月均气温对三叶青林下容器栽培苗光合特性及其块根总黄酮含量的影响

文章比较了2015—2019年五府山月均气温对三叶青林下容器栽培苗光合生理及其块根总黄酮含量的影响。结果表明,2015—2019年,五府山1月的气温最低,2—6月气温逐渐提升,7—8月气温达到最高值,9—12月气温逐渐下降。随着1—6月气温逐渐提高,五府山三叶青林下容器栽培苗叶绿素含量SPAD值、净光合速率(P_(n))、气孔导度(G_(s))、蒸腾速率(T_(r))、气孔限制值(L_(s))、瞬时羧化速率(CUE)、初始荧光(F_(o))、最大荧光(F_(m))、光下最小荧光(F′_(o))、光下最大荧光(F′_(m))、稳态荧光(F_(s))、PSⅡ最大光能转化效率(F_(v)/F_(m))、PSⅡ潜在光化学效率(F_(v)/F_(o))、PSⅡ实际光化学效率(ΦPSⅡ)、开放的PSⅡ反应中心捕获激发能效率(F′_(v)/F′_(m))、光化学淬灭系数(q P)和块根总黄酮含量显著提高(P<0.05),胞间CO 2浓度(C_(i))、水分利用效率(WUE)和非光化学淬灭系数(NPQ)显著下降(P<0.05);气温在7—8月达到最高值,五府山三叶青林下容器栽培苗叶绿素含量SPAD值、P_(n)、G_(s)、T_(r)、L_(s)、CUE、F_(o)、F_(m)、F′_(o)、F′_(m)、F_(s)、F_(v)/F_(m)、F_(v)/F_(o)、ΦPSⅡ、F′_(v)/F′_(m)、q P和块根总黄酮含量达到最大值,C_(i)、WUE和NPQ达到最低值;9—12月气温逐渐下降,五府山三叶青林下容器栽培苗叶绿素含量SPAD值、P_(n)、G_(s)、T_(r)、L_(s)、CUE、F_(o)、F_(m)、F′_(o)、F′_(m)、F_(s)、F_(v)/F_(m)、F_(v)/F_(o)、ΦPSⅡ、F′_(v)/F′_(m)、q P和块根总黄酮含量显著下降(P<0.05),C_(i)、WUE和NPQ显著提高(P<0.05)。本试验结果可为三叶青林下容器生态栽培提供气象因子(气温)依据。

基于改进指数平滑算法的气温预测研究

本文主要研究了基于改进指数平滑算法的气温预测问题。首先引入时间序列模型概念,对常用气温预测模型进行简要分析,另外对一阶指数平滑算法进行相关推导,同时提出了自适应指数平滑算法;其次,结合广西容县近30年月均气温实测数据,分别建立BP神经网络预测模型、传统指数平滑算法预测模型以及改进后的基于自适应指数平滑算法的预测模型,对2016年气温数据进行预测并分析模型优势;最后,将改进模型用于预测2017年和2018年中未知月份的月平均气温值,并针对实验结果进行数据分析修正。通过对不同预测模型的比较和仿真实验,结果表明基于自适应指数平滑算法的气温预测模型预测精度较高,实用性强,具有一定的推广性。

The extreme dry/wet events in northern China during recent 100 years

Using monthly precipitation and monthly mean temperature, a surface humid index was proposed. According to the index, the distributed characteristics of extreme dryness has been fully analyzed. The results indicated that there is an obvious increasing trend of extreme dryness in the central part of northern China and northeastern China in the last 10 years, which shows a high frequency period of extreme dryness; while a low frequency period in the regions during the last 100 years. Compared with variation trend of the temperature in these regions, the region of high frequent extreme dryness is consistent with the warming trend in the same region.

