The Bear Brook Watershed in Maine: Multi-decadal whole-watershed experimental acidification

The Bear Brook Watershed in Maine (BBWM) is a long-term research site established to study the response of forest ecosystem function to environmental disturbances of chronic acidic deposition and ecosystem nitrogen enrichment. Starting in 1989, the West Bear (treated) watershed received bimonthly applications of ammonium sulfate [(NH₄)₂SO₄] fertilizer from above the canopy, whereas East Bear (reference) received ambient deposition. The treatments were stopped in 2016, marking the beginning of the recovery phase. Research at the site has focused on soils, streams, and vegetation. Here, we describe data collected over three decades at the BBWM—input and stream output nutrient fluxes, quantitative soil pits and soil chemistry, and soil temperature and moisture.     

连续台风时期香港区域的水汽变化分析

利用香港卫星定位参考站网GNSS观测数据,提取强热带风暴"塔拉斯"与热带风暴"洛克"影响期间各测站天顶方向对流层延迟,反演香港区域大气可降水量;根据香港区域49个天文台气象站提供的实测降雨量数据,分析大气可降水量与实际降雨量的相关性,以及两次台风对香港区域水汽时空分布的不同影响。结果表明,大气可降水量在台风影响前期均上升,在大量降雨后回落,但在连续台风的间歇期间,仍高于台风来临前的水平;水汽累积是大量降雨的前提条件,当水汽累积量相近时,水汽累积时长与累积降雨量呈正相关;台风期间大气可降水量值超过65 mm的区域面积与台风等级相关,台风路径对局部水汽分布有一定的影响。     

基于PSR-WSVM模型的边坡位移预测

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。     

Gamma-Hadron Separation using Čerenkov Photon Density Fluctuations

In the atmospheric Čerenkov technique γ-rays are detected against the abundant background produced by hadronic showers. In order to improve the signal to noise ratio of theexperiment, it is necessary to reject a significant fraction of hadronic showers. Traditional background rejection methods based on image shape parameters have been extensively used for the data from imaging telescopes. However, non-imaging Čerenkov telescopes have to develop very different means of statistically identifying and removing cosmic ray events. Some of the parameters, which could be potentially important for non-imaging arrays, are the temporal and spectral differences, the lateral distributions and density fluctuations of Čerenkov photons generated by γ-ray and hadron primaries. Here we study the differences in fluctuations of Čerenkov photon density in the light pool at the observation level from showers initiated by photons and those initiated by protons or heavier nuclei. The database of simulated events for the PACT array has been used to evaluate the efficiency of the new technique. Various types of density fluctuations like the short range and medium range fluctuations as well as flatness parameter are studied. The estimated quality factors reflect the efficiencies with which the hadrons can be rejected from the data. Since some of these parameters are independent, the cuts may be applied in tandem and we demonstrate that the proton rejection efficiency of ∼90% can be achieved. Use of density fluctuations is particularly suited for wavefront sampling observations and it seems to be a good technique to improve the signal to noise ratio. This revised version was published online in July 2006 with corrections to the Cover Date.     

The effects of topographically-controlled thermal tides in the martian upper atmosphere as seen by the MGS accelerometer

Mars Global Surveyor accelerometer observations of the martian upper atmosphere revealed large variations in density with longitude during northern hemisphere spring at altitudes of 130-160 km, all latitudes, and mid-afternoon local solar times (LSTs). This zonal structure is due to tides from the surface. The zonal structure is stable on timescales of weeks, decays with increasing altitude above 130 km, and is dominated by wave-3 (average amplitude 22% of mean density) and wave-2 (18%) harmonics. The phases of these harmonics are constant with both altitude and latitude, though their amplitudes change significantly with latitude. Near the South Pole, the phase of the wave-2 harmonic changes by 90° with a change of half a martian solar day while the wave-3 phase stays constant, suggesting diurnal and semidiurnal behaviour, respectively. We use a simple application of classical tidal theory to identify the dominant tidal modes and obtain results consistent with those of General Circulation Models. Our method is less rigorous, but simpler, than the General Circulation Models and hence complements them. Topography has a strong influence on the zonal structure.     

