Simulations of lunar equatorial regolith temperature profile based on measurements of Diviner on Lunar Reconnaissance Orbiter

Lunar equatorial regolith temperature profiles were simulated using the half-limited solid heat conduction model. Based on the infrared data measured using the Diviner radiometer on the Lunar Reconnaissance Orbiter launched by the United Sates in June 2009, three factors influencing temperature profiles were analyzed. The infrared brightness temperature data from Diviner channel 7 were used to retrieve surface temperature. In simulating regolith temperature profiles, the retrieved temperature, rather than temperatures calculated from solar radiance at the lunar surface, were used as the input for surface temperature in solving the heat-conductive equation. The results showed that the bottom-layer temperature at depths of 6 m approached almost 246 K after 10000 iterations. The temperature was different to the temperature of 250 K at the same depth encountered in simulations using solar radiance. Simulations from both methods of surface temperatures over a lunar day gave similar variations. At lunar night, the temperature difference between the two was about 2 K; the main differences occurred when the solar elevation angle was very low when surface temperatures are largely affected by terrain topography. With no certainty in lunar temperature profiles at present, the advantage of the retrieval method using infrared sensor data as input to the boundary conditions in solving the lunar heat conduction equation is that simulations of surface temperature variations are more accurate. This is especially true in areas with large variations in terrain topography, where surface temperatures vary greatly because of shading from the sunlight.     

水体表面温度反演研究综述

水体表面温度是研究全球或区域气候变化、数值天气预报的重要参数,是控制水体与大气热量、水分交换的重要变量,对理解水体生物物理过程具有重要意义。卫星观测水表温度具有传统手段不可比拟的技术优势,同时也存在精度和质量上的限制和挑战。本文总结了观测水表温度常用的红外、微波传感器及其分辨率特征,并比较分析了各类传感器的优势、劣势和分辨率适用的时空尺度;在区别不同手段观测的水表温度基础上,分别概述了红外遥感和微波遥感反演水表温度的理论基础,以及常用的算法模型;基于水表温度反演的原理和过程,系统分析了云、水汽、气溶胶、比辐射率等不确定性因素,对反演精度的影响及解决方法,并对精度验证方法做了简单介绍;最后,对水体表面温度反演的发展趋势进行了展望,并指出多源数据的同化融合、优势互补是提升水温反演精度的重要途径。     

航空重力测量的数据归算方法

采用径向改正方法将航线高度处的重力观测值归算到平均飞行高度面,采用交叉点两步平差法来进行测线系统误差补偿,并选用加权平均法和Shepard曲面拟合法对重力观测值作格网化处理。对美国大地测量局（NGS）发布的EN01进行数据处理,〖JP〗给出大地高6 200 m处2°×3°范围内5′×5′规则格网重力扰动数据。相对于该区域的EGM2008格网重力扰动参考值,加权平均法和Shepard曲面拟合法精度分别为±1.59 mGal和±1.36 mGal。     

利用微波遥感土壤水分产品监测东北地区春涝范围和程度

地表土壤水分是判断农田涝害的直接数据源,以欧洲太空局1978~2010 年微波遥感土壤水分产品、2013 年SMOS MIRAS L3 级土壤水分产品和气象站点的月降水数据为基础,结合土壤水分距平指数和土壤水分异常指数,分析2013 年东北地区春涝影响范围和严重程度。结果表明:① 东北地区以黑龙江省受涝面积最大,约11 万km²,约占黑龙江省总面积的1/4;② 比较多年的月降水数据与涝灾程度,发现冬春季节强降水是引发春涝的主要原因之一;③ 春涝的严重程度与高程呈现负相关关系,涝灾区域多集中在高程500 m以下。     

Foreground removal from Planck Sky Model temperature maps using a MLP neural network

Unfortunately, the Cosmic Microwave Background (CMB) radiation is contaminated by emission originating in the Milky Way (synchrotron, free‐free and dust emission). Since the cosmological information is statistically in nature, it is essential to remove this foreground emission and leave the CMB with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80 % of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Maximum likelihood algorithm for parametric component separation in cosmic microwave background experiments

