Monitoring and interpreting the ocean uptake of atmospheric CO2

The oceans are an important sink for anthropogenically produced CO(2), and on time scales longer than a century they will be the main repository for the CO(2) that humans are emitting. Our knowledge of how ocean uptake varies (regionally and temporally) and the processes that control it is currently observation-limited. Traditionally, and based on sparse observations and models at coarse resolution, ocean uptake has been thought to be relatively invariant. However, in the few places where we have enough observations to define the uptake over periods of many years or decades, it has been found to change substantially at basin scales, responding to indices of climate variability. We illustrate this for three well-studied regions: the equatorial Pacific, the Indian Ocean sector of the Southern Ocean, and the North Atlantic. A lesson to take from this is that ocean uptake is sensitive to climate (regionally, but presumably also globally). This reinforces the expectation that, as global climate changes in the future owing to human influences, ocean uptake of CO(2) will respond. To evaluate and give early warning of such carbon-climate feedbacks, it is important to track trends in both ocean and land sinks for CO(2). Recent coordinated observational programmes have shown that, by organization of an observing network, the atmosphere-ocean flux of CO(2) can, in principle, be accurately tracked at seasonal or better resolution, over at least the Northern Hemisphere oceans. This would provide a valuable constraint on both the ocean and (by difference) land vegetation sinks for atmospheric CO(2).     

Understanding the impact of climate change on pavements with CMIP5, system dynamics and simulation

There is an increasing awareness regarding the impact of climate change on performance and durability of pavements. The objective of this paper is to present a framework of using the global climate forecasts, system dynamics and Monte Carlo analyses to evaluate the rate of change in climate change parameters and understand the impact of climate change on pavements. Changes in maximum air temperature and annual precipitation levels were determined for seven cities across the US, for RCP 4.5 and RCP 8.5 scenarios, using downscaled CMIP5 model output. A system dynamics model was utilised to link the changes in climate change-related parameters to deterioration and life of pavements. Percent of roads that need rehabilitation at different times, up to a time span of 100 years were predicted with simulations of the system dynamics model. Using regression equations developed on the basis of the output data, Monte Carlo analyses were then conducted to obtain distribution and 90% confidence intervals for percent of roads requiring rehabilitation at 50 and 100 years, for no climate change, climate change and climate change with different mitigation scenarios. The results clearly show the significant increase in deterioration of roads as a result of predicted climate change, compared to a ‘no climate change’ scenario. The conclusions are that the CMIP5 model output can be utilised successfully to obtain statistical data regarding climate change parameters that are relevant for pavement design and that a sequential use of the tool, system dynamic and Monte Carlo simulation can be utilised by public agencies to estimate climate change-related parameters for different scenarios, the risk of negative impact of such change on pavement lives and evaluate the effectiveness of various mitigation approaches. This can help them in making justifiable decisions regarding the consideration of climate changes in design of pavements.     

A Robustness Analysis of CMIP5 Models over the East Asia-Western North Pacific Domain

The Coupled Model Intercomparison Project (CMIP) is an international community-based infrastructure that supports climate model intercomparison, climate variability, climate prediction, and climate projection. Improving the performance of climate models over East Asia and the western North Pacific has been a challenge for the climate-modeling community. In this paper, we provide a synthesis robustness analysis of the climate models participating in CMIP-Phase 5 (CMIP5). The strengths and weaknesses of the CMIP5 models are assessed from the perspective of climate mean state, interannual variability, past climate change during the mid-Pliocene (MP) and the last millennium, and climate projection. The added values of regional climate models relative to the driving global climate models are also assessed. Although an encouraging increase in credibility and an improvement in the simulation of mean states, interannual variability, and past climate changes are visible in the progression from CMIP3 to CMIP5, some previously noticed biases such as the ridge position of the western North Pacific subtropical high and the associated rainfall bias are still evident in CMIP5 models. Weaknesses are also evident in simulations of the interannual amplitude, such as El Niño-Southern Oscillation (ENSO)-monsoon relationships. Coupled models generally show better results than standalone atmospheric models in simulating both mean states and interannual variability. Multi-model intercomparison indicates significant uncertainties in the future projection of climate change, although precipitation increases consistently across models constrained by the Clausius-Clapeyron relation. Regional ocean-atmosphere coupled models are recommended for the dynamical downscaling of climate change projections over the East Asia-western North Pacific domain.     

