Spatial trends of dustfall over northern China in the spring and their influencing factors

The spatial trends of dustfall of different sizes over northern China during April and May 2001,and March 2002,and their influencing factors,were analyzed.We divided the dustfall into seven grades based on particle size.Total dustfall and dustfall for each grade were highest in desert regions then in regions undergoing desertification,and the total dustfall,dustfall 【100 μm and dustfall 】250 μm were higher in western agricultural regions closer to desert areas than in eastern agricultural regions.The spatial trends in dustfall 【300 μm in diameter were most strongly correlated with dust events,and the content of coarse particles increased with increasing severity of dust events.Because the spatial trend for dust events appears to be controlled by geomorphic conditions,vegetation coverage,soil moisture,and the distance from dust source,dustfall 【300 μm in diameter appears to have the same controlling factors as dust events,but the control decreases with increasing particle size.Wind,the driving force for dust emissions,also influenced the spatial trends in dustfall 【200 μm in diameter,and especially for dustfall 50 to 100 μm in diameter.Although dustfall 【300 μm in diameter and precipitation were not strongly spatially correlated,there is some evidence that high precipitation decreased deposition by restraining blowing sand.The coarser the dustfall,the weaker the correlation with wind speed;however,transport of larger particles still occurs,and further research will be required to test the possibility that this dust is entrained mainly by the small-scale dust devils that are commonly observed in the study area.

Human settlement's social network analysis based on spatial trend surface model:a case study of Chongqing Municipality

Integrated with GIS and remote sensing(RS) technology,a systematic analysis and its methodology for human-settlements social environment has been introduced.This methodology has been called spatial trend field model(STFM).STFM's application history in the field of human-settlements social environment has been discussed at first.Then,some index data models have been created through STFM,which include population density trend field,human activity strength trend field,city-town spatial density trend field,urbanization ratio trend field,road density trend field,GDP spatial density trend field and PER-GDP spatial density trend field.With all above-mentioned indexes as input data,through Iterative Self-Organizing Data Analysis Techniques Algorithm(ISODATA),this paper makes a verification study of Chongqing municipality.The result of the case study confirms that STFM methodology is credible and has high efficiency for regional human-settlements study.

Analysis on Temporal-spatial Distribution and Change Trend of the Temperature in Beibei District

[ Objective] The research aimed to analyze temporal-spatial distribution and change trend of the temperature in Beibei District. [ Method] Based on temperature observation data at 6 ground meteorological observatories of Beibei District from 1951 to 2010, EOF and linear trend method were used to analyze temporal-spatial distribution and change characteristics of the temperature in Beibei District in recent 60 years. [ Result] Tem- perature in Beibei District in recent 60 years overall presented rise trend, and average rise velocity was 0.045 ~C/10 a. Temperature rise in autumn was the most obvious, while summer temperature presented decline trend. Average temperature presented gradual rise trend from January to July and gradual decrease trend from August to December. Seen from spatial distribution, temperature in the whole district was higher in the west and lower in the middle. Abnormal spatial distribution of the average temperature in the whole district mainly had consistent higher （lower） type, south- north reverse type and east-west reverse type. [ Condusionl The research provided theoretical basis for effective disaster prevention and reduction in the zone.

Assessment of Spatial Distribution and Temporal Trends of Precipitation and Its Extremes over Nigeria

This study analyzed the spatial distribution and temporal trends of precipitation and its extremes over Nigeria from 1979-2013 using climate indices, in order to assess climatic extremes in the country. Daily precipitation data used in this study were obtained from Nigeria Meteorological Agency (NIMET), Lagos. The study used climate indices developed by the Expert Team on Climate Change Detection (ETCCDI) for assessing extreme precipitation. Sen’s slope estimator and Mann-Kendall trend test were employed in data analysis. Results revealed that precipitation and its extremes varied spatially across Nigeria. Significant negative trends were observed in most of the precipitation indices for the period under study. Furthermore, significant downward trends were observed in the CWD (Consecutive Wet Day) while the CDD (Consecutive Dry Day) showed significant upward trends in all the regions. These spatial and temporal changes indicate that Nigeria’s climate is trending towards a warmer and drier condition, which could be attributed to global warming-induced climate change;which altered historical rainfall patterns thereby leading to extreme events. The findings of this study have provided useful information in understanding the extreme events that are assumed by the general populace to be normal recurrent events in Nigeria. The results of the analysis of yearly and decadal changes in precipitation totals and extreme values for the last 35 years (1979-2013) suggest the likelihood of severe impacts on water resources, agriculture, and water-sensitive economic activities

