Simulations of the Impact of Lakes on Local and Regional Climate Over the Tibetan Plateau     

Lingjing Zhu  Xin Liu  Lei Tian  Qunhui Zhang 《大气与海洋》2018,56(4):230-239

ABSTRACT

Because of the high elevation and complex topography of the Tibetan Plateau (TP), the role of lakes in the climate system over the Tibetan Plateau is not well understood. For this study, we investigated the impact of lake processes on local and regional climate using the Weather Research and Forecasting (WRF) model, which includes a one-dimensional physically based lake model. The first simulation with the WRF model was performed for the TP over the 2000–2010 period, and the second was carried out during the same period but with the lakes filled with nearby land-use types. Results with the lake simulation show that the model captures the spatial and temporal patterns of annual mean precipitation and temperature well over the TP. Through comparison of the two simulations, we found that the TP lakes mainly cool the near-surface air, inducing a decreasing sensible heat flux for the entire year. Meanwhile, stronger evaporation produced by the lakes is found in the fall. During the summer, the cooling effect of the lakes decreases precipitation in the surrounding area and generates anomalous circulation patterns. In conclusion, the TP lakes cool the near-surface atmosphere most of the time, weaken the sensible heat flux, and strengthen the latent heat flux, resulting in changes in mesoscale precipitation and regional-scale circulation.  相似文献   

Research on Parallel Algorithms for uv-faceting Imaging     

《Chinese Astronomy and Astrophysics》2019,43(3):424-443

The uv-faceting imaging is one of the widely used large field of view imaging technologies, and will be adopted for the data processing of the low-frequency array in the first stage of the Square Kilometre Array (SKA1). Due to the scale of the raw data of SKA1 is unprecedentedly large, the efficiency of data processing directly using the original uv-faceting imaging will be very low. Therefore, a uv-faceting imaging algorithm based on the MPI (Message Passing Interface)+OpenMP (Open Multi-Processing) and a uv-faceting imaging algorithm based on the MPI+CUDA (Compute Unified Device Architecture) are proposed. The most time-consuming data reading and gridding in the algorithm are optimized in parallel. The verification results show that the results of the proposed two algorithms are basically consistent with that obtained by the current mainstream data processing software CASA (Common Astronomy Software Applications), which indicates that the proposed two algorithms are basically correct. Further analysis of the accuracy and total running time shows that the MPI+CUDA method is better than the MPI+OpenMP method in both the correctness rate and running speed. The performance test results show that the proposed algorithms are effective and have certain extensibility.  相似文献   

An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest     

《Chinese Astronomy and Astrophysics》2020,44(1):41-60

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.  相似文献   

The Basic Shape Classification of Space Debris with Light Curves     

LU Yao  ZHAO Chang-yin 《Chinese Astronomy and Astrophysics》2021,45(2):190-208

We study the machine learning method for classifying the basic shape of space debris in both simulated and observed data experiments, where light curves are used as the input features. In the dataset for training and testing, simulated light curves are derived from four types of debris within different shapes and materials. Observed light curves are extracted from Mini-Mega TORTORA (MMT) database which is a publicly accessible source of space object photometric records. The experiments employ the deep convolutional neural network, make comparisons with other machine learning algorithms, and the results show CNN (Convolutional Neural Network) is better. In simulational experiments, both types of cylinder can be distinguished perfectly, and two other types of satellite have around 90% probability to be classified. Rockets and defunct satellites can achieve 99% success rate in binary classification, but in further sub-classes classifications, the rate becomes relatively lower.  相似文献   

基于斩波轮技术的K波段接收机噪声校准研究          下载免费PDF全文

王凯  王洋  陈卯蒸  段雪峰  闫浩  马军  陈晨雨  曹亮 《天文学报》2020,61(1):1

接收机是射电天文中用于探测微弱射电信号的重要接收设备.接收机的强度校准就是将接收机对射电源的响应转换为天文意义上的流量密度.常规方法就是使用经典的冷热负载法,将接收机自身的强度响应转换为一个等效的温度值,之后再据此对射电源做进一步标定.通过搭建基于斩波轮技术的K波段接收机强度校准平台,使用斩波轮法测试K波段常温接收机的噪声温度,并与传统冷热负载法的测试结果进行比对.结果显示,在晴好天气条件下,斩波轮法在30°、90°仰角下噪声温度的最大测试误差为7.5%和8.4%,可以很好地应用于实际噪声温度测试中;但在5°仰角测试中,由于过低仰角引入了地面噪声,使得斩波轮法的测试误差上升至20%–30%之间而无法使用.希望在此基础上进一步开展K波段天空亮温度的理论计算与实测,从而完善斩波轮技术的应用,使之可以满足在不同气象条件下的噪声校准测试需求.  相似文献   

Research on the Application of Fast-steering Mirror in Stellar Interferometers     

Mei Rong  Hu Zhong-wen  Xu Teng  Sun Chang-sheng 《Chinese Astronomy and Astrophysics》2018,42(3):475-486

