Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region

Soil temperature (T _S) strongly influences a wide range of biotic and abiotic processes. As an alternative to direct measurement, indirect determination of T _S from meteorological parameters has been the focus of attention of environmental researchers. The main purpose of this study was to estimate daily T _S at six depths (5, 10, 20, 30, 50 and 100?cm) by using a multilayer perceptron (MLP) artificial neural network (ANN) model and a multivariate linear regression (MLR) method in an arid region of Iran. Mean daily meteorological parameters including air temperature (T _a), solar radiation (R _S), relative humidity (RH) and precipitation (P) were used as input data to the ANN and MLR models. The model results of the MLR model were compared to those of ANN. The accuracy of the predictions was evaluated by the correlation coefficient (r), the root mean-square error (RMSE) and the mean absolute error (MAE) between the measured and predicted T _S values. The results showed that the ANN method forecasts were superior to the corresponding values obtained by the MLR model. The regression analysis indicated that T _a, RH, R _S and P were reasonably correlated with T _S at various depths, but the most effective parameters influencing T _S at different depths were T _a and RH.     

Dependability of rainfall to topography and micro-climate: an observation using geographically weighted regression

Theoretical and Applied Climatology - The dependability of rainfall to topography and micro-climate of the region in an eco-sensitive Western Ghats of India is evaluated using the geographically...     

Statistical downscaling of precipitation using local regression and high accuracy surface modeling method

Downscaling precipitation is required in local scale climate impact studies. In this paper, a statistical downscaling scheme was presented with a combination of geographically weighted regression (GWR) model and a recently developed method, high accuracy surface modeling method (HASM). This proposed method was compared with another downscaling method using the Coupled Model Intercomparison Project Phase 5 (CMIP5) database and ground-based data from 732 stations across China for the period 1976–2005. The residual which was produced by GWR was modified by comparing different interpolators including HASM, Kriging, inverse distance weighted method (IDW), and Spline. The spatial downscaling from 1° to 1-km grids for period 1976–2005 and future scenarios was achieved by using the proposed downscaling method. The prediction accuracy was assessed at two separate validation sites throughout China and Jiangxi Province on both annual and seasonal scales, with the root mean square error (RMSE), mean relative error (MRE), and mean absolute error (MAE). The results indicate that the developed model in this study outperforms the method that builds transfer function using the gauge values. There is a large improvement in the results when using a residual correction with meteorological station observations. In comparison with other three classical interpolators, HASM shows better performance in modifying the residual produced by local regression method. The success of the developed technique lies in the effective use of the datasets and the modification process of the residual by using HASM. The results from the future climate scenarios show that precipitation exhibits overall increasing trend from T1 (2011–2040) to T2 (2041–2070) and T2 to T3 (2071–2100) in RCP2.6, RCP4.5, and RCP8.5 emission scenarios. The most significant increase occurs in RCP8.5 from T2 to T3, while the lowest increase is found in RCP2.6 from T2 to T3, increased by 47.11 and 2.12 mm, respectively.

     

Optimization of the time series NDVI-rainfall relationship using linear mixed-effects modeling for the anti-desertification area in the Beijing and Tianjin sandstorm source region

Theoretical and Applied Climatology - Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote...     

Comprehensive modeling of monthly mean soil temperature using multivariate adaptive regression splines and support vector machine

Soil temperature (T _s) and its thermal regime are the most important factors in plant growth, biological activities, and water movement in soil. Due to scarcity of the T _s data, estimation of soil temperature is an important issue in different fields of sciences. The main objective of the present study is to investigate the accuracy of multivariate adaptive regression splines (MARS) and support vector machine (SVM) methods for estimating the T _s. For this aim, the monthly mean data of the T _s (at depths of 5, 10, 50, and 100 cm) and meteorological parameters of 30 synoptic stations in Iran were utilized. To develop the MARS and SVM models, various combinations of minimum, maximum, and mean air temperatures (T _min, T _max, T); actual and maximum possible sunshine duration; sunshine duration ratio (n, N, n/N); actual, net, and extraterrestrial solar radiation data (R _s, R _n, R _a); precipitation (P); relative humidity (RH); wind speed at 2 m height (u ₂); and water vapor pressure (V_p) were used as input variables. Three error statistics including root-mean-square-error (RMSE), mean absolute error (MAE), and determination coefficient (R ²) were used to check the performance of MARS and SVM models. The results indicated that the MARS was superior to the SVM at different depths. In the test and validation phases, the most accurate estimations for the MARS were obtained at the depth of 10 cm for T _max, T _min, T inputs (RMSE = 0.71 °C, MAE = 0.54 °C, and R ² = 0.995) and for RH, V _p, P, and u ₂ inputs (RMSE = 0.80 °C, MAE = 0.61 °C, and R ² = 0.996), respectively.     

