Comparison of wind-stress algorithms and their influence on wind-stress curl using buoy measurements over the shelf off Bodega Bay, California

The main objectives of this study were to compare three wind-stress algorithms of varying intricacy and estimate the extent to which each method altered computed wind-stress curl. The algorithms included (1) a simple bulk formula for neutral conditions that is dependent only on wind velocity components; (2) a formula that in addition to dependence on wind components includes a simplified effect of thermal stability through differences in air and sea temperatures; and (3) an algorithm that includes full treatment of dynamics and atmospheric stability. Data for the analysis were from a field program that used a special buoy network off Bodega Bay during 28 June–4 August 2001.A diamond-shaped setup of five closely separated buoys in Bodega Bay allowed for one of the first attempts to compute wind-stress curl over the ocean using buoy measurements. Based on an analysis of the available dataset, the marine layer over Bodega Bay is characterized by positive wind-stress curl with a median value around 0.2 Pa (100 km)⁻¹ and maximum values reaching 2.5 Pa (100 km)⁻¹. Positive wind-stress curl was observed for all wind speed conditions, whereas negative wind-stress curl episodes were associated mostly with low-wind conditions.Comparison of wind-stress curl computed using the three algorithms showed that differences among them can be significant. The first and third algorithms indicated similar stress curl (difference around 10%), but the differences between these two and the second algorithm were much higher (approximately 40%). The reason for the difference is the stability correction, which in the third algorithm strongly decreases with an increase in wind speeds, but stays at a similar level for all wind speeds in the second algorithm. Consequently, for higher wind speeds the variability of wind stress calculated using the second algorithm is greater than for the other two algorithms, causing significant differences in computed wind-stress curl (root mean-square error equal to 0.19 Pa (100 km)⁻¹).Despite the apparent biases in computed wind stress and wind-stress curl among the algorithms, all of them show a significant trend of decreasing sea-surface temperature (SST) with increasing wind-stress curl. The bootstrapping analysis has revealed that both the along-shore wind stress and wind-stress curl have noticeable correlation with the changes in the sea-surface temperature as an indirect indication of the upwelling. An additional analysis, based on the low-pass filtered data, showed also significant agreement between the measured divergence in the cross-shore surface transport and the wind-stress curl computed for all three algorithms.     

湘西沃溪钨锑金矿床黄铁矿中发现Au-Sb矿物相

利用扫描电镜和电子探针等方法,对沃溪钨锑金矿床中产于(块状白钨矿-石英脉中的)黄铁矿微裂隙中的自然金和Au-Sb矿物相进行了较详细的观察和研究。结果表明,黄铁矿中Au-Sb矿物相除了有前人已经鉴定出的方锑金矿(AuSb2.13)外,还新发现有锑金矿(Au1.02Sb)矿物相。二者以显微颗粒的形式存在于黄铁矿显微裂隙中。黄铁矿微裂隙中Au-Sb矿物相的存在,指示矿床成矿在黄铁矿形成之后存在Au-Sb混溶的成矿流体。自然金、方锑金矿、锑金矿等矿物的沉淀析出可能是Au-Sb混溶流体从高温(高于350℃)向低温(250℃)演变的结果。此外,Au-Sb矿物相的发现对改进矿石冶炼中Au、Sb的分离技术有参考价值。     

Magnetite solubility and iron transport in magmatic-hydrothermal environments

We have examined the effect of pressure on the apparent equilibrium constant, K′, for magnetite solubility (Fe₃O₄^mt + 6HCl^fluid + H₂^fluid = 3FeCl₂^fluid + 4H₂O^fluid) and the relative iron-carrying capacities of magmatic vapor and brine by conducting experiments in a rhyolite melt-vapor-brine-magnetite system at 800°C, f_O2 = NNO and pressures ranging from 100 to 145 MPa. Iron concentrations in synthetic vapor and brine fluid inclusions were quantified by using laser-ablation inductively-coupled-plasma-mass-spectrometry (LA-ICPMS). Hydrogen chloride (HCl) concentrations in magmatic vapor were inferred by potentiometric measurements of H⁺ in quenched run product fluids. These data yield calculated values for log K′, assuming a_H2O = X_H2O, of 1.7, 4.9, 6.2, 6.8 and 9.1 at 100, 110, 130, 140 and 145 MPa, respectively. The concentration of iron in magmatic vapor increases by an order of magnitude, whereas the concentration of iron in magmatic brine remains constant (within 1σ) with increasing pressure as the 800°C critical pressure is approached along the vapor-brine solvus. The concentrations of iron in vapor and brine fluid inclusions yield calculated partition coefficients (D_Fe^v/b) of 0.05, 0.14, 0.27 and 0.56 at 110, 130, 140 and 145 MPa, respectively. Our data reveal that pressure fluctuations may significantly affect the value of log K′. More importantly, the data demonstrate conclusively that a significant amount of iron can be transported by a low-density aqueous vapor in the magmatic-hydrothermal environment.     