Recent relative sea-level trends: an attempt to quantify the forcing factors

Local sea-level is affected by a number of forcing factors, which all contribute to the trends observed by tide gauges. Here we use the fingerprints of main factors contributing to secular sea-level trends to construct an initial empirical model that explains best the trends in sea-level as recorded by the large number of coastal tide gauges over the last 50 years. The forcing factors considered include steric changes derived from observations, post-glacial rebound as predicted by geophysical models and mass changes in the Greenland and Antarctic ice sheets as predicted by the static sea-level equation. The approximation of the observed spatial pattern of sea-level trends through a model based on the spatial fingerprints of the main forcing factors fully utilizes the information contents of the available observations and models and allows the interpolation of the sea-level trends between the tide gauges. As a result, we obtain the global picture of sea-level trends due to the forcing factors accounted for in the analysis. Moreover, we derive constraints on the mass changes of the large ice sheets.The empirical models explain about 15% of the variance of the sea-level trends. Nevertheless, the models are correlated with the observations on the level of 0.38+/-0.07, indicating that most of the unexplained variance is due to contributions with small spatial scales. Averaged over the last five decades, the results indicate that the Antarctic and Greenland ice sheets have been melting with an equivalent contribution to global sea-level rise of 0.39+/-0.11 and 0.10+/-0.05 mm yr(-1), respectively. The steric signal derived from observations is clearly identified in the sea-level trends and is found to be at a minimum of 0.2 mm yr(-1), with the most likely value being close to 0.35 mm yr(-1). The global tide gauge network, which covers only a small fraction of the ocean surface, appears to sense an average sea-level rise larger than the global average. Extrapolating the regression models to the global ocean and taking into account the uncertainties in the extrapolation results in a most likely global average of the order of 1.05+/-0.75 mm yr(-1).     

Orientational effects in geophysical fluid dynamics

The approach, accounting the interaction between essentially different scales of turbulent fluid motions on a rotating sphere, is developed. Representation of the large-scale oceanic circulation as a turbulent flow with orientational effects due to synoptic (mesoscale) eddies is the basis of this technique. The scale of these eddies is much less than that of the considered problem, their energetic significance however is important. Such representation leads to employment of nontrivial angular momentum equation, i.e. to micropolar or asymmetrical hydrodynamics. It allows to define a function which would characterize the averaged vorticity of mesoscale (subgrid) motions and does not relate to the mean flow vorticity. Using this parameterization, the calculations with barotropic and 2-layer global ocean models have been carried out. The model results do show an increase of basic ocean gyre transports.     

FEG-SEM examination of alumina scales formed on FeCrAl alloys

Abstract

Field emission gun scanning electron microscopy (FEGSEM) with electron backscattered diffraction (EBSD) has been used to investigate the microstructure and the oxidation behaviour of ultra-high purity Fe–20Cr–5Al model alloys and a commercial Fe–20Cr–5Al alloy. The model alloys contain controlled additions of phosphorus and carbon impurities and increased levels of more beneficial elements including yttrium, hafnium and titanium. The samples studied were oxidised at 800°C and 1200°C in humidified air for up to 3100 h, and 900°C and 1000°C for 1 h in laboratory air. At the higher temperature, well-adhered, compact and highly protective α-alumina scales formed, whereas at the lower temperature the scales formed were a less protective type of metastable alumina.

