Search Results (46)

The Abu Farayed Granite (AFG), located in the southeastern desert of Egypt, was intruded during the early to late stages of Pan-African orogeny that prevailed within the Arabian–Nubian Shield. The AFG intrudes an association of gneisses, island arc volcano–sedimentary rocks, and serpentinite masses. Field observations, supported by remote sensing and geochemical data, reveal a composite granitic intrusion that is differentiated into two magmatic phases. The early granitic phase comprises weakly deformed subduction-related calc–alkaline rocks ranging from diorite to tonalite, while the later encloses undeformed granodiorite and granite. Landsat-8 (OLI) remote sensing data have shown to be highly effective in discriminating among the different varieties of granites present in the area. Furthermore, the data have provided important insights into the structural characteristics of the AFG region. Specifically, the data indicate the presence of major tectonic trends with ENE–WSW and NW–SE directions transecting the AFG area. Geochemically, the AFG generally has a calc–alkaline metaluminous affinity with relatively high values of Cs, Rb, K, Sr, Nd, and Hf but low contents of Nb, Ta, P, and Y. The early magmatic phase has lower alkalis and REEs, while the later phases have higher alkalis and REEs with distinctly negative Eu anomalies. The AFG is structurally controlled, forming a N–S arch, which may be due to the influence of the wadi Hodein major shear zone. The diorite and tonalite are believed to have been originally derived from subduction-related magmatism during regional compression. This began with the dehydration of the descending oceanic crust with differential melting of the metasomatized mantle wedge. Magma ascent was long enough to react with the thickened crust and therefore suffered fractional crystallization and assimilation (AFC) to produce the calc–alkaline diorite–tonalite association. The granodiorite and granites were produced due to partial melting, assimilation, and fractionation of lower crustal rocks (mainly diorite–tonalite of the early stage) after subduction and arc volcanism during a late orogenic relaxation–rebound event associated with uplift transitioning to extension. Full article

In this study, we explore the interannual variability of Sea Surface Salinity (SSS) in the Dotson–Getz Trough located in West Antarctica, focusing on the month of February. Utilizing the oceanic analysis product EN4, we first validate the EN4 SSS with data from a singular ship-based survey, and then delve into potential factors that may influence SSS, with a particular emphasis on surface freshwater flux, sea ice concentration (SIC), and also the surface stress curl, which will induce upwelling via Ekman transport to affect the SSS. Our findings primarily indicate a link between SSS and sea ice concentration, showcasing a negative correlation where the peak (average) coefficient is around −0.6 (−0.4), further affirming the substantial interannual variability of SSS in this region. Full article

For breathing humans, the respiratory quotient (RQ = CO₂ moles released/O₂ mols consumed) ranges from 0.7 to 1.0. In Part I, the literature on the RQ was reviewed and Keeling’s data on atmospheric CO₂ and O₂ concentrations (1991–2018) were used in the estimation of the global RQ as 0.47. A new interpretation of RQ_Glob is provided in Part II by treating the planet as a “Hypothetical Biological system (HBS)”. The CO₂ and O₂ balance equations are adopted for estimating (i) energy-based RQ_Glob(En) and (ii) the CO₂ distribution in GT/year and % of CO₂ captured by the atmosphere, land, and ocean. The key findings are as follows: (i) The RQ_Glob(En) is estimated as 0.35 and is relatively constant from 1991 to 2020. The use of RQ_Glob(En) enables the estimation of CO₂ added to the atmosphere from the knowledge of annual fossil fuel (FF) energy data; (ii) The RQ method for the CO₂ budget is validated by comparing the annual CO₂ distribution results with results from more detailed models; (iii) Explicit relations are presented for CO₂ sink in the atmosphere, land, and ocean biomasses, and storage in ocean water from the knowledge of curve fit constants of Keeling’s curves and the RQ of FF and biomasses; (iv) The rate of global average temperature rise (0.27 °C/decade) is predicted using RQ_Glob,(En) and the annual energy release rate and compared with the literature data; and (v) Earth’s mass loss in GT and O₂ in the atmosphere are predicted by extrapolating the curve fit to the year 3700. The effect of RQ_Glob and RQ_FF on the econometry and policy issues is briefly discussed. Full article