The Spatial-Temporal Characteristics of Meteorological Disasters in the Southwest Region of Zhejiang Province during 1953-2022

Meteorological disasters are some of the most serious and costly natural disasters, which have larger effects on economic and social activity. Liuchun Lake is an ecotourism area in the southwest region of Zhejiang province, where also has experienced meteorological disasters including rainstorm and cold wave. Understanding the temporal-spatial characteristics of meteorological disasters is important for the local tourism and economic development. Based on the daily temperature and precipitation from 18 meteorological stations in the southwest of Zhejiang province during 1953-2022 and some statistical approaches, the temporal and spatial characteristics of meteorological disasters (Freezing, Rainstorm, Cold wave) are analyzed. The results indicate that 1) Rainstorm occurred frequently around the Liuchun lake, the frequency was about 8 times/a, it can also reach about 3 times/a in the other region. Freezing and cold wave (including strong cold wave and extremely cold wave) had the same spatial distribution as rainstorm, however, except for Liuchun lake, they occurred less than one time in the other regions;2) The trend of rainstorm had larger spatial difference, it increased in all the study area, but it increased more significantly around the study area than around Liuchun lake. Freezing was on the downtrend in the whole region, with 93.3% of the stations passed the 95% significant level. Cold wave also showed a declined trend, but it was insignificantly at most of the stations, only 33% of the stations passed the 90% significant level. Compared with cold wave, strong cold wave and extremely strong cold wave had weaker decline in all the regions. In general, from 1953 to 2022 rainstorm showed an increasing trend, it was the main meteorological disaster in the study area, cold wave displayed a decreasing trend, but it still occurred about 2 - 3 times/a in most regions.

肺结核发病的时空分布特征和气象因素分析

通过对2015—2019年全国肺结核发病率数据(不含香港地区、澳门地区和台湾地区)可视化,探究全国肺结核发病的时空分布特征;通过空间自相关分析和拉格朗日乘数(LM)检验,选取面板数据空间杜宾模型探究有关气象因素对肺结核发病的影响。研究结果表明,每年的1月和3月是全国肺结核的高发期,且全国肺结核发病率存在空间聚集性,高发区域是新疆、西藏和青海等西北部地区;气温和湿度与当地肺结核发病是负相关关系,与周边地区的肺结核发病是正相关关系。

Soil trend effect on genetic correlation of crop properties

Analysis of influence of spatial trend on calculated genetic correlation coeffi-cient was carried out on winter wheat variety trial of a random block design. The result indicated that significant spatial structure existed in thousand kernel weight and kernels per head of winter wheat. Simulated data based on field data demonstrate that strong spatial trend is one of the important causes for genetic correlation coefficient (absolute value) being greater than 1. We suggested that analysis of spatial structure of field data by geostatistical technology be conducted before calculating genetic correlation coefficient.

Trends and Scales of Observed Soil Moisture Variations in China

A new soil moisture dataset from direct gravimetric measurements within the top 50-cm soil layers at 178 soil moisture stations in China covering the period 1981 1998 are used to study the long-term and seasonal trends of soil moisture variations, as well as estimate the temporal and spatial scales of soil moisture for different soil layers. Additional datasets of precipitation and temperature difference between land surface and air （TDSA） are analyzed to gain further insight into the changes of soil moisture. There are increasing trends for the top 10 cm, but decreasing trends for the top 50 cm of soil layers in most regions. Trends in precipitation appear to dominantly influence trends in soil moisture in both cases. Seasonal variation of soil moisture is mainly controlled by precipitation and evaporation, and in some regions can be affected by snow cover in winter. Timescales of soil moisture variation are roughly 1-3 months and increase with soil depth. Further influences of TDSA and precipitation on soil moisture in surface layers, rather than in deeper layers, cause this phenomenon. Seasonal variations of temporal scales for soil moisture are region-dependent and consistent in both layer depths. Spatial scales of soil moisture range from 200-600 km, with topography also having an affect on these. Spatial scales of soil moisture in plains are larger than in mountainous areas. In the former, the spatial scale of soil moisture follows the spatial patterns of precipitation and evaporation, whereas in the latter, the spatial scale is controlled by topography.