Preliminary examination showed that the texture of the formed alumina scale was unaffected by the texture of the underlying substrate and the substrate compositions. At the higher temperature, the study revealed that the alumina scale comprised two distinct regions; the outer region at the scale/gas interface contained small, equiaxed (0.5–1 micron) grains and the inner region at the scale/metal interface contained, columnar grains that are 2–3 times larger than the equiaxed ones. However, at the lower temperature these two distinct regions were not apparent. Instead, grains of predominantly metastable alumina were observed. The links between texture morphology and oxide growth mechanisms will be discussed in this paper.     

SeaWiFS on-orbit gain and detector calibrations: effect on ocean products

The NASA Ocean Biology Processing Group's Calibration and Validation Team has analyzed the mission-long Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) on-orbit gain and detector calibration time series to verify that lunar calibrations, obtained at nonstandard gains and radiance ranges, are valid for Earth data collected at standard gains and typical ocean, cloud, and land radiances. For gain calibrations, a constant voltage injected into the postdetector electronics allows gain ratios to be computed for all four detectors in each band. The on-orbit lunar gain ratio time series show small drifts for the near infrared bands. These drifts are propagated into the ocean color data through the atmospheric correction parameter epsilon, which uses the 765/865 nm band ratio. An anomaly analysis of global mean normalized water-leaving radiances at 510 nm shows a small decrease over the mission, while an analysis of epsilon shows a corresponding increase. The drifts in the lunar time series for the 765 and 865 nm bands were corrected. An analysis of the revised water-leaving radiances at 510 nm shows the drift has been eliminated, while an analysis of epsilon shows a reduced drift. For detector calibrations, solar diffuser observations made by the individual detectors in each band allows the response of the detectors to be monitored separately. The mission-long time series of detector calibration data show that the variations in the response of the individual detectors are less than 0.5% over the mission for all bands except the 865 nm band, where the variations are less than 1%.     

Rates of fireside corrosion of superheater and reheater tubes: making sense of available data

Abstract

Interpretation and use of a body of field data for corrosion of superheater and reheater (SH/RH) tubes in coal fired boilers was found to be unsatisfactory without some indication of how the corrosive environment encountered differed when different coals were burned. A new factor intended to represent the relative corrosion potential (RCP) of the coal burned is suggested, based on the accepted mechanism of accelerated corrosion of SH/RH tubes by the development of low melting complex sulphates beneath ash deposits. Initial testing of the RCP concept was encouraging, given the difficulty in some cases of ensuring accurate representation of the actual coal burned during the corrosion exposures. However, some data suggested that new boiler operating modes, such as various approaches to emissions reduction through staging of the combustion process, appeared to be capable of causing significantly more rapid corrosion of SH/RH tubes than would be expected from the RCP value for the coal. Although increased corrosion with some emissions control systems has been recognised in practice, understanding of the particular corrosion process involved is lacking. Some degree of mechanistic understanding of the key features of this form of corrosion is needed to provide a firm basis for application of concepts such as RCP or development of improved versions.     

ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan

We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981-2000 is assessed using several statistical tests and quantile-quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081-2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.     

Introduction. Stochastic physics and climate modelling

Finite computing resources limit the spatial resolution of state-of-the-art global climate simulations to hundreds of kilometres. In neither the atmosphere nor the ocean are small-scale processes such as convection, clouds and ocean eddies properly represented. Climate simulations are known to depend, sometimes quite strongly, on the resulting bulk-formula representation of unresolved processes. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical effects of unresolved scales in ways which conventional bulk-formula representations are incapable of so doing. The application of stochastic physics to climate modelling is a rapidly advancing, important and innovative topic. The latest research findings are gathered together in the Theme Issue for which this paper serves as the introduction.     