In biology, respiratory quotient (RQ) is defined as the ratio of CO₂ moles produced per mole of oxygen consumed. Recently, Annamalai et al. applied the RQ concept to engineering literature to show that CO₂ emission in Giga Tons per Exa J of energy = 0.1 ∗ RQ. Hence, the RQ is a measure of CO₂ released per unit of energy released during combustion. Power plants on earth use a mix of fossil fuels (FF), and the RQ of the mix is estimated as 0.75. Keeling’s data on CO₂ and O₂ concentrations in the atmosphere (abbreviated as atm., 1991–2018) are used to determine the average RQ_Glob of earth as 0.47, indicating that 0.47 “net” moles of CO₂ are added to which means that there is a net loss of 5.6 kg C(s) from earth per mole of O₂ depleted in the absence of sequestration, or the mass loss rate of earth is estimated at 4.3 GT per year. Based on recent literature on the earth’s tilt and the amount of water pumped, it is speculated that there could be an additional tilt of 2.7 cm over the next 17 years. While RQ of FF, or biomass, is a property, RQ_Glob is not. It is shown that the lower the RQ_Glob, the higher the acidity of oceans, the lesser the CO₂ addition to atm, and the lower the earth’s mass loss. Keeling’s saw-tooth pattern of O₂ is predicted from known CO₂ data and RQ_Glob. In Part II, the RQ concept is expanded to define energy-based RQ_Glob,En, and adopt the CO₂ and O₂ balance equations, which are then used in developing the explicit relations for CO₂ distribution amongst atm., land, and ocean, and the RQ-based results are validated with results from more detailed literature models for the period 1991–2018. Full article

The Philippines is highly vulnerable to multiple climate-related hazards due to its geographical location and weak adaptation measures. Floods are the most catastrophic hazards that impact lives, livelihoods, and, consequently, the economy at large. Understanding the ability of the general circulation models to simulate the observed rainfall using the latest state-of-the-art model is essential for reliable forecasting. Based on this background, this paper objectively aims at assessing and ranking the capabilities of the recent Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the observed rainfall over the Philippines. The Global Precipitation Climatology Project (GPCP) v2.3 was used as a proxy to gauge the performance of 11 CMIP6 models in simulating the annual and rainy-season rainfall during 1980–2014. Several statistical metrics (mean, standard deviation, normalized root means square error, percentage bias, Pearson correlation coefficient, Mann–Kendall test, Theil–Sen slope estimator, and skill score) and geospatial measures were assessed. The results show that that CMIP6 historical simulations exhibit satisfactory effectiveness in simulating the annual cycle, though some models display wet/dry biases. The CMIP6 models generally underestimate rainfall on the land but overestimate it over the ocean. The trend analysis shows that rainfall over the country is insignificantly increasing both annually and during the rainy seasons. Notably, most of the models could correctly simulate the trend sign but over/underestimate the magnitude. The CMIP6 historical rainfall simulating models significantly agree on simulating the mean annual cycle but diverge in temporal ability simulation. The performance of the models remarkably differs from one metric to another and among different time scales. Nevertheless, the models may be ranked from the best to the least best at simulating the Philippines’ rainfall in the order GFDL, NOR, ACCESS, ENS, MRI, CMCC, NESM, FIO, MIROC, CESM, TAI, and CAN. The findings of this study form a good basis for the selection of models to be used in robust future climate projection and impact studies regarding the Philippines. The climate model developers may use the documented shortcoming of these models and improve their physical parametrization for better performance in the future. Full article

Clinopyroxene, one of the primary rock-forming minerals in mafic rocks, is the major host of lithophile elements in the mantle lithosphere and plays a crucial role in understanding mantle evolution and rock petrogenesis. Taking the Bingdaban ophiolite as an example, this study employed electron probe microanalysis and in situ trace element analysis to investigate the geochemistry of clinopyroxene in gabbros to determine the magma series and evolution, constrain the physicochemical conditions of the magmatic processes and explore the petrogenesis and tectonic setting. Representative gabbro samples were subjected to zircon U–Pb isotopic analysis, yielding an age of 424.3 ± 5.9 Ma. Geochemical investigations revealed that the Bingdaban gabbros exhibit tholeiitic composition, suggesting a genesis associated with enriched mid-ocean ridge basalt (E-MORB). Mineralogical analyses indicated that the clinopyroxene in the gabbros was Mg-rich, Fe-poor, and alkali-poor, representing a subalkaline series. The compositional end members of clinopyroxene were calculated as Wo_38.9–48.0En_30.9–48.1Fs_10.4–24.4, indicating a predominance of diopside with a minor amount of augite. Temperature–pressure conditions imply that these rocks formed in a high-temperature, low-pressure, and shallow-source environment. Compositional estimates of the melt in equilibrium with clinopyroxene are consistent with the overall characteristics of the host rock, reflecting an E-MORB setting. The Bingdaban gabbro likely originated from an initially depleted mantle source that later received an input of enriched mantle material, indicating formation in either an initial oceanic or immature back-arc basin tectonic setting. Full article