江南一次持续性暴雨过程中线状中尺度对流系统模态转换机理研究

利用地面观测资料、探空资料、NCEP再分析资料、多普勒雷达资料及WRF输出资料,研究了2014年6月20—21日发生在江南地区的一次持续性暴雨过程中中尺度对流系统(mesoscale convective system,MCS)的演变过程、结构特征及模态转变机理。此次暴雨发生在500 h Pa东移发展的短波槽前、850 h Pa切变线与低空暖湿急流之间的不稳定区。MCS演变过程中组织模态发生转变,对流东移发展形成拖尾型(tailing stratiform,TS) MCS,后逐渐转变为平行型(parallel stratiform,PS) MCS。环境风场上,TS型MCS表现为垂直对流线的相对入流,弓状回波北侧有气旋生成; PS型MCS低层表现为垂直对流线的相对入流,中高层表现为平行向相对入流。TS型MCS中,强对流区位于正扰动气压带,形成垂直作用于对流线的气压梯度力,导致相对入流垂直对流线;而在平行对流线方向上,扰动气压变化小,平行相对气流弱,整体呈现为较强的垂直向相对气流; PS型MCS中,气压扰动整体表现为西南正气压扰动与东北负气压扰动的分布特征,在西南-东北向气压梯度力作用下,形成平行对流线向后的相对入流,导致MCS模态的转变。     

南京北郊污染物来源及跨区域输送过程研究

利用全国空气质量指数(Air Quality Index,AQI)、PM_(2.5)地面观测数据、全球数据同化系统GDAS数据和FNL再分析气象资料,研究了2015/2016年冬季南京北郊空气质量变化特征以及环境输送条件和污染物源区。结果表明:以AQI为代表的冬季江淮地区污染程度存在3种典型的污染物跨区域输送路径—西北路径、北方路径和西南路径。西北路径通常发生在蒙古高压较强,且处于平均位置时刻,南京北郊上空有冷平流,不利于污染物扩散;北方路径对应蒙古高压弱,东北附近为弱高压控制,偏北气流将污染物带至南京北郊,如跨海洋,则污染减弱;西南路径对应南京北郊为边界层内反气旋式环流中心,下沉气流十分不利于污染物扩散。影响南京北郊污染的潜在源区主要分布在河北南部、山东西部、河南南部、安徽东部和湖北西部。河北省是重要的污染源区,河北南部和山东西部污染物通过北方路径输送至南京北郊,因此北方路径虽发生污染概率少于其他两种,却是形成南京北郊严重污染的重要路径。河南南部污染物通过西北路径输送。安徽和湖北污染物通过西南路径输送。定量分析表明,平流输送是南京北郊重度污染的重要原因,近地层风速对AQI的平流输送占AQI变化的贡献率超过70%,甚至可达85%。     

Numerical modeling of pollutant transport and chemistry during a high‐ozone event in northern Taiwan

An air pollution prediction model system (APOPS) is developed and applied to northern Taiwan with complex terrain and local thermal circulations. It consists of a nonhydrostatic mesoscale meteoro‐logical model system (MMPMS) and a gas/aerosol transport and air quality model (GATAM). The basic processes relevant to modeling the urban air pollution problems such as meteorology, dispersion, chemistry and deposition are solved at the same time on practically the same grid. The APOPS was tested on a high‐ozone event in northern Taiwan on 16 November 1998. Comparison with observed surface winds shows able to predict local flow patterns such as sea/land breezes and mountain‐valley wind in this high air pollution episode. The predicted surface concentrations of ozone and other pollutants are compared with measured values, and a fairly good agreement with the mean normalized biases of −6%, −11%, for one‐day simulation and for daytime, respectively, is obtained for ozone. Thus, it is confirmed that the APOPS can be utilized to predict urban air quality in complex terrain area.     

京津冀地区一次严重霾天气过程及其影响因素分析

利用大气污染监测资料、常规气象观测资料及NCEP再分析资料,对2013年1月9—17日京津冀地区一次严重霾天气过程的特征及其与气象条件的关系进行分析。结果表明：此次霾天气过程京津冀地区6个城市（北京、天津、石家庄、保定、邯郸、唐山）的PM10、SO2和NO2污染物日平均浓度均较高,变化趋势基本相同,其中PM10日平均浓度的变化幅度最大,峰值出现在11—13日之间;石家庄、保定和邯郸市的污染最严重,PM10日平均浓度最大值分别为0.94 mg·m－3、0.95 mg·m－3和0.82 mg·m－3。SO2和NO2日平均浓度的变化幅度较小,但浓度值均较大,基本为0.10 mg·m－3以上。影响此次霾天气过程的大范围环流形势为纬向型,存在较强的逆温层,弱下沉运动使近地层大气处于静稳状态,不利于污染物扩散,而近地面较小的风速和低层相对湿度小于90％为霾的形成提供了有利条件。另外,后向轨迹分析表明,此次污染过程京津冀地区的气团主要来自新疆地区,路径主要是从西北气流转为西南气流,携带南方的湿空气和污染物向京津冀地区输送。     

