-2006 from 9.6 Tg C a-1 to 30.4 Tg Ca-1 (hourly ΔSST) and 31.2 TgC a-1 (monthly average of ΔSST measurements). Diurnal warming in this region, therefore, has a large impact on the annual net CO2 flux but diurnal covariations are negligible. However, in this region of the Atlantic the uptake and outgassing of CO2 is approximately balanced over the annual cycle, so although we find diurnal warming has a very large effect here, the Atlantic as a whole is a very strong carbon sink (e.g. -920 TgC a-1 Takahashi et al., 2002) making this is a small contribution to the Atlantic carbon budget. [ABSTRACT FROM AUTHOR]

Long-term temporal averaging of meteorological data, such as wind speed and air pressure, can cause large errors in air-sea carbon flux estimates. Other researchers have already shown that time averaging of wind speed data creates large errors in flux due to the non-linear dependence of the gas transfer velocity on wind speed (Bates and Merlivat, 2001). However, in general, wind speed is negatively correlated with air pressure, and a given fractional change in the pressure of dry air produces an equivalent fractional change in the atmospheric partial pressure of carbon dioxide (pCO2air). Thus low pressure systems cause a drop in pCO2air, which together with the associated high winds, promotes outgassing/reduces uptake of CO2 from the ocean. Here we quantify the errors in global carbon flux estimates caused by using monthly or climatological pressure data to calculate pCO2air (and thus ignoring the covariance of wind and pressure) over the period 1990-1999, using two common parameterisations for gas transfer velocity. Results show that on average, compared with estimates made using 6 hourly pressure data, the global oceanic sink is systematically overestimated by 7% (W92) and 10% (WM99) when monthly mean pressure is used, and 9% (W92) and 12% (WM99) when climatological pressure is used. [ABSTRACT FROM AUTHOR]

FLake, a 1-dimensional freshwater lake model, is tuned for 244 globally distributed large lakes using lake surface water temperatures (LSWTs) derived from Along-Track Scanning Radiometers (ATSRs). The model, tuned using only 3 lake properties; lake depth, albedo (snow and ice) and light extinction co-efficient, substantially improves the measured biases in various features of the LSWT annual cycle, including the LSWTs of saline and high altitude lakes. The daily mean absolute differences (MAD) and the spread of differences (± standard deviations) across the trial seasonally ice covered lakes (lakes with a lake-mean LSWT remaining below 1 °C for part of the annual cycle) is reduced from 3.01±2.25 °C (pre-tuning) to 0.84±0.51 °C (post-tuning). For nonseasonally ice-covered trial lakes (lakes with a lake-mean LSWT remaining above 1 °C throughout its annual cycle), the average daily mean absolute difference (MAD) is reduced from 3.55±3.20 °C to 0.96±0.63 °C. The post tuning results for the trial lakes (35 lakes) are highly representative of the post tuning results of the 244 lakes. The sensitivity of the summer LSWTs of deeper lakes to changes in the timing of ice-off is demonstrated. The modelled summer LSWT response to changes in ice-off timing is found to be strongly affected by lake depth and latitude, explaining 0.50 (R²adj, p = 0.001) of the inter-lake variance in summer LSWTs. Lake depth alone explains 0.35 (p = 0.003) of the variance. The tuning approach undertaken in this study, over comes the obstacle of the lack of available lake characteristic information (snow and ice albedo and light extinction co-efficient) for individual lakes. Furthermore, the tuned values for lake depth, snow and ice albedo and light extinction co-efficient for the 244 lakes provide guidance for improving LSWTs modelling in FLake. [ABSTRACT FROM AUTHOR]

Background: Prior studies offer conflicting findings on whether Alzheimer's disease (AD) is associated with an increased risk of hospitalization.Methods: We investigated AD and hospitalization in the Washington Heights-Inwood Columbia Aging Project (WHICAP), a community-based study of 2,334 elders in New York City. In 1996, an electronic medical records system was established that allows an e-mail alert to be sent to the research team whenever WHICAP subjects are admitted to Columbia-Presbyterian Medical Center (CPMC), the site of hospital care for the majority of subjects.Results: Of the WHICAP cohort, 13.1% was admitted to CPMC in 21 months of follow-up; 17.5% of AD patients and 11.9% of unaffected subjects were admitted (p<.01). Multivariate logistic regression models showed that more advanced AD (Clinical Dementia Rating scale 3+) was a significant risk factor for hospitalization independently of age, gender, education, comorbid medical conditions, and death in the follow-up period (OR 2.3; 95% CI: 1.1, 4.6); subjects with mild or moderate AD did not show a significantly elevated risk. The prevalence of psychiatric symptoms did not differ between AD subjects who were hospitalized in the reporting period and AD subjects who were not hospitalized. Infectious disease was a more common discharge diagnosis for subjects with AD (p<.05).Conclusions: In this community-based cohort, subjects with severe AD were more likely to be hospitalized than unaffected subjects. The increased use of hospital care by these AD patients appears to be specific to AD but is not a result of psychiatric morbidity or end-of-life care. Rather, a greater risk of medical complications that require hospital care, especially infections, appears to be characteristic of severe AD. [ABSTRACT FROM AUTHOR]

Surface temperature is a key aspect of weather and climate, but the term may refer to different quantities that play interconnected roles and are observed by different means. In a community-based activity in June 2012, the EarthTemp Network brought together 55 researchers from five continents to improve the interaction between scientific communities who focus on surface temperature in particular domains, to exploit the strengths of different observing systems and to better meet the needs of different communities. The workshop identified key needs for progress towards meeting scientific and societal requirements for surface temperature understanding and information which are presented in this community paper. A "whole-Earth" perspective is required with more integrated, collaborative approaches to observing and understanding Earth's various surface temperatures. It is necessary to build understanding of the relationships between different surface temperatures, where presently inadequate, and undertake large-scale systematic intercomparisons. Datasets need to be easier to obtain and exploit for a wide constituency of users, with the differences and complementarities communicated in readily understood terms, and realistic and consistent uncertainty information provided. Steps were also recommended to curate and make available data that are presently inaccessible, develop new observing systems and build capacities to accelerate progress in the accuracy and usability of surface temperature datasets. [ABSTRACT FROM AUTHOR]

We report on the characterization of planar waveguides formed in the Raman-active crystal KGd(WO4 )2 using swift carbon, fluorine, and oxygen ion irradiation. The characterization of the waveguiding regions was performed using high-resolution niicroreflectivity and micro-Raman spectroscopy. The high-resolution microreflectivity measurement fully characterizes the refractive index profile of the barrier formed by amorphization of the crystal and detects other index variations not detected by the m-line technique. Raman spectroscopy measurements reveal details of the Raman properties of the crystal in the waveguiding region in relation to the rest of the sample for the different ion irradiations. Both of these measurement techniques are shown to be important for use of KGd(WO4)2 in integrated Raman-active devices. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]