Paleozoic northward drift of the North Tien Shan (Central Asia) as revealed by Ordovician and Carboniferous paleomagnetism

Three new Middle–Late Ordovician and two new Early Carboniferous paleomagnetic poles have been obtained from the North Tien Shan Zone (NTZ) of the Ural–Mongol belt in Kyrgyzstan and Kazakhstan. Paleolatitudes for the Carboniferous are unambiguously northerly and average 15.5°N, whereas the Ordovician paleolatitudes (6°, 9°, and 9°) are inferred to be southerly, given that a very large (180°) rotation of the NTZ would be necessary during the middle Paleozoic if the other polarity option was chosen. Thus, the NTZ drifted northward during much of the Paleozoic; east–west drift cannot be determined, as is well known, from paleomagnetic data. In addition, detailed thermal demagnetization analysis reveals two overprints, one of recent age and the other of Permian age, which is a time of strong deformation in the NTZ. The paleolatitude of the combined Permian overprint is 30.5+2°N. The paleolatitudes collectively track those predicted for the area by extrapolation from Baltica very well, but are different from those of Siberia for Ordovician times. This finding is compatible with Sengör and Natal'in's [Sengör, A.M.C., Natal'in, B.A., 1996. Paleotectonics of Asia: fragments of a synthesis. In: Yin A., Harrison, M. (Eds.), The Tectonic Evolution of Asia. Cambridge Univ. Press, Cambridge, pp. 486–640] model of tectonic evolution of the Ural–Mongol belt and disagrees with the models of other researchers. Declinations of the Ordovician and Early Carboniferous results range from northwesterly to northeasterly, and are clearly affected by local relative rotations, which seem characteristic for the entire NTZ, because the Permian overprint declinations also show such a spread. Apparently, the important latest Paleozoic–Triassic deformation involved shear zone-related rotations as well as folding and significant granitic intrusions.     

Evaluation of the AMIP soil moisture simulations

The Atmospheric Model Intercomparison Project (AMIP) conducted simulations by 30 different atmospheric general circulation models forced by observed sea surface temperatures for the 10-year period, 1979–1988. These models include a variety of different soil moisture parameterizations which influence their simulations of the entire land surface hydrology, including evaporation, soil moisture, and runoff, and their simulations of the energy balance at the surface. Here we compare these parameterizations, and evaluate their simulations of soil moisture by comparing them with actual observations of soil moisture, literally ground truth. We compared model-generated ‘data sets' and simulations of soil moisture with observations from 150 stations in the former Soviet Union for 1979–1985 and Illinois for 1981–1988. The spatial patterns, mean annual cycles, and interannual variations were compared to plant-available soil moisture in the upper 1 m of soil. The model-generated ‘data sets' are quite different from the observations, and from each other in many regions, even though they use the same bucket model calculation method. The AMIP model simulations are also quite different from each other, especially in the tropics. Models with 15-cm field capacities do not capture the observed large high latitude values of soil moisture. In addition, none of the models properly simulate winter soil moisture variations in high latitudes, keeping soil moisture constant, while observations show that soil moisture varies in the winter as much as in other seasons. The observed interannual variations of soil moisture were not captured by any of the AMIP models. Several models have large soil moisture trends during the first year or two of the AMIP simulations, with potentially large impacts on global hydrological cycle trends and on other climate elements. This is because the simulations were begun without spinning up the soil moisture to the model climatology. The length of time it took for each to reach equilibrium depended on the particular parameterization. Although observed temporal autocorrelation time scales are a few months, some models had much longer time scales than that. In particular, the three parameterizations based on the Simple Biosphere model (SiB) had trends in some regions for virtually the entire AMIP simulation period.     

The Marinoan glaciation (Neoproterozoic) in northeast Svalbard

Two separate and distinct diamictite‐rich units occur in the mixed carbonate‐siliciclastic Polarisbreen Group, which comprises the top kilometer of >7 km of Neoproterozoic strata in the northeast of the Svalbard archipelago. The platformal succession accumulated on the windward, tropical to subtropical margin of Laurentia. The older Petrovbreen Member is a thin glacimarine diamictite that lacks a cap carbonate. It contains locally derived clasts and overlies a regional karstic disconformity that was directly preceded by a large (>10‰) negative δ¹³C anomaly in the underlying shallow‐marine carbonates. This anomaly is homologous to anomalies in Australia, Canada and Namibia that precede the Marinoan glaciation. The younger and thicker Wilsonbreen Formation comprises terrestrial ice‐contact deposits. It contains abundant extrabasinal clasts and is draped by a transgressive cap dolostone 3–18 m thick. The cap dolostone is replete with sedimentary features strongly associated with post‐Marinoan caps globally, and its isotopic profile is virtually identical to that of other Marinoan cap dolostones. From the inter‐regional perspective, the two diamictite‐rich units in the Polarisbreen Group should represent the first and final phases of the Marinoan glaciation. Above the Petrovbreen diamictite are ～200 m of finely laminated, dark olive‐coloured rhythmites (MacDonaldryggen Member) interpreted here to represent suspension deposits beneath shorefast, multi‐annual sea ice (sikussak). Above the suspension deposits and below the Wilsonbreen diamictites is a <30‐m‐thick regressive sequence (Slangen Member) composed of dolomite grainstone and evaporitic supratidal microbialaminite. We interpret this sabkha‐like lagoonal sequence as an oasis deposit that precipitated when local marine ice melted away under greenhouse forcing, but while the tropical ocean remained covered due to inflow of sea glaciers from higher latitudes. It appears that the Polarisbreen Group presents an unusually complete record of the Marinoan snowball glaciation.     