On the rate and causes of twentieth century sea-level rise

Both the rate and causes of twentieth century global sea-level rise (GSLR) have been controversial. Estimates from tide-gauges range from less than one, to more than two millimetre yr(-1). In contrast, values based on the processes mostly responsible for GSLR-mass increase (from mountain glaciers and the great high latitude ice masses) and volume increase (expansion due to ocean warming)-fall below this range. Either the gauge estimates are too high, or one (or both) of the component estimates is too low. Gauge estimates of GSLR have been in dispute for several decades because of vertical land movements, especially due to glacial isostatic adjustment (GIA). More recently, the possibility has been raised that coastal tide-gauges measure exaggerated rates of sea-level rise because of localized ocean warming. Presented here are two approaches to a resolution of these problems. The first is morphological, based on the limiting values of observed trends of twentieth century relative sea-level rise as a function of distance from the centres of the ice loads at last glacial maximum. This observational approach, which does not depend on a geophysical model of GIA, supports values of GSLR near 2 mm yr(-1). The second approach involves an analysis of long records of tide-gauge and hydrographic (in situ temperature and salinity) observations in the Pacific and Atlantic Oceans. It was found that sea-level trends from tide-gauges, which reflect both mass and volume change, are 2-3 times higher than rates based on hydrographic data which reveal only volume change. These results support those studies that put the twentieth century rate near 2 mm yr(-1), thereby indicating that mass increase plays a much larger role than ocean warming in twentieth century GSLR.     

Economic value of improved quantification in global sources and sinks of carbon dioxide

On average, about 45 per cent of global annual anthropogenic carbon dioxide (CO(2)) emissions remain in the atmosphere, while the remainder are taken up by carbon reservoirs on land and in the oceans-the CO(2) 'sinks'. As sink size and dynamics are highly variable in space and time, cross-verification of reported anthropogenic CO(2) emissions with atmospheric CO(2) measurements is challenging. Highly variable CO(2) sinks also limit the capability to detect anomolous changes in natural carbon reservoirs. This paper argues that significant uncertainty reduction in annual estimates of the global carbon balance could be achieved rapidly through coordinated up-scaling of existing methods, and that this uncertainty reduction would provide incentive for accurate reporting of CO(2) emissions at the country level. We estimate that if 5 per cent of global CO(2) emissions go unreported and undetected, the associated marginal economic impacts could reach approximately US$20 billion each year by 2050. The net present day value of these impacts aggregated until 2200, and discounted back to the present would have a mean value exceeding US$10 trillion. The costs of potential impacts of unreported emissions far outweigh the costs of enhancement of measurement infrastructure to reduce uncertainty in the global carbon balance.     

Amperometric acetylcholinesterase biosensor for pesticides monitoring utilising iron oxide nanoparticles and poly(indole-5-carboxylic acid)

A new electrochemical sensing device was constructed for determination of pesticides. In this report, acetylcholinesterase was bioconjugated onto hybrid nanocomposite, i.e. iron oxide nanoparticles and poly(indole-5-carboxylic acid) (Fe₃O₄NPs/Pin5COOH) was deposited electrochemically on glassy carbon electrode. Fe₃O₄NPs was showed as an amplified sensing interface at lower voltage which makes the sensor more sensitive and specific. The enzyme inhibition by pesticides was detected within concentrations ranges between 0.1–60 and 1.5–70 nM for malathion and chlorpyrifos, respectively, under optimal experimental conditions (sodium phosphate buffer, pH 7.0 and 25?°C). Biosensor determined the pesticides level in water samples (spiked) with satisfactory accuracy (96%–100%). Sensor showed good storage stability and retained 50% of its initial activity within 70 days at 4 °C.     

Multivariate GP-VAR models for robust structural identification under operational variability