Freshwater content (FWC), generally characterized in the Arctic Ocean by salinities lower than 34.8 psu, has shifted in both quantity and distribution in recent decades in the Arctic Ocean. This has been largely driven by changes in the volume and salinity of freshwater sources and the direction and magnitude of major currents. In this study, we analyze the variability in FWC and other physical oceanographic variables from 1993 to 2021 in the Arctic Ocean and Beaufort Gyre (BG) using in situ and remote sensing observations and five ocean models and reanalysis products. Generally, ocean models and reanalysis products underestimate FWC in the BG when compared with observations. Modeled FWC and sea surface height (SSH) in the BG are well correlated during the time period and are similar to correlations of the observational data of these variables. ORAS5 compares best to EN4 salinity over the entire study period, although GLORYS12 agrees well pre-2007 and SODA post-2007. Outside the BG, consistency between modeled SSH, FWC, and limited observations varies between models. These comparisons help identify discrepancies in ocean model and reanalysis products while highlighting areas where future improvements are necessary to further our understanding of Arctic FWC. As observations are scarce in the Arctic, these products and their accuracy are important to studying this dynamic and vulnerable ocean. Full article

The Instituto Español de Oceanografía (IEO, Spanish Institute of Oceanography) has maintained different monitoring programs in the Spanish Mediterranean waters (Western Mediterranean) since 1992. All these monitoring programs were unified in 2007 under the current program RADMED (series temporales de datos oceanográficos en el Mediterráneo), which is devoted to the in situ multidisciplinary sampling of the water column of coastal and open-sea waters by means of periodic oceanographic campaigns. These campaigns, together with a network of tide-gauges, are part of the IEO Observing system (IEOOS). In some cases, the temperature and salinity time series collected in the frame of these monitoring programs are now more than 30 years long, whereas sea level time series date to the beginning of the 1940s. This information has been complemented with international databases and has been analyzed in numerous works by the Grupo mediterráneo de Cambio Climático (GCC; Mediterranean Climate Change Group) for more than 20 years. These works have been devoted to the detection and quantification of the changes that climate change is producing on the physical, chemical, and biological properties of the Spanish Mediterranean waters. In this work, we review the results obtained by the GCC since 2005 in relation to the changes in the physical properties of the sea: water column temperature, salinity, and density, heat content, mixed layer depth, and sea level. Time series and results are updated from the last works, and the reliability of the existing time series for the detection of climatologies and long-term trends are analyzed. Furthermore, the different sources of uncertainty in the estimation of linear trends are considered in the present work. Besides this review and update of the results obtained from the data collected in the frame of the IEOOS, we conduct a review of the existing monitoring capabilities from other institutions in the Spanish Mediterranean waters and a review of results dealing with climate change in the Spanish Mediterranean obtained by such institutions. In particular, we include a review of the results obtained by SOCIB (Servicio de Observación y Predicción Costero de las Islas Baleares; Balearic Islands costal observing and forecasting system) in relation to the study of marine heat waves and the warming of the sea surface, and the results corresponding to the intense warming of the Catalan continental shelf at L’Estartit oceanographic station. All these results evidence that the surface Spanish Mediterranean waters are warming up at a rate higher than that affecting the global ocean (>2 °C/100 years). This warming and a salinity increase are also observed along the whole water column. Marine heat waves are increasing their intensity, frequency, and duration since 1982, and coastal sea level is increasing at a rate of 2.5 mm/yr. The salinity increase seems to have compensated for the warming, at least at surface and intermediate waters where no significant trends have been detected for the density. This could also be the reason for the lack of significant trends in the evolution of the mixed layer depth. All these results highlight the importance of monitoring the water column and the necessity of maintaining in situ sampling programs, which are essential for the study of changes that are occurring throughout the Spanish Mediterranean waters. Full article