Single star scidar: atmospheric parameters profiling using the simulated annealing algorithm

In this paper, we present a new method to estimate, for each turbulent layer labelled i , the horizontal wind speed   v ( h _i )  , the standard deviation of the horizontal wind speed fluctuations  σ _v ( h_i )  and the integrated value of   C ² _n   over the thickness  Δ h_i   of the turbulent layer   C ² _n ( h_i )Δ h_i   , where   h_i   is the altitude of the turbulent layer. These parameters are extracted from single star scintillation spatiotemporal cross-correlation functions of atmospheric speckles obtained within the generalized mode. This method is based on the simulated annealing algorithm to find the optimal solution required to solve the problem. Astrophysics parameters for adaptive optics are also calculated using   C ² _n ( h_i )  and   v ( h_i )  values. The results of other techniques support this new method.     

Correcting systematic effects in a large set of photometric light curves

We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.     

Atmospheric radiative transfer simulation for atmospheric correction of remote sensing data

IntroductionThe radiance leaving the earth-atmosphere sys-tem which can be sensed by a satellite borne ra-diometer is the sum of radiation emission fromtheearth surface and each atmospheric level that aretransmittedtothe top of the atmosphere.The radia-tion emissionfromthe earthsurface andthe radianceof each atmospheric level can be separated fromtheradiance at the top the atmospheric level a satellitemeasured.Thus,the earth surface parameters willbe retrieved from the surface radiance after a…     

Metamorphism in Archaean greenstone belts: calculated fluid compositions and implications for gold mineralization

An inescapable consequence of the metamorphism of greenstone belt sequences is the release of a large volume of metamorphic fluid of low salinity with chemical characteristics controlled by the mineral assemblages involved in the devolatilization reactions. For mafic and ultramafic sequences, the composition of fluids released at upper greenschist to lower amphibolite facies conditions for the necessary relatively hot geotherm corresponds to those inferred for greenstone gold deposits (X_CO2= 0.2–0.3). This result follows from the calculation of mineral equilibria in the model system CaO–MgO–FeO–Al₂O₃–SiO₂–H₂O–CO₂, using a new, expanded, internally consistent dataset. Greenstone metamorphism cannot have involved much crustal over-thickening, because very shallow levels of greenstone belts are preserved. Such orogeny can be accounted for if compressive deformation of the crust is accompanied by thinning of the mantle lithosphere. In this case, the observed metamorphism, which was contemporaneous with deformation, is of the low-P high-T type. For this type of metamorphism, the metamorphic peak should have occurred earlier at deeper levels in the crust; i.e. the piezothermal array should be of the ‘deeper-earlier’type. However, at shallow crustal levels, the piezothermal array is likely to have been of ‘deeper-later’type, as a consequence of erosion. Thus, while the lower crust reached maximum temperatures, and partially melted to produce the observed granites, mid-crustal levels were releasing fluids prograde into shallow crustal levels that were already retrograde. We propose that these fluids are responsible for the gold mineralization. Thus, the contemporaneity of igneous activity and gold mineralization is a natural consequence of the thermal evolution, and does not mean that the mineralization has to be a consequence of igneous processes. Upward migration of metamorphic fluid, via appropriate structurally controlled pathways, will bring the fluid into contact with mineral assemblages that have equilibrated with a fluid with significantly lower X_CO2. These assemblages are therefore grossly out of equilibrium with the fluid. In the case of infiltrated metabasic rocks, intense carbonation and sulphidation is predicted. If, as seems reasonable, gold is mobilized by the fluid generated by devolatilization, then the combination of processes proposed, most of which are an inevitable consequence of the metamorphism, leads to the formation of greenstone gold deposits predominantly from metamorphic fluids.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.