Trends in Monthly Temperature and Precipitation Extremes in the Zhujiang River Basin,South China(1961-2007)

Monthly temperature and precipitation time-series for the Zhujiang River Basin are analyzed in order to identify changes in climate extremes. Daily temperature and precipitation data from 1961 to 2007 of 192 meteorological stations are used. Two temperature indicators （monthly mean and monthly maximum mean） and three precipitation indicators （monthly total, monthly maximum consecutive 5-day precipitation, and monthly dry days） are analyzed. Tendencies in all five indicators can be observed. Many stations show significant positive trends （above the 90% confidence level） for monthly mean temperatures and monthly maximum mean temperatures. For all months, a significant increase in temperature from 1961 to 2007 can be observed in the entire basin with the coastal area in particular. Positive trends of precipitation extremes can be observed from January to March. Negative trends are detected from September to November. The number of dry days in October increased significantly at 40% of all meteorological stations. Stations with changes of monthly precipitation extremes are scattered over the Zhujiang River Basin. An aggregation of heat waves and droughts can be detected which is accompanied by significant increases of temperature extremes and the negative tendencies in precipitation extremes. The detection of tendencies in climate station density. extremes essentially relies on a good data quality and high

Characteristics of Spatial and Temporal Variations of Monthly Mean Surface Air Temperature over Qinghai-Tibet Plateau

The recorded meteorological data of monthly mean surface air temperature from 72 meteorological stations over the Qinghal-Tibet Plateau in the period of 1960-2003 have been analyzed by using Empirical Orthogonal Function （EOF） method, to understand the detailed features of its temporal and spatial variations. The results show that there was a high consistency of the monthly mean surface air temperature, with a secondarily different variation between the north and the south of the plateau. Warming trend has existed at all stations since the 1960s, while the warming rates were different in various zones. The source regions of big rivers had intense warming tendency. June, November and December were the top three fast-warming months since the 1960s; while April, July and September presented dramatic warming tendency during the last decade.

CHARACTERISTICS OF CHANGE IN TEMPERATURE DURING THE PAST 50 YEARS IN JILIN PROVINCE OF CHINA

Based on the monthly mean temperatu re,the changing processes and tendencies of temperature during1951-2000in Jilin Province,which i s in Northeast China,are analyzed.A nd the spatial characteristics of th e change are submitted.In the past 50years the te mperature of Jilin Province was increasing just like the other areas in th e world.Since 1990,the increasing of temperature has been more obvious th an that in the previous 40a.From the west to the east,the province has larger tem perature rising.According to Principal Component Analysis(PCA)of temperature field,Jilin Province is divided int o 3regions and the degree of becoming warmer is different from region to re gion.During the period of 1951to 2000,the annual temperature in Jilin Province has been rising,so has the temperature in winter and summer.The average temperature in t he 1990s was 0.5-2.0℃higher than that in the 1950s.From the west to the east,the increasing of temperature becam e smaller.

Impact of Autumn SST in the Japan Sea on Winter Rainfall and Air Temperature in Northeast China

We studied the impact of sea surface temperature anomaly(SSTA) in the Japan Sea and the sea area east of Japan on the winter rainfall and air temperature in Northeast(NE) China using the singular value decomposition(SVD) and empirical orthogonal function(EOF). The monthly-mean rainfall data observed at 160 stations in China, monthly-mean sea surface temperature(SST) of the Hadley Center for Climate Prediction and Research and monthly-mean air temperature from the NCEP reanalysis during 1960–2011 were used. Correlation analysis indicates that the SSTAs in the Japan Sea in September may last for three or four months and are an important index for forecasting the winter rainfall and air temperature in NE China. Positive SSTAs in the central Japan Sea and in the sea area east of Tokyo correspond to positive rainfall anomaly and negative air temperature anomaly in NE China. With the rise of SST in the Japan Sea, a weak cyclone appears over the Japan Sea. The northeasterly wind transports water vapor from the Okhotsk to NE China, resulting in more rainfall and lower air temperature. Negative SSTA years are accompanied by warmer air temperature and less snow in NE China. The 1000 h Pa geopotential height anomaly and wind anomaly fields are simulated by IAP-9L model, which supports the analysis results.