Spatial Information Research for Temperature and Precipitation Climate Data in Hengduan Mountains

[Objective] The aim was to study the spatial information of temperature and precipitation data in Hengduan mountains. [Method] Considering GIS spatial interpolation and numerical statistics theory, spatial prediction were carried out to the ten years average temperature and precipitation flux observation data in 109 sparse meteorological stations in Hengduan Mountains. Based on the spatial range of geographic position of Hengduan Mountains, and 1∶1 000 000 scale DEM as data sources, and using trend surface simulation and residual ordinary Kriging interpolation correction method, the spatial continuous surface for annual average temperature and precipitation were studied. [Result] It was scientific and reasonable to use certain unevenly distributed sparse climate observation station value, and by dint of trend simulation and residue interpolation method to get climate consecutive spatial result. This method can not only accurate the temperature and precipitation spatial distributions to grid point, but also can reflect macro and micro geography factors and topographic influence factor of variation. Furthermore, it can be predicted error term trend surface reasonable spatial distribution. Simulation results were basically in accordance with the objective law, and can be used for the region climate data spatial informatization simulation. [Conclusion] The study provided scientific spatial basic data for the further study of ecological and vegetation in Hengduan Mountains.

Intermonthly Difference of Multi-attribute Characteristics of Rainstorm in China Based on Spatial-temporal Differentiation

Based on the daily precipitation data of 545 meteorological stations in China from 1961 to 2016, the spatial-temporal variation characteristics of rainstorm rainfall and rainy days in different months of China were diagnosed from three aspects: climatic characteristics, variation trend and interannual variation. The results showed that:(1) Rainstorm rainfall and rainy days in different months of China from 1961 to 2016 had similar spatial characteristics in corresponding months. From January to July, the high-value areas of rainstorm rainfall and rainy days gradually expanded from southeast coast to northwest inland, but mainly distributed in the east area of Hu Huanyong Line. From August to December, it shrank from northwest to southeast coastal areas. Rainstorm rainfall and rainy days were less distributed in different months in the west area of Hu Huanyong Line;(2) From 1961 to 2016, the spatial-temporal variation characteristics of rainstorm rainfall in different months in China were basically consistent with that of rainy days. May to August was the most significant month for the variation trend of rainstorm rainfall and rainy days in China. It mainly distributed in the southeast monsoon area, and was mainly increasing trend. The trend of rainstorm rainfall and rainy days in northwest China changed slightly in different months;(3) The interannual variability of rainstorm rainfall in different months in China from 1961 to 2016 was similar to that of rainy days. The fluctuation characteristics from April to October were larger in the northern region. The southern region fluctuated greatly from November to December in January to March. With the development of the month, the high-value areas with large daily fluctuations of rainstorm rainfall and rainy days gradually expanded from southeast to northwest, northeast and southwest, and the fluctuations in southeast tended to decrease, then shrank from northwest, northeast and southwest to southeast, with the increasing fluctuations in southeast. The study has certain reference significance for flood control and disaster reduction and water resources planning and utilization.