In stellar interferometers, the fast-steering mirror (FSM) is widely utilized to correct the wavefront tilt caused by the atmospheric turbulence and internal instrumental vibration, because of its high resolution and fast response frequency. In this study, the non-coplanar error between the FSM and the actuator deflection axis introduced by the manufacturing, assembly, and adjustment is analyzed systematically. Via a numerical method, the additional optical path difference (OPD) caused by the above factors is studied, and its effect on the fringe tracking accuracy of a stellar interferometer is also discussed. On the other hand, the starlight parallelism between the beams of two arms is one of the main factors for the loss of fringe visibility. By analyzing the influence of wavefront tilt caused by the atmospheric turbulence on fringe visibility, a simple and efficient real-time correction scheme of starlight parallelism is proposed based on a single array detector. The feasibility of this scheme is demonstrated by a laboratory experiment. The results show that after the correction of fast-steering mirror, the starlight parallelism meets preliminarily the requirement of a stellar interferometer on the wavefront tilt.  相似文献   

徐州市水土流失时空变化研究     

陈报章  渠俊峰  葛梦玉  沈艳文  王安妮  王国斌 《地球信息科学学报》2018,20(11):1622-1630

本文以3S技术为支撑,在修正水土流失方程（RUSLE）的基础上,针对徐州黄泛平原-丘陵地带的特殊地形地貌、对2000年以来徐州市水土流失时空变化特征进行了分析。结果表明：2000-2014年徐州市土壤侵蚀等级以微度为主,微度侵蚀面积占总侵蚀面积多年平均达到76.34%;中度侵蚀次之,所占比例在10%~17%间;剧烈侵蚀所占比例最少。轻度及以上土壤侵蚀等级主要发生在中部微山湖下游、京杭大运河一带的丘陵岗地地区、主城区与故黄河北岸的黄泛平原地区,以及丰县、新沂、邳州的局部区域;土壤侵蚀存在一定程度年际变化特征,睢宁、丰县、邳州的部分地区侵蚀面积年际变化较为明显,土壤侵蚀总面积整体上呈现下降趋势。  相似文献   

基于Stacking集成学习的恒星/星系分类研究          下载免费PDF全文

李超  张文辉  李然  王俊义  林基明 《天文学报》2020,61(2):21-111

机器学习在当今诸多领域已经取得了巨大的成功,但是机器学习的预测效果往往依赖于具体问题.集成学习通过综合多个基分类器来预测结果,因此,其适应各种场景的能力较强,分类准确率较高.基于斯隆数字巡天(Sloan Digital Sky Survey,SDSS)计划恒星/星系中最暗源星等集分类正确率低的问题,提出一种基于Stacking集成学习的恒星/星系分类算法.从SDSS-DR7(SDSS Data Release 7)中获取完整的测光数据集,并根据星等值划分为亮源星等集、暗源星等集和最暗源星等集.仅针对分类较为复杂且困难的最暗源星等集展开分类研究.首先,对最暗源星等集使用10折嵌套交叉验证,然后使用支持向量机(Support Vector Machine,SVM)、随机森林(Random Forest,RF)、XGBoost(eXtreme Gradient Boosting)等算法建立基分类器模型;使用梯度提升树(Gradient Boosting Decision Tree,GBDT)作为元分类器模型.最后,使用基于星系的分类正确率等指标,与功能树(Function Tree,FT)、SVM、RF、GBDT、XGBoost、堆叠降噪自编码(Stacked Denoising AutoEncoders,SDAE)、深度置信网络(Deep Belief Network,DBN)、深度感知决策树(Deep Perception Decision Tree,DPDT)等模型进行分类结果对比分析.实验结果表明,Stacking集成学习模型在最暗源星等集分类中要比FT算法的星系分类正确率提高了将近10%.同其他传统的机器学习算法、较强的提升算法、深度学习算法相比,Stacking集成学习模型也有较大的提升.  相似文献   

Developing constitutive models from EPR‐based self‐learning finite element analysis          下载免费PDF全文

Ali Nassr  Akbar Javadi  Asaad Faramarzi 《国际地质力学数值与分析法杂志》2018,42(3):401-417

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.  相似文献   

Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques     

Muhammad Al-Amin Hoque  Stuart Phinn  Chris Roelfsema  Iraphne Childs 《International Journal of Digital Earth》2018,11(3):246-263

Tropical cyclones and their devastating impacts are of great concern to coastal communities globally. An appropriate approach integrating climate change scenarios at local scales is essential for producing detailed risk models to support cyclone mitigation measures. This study developed a simple cyclone risk-modelling approach under present and future climate change scenarios using geospatial techniques at local scales, and tested using a case study in Sarankhola Upazila from coastal Bangladesh. Linear storm-surge models were developed up to 100-year return periods. A local sea level rise scenario of 0.34?m for the year 2050 was integrated with surge models to assess the climate change impact. The resultant storm-surge models were used in the risk-modelling procedures. The developed risk models successfully identified the spatial extent and levels of risk that match with actual extent and levels within an acceptable limit of deviation. The result showed that cyclone risk areas increased with the increase of return period. The study also revealed that climate change scenario intensified the cyclone risk area by 5–10% in every return period. The findings indicate this approach has the potential to model cyclone risk in other similar coastal environments for developing mitigation plans and strategies.  相似文献