While the concept of structural monitoring has been around for a number of decades, it remains under-exploited in practice. A main driver for this shortcoming lies in the difficulty to robustly and autonomously interpret the information that is extracted from dynamic data. This hindrance in properly deciphering the collected information may be attributed to the uncertainty that is inherent in i) the finite set of measured data, ii) the models employed for capturing the manifested dynamics, and more importantly, iii) the susceptibility of these systems to variations in Environmental and Operational Parameters (EOPs). In previous work of the authors, a Gaussian Process (GP) time-series approach has been introduced, which serves as a hierarchical input–output method to account for the influence of EOPs on structural response. This in turn enables a robust structural identification. In this scheme, the short-term dynamics are modeled by means of linear-in-the-parameters time-series models, while EOV dependence – acting on a long-term time scale – is achieved via GP regression of the model coefficients on measured EOPs. This work corresponds to a further advancement on this modeling approach, corresponding to its generalization to the vector response case. Particularly, the problem of global identification here is solved via an Expectation–Maximization algorithm tailored to the GP time-series model structure. Moreover, an EOP-dependent innovations covariance matrix is integrated in the model, which helps to capture variation in the vibration power. The resulting model does not only have the capability to represent the long-term response of a structure under variable EOPs, but also facilitates the enhanced tracking of modal quantities in contrast to traditional operational modal analysis techniques. The proposed approach is exemplified on the identification of the vibration response of a simulated wind turbine blade at different points along the blade axis in the flap-wise direction, under variability of both the acting wind speeds and ambient temperatures.     

Optimization of a semianalytical ocean color model for global-scale applications

Semianalytical (SA) ocean color models have advantages over conventional band ratio algorithms in that multiple ocean properties can be retrieved simultaneously from a single water-leaving radiance spectrum. However, the complexity of SA models has stalled their development, and operational implementation as optimal SA parameter values are hard to determine because of limitations in development data sets and the lack of robust tuning procedures. We present a procedure for optimizing SA ocean color models for global applications. The SA model to be optimized retrieves simultaneous estimates for chlorophyll (Chl) concentration, the absorption coefficient for dissolved and detrital materials [a(cdm)(443)], and the particulate backscatter coefficient [b(bp)(443)] from measurements of the normalized water-leaving radiance spectrum. Parameters for the model are tuned by simulated annealing as the global optimization protocol. We first evaluate the robustness of the tuning method using synthetic data sets, and we then apply the tuning procedure to an in situ data set. With the tuned SA parameters, the accuracy of retrievals found with the globally optimized model (the Garver-Siegel-Maritorena model version 1; hereafter GSM01) is excellent and results are comparable with the current Sea-viewing Wide Field-of-view sensor (SeaWiFS) algorithm for Chl. The advantage of the GSM01 model is that simultaneous retrievals of a(cdm)(443) and b(bp)(443) are made that greatly extend the nature of global applications that can be explored. Current limitations and further developments of the model are discussed.     

On-orbit vicarious calibration of ocean color sensors using an ocean surface reflectance model

Recent advances in global biogeochemical research demonstrate a critical need for long-term ocean color satellite data records of consistent high quality. To achieve that quality, spaceborne instruments require on-orbit vicarious calibration, where the integrated instrument and atmospheric correction system is adjusted using in situ normalized water-leaving radiances, such as those collected by the marine optical buoy (MOBY). Unfortunately, well-characterized time-series of in situ data are scarce for many historical satellite missions, in particular, the NASA coastal zone color scanner (CZCS) and the ocean color and temperature scanner (OCTS). Ocean surface reflectance models (ORMs) accurately reproduce spectra observed in clear marine waters, using only chlorophyll a (C(a)) as input, a measurement for which long-term in situ time series exist. Before recalibrating CZCS and OCTS using modeled radiances, however, we evaluate the approach with the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS). Using annual C(a) climatologies as input into an ORM, we derive SeaWiFS vicarious gains that differ from the operational MOBY gains by less than +/-0.9% spectrally. In the context of generating decadal C(a) climate data records, we quantify the downstream effects of using these modeled gains by generating satellite-to-in situ data product validation statistics for comparison with the operational SeaWiFS results. Finally, we apply these methods to the CZCS and OCTS ocean color time series.     