Analysis on Temporal and Spatial Variation Characteristics of the Precipitation in Hexi Corridor in Recent 58 Years

[ Objective] The research aimed to analyze temporal and spatial variation characteristics of the precipitation in Hexi Corridor in the past 58 years. [Method] Based on monthly rainfall data in Hexi Corridor from 1951 to 2008, by using moving average, wavelet analysis and climate trend coefficient, variation rule of the precipitation in Hexi Corridor in the past 58 years was analyzed. [ Result] Average rainfall in Hexi Corridor in the past 58 years was 130.4 mm. Precipitation mainly concentrated in summer, occupying 59.08% of the annual rainfall. From June to September, it occupied 72.57% of the annual precipitation. Interdecadal change of the precipitation in Hexi Corridor wasn＇t severe. Average rainfall in each dec- ade was from 120.8 to 139.0 mm. The precipitation series had periods of the 5, 10, 21 and 32 years in Hexi Corridor from 1951 to 2008. in the fu- ture, annual, spring, summer and winter precipitation would have small increase tendency. Increase amplitude of the annual precipitation in Shule River basin was the biggest （5.231 -0.062 mm/10 a）. The increase amplitude in the south and southeast of the Heihe River basin was bigger than that in the northwest. The smallest increase amplitude of the annual precipitation was 3.280 -0.098 mm/10 a in Shiyang River basin. [ Conclusion] This research could provide beneficial reference for coordinated development between local social economy and ecological environment.

Spatial and Temporal Variation Characteristics of Gale Days in China from 1961 to 2016

Based on data of hail days at 2 481 stations during 1961-2016,the temporal and spatial distribution characteristics and periodic variation of gale days in China and seven geographical regions were analyzed by using a variety of statistical methods. The results showed that: in time,the gale days in China and the seven geographical areas all showed a decreasing trend from 1961 to 2016. In the Tibet( Southeast China and Southwest China) region,the annual number of single-station gale days was the most( least),but the decrease ratio was the least( most). In the significance oscillation period,it was 14 years in the whole country,60 years in Northeastern China,Northern China and east part of Northwestern China,7,14 and 60 years in the west of Northwestern China,Southwestern China and Southeastern China,7 and 60 years in the Tibet region. The mutation of gale days generally occurred in 1991,1993,1989,1997,1986,1997,1992 and 1984 in the whole country,Northeastern China,Northern China,east part of Northwestern China,west part of Northwestern China,Tibet,Southwestern China and Southeastern China,but only the east of Northwestern China and Tibet region passed 0. 05 of significance test. In space,the annual average gale days showed the pattern of southeast low and northwest high in China from 1961 to 2016. The annual average gale days were more abundant in the central and western Tibet,the southern Qinghai,eastern Xinjiang,western Sichuan,northern Inner Mongolia and northern Gansu. These regions were dominated by positive anomaly in the 1970 s and the 1980 s,but negative in other decades. Annual gale days in most regions of China showed a decreasing trend during 1961-2016,and fluctuation presented high in east region and low in west region beside " Hu Huanyong line".

Effect of Mathematical Expression of Vegetation Indices on the Estimation of Phenology Trends from Satellite Data

Vegetation indices(VIs) from satellite remote sensing have been extensively applied to analyze the trends of vegetation phenology. In this paper, the NDVI(normalized difference vegetation index) and SR(simple ration), which are calculated from the same spectral bands of MODIS data with different mathematical expressions, were used to extract the start date(SOS) and end date(EOS) of the growing season in northern China and Mongolia from 2000 to 2015. The results show that different vegetation indices would lead to differences in vegetation phenology especially in their trends. The mean SOS from NDVI is 15.5 d earlier than that from SR, and the mean EOS from NDVI is 13.4 d later than that from SR. It should be noted that 16.3% of SOS and 17.2% of EOS derived from NDVI and SR exhibit opposite trends. The phenology dates and trends from NDVI are also inconsistent with those of SR among various vegetation types. These differences based on different mathematical expressions in NDVI and SR result from different resistances to noise and sensitivities to spectral signal at different stage of growing season. NDVI is prone to be effected more by low noise and is less sensitive to dense vegetation. While SR is affected more by high noise and is less sensitive to sparse vegetation. Therefore, vegetation indices are one of the uncertainty sources of remote sensing-based phenology, and appropriate indices should be used to detect vegetation phenology for different growth stages and estimate phenology trends.