Climate-induced Changes in Spring Maize Water Requirement in Xiliaohe River Watershed

Xiliaohe River watershed plays an important role in regional and national grain security.With the development of society and economy,water consumption that increased dramatically causes water shortages.Crop water requirement can provide quantitative basis for making regional irrigation scheme.In this study,spring maize water requirement is calculated by using PenmanMonteith formula and spring maize coefficient from May to September at 10 meteorological stations in Xiliaohe River watershed from 1951 to 2005.The variation trend of the spring maize water requirement during the whole growing stage,water requirement in every month,and meteorological influencing factors are obtained by using Mann-Kendall method,and the degree of grey incidence between the water requirement and meteorological influencing factors are shown.The results are the spring maize water requirement during the whole growing stages increases at half of the stations in Xiliaohe River watershed,and are remarkably affected by the water requirement in May.The monthly mean,maximum and minimum air temperature form May to September show an increasing trend in Xiliaohe River watershed in recent 55 years.The monthly mean and minimum air temperature increases notably.The relative humidity,precipitation,wind speed and sunshine show a decreasing trend with variety for different months.The monthly maximum air temperature,wind speed,sunshine and monthly mean air temperature have the highest correlation degree with spring maize water requirement from May to September.

Historical and Future Climatic Change Scenarios for Temperature and Rainfall for Iraq

The world is facing a big challenge of climatic change, mainly due to increasing concentrations of GHGs （greenhouse gases） in the atmosphere. Many researches indicated that the climate change occurred disproportionately on developing countries such as MENA （Middle East and North Africa） countries. The climatic model CGCM3.1 （T47） 2 is used in this research to explain the changes in average temperatures and the rainfall on the MENA region with special emphases on Iraq. Historical records （1900-2009） and future （2020-2099） were studied and compared; each period was divided to four sub-periods of thirty years. The results showed that the average monthly temperature for the four historical periods fluctuated between the lowest and highest value as follows： 9.2-32.9, 10.3-32.7, 9.3-32.8 and 8.6-33.9 （℃）. The rainfall for historical periods kept on the same distribution during the past 109 years, and fluctuated between the lowest and highest value of 21.3 mm and 37.6 mm with an average that reached up to 26.51 mm. For the future period, the maximum average monthly temperature reached up to 37.41 （℃） during June and minimum average monthly temperature reached up to 4.24 （℃） during January. The average monthly temperature fluctuated giving a clear impression that the future portends a higher temperature. The average monthly rainfall, for the future period, fluctuated between the lowest and highest value of 12.91 mm and 20.63 mm with an average that reached 16.84 mm which represent a reduction percentage of about 36.47% relative to the historical record of rainfall for the sanae months.

Reconstruction of October Mean Temperature since 1796 in Wuying Based on Tree Ring Data

The monthly mean temperature for October in the Fenglin National Natural Reserve of Wuying, in Heilongjiang province, was reconstructed for the period running from 1796 to 2004 using RES tree ring chronology. The explained variance of the reconstruction is 34.8%. In the past 209 years, there are 4 colder and 4 warmer periods according to the reconstructed series. A period of 3.33-year is found significant based on the power spectrum method. Abrupt changes are also detected in the reconstructed series with 30-year time scale based on the smoothing t-test, smoothing F-test and Le Page test methods. Significant abrupt changes in mean value are observed for around 1871 and 1900, and a significant abrupt change in standard deviation is observed for around 1851.

国家基本/基准站地面气温资料城市化偏差订正

城市化偏差是中国地面气温观测记录中最大的系统性偏差,订正该偏差可为大尺度气候变化监测和研究提供准确的基础资料。论文介绍了用于单站地面月平均气温序列城市化偏差订正的一个方法,并利用该方法订正了685个国家基本/基准站1961—2015年地面年及月平均气温序列中的城市化偏差。采取自东往西迭代订正的方法,即从东往西逐经度订正,订正完的目标站也可作为参考站。首先,规定目标站的参考站在300 km范围内,并利用2站的去线性趋势年均气温的相关系数作为标准,规定相关系数最大且通过信度水平为0.005显著性检验的4个候选参考站作为该目标站的参考站;然后,对各个参考站年均气温与其对应目标站年均气温求相关,并以其平方为权重计算各参考站月和年均气温的平均值序列,即为各目标站年和月平均地面气温参考序列;其次,利用目标站气温序列趋势及其参考序列趋势之差作为总的订正值,订正目标站气温序列中包含的城市化偏差。较大的城市化偏差出现在华北地区、华中部分地区、东北北部、西南及西部部分地区,介于0.1～0.3℃/10 a;在中国西北部分地区、西藏西部及南部、东北南部、华南沿海、华东及华中个别站存在负偏差;对整个中国而言,相对城市化偏差为19.6%。以北京、武汉、银川、深圳作为华北、华中、西北和华南地区的大城市代表站,发现其在过去55 a的相对城市化偏差分别为67.0%、75.4%、32.7%和50.3%,与前人针对单站评估城市化影响的结果基本一致,说明论文的订正方法较为合理。论文介绍的城市化偏差订正方法,可用于订正中国等快速城市化地区地面气温观测资料的系统偏差,订正后的气温数据在很大程度上消除了城市化因素引起的不确定性。