Impact of climate warming on the ground surface temperature in the sporadic permafrost zone of the Tatra Mountains,Poland and Slovakia

This paper examines the influence of climate change on the temperature of a debris slope surface in the zone of sporadic permafrost occurrence in the Tatra Mountains. This involved applications of linear regression equations which describe statistical dependence of the ground surface temperature (GST) upon the current air temperature in snow-free periods, or upon the previous air temperature and snow depth. These equations are validated using the daily air temperature and snow depth at a reference synoptic station and GST at 5 sites located in different topographic conditions. In order to estimate mean winter half-year, mean summer half-year and mean annual GST at these sites in hydrological years 1955–2010, archival meteorological data were used. The maximum errors in these estimations, determined for two reference years, were 0.5 °C, 0.2 °C and 0.1 °C respectively. The results show that the debris slopes thermal sensitivity to climate warming decreases with the increase of: a) shading, 2) altitude, and 3) depth of seasonal snow cover. In general, the changes of the air temperature influence the changes of mean annual ground surface temperature more in snow-free periods than in snow periods, whereas the degradation of orographically conditioned permafrost patches occurs faster in the places where snow cover is thin during the whole winter. The decrease of the depth of a thick snow cover may be accompanied by the decrease of its bottom temperature, despite the increase of the winter air temperature. We infer that in special orographic-nival conditions, the increase of mean annual air temperature may be accompanied by the decrease of mean annual ground surface temperature.     

NOAA-NASA Coastal Zone Color Scanner reanalysis effort

Satellite observations of global ocean chlorophyll span more than two decades. However, incompatibilities between processing algorithms prevent us from quantifying natural variability. We applied a comprehensive reanalysis to the Coastal Zone Color Scanner (CZCS) archive, called the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration (NOAA-NASA) CZCS reanalysis (NCR) effort. NCR consisted of (1) algorithm improvement (AI), where CZCS processing algorithms were improved with modernized atmospheric correction and bio-optical algorithms and (2) blending where in situ data were incorporated into the CZCS AI to minimize residual errors. Global spatial and seasonal patterns of NCR chlorophyll indicated remarkable correspondence with modern sensors, suggesting compatibility. The NCR permits quantitative analyses of interannual and interdecadal trends in global ocean chlorophyll.     

Compressive damage mechanism of GFRP composites under off-axis loading: Experimental and numerical investigations

Experimental and computational studies of the microscale mechanisms of damage formation and evolution in unidirectional glass fiber reinforced polymer composites (GFRP) under axial and off-axis compressive loading are carried out. A series of compressive testing of the composites with different angles between the loading vector and fiber direction were carried out under scanning electron microscopy (SEM) in situ observation. The damage mechanisms as well as stress strain curves were obtained in the experiments. It was shown that the compressive strength of composites drastically reduces when the angle between the fiber direction and the loading vector goes from 0° to 45° (by 2.3–2.6 times), and then slightly increases (when the angle approaches 80–90°). At the low angles between the fiber and the loading vector, fiber buckling and kinking are the main mechanisms of fiber failure. With increasing the angle between the fiber and applied loading, failure of glass fibers is mainly controlled by shear cracking. For the computational analysis of the damage mechanisms, 3D multifiber unit cell models of GFRP composites and X-FEM approach to the fracture modeling were used. The computational results correspond well to the experimental observations.     

Numerical modeling of displacements due to ocean tide loading: case study at GPS stations in Taiwan and western Pacific

Abstract

We model the horizontal and radial displacements due to ocean tidal loading (OTL) in a computer program DISOTL (DISplacements due to Ocean Tide Loading). Numerical modeling of OTL considers an inner zone and outer zone contributions. A local tide model and shoreline defined by a GMT and Taiwan digital elevation model is used for the inner zone. OTL-induced displacements from DISOTL, GOTIC2 and BS computer programs differ at the millimeter level in amplitude, but the phase difference can be over 10º. Such displacements at 13 IGS stations in the western Pacific can be up to 8.5 cm in amplitude (KWJ1, Marshall Islands). At stations around Taiwan, the radial displacements can be up to 5.5 cm (MZUM, Matzu Islands). This implies that such large OTL effects (over 1 cm) will have a profound influence on precise GPS positioning. To establish a new global positioning system GPS reference frame in Taiwan, the use of a precise computer program is critical. A case study of coastal and offshore-island GPS continuous stations suggests that DISOTL can model OTL corrections to a 1mm accuracy and reduce coordinate variations by up to 35%.