We discuss an approach to the component separation of microwave, multifrequency sky maps as those typically produced from cosmic microwave background (CMB) anisotropy data sets. The algorithm is based on the two-step, parametric, likelihood-based technique recently elaborated on by Eriksen et al., where the foreground spectral parameters are estimated prior to the actual separation of the components. In contrast with the previous approaches, we accomplish the former task with help of an analytically derived likelihood function for the spectral parameters, which, we show, yields estimates equal to the maximum likelihood values of the full multidimensional data problem. We then use these estimates to perform the second step via the standard, generalized-least-squares-like procedure. We demonstrate that the proposed approach is equivalent to a direct maximization of the full data likelihood, which is recast in a computationally tractable form. We use the corresponding curvature matrices to characterize statistical properties of the recovered parameters. We incorporate in the formalism some of the essential features of the CMB data sets, such as inhomogeneous pixel domain noise, unknown map offsets as well as calibration errors and study their consequences for the separation. We find that the calibration is likely to have a dominant effect on the precision of the spectral parameter determination for a realistic CMB experiment. We apply the algorithm to simulated data and discuss the results. Our focus is on partial sky, total intensity and polarization, CMB experiments such as planned balloon-borne and ground-based efforts, however, the techniques presented here should be also applicable to the full-sky data as for instance, those produced by the Wilkinson Microwave Anisotropy Probe ( WMAP ) satellite and anticipated from the Planck mission.     

Phase shift sequences for an adding interferometer

Cosmic microwave background (CMB) polarimetry has the potential to provide revolutionary advances in cosmology. Future experiments to detect the very weak B-mode signal in CMB polarization maps will require unprecedented sensitivity and control of systematic errors. Bolometric interferometry may provide a way to achieve these goals. In a bolometric interferometer (or other adding interferometer), phase shift sequences are applied to the inputs in order to recover the visibilities. Noise is minimized when the phase shift sequences corresponding to all visibilities are orthogonal. We present a systematic method for finding sequences that produce this orthogonality, approximately minimizing both the length of the time sequence and the number of discrete phase shift values required. When some baselines are geometrically equivalent, we can choose sequences that read out those baselines simultaneously, which has been shown to improve the signal-to-noise ratio.     

Impact of Galactic polarized emission on B-mode detection at low multipoles

We use a model of polarized Galactic emission developed by the Planck collaboration to assess the impact of foregrounds on B -mode detection at low multipoles. Our main interest is in applications of noisy polarization data and in particular in assessing the feasibility of B -mode detection by Planck . This limits the complexity of foreground subtraction techniques that can be applied to the data. We analyse internal linear combination techniques and show that the offset caused by the dominant E -mode polarization pattern leads to a fundamental limit of   r ∼ 0.1  for the tensor–scalar ratio even in the absence of instrumental noise. We devise a simple, robust, template fitting technique using multifrequency polarization maps. We show that template fitting using Planck data alone offers a feasible way of recovering primordial B -modes from dominant foreground contamination, even in the presence of noise on the data and templates. We implement and test a pixel-based scheme for computing the likelihood function of cosmological parameters at low multipoles that incorporates foreground subtraction of noisy data.     

Limits on isocurvature perturbations from non-Gaussianity in WMAP temperature anisotropy

We study the effect of primordial isocurvature perturbations on non-Gaussian properties of cosmic microwave background (CMB) temperature anisotropies. We consider generic forms of the non-linearity of isocurvature perturbations which can be applied to a wide range of theoretical models. We derive analytical expressions for the bispectrum and the Minkowski Functionals for CMB temperature fluctuations to describe the non-Gaussianity from isocurvature perturbations. We find that the isocurvature non-Gaussianity in the quadratic isocurvature model, where the isocurvature perturbation S is written as a quadratic function of the Gaussian variable  σ,  S =σ²−〈σ²〉  , can give the same signal-to-noise ratio as   f _NL= 30  even if we impose the current observational limit on the fraction of isocurvature perturbations contained in the primordial power spectrum α. We give constraints on isocurvature non-Gaussianity from Minkowski Functionals using the Wilkinson Microwave Anisotropy Probe ( WMAP ) 5-year data. We do not find a significant signal of isocurvature non-Gaussianity. For the quadratic isocurvature model, we obtain a stringent upper limit on the isocurvature fraction  α < 0.070  (95 per cent CL) for a scale-invariant spectrum which is comparable to the limit obtained from the power spectrum.