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.     

乌鲁木齐大气混合层厚度和稳定度与大气污染的关系

利用乌鲁木齐市4座10层100 m梯度气象塔2013年6月~2014年4月气象观测资料和7个环境监测站[WTBX]AQI[WTBZ]资料，计算并分析了大气混合层厚度和稳定度特征，探讨了大气混合层厚度和稳定度与污染的关系。结果表明：乌鲁木齐市混合层厚度夏季郊区高、城区低，冬季从南郊—城区—北郊随地势降低依次降低；夏季和冬季分别在1 559～1 772 m和526～1 156 m之间。地面至2 km以上每500 m高度间隔统计混合层厚度，500～1 000 m出现频率最多；月变化为6～9月基本在500 m以上，且每个高度区间其概率均超过10%，10月～次年2月1 500 m以上区间概率明显减小；日变化为中午13:00～16:00达到最高值，下午和傍晚迅速下降。白天较大的感热输送提供充足的热力条件，这也体现出白天以不稳定层结为主，夜间则以稳定层结为主。大气稳定度分类结果，夏季郊区和城区不稳定（A～C类）所占比例差不多，冬季北郊稳定（E、F类）所占比较最大、城区最弱。[WTBX]AQI指数冬季最大，从南郊—城区—北郊依次增大，这与采暖期污染物多、南郊比北郊地势高有利于扩散输送有关。总体来看，乌鲁木齐大气混合层厚度空间分布与气象要素、大气稳定度、地形等密切相关，对AQI[WTBZ]指数分布有重要影响，这对近地层大气污染状况预报有着重要的指导意义。     

高精度直升机机载LiDAR在高速公路改扩建勘测中的应用可行性研究

机载LiDAR在公路勘测方面的用途日益广泛。该文对直升机机载LiDAR在高速公路改扩建中的应用技术路线可行性进行了研究论证,从地面控制测量、点云数据获取、点云数据处理、成果应用等多个方面进行了阐述,通过分析LiDAR点云数据在5种不同地面控制点布设方案校正下的点云数据精度,论证了利用地面控制点对直升机机载LiDAR点云数据进行平面和高程校正的可行性。     

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…     

差分法周跳探测与修复方法改进

在目前常用的周跳探测与修复方法基础上 ,提出了首先将观测资料按照观测历元不连续分成若干小弧段 ,然后利用差分法进行周跳探测 ,根据差分后周跳放大的特性判断周跳和野值 ,并确定其位置利用宽带组合和电离层组合的方法解算周跳大小。通过实例验证了其有效性。     

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.