四川省汛期小时极端降水精细化特征

使用2012-2021年四川省2985个气象站5-9月逐小时降水资料,分析了小时极端降水的精细化特征.研究结果表明:四川省汛期小时降水在第99百分位出现转折性变化,小时极端降水阈值随海拔升高而减小.总体上小时极端降水贡献率四川盆地最高,攀西地区次之,川西高原最低,其与汛期降水量的多少基本匹配.研究期内各个区域的汛期小时极端降水贡献率均以增加趋势为主,川西高原和攀西地区尤其显著,但空间差异非常大.在一天中,各区域小时极端降水都呈“单峰型”,夜间出现小时极端降水的概率相对更大,不同地区的峰值出现时间有所不同,中午时段均不易出现小时极端降水.研究期内小时极端降水出现峰值更高、谷值更低的变化趋势.小时极端降水过程达峰快、减弱慢,开始时间越晚持续时间越长.四川盆地和攀西地区下午至前半夜多为1~3 h短过程,后半夜多为3~11 h持续过程,而且川西高原的开始时间略晚,持续时间更长.

Characteristics of Spatial Structural Patterns and Temporal Variability of Annual Precipitation in Ningxia

[Objective] The aim was to study the characteristics of the spatial structural patterns and temporal variability of annual precipitation in Ningxia.[Method] Using rotated empirical orthogonal function,the precipitation concentration index,wavelet analysis and Mann-Kendall rank statistic method,the characteristics of precipitation on the spatial-temporal variability and trend were analyzed by the monthly precipitation series in Ningxia during 1951-2008.[Result] In Ningxia,the spatial structural patterns of annual precipitation appeared 'North-south type' and 'North-center-south type'.It increased from north to south,the changes of interannual precipitation decreased from north to south.Precipitation changed significantly in month and distributed differently in the Yellow River irrigation area.But it was conversely steady in central arid zone and mountainous area of southern Ningxia.The probability of single abundant precipitation year was higher than single short precipitation year and the continuous short precipitation year was higher than continuous abundant precipitation year.The main cycles were 3a,6a and 10a approximately.In the mid arid zone and the mountainous area of southern Ningxia,the probability of precipitation reduction was about 75% and the Yellow river irrigation area,71.4%,respectively.The reduction in the entire area was about 73.3%.The annual precipitation in the middle arid area and irrigation area was increasing.The variability would change slowly for the intra-annual distribution of precipitation.Especially,the reduction tendency rate in the middle arid area reached 100.0%.[Conclusion] The study provided references for the effective utilization of the local precipitation,and the coordinated development of the regional social economy and ecological environment.

1960-2020年河南省极端降水时空演变特征

全球变暖加快了水文循环速度,导致极端降水事件频发,增强了城市排水负荷和洪涝风险,并影响了区域气候的时空特征。在河南省均匀选取26个雨量站对1960—2020年61年间的降水资料进行研究,采用趋势分析、Kriging插值、M-K突变分析、Morlet小波变换和Spearman相关系数等方法对河南省9个极端降水指数的时空演变特征进行分析。结果显示:河南省年降水量呈上升趋势,极端降水事件呈下降趋势,河南省整体气候逐渐变得湿润。河南省极端降水指数具有显著空间差异,东南部极端降水风险显著大于西北部。除降水强度、最大连续降水日数和1 d最大降水量外,其余指数与年降水量、汛期和6—9月的各月降水量具有良好的相关性,这对于评估年降水量及其年内分布特征、极端降水事件频率有较好的参考作用。结果表明:降水从短历时高强度向长历时低强度演变,要应对此类长历时极端降水的风险,防涝思路应从提高短时间大量排水能力转变到提高长时间低强度吸收降水能力。

太仓市耕地土壤基本属性空间分布特征研究

为掌握江苏省太仓市耕地土壤基本属性,于2021年秋季采集区域内88个土壤样品,样品经制备、实验室检测后,获取土壤有机质(SOM)、全氮(TN)、全磷(TP)、全钾(TK)、酸碱度(pH)5项属性值。基于ArcGIS软件地统计分析模块中的普通克里格插值功能,得到土壤属性的空间分布特征。结果显示,太仓市SOM、TN、TP和TK分别为25.26、1.48、1.45和10.53 g/kg。在空间分布上,SOM和TN具有一定的相似性,整体上呈“西高东低”的趋势;TP和TK分别为“北高南低”和“东高西低”。太仓市pH均值为7.51,呈中性偏弱碱性。

