Swelter in the city: Urban greenery and its effects on temperature in Guwahati,India

Changing urban landscape with multistoried high rises, roads and pavements is continuously reducing urban green space. These structures result in high surface temperature variation within cities. To explore the relationship between surface temperature and normalized difference vegetation index (NDVI), this study estimates two models—geographically weighted regression (GWR) and a fixed effect panel data model in relation to the Guwahati Metropolitan Area (GMA), a secondary city in north east India. The results indicate the superiority of GWR regression in presence of spatial dependence. Panel data analysis shows that the densely populated urban areas in the GMA with less than 10 per cent greenery are 1°C warmer than the sub-urban areas with 50 per cent greenery.     

Mini-inflation prior to the cosmic confinement transition?

The onset of the confinement transition in the early universe is studied within the Friedmann model. Exploiting a bag model equation of state for the deconfined matter, which is generalized to include also metastable states, the possibility of a mini-inflationary epoch is demonstrated. A criterion of metastability is derived to estimate parameters of this mini-inflation.     

VIIRS/DNB夜间灯光月度产品插补方法对比——以北京为例

新一代VIIRS/DNB(Visible Infrared Imaging Radiometer Suite Day/Night Band)夜间灯光数据因其具备更精细的时空分辨率、数据不存在饱和现象、不同年份数据可比性强等优点而迅速代替DMSP/OLS(Defense Meteorological Satellite Program's Operational Linescan System)夜间灯光数据成为新的研究热点。但由于杂散光的污染,VIIRS/DNB夏季数据数值缺失严重,致使数据在空间和时间上不连续,因此,插补缺失数据成为后续应用的前提。鉴于此,论文从插补结果异常值、与参照值对比、计算性能三个方面,系统比较了三次样条插值(样条)、三次Hermite插值(Hermite)、灰色预测模型(GM)、三次指数平滑法(指数)4种插补方法的适用性,以期为插补VIIRS/DNB夜间灯光数据提供方法选择的依据。研究结果表明：①异常值比较方面,Hermite法未出现异常值,另外3种算法仅出现少量异常值(0.02%~1.34%);②与参照值的对比方面,Hermite法与参考值接近程度最高,GM接近程度最低,样条法和指数法介于两者中间;③算法性能比较方面,4种方法都具备计算简单、容易编程的特点,但指数法的算法时长是另外3种方法的10倍以上。因此,综合多方表现,当插补月份前后两侧均有足够长的原始数据时,插补效果好、计算速度快、不会出现过冲现象的Hermite法最适宜,样条法次之;当插补月份仅单侧有足够长的数据时,适宜采用指数法(插补效果好、计算速度较慢)或GM(插补效果偏低、计算速度快)进行插补。     

Analysis of Spatio-temporal Land Surface Temperature and Normalized Difference Vegetation Index Changes in the Andassa Watershed,Blue Nile Basin,Ethiopia

Analysis of the nexus between vegetation dynamics and climatic parameters like surface temperature is essential in environmental and ecological studies and for monitoring of the natural resources. This study explored the spatio-temporal distribution of land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) and the relationship between them in the Andassa watershed from 1986 to 2016 periods using Landsat data. Monthly average air temperature data of three meteorological sites were used for validating the results. The findings of the study showed that the LST of the Andassa watershed has increased during the study periods. Overall, average LST has been rising with an increasing rate of 0.081°C per year. Other results of this study also showed that there has been a dynamic change in vegetation cover of the watershed in all seasons. There was also a negative correlation between LST and NDVI in all the studied years. From this study we can understand that there has been degradation of vegetation and intensification of LST from 1986 to 2016.     

空间分辨率对中国夏季降水时空演变特征的影响

本文使用1979—2021年国家气候中心160站(R₁₆₀)和国家级地面气象观测站2 314站(R₂₃₁₄)逐月降水观测资料,利用EOF (Empirical Orthogonal Function)分解和相关分析等方法,研究两类资料夏季降水时空变化特征及其与海气因素之间物理联系的表征水平差异,并分析了差异的可能原因。结果表明,R₁₆₀在我国西北、青藏高原等地区站点极为稀疏,导致其各EOF模态对上述地区降水的时空变化特征描述失真,中东部地区偏低的空间分辨率会使局地强降水的变化特征信号损失,造成降水的年际变率降低。而R₂₃₁₄主模态能够更为真实地反映我国降水的时空演变特征,特别是在极端降水频发的江淮地区以及降水受局地地形影响较大的山区,其EOF主模态的空间分布和时间系数演变与ENSO (El Niño-Southern Oscillation)、西太平洋副热带高压、青藏高原雪盖等气候强迫信号之间的相关性更为显著。     