Chlorine in submarine glasses from the Lau Basin: seawater contamination and constraints on the composition of slab-derived fluids

Measurements of chlorine concentrations in matrix glasses from 18 primitive (>6 wt% MgO) and eight evolved lavas from active spreading centers in the Lau Basin back-arc system provide insight into the processes which control chlorine concentrations in subduction-related magmas, and can be used to investigate chlorine enrichment related to fluids derived from the underlying subducted slab. Chlorine contents of the glasses are highly variable (0.008-0.835 wt%) and generally high with respect to uncontaminated mid-ocean ridge basalt. Chlorine contents are highest in fractionated lavas from propagating ridge tips and lowest in more primitive basaltic lavas. Two different styles of enrichment in chlorine (relative to other incompatible elements) are recognized. Glasses from the Central Lau Spreading and Eastern Lau Spreading Center typically have low Ba/Nb ratios indicating minimal input of slab-derived components, and high to very high ratios of chlorine relative to K₂O, H₂O, and TiO₂. This style of chlorine enrichment is highest in the most fractionated samples and is consistent with crustal assimilation of chlorine-rich altered ocean crust material. Data from the literature suggest that contamination by chlorine-rich seawater-derived components also characterizes the Woodlark Basin and North Fiji Basin back-arc systems. The second style of chlorine enrichment reflects input from slab-derived fluid(s) to the mantle wedge from the adjacent Tonga subduction zone. Basaltic glasses from the Valu Fa Ridge and Mangatolu Triple Junction show correlations between ratios of chlorine and K₂O, H₂O, and TiO₂ and indices of slab-derived fluid input such as Ba/Nb, Ba/Th and U/Th, consistent with chlorine in these lavas originating from a saline fluid added to the mantle wedge. Within the Valu Fa Ridge the measured range of chlorine contents equates to a chlorine flux of 224-1120 kg/m/yr to the back-arc crust. Using a simple melting model and additional data from other back-arc and arc sample suites we conclude that chlorine is a major component within the slab fluids that contribute to many arc and back-arc melting systems, and probably plays an important role in regulating trace element transport by slab fluids in the mantle wedge. For the back-arc suites we have examined the estimated Cl/H₂O and Cl/K₂O ratios in the slab fluid component correlate with proximity to the arc front, suggesting that progressive dehydration of the slab and/or re-equilibration and transport within the mantle wedge may influence the overall degree of chlorine enrichment within the slab fluid component. The degree of chlorine enrichment observed in most back-arc lavas also appears too great to be explained solely by melting of amphibole, phlogopite or apatite within the mantle source and suggests that chlorine must be present in another phase, possibly a chlorine-rich fluid.     

Tar ‘specks’ in the North Atlantic

A number of dark specks retained on filters, through which seawater had been filtered, contained material that absorbed UV light very strongly. This material was most likely sunken pieces of tar. The amount was 0.12 μg/l on an average and was independent of hydrographic parameters.     

Evaluation of machine learning models for rice dry biomass estimation and mapping using quad-source optical imagery

ABSTRACT

Several machine learning regression models have been advanced for the estimation of crop biophysical parameters with optical satellite imagery. However, literature on the comparative performances of such models is still limited in range and scope, especially under multiple data sources, despite the potential of multi-source imagery to improving crop monitoring in cloudy areas. To fill in this knowledge gap, this study explored the synergistic use of Landsat-8, Sentinel-2A, China’s environment and disaster monitoring and forecasting satellites (HJ-1 A and B) and Gaofen-1 (GF-1) data to evaluate four machine learning regression models that include Random Forest (RF), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), and Gradient Boosting Decision Tree (GBDT), for rice dry biomass estimation and mapping. Taking a major rice cultivation area in southeast China as case study during the 2016 and 2017 growing seasons, a cross-calibrated time series of the Enhanced Vegetation Index (EVI) was obtained from the quad-source optical imagery and on which the aforementioned models were applied, respectively. Results indicate that in the before rice heading scenario, the most accurate dry biomass estimates were obtained by the GBDT model (R² of 0.82 and RMSE of 191.8 g/m²) followed by the RF model (R² of 0.79 and RMSE of 197.8 g/m²). After heading, the k-NN model performed best (R² of 0.43 and RMSE of 452.1 g/m²) followed by the RF model (R² of 0.42 and RMSE of 464.7 g/m²). Whist the k-NN model performed least in the before heading scenario, SVM performed least in the after heading scenario. These findings may suggest that machine learning regression models based on an ensemble of decision trees (RF and GBDT) are more suitable for the estimation of rice dry biomass, at least with optical satellite imagery. Studies that would extend the evaluation of these machine learning models, to other parameters like leaf area index, and to microwave imagery, are hereby recommended.