大数据的6种地理学应用范式

随着大数据时代的来临,多源大数据正在兴起,数据驱动研究范式与地理学日益融合。基于个体行为的地理空间大数据可提供对海量个体行为模式的观察,从而实现“由人及地”的社会感知,支持城市管理、交通、公共卫生等不同应用。本文从应用角度,以地理空间大数据为重点,梳理其支持的6种应用范式,按照层次从低到高依次为描述时空分布、识别异常对象、发现普适规律、揭示关联关系、预测未来趋势及优化空间决策。其中,第1个方向是对地理现象和地理要素时空特征的简单刻画;第2~4个方向则注重探寻时空分布特征背后的规律和机理;最后两项,则是在决策层面提供支持。继而,本文指出大数据应用中数据获取、分析方法和应用目标3方面的问题。

县域耕地非农化时空演变特征及动态趋势研究——以安徽省为例

耕地是国家粮食安全的物质基础,把握耕地非农化的时空演变规律及动态趋势,对保障粮食供给和可持续发展具有重要意义。以安徽省为研究对象,基于ArcGIS、GeoDa和Matlab软件,提取安徽省1995—2020年耕地非农化数据,在县域尺度上,采取探索性空间数据分析方法研究耕地非农化时空演变特征,运用MarKov链分析耕地非农化的动态演变趋势,为合理管控耕地非农化提供科学依据。结果表明,安徽省耕地非农化面积高值区主要位于安徽省中部(合肥都市圈)重点发展区,低值区主要集中在安徽省北部和南部一些经济欠发达地区,空间集聚性呈先减后增再减趋势,集聚效应逐渐减弱,冷热点区在空间上形成了“块状热点集群”和“点状冷点集群”。安徽省县域耕地非农化水平的趋势主要表现为:不同等级间不够稳定,易发生转移;等级转移基本发生在相邻类型之间,较少出现“跳跃式”转移;考虑空间因素后发现,相邻县区差异化的耕地非农化水平对本县区发生等级转移的概率有不同程度的影响,随着空间溢出效应增强,维持原等级的概率越低,更易发生转移;等级转移的概率同时受空间滞后类型和初始等级的影响。

1979-2020年西北地区地表风速的年代际变化特征

基于1979-2020年西北地区173个气象站点10 m风速观测资料和ERA-5再分析资料,揭示了西北地区年、各季节风速的年代际变化特征及2003/2004年年代际变化可能的环流背景。结果表明:1979-2020年趋势分布存在显著的区域差异,风速增大区域主要位于甘肃中部和东部、陕西、新疆西南和东北部分地区,其余站点风速大体减小。呈现减小趋势的站点数明显多于增加趋势的站点数,呈现减小趋势站点平均地表风速大于整个西北平均的风速值,呈现增加趋势的站点的平均地表风速小于整个西北平均的风速值,并且在2004年后明显增大。年平均和各季节第一模态的空间分布与1979-2020年趋势分布相似,时间序列的年代际变化发生在2000年前后。年平均和各季节第二模态除宁夏和陕西南部地区为负异常,其余站点大体均为正异常,其时间序列均发生了两次突变,分别发生在1987/1988年和2003/2004年。1987/1988年的西北地区风速变化成因已有大量研究,本研究重点分析了2003/2004年西北风速年代际变化成因的环流因子。从500 hPa位势高度2004-2020年与1988-2003年的合成差图可知,春季环流场呈现中亚-北欧的经向偶极子模态,夏季和秋季呈现为“丝绸之路”模态,冬季呈现“斯堪的纳维亚”模态,年平均呈现为北极涛动负位相。可见,2003/2004年前后四季和年平均环流背景变化都各有特点,它们如何影响中国西北地表风速2003/2004年的年代际变化的物理过程待于进一步深入研究。