基于城市化偏差订正的中国大陆1961-2015年月平均地面气温网格数据集

基于中国气象局国家气象信息中心提供的国家级地面气象站均一化气温月值数据,选择763个国家站的数据;以目标站周围300 km范围内的站点为参考站,利用参考站和目标站去线性趋势年平均气温序列的相关系数判定,取相关系数最大,并且显著性水平为0.005的显著性检验的4个参考站作为该目标站的参考站;然后,以各个参考站与其目标站年平均气温序列相关系数的平方为权重,计算参考站月平均气温加权平均值,即为参考序列;再利用城市站序列趋势和参考序列趋势的差值作为订正值,对目标站进行线性订正;最后,利用反距离权重插值法将全国范围763个站点的气温数据插值成2°×2°的格点数据。以北京、武汉、银川、深圳作为华北、华中、西北和华南地区的大城市代表站,发现其在过去55年的相对城市化偏差分别为67.0%、75.4%、32.7%和50.3%,与前人针对单站评估城市化影响的结果基本一致。该数据集存储为.txt格式,每个文件按照年月命名,每个文件由头文件和18行、32列的平均气温(℃)数据组成,前6行是头文件,分别为列数,行数,左下角格点经度,左下角格点纬度,网格大小,缺测值。数据集由660个数据文件组成,数据量为2.75 MB(压缩为1个文件,895 KB)。

Temporal and spatial analysis of changes in snow cover in western Sichuan based on MODIS images

We developed a method for analyzing the change in snow cover using MODIS imagery.The method was applied to images of western Sichuan Province,China taken between 2002 and 2008.The model for extracting data on snow cover from MODIS images was created by spectral analysis.The multi-temporal snow layers were used to evaluate the temporal and spatial change in the area under snow cover between 2002 and 2008 using overlay and statistical analysis in ARCGIS.The majority(60.4%) of western Sichuan was rarely covered by snow and only 0.3% was covered by perennial snow in 2002.Snow cover was pri-marily distributed in Garzê and Aba.The area under snow cover was significantly and negatively correlated with the average monthly temperature and rainfall in 2002.The largest area under snow cover was measured in 2006 and the smallest was in 2007.Similarly,the area of snowmelt was the highest in 2006 and lowest in 2007.In general,the elevation of the snow line in-creased throughout the period 2002-2008;however,the elevation decreased in some years.Our results provide an important insight into the distribution of snow in this region,and may be useful for climate modeling and predicting the availability of water resources and the occurrence of floods and droughts.

SIGNATURES OF UNIVERSAL CHARACTERISTICS OF FRACTAL FLUCTUATIONS IN GLOBAL MEAN MONTHLY TEMPERATURE ANOMALIES

This paper proposes a general systems theory for fractals visualising the emergence of successively larger scale fluctuations resulting from the space-time integration of enclosed smaller scale fluctuations. Global gridded time series data sets of monthly mean temperatures for the period 1880- 2007/2008 are analysed to show that data sets and corresponding power spectra exhibit distributions close to the model predicted inverse power law distribution. The model predicted and observed universal spectrum for interannual variability rules out linear secular trends in global monthly mean temperatures. Global warming results in intensification of fluctuations of all scales and manifested immediately in high frequency fluctuations.