The monitoring of coastal areas using remote sensing techniques is an important issue to determine the bio-optical properties of the water column and the seabed composition. New hyperspectral satellite sensors (e.g., PRISMA, DESIS or EnMap) are developed to periodically observe ecosystems. The uncertainties in the retrieved geophysical products remain a key issue to release reliable data useful for the end-users. In this study, an analytical approach based on Information theory is proposed to investigate the Cramér–Rao lower Bounds (CRB) for the uncertainties in the ocean color parameters. Practically, during the inversion process, an a priori knowledge on the estimated parameters is used since their range of variation is supposed to be known. Here, a Bayesian approach is attempted to handle such a priori knowledge. A Bayesian CRB (BCRB) is derived using the Lee et al. semianalytical radiative transfer model dedicated to shallow waters. Both environmental noise and bio-optical parameters are supposed to be random vectors that follow a Gaussian distibution. The calculation of CRB and BCRB is carried out for two hyperspectral images acquired above the French mediterranean coast. The images were obtained from the recently launched hyperspectral sensors, namely the DESIS sensor (DLR Earth Sensing Imaging Spectrometer, German Aerospace Center), and PRISMA (Precursore IpperSpettrale della Mission Applicativa—ASI, Italian Space Adjency) sensor. The comparison between the usual CRB approach, the proposed BCRB approach and experimental errors obtained for the retrieved bathymetry shows the better ability of the BCRB to determine minimum error bounds. Full article

As the most relevant indicator of global warming, the ocean heat content (OHC) change is tightly linked to the Earth’s energy imbalance. Therefore, it is vital to study the OHC and heat absorption and redistribution. Here we analyzed the characteristics of global OHC variations based on a previously reconstructed OHC dataset (named OPEN) with four other gridded OHC datasets from 1993 to 2021. Different from the other four datasets, the OPEN dataset directly obtains OHC through remote sensing, which is reliable and superior in OHC reconstruction, further verified by the Clouds and the Earth’s Radiant Energy System (CERES) radiation flux data. We quantitatively analyzed the changes in the upper 2000 m OHC of the oceans over the past three decades from a multisource and multilayer perspective. Meanwhile, we calculated the global ocean heat uptake to quantify and track the global ocean warming rate and combined it with the Oceanic Niño Index to analyze the global evolution of OHC associated with El Niño–Southern Oscillation variability. The results show that different datasets reveal a continuously increasing and non-decaying global ocean warming from multiple perspectives, with more heat being absorbed by the subsurface and deeper ocean over the past 29 years. The global OHC heating trend from 1993 to 2021 is 7.48 ± 0.17, 7.89 ± 0.1, 10.11 ± 0.16, 7.78 ± 0.17, and 12.8 ± 0.26 × 10²² J/decade according to OPEN, IAP, EN4, Ishii, and ORAS5, respectively, which shows that the trends of the OPEN, IAP, and Ishii datasets are generally consistent, while those of EN4 and ORAS5 datasets are much higher. In addition, the ocean warming characteristics revealed by different datasets are somewhat different. The OPEN OHC dataset from remote sensing reconstruction shows a unique remote sensing mapping advantage, presenting a distinctive warming pattern in the East Indian Ocean. Meanwhile, the OPEN dataset had the largest statistically significant area, with 85.6% of the ocean covered by significant positive trends. The significant and continuous increase in global ocean warming over the past three decades, revealed from remote sensing reconstruction, can provide an important reference for projecting ocean warming in the context of global climate change toward the United Nations Sustainable Development Goals. Full article

The mode bias is present and time-dependent due to imperfect configurations. Data assimilation is the process by which observations are used to correct the model forecast, and is affected by the bias. How to reduce the bias is an important issue. This paper investigates the roles of a simple bias correction scheme in ocean data assimilation. In this scheme, the misfits between modeled and monthly temperature and salinity with interannual variability from the Met Office Hadley Centre subsurface temperature and salinity data set (EN4.2.2) are used for the innovations in assimilation via the Ensemble Optimal Interpolation method. Two assimilation experiments are implemented to evaluate the impacts of bias correction. The first experiment is a data assimilation system without bias correction. In the second experiment, the bias correction is applied in assimilation. For comparison, the nature run with no assimilation and no bias correction is also conducted. When the bias correction is not applied, the assimilation alone leads to a rising trend in the heat and salt content that is not found in the observations. It is a spurious temporal variability due to the effect of the bias on the data assimilation. Meanwhile, the assimilation experiment without bias correction also produces significant negative impacts on the subsurface salinity. The experiment with bias correction performs best with notable improvements over the results of the other two experiments. Full article