辽宁北部典型流域水生态功能三级分区与水生态服务功能评价

流域水生态功能区划是水生态和水资源综合保护的重要前提和基础。在综合分析调查辽河流域辽北地区典型流域自然环境特征、水文数据、地理信息数据的基础上,结合辽河流域水生态功能一级、二级分区结果,建立水生态功能三级分区指标体系,对辽宁省辽河流域内清河、汎河流域进行水生态功能三级分区。结果表明：清河流域可分为7个水生态功能三级区,汎河流域可分为4个水生态功能三级区,水生态服务功能类型共划分为5类：生物多样性与生物栖息地维持功能,产品提供与农业生产功能,水源涵养与水文调蓄功能,人居保障与城市发展功能,水土保持与生态修复功能。水生态功能三级分区结果为辽河流域实施水生态综合管理提供了科技支撑,同时也为中国水生态功能分区技术规范的制定提供了科学依据。     

深圳S波段与X波段双偏振雷达在定量降水估计中的应用

双偏振多普勒天气雷达的一个重要应用是进行定量降水估计（QPE）,它可以获得反射率（Z_H）、差分反射率（Z_DR）和差传播相移率（K_dp）这些与降水粒子有关的信息,常用的双偏振雷达降水估计方法有基于Z_H的R（Z_H）、基于Z_H和Z_DR的R（Z_H,Z_DR）、基于K_dp的R（K_dp）和基于K_dp与Z_DR的R（K_dp,Z_DR）这4种。文中利用深圳市S波段和X波段双偏振多普勒雷达探测资料,结合高精度地形数据和雨滴谱仪观测数据,设计了基于双偏振量的定量降水估计方法:首先利用地形数据和雷达地理信息,分析了雷达的遮挡状况,形成了这两部雷达的复合平面扫描仰角信息;随后利用雨滴谱仪观测资料,使用T矩阵方法统计得到了深圳地区的上述4种降水反演方法的参数;最后设计了混合降水反演方法,基于双偏振信号（即K_dp和Z_DR）的强弱,使用不同的降水反演方法进行定量降水估计。基于12个降水个例,利用各反演方法产生的定量降水估计结果与雨量计观测资料比较。结果表明,混合降水反演方法在降水反演的准确度和稳定性上均优于任何一种单一定量降水估计反演方法。基于文中介绍的定量降水估计方法,使用深圳S波段和X波段雷达产生了定量降水估计产品,并与深圳目前业务定量降水估计产品进行对比评估。结果表明,使用本方法产生的定量降水估计产品在准确度和稳定性上要优于目前的业务产品。此外,X波段雷达的定量降水估计产品性能要略高于S波段雷达的定量降水估计产品,这说明高时、空分辨率的X波段雷达可以提高定量降水估计精度。但由于雷达扫描平面内双偏振雷达对融化层和冰区的偏振量观测与降水的关系尚未明确,因此,本方法仅适用于雷达扫描平面内液态降水区。      

云下部正电荷区与负地闪预击穿过程

三维雷电观测系统LMA(Lightning Mapping Array)是最近发展起来的基于GPS时钟同步的闪电VHF辐射源到达时间差(TOA)定位技术,能以很高的时间分辨率(50 ns)和空间定位精度(50—100 m)展现闪电放电发展过程的三维时空分布,揭示雷暴中电荷结构及其与放电过程的关系。文中利用三维雷电VHF辐射源观测资料分析了负地闪预击穿过程的时空分布特征,讨论了云下部正电荷区对负地闪发生的影响,其结果表明在首次回击之前存在长时间预击穿过程的负地闪中,预击穿过程是云中部负电荷区与下部正电荷区之间的一种云内放电过程,闪电起始于云中部负电荷区,然后向下发展传输,进入正电荷区后闪电通道在云下部正电荷区水平发展,其放电特征与反极性云闪放电一致,云内放电过程最后阶段的K型击穿激发了地闪的梯级先导,梯级先导穿过云下部正电荷区向下发展传输。云下部正电荷的存在是导致负地闪首次回击之前存在长时间云内预击穿过程的主要原因。