基于新型探测资料对西安一次弱降水预报失误的原因分析

利用微波辐射计、激光测风雷达、多普勒雷达、相控阵雷达等新型探测资料、地面加密观测资料、ERA5再分析及多模式数值预报结果对2022年4月24日西安城区一次弱降水预报出现明显失误的原因进行分析,结果表明：(1)全球数值预报模式和中尺度数值预报模式对本次过程西安城区均报有明显降水,主要原因为模式对低层相对湿度预报明显偏大;(2)多种新型探测数据分析认为近地层湿度条件较差及中层的绝对水汽含量低,中层的干暖空气不利于成云致雨,垂直上升运动不强,且由于低层非常干燥,使水滴在下沉过程中蒸发,从而无法形成雨滴下落,这些原因共同造成西安城区无降水,低层相对湿度预报偏大是造成这次西安城区降水预报失误的主要原因之一;(3)造成西安城区近地层湿度条件差的原因是城市干热岛效应和低层干暖平流输送,且降水云团翻越秦岭后其湿空气绝热下沉至城区后出现增温降湿,使得城区形成较为深厚的干层,即使有雨滴在下落过程中也会造成更强的蒸发,这也是城区没有降水的重要原因之一;(4)预报员主观预报订正出现空报主要是源于对边界层水汽、抬升条件等关键降水要素缺乏订正能力,且对大城市的干热岛效应和秦岭山区地形影响研究不足。     

使用Python函数式编程进行空间回归分析

针对使用传统的编程方式进行空间回归分析过于繁杂的问题,本文提出将Python函数式编程引入空间回归分析方法,分析和探讨脚本语言＋函数式编程方式在GIS数据分析中的推广应用前景。编程实践证明,采用Python函数式编程,结合既有的开源软件包,可以有效提高编程效率,减少代码量,将实践人员的注意力集中在问题本身。     

Extending self-organizing maps for supervised classification of remotely sensed data

An extended self-organizing map for supervised classification is proposed in this paper. Unlike other traditional SOMs, the model has an input layer, a Kohonen layer, and an output layer. The number of neurons in the input layer depends on the dimensionality of input patterns. The number of neurons in the output layer equals the number of the desired classes. The number of neurons in the Kohonen layer may be a few to several thousands, which depends on the complexity of classification problems and the classification precision. Each training sample is expressed by a pair of vectors ： an input vector and a class codebook vector. When a training sample is input into the model, Kohonen＇s competitive learning rule is applied to selecting the winning neuron from the Kohouen layer and the weight coefficients connecting all the neurons in the input layer with both the winning neuron and its neighbors in the Kohonen layer are modified to be closer to the input vector, and those connecting all the neurons around the winning neuron within a certain diameter in the Kohonen layer with all the neurons in the output layer are adjusted to be closer to the class codebook vector. If the number of training sam- ples is sufficiently large and the learning epochs iterate enough times, the model will be able to serve as a supervised classifier. The model has been tentatively applied to the supervised classification of multispectral remotely sensed data. The author compared the performances of the extended SOM and BPN in remotely sensed data classification. The investigation manifests that the extended SOM is feasible for supervised classification.     

内蒙古区域数值预报对探空和地面观测资料的敏感性试验研究

基于内蒙古睿图预报系统的低分辨率版本和WRFDA-FSO诊断工具,评估2021年7月现有探空和地面观测对内蒙古睿图预报系统预报的影响。该方法计算代价相对低廉,并允许根据观测变量、观测类型、气压层次、地理区域等观测的子集对观测影响进行划分。代价函数为以干总能量为度量的背景场和分析场的预报误差之间的差异。结果表明:观测影响的总体总和为负,观测对预报起正贡献作用。对12 h预报误差减小贡献最大的观测来自探空观测的动力变量(U、V风分量)。而单时次单位数量平均观测影响,探空观测的贡献约为地面观测的1/2。探空观测对12 h预报误差减小从近地面层至模式层顶均保持正贡献作用,并在对流层中低层和对流层高空急流层存在两个极大值区域;地面观测在850 hPa以下低层正贡献占比明显。探空观测在被同化系统同化时均总体具有有利的影响,也反映出探空观测数据稳定、质量较高的特征;地面观测对12 h预报误差减小起正贡献作用次数最多的区域在河套地区尤为显著。同时,探讨了需进一步提高地面观测资料同化率的问题。     

试论中国城市化发展模式

结合城市化的新观念,提出了中国城市化发展新理论模式--中国城乡网络化发展模式.城乡网络化发展模式建立在区域综合协调发展基础之上,指的是在一定区域范围内城乡之间各种经济活动主体构成一个有序化的关联系统及其运行过程,并通过这个过程获得一种特有的网络组织功能效应.同时,还在此理论基础上针对我国东部、中部、西部地区各自的现实条件,分别对其实施城乡网络化发展进行了初步构想.