This research aims to examine how the Western Pacific North equatorial countercurrent (NECC) flow reacts to two different forms of El Niño (EN) over a 40-year period. To establish the prevailing modes for each season, we implemented Empirical Orthogonal Function (EOF) analysis on the eastward current component of the Ocean Reanalysis System 5 (ORAS5) dataset. In comparison to the Central Pacific (CP) episode, the time series principal component of the first mode (PC1) demonstrated that the strongest NECC’s magnitude often emerged during the development period (spring to fall) of the Eastern Pacific (EP) EN event. However, in episode CP 2002/2003, we witnessed an abnormal behavior in which the stronger NECC manifested. This was due to the emergence of a strong anomalous westerly wind, which differed from other CP events and forced the NECC’s magnitude to be greater. When approaching the peak stage, on the other hand, the magnitude of the NECC during the CP episode was typically greater than that of the EP episode. The NECC’s magnitude fell greatly in the second year of the EP episode, particularly during the spring season, since most EP episodes would transition into an La Niña (LN) event in the succeeding event. During the EP EN, it was found that the strength of the westerly wind had a bigger effect on the NECC than during the CP EN. Full article

Motivated by the need for a simple and effective assimilation scheme that could be used in a relocatable ocean model, a new assimilation algorithm called ensemble optimal smoothing (EnOS) was developed. This scheme was a straightforward extension of the ensemble optimal interpolation (EnOI) by involving time correlation information in the Kalman gain. The main advantage of this scheme was the ability to estimate the present state from the time history of observation. We first examined the new scheme in an ideal ocean model using simulated observations. Further applying these two assimilation schemes to the Chinese offshore and adjacent waters, the root-mean-square error (RMSE) of the EnOS scheme was reduced by 6.4% relative to EnOI. The results showed that the EnOS was more efficient and effective in eliminating model errors when compared to the EnOI scheme. Full article

EnOcean, a commonly used control protocol in smart lighting systems, provides authentication, as well as message integrity verification services, and can resist replay attack and tamper attack. However, since the device identity information transmitted between sensors in smart lighting control systems is easily accessible by malicious attackers, attackers can analyze users’ habits based on the intercepted information. This paper analyzed the security of the EnOcean protocol using a formal analysis method based on the colored Petri net (CPN) theory and the Dolev–Yao attacker model and found that the protocol did not anonymize the device identity information and did not have a communication key update mechanism, so an attacker could easily initiate a key compromise impersonation attack (KCIA) after breaking the pre-shared communication key. To address the above security issues, this paper proposed an EnOcean-A protocol with higher security based on the EnOcean protocol. The EnOcean-A protocol introduced a trusted third-party server to send communication keys to communication devices because devices must obtain different communication keys from the trusted third-party server each time they communicated. Thus, this protocol could resist a KCIA and achieve forward security. Meanwhile, the device identity information was anonymized using a homomorphic hash function in the EnOcean-A protocol, and the dynamic update mechanism of the device identity information was added so that an attacker could not obtain the real identity information of the device. Finally, the formal analysis of the EnOcean-A protocol showed that the new protocol could resist a KCIA and ensure the anonymity and untraceability of the communication device, which had higher security compared with the EnOcean protocol. Full article

Reconstructing the vertical structures of the ocean from sea surface information is of great importance for ocean and climate studies. In this study, an ensemble machine learning (Ens-ML) model is proposed to retrieve ocean subsurface thermal structure (OSTS) by using satellite-derived sea surface data and Argo data in the South China Sea (SCS). The input data include sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS), sea surface wind (SSW), and geographic information (including longitude and latitude). We select three stable machine learning models, namely, extreme gradient boosting (XGBoost), RandomForest and light gradient boosting machine (LightGBM) as our benchmark models, and then use an artificial neural network (ANN) technique to combine outputs from the three individual models. The proposed Ens-ML model using sea surface data only by SSH, SST, SSS, and SSW performs less satisfactorily than that considering the contribution of geographical information, indicating that the geographical information is essential to estimate the OSTS accurately. The estimated OSTS from the Ens-ML model are compared with Argo data. The results show that the proposed Ens-ML model can accurately estimate the OSTS (upper 1000 m) in the SCS, which is relatively more accurate and precise than the individual models. The performance of the Ens-ML model also varies with season, and better estimation is obtained in winter, which is probably due to stronger mixing and weaker stratification. This study shows the great potential and advantage of the multi-model ensemble of machine learning algorithm for the ocean’s interior information retrieving, showing great potential in expanding the scope of ocean observations. Full article