基于土壤湿度和年际增量方法的中国夏季气温预测试验

本文利用中国160站月平均气温资料和欧洲中心ERA-Interim逐月再分析表层土壤湿度资料,通过相关分析选取欧亚大陆9个关键区的土壤湿度年际增量作为预测因子,采用变形的典型相关分析(BP-CCA)结合集合典型相关分析(ECC)的方法建立集合预测模型,对我国东部夏季气温年际增量进行预测,进而预测夏季气温。其中,1980—2004年的资料用于历史拟合试验,而2005—2014年的资料用于独立样本预测试验。首先利用BP-CCA方法对9个因子分别建立单因子预测模型,然后采用ECC方法对9个预测因子按照不同的组合方式建立集合预测模型,并且分析预测技巧。结果表明,不同预测因子的组合对我国夏季气温的预测能力不同:勒拿河下游地区、中国黄河以南地区、叶尼塞河下游地区、西西伯利亚平原地区以及印度半岛西北部地区的土壤湿度对华北夏季气温预测效果较好;中国黄河以南地区、叶尼塞河下游地区、印度半岛西北部地区、贝加尔湖东北地区以及贝加尔湖以西地区的土壤湿度对江淮夏季气温有较高预测技巧。所建立的两组集合预测模型均显示了较好的实际预测能力:华北气温预测模型预测气温距平的同号率为8/10,平均均方根误差为3.4%;江淮气温预测模型预测气温距平的同号率为7/10,平均均方根误差为2.7%。并且两组模型预测出的华北和江淮气温的预测评分(PS)均超过80分,而国际上通用的距平相关系数(ACC)均在0.3以上。这说明土壤湿度因子中包含对我国夏季气温有用的预测信号,可以考虑将土壤湿度应用于夏季气温预测业务中。     

基于土壤湿度和年际增量方法的我国夏季降水预测试验

选取欧亚大陆9个关键区的土壤湿度年际增量作为预测因子,采用变形的典型相关分析(BP-CCA)结合集合典型相关分析(ECC)方法建立集合预测模型,对我国东部夏季降水的年际增量进行预测,进而预测夏季降水。其中,1980~2004年的资料用于历史预测试验,而2005~2014年的资料用于独立样本预测试验。首先利用BP-CCA方法对9个因子分别建立单因子预测模型,然后采用ECC方法对9个预测因子按照不同的组合方式建立集合预测模型,并且对独立样本检验的效果进行了评估。结果表明,不同预测因子的组合对我国夏季降水均表现出一定的预测能力:东欧平原、贝加尔湖以北、我国河套地区及长江以南地区的土壤湿度对华北夏季降水预测效果较好;而巴尔喀什湖以北地区、我国西北地区、河套地区以及长江以南地区的土壤湿度对江淮夏季降水有较好预测效果;东欧平原、巴尔喀什湖以北地区以及我国河套地区的土壤湿度对华南降水预测技巧较高。这三组模型预测出的降水变化趋势与相应区域的观测结果较为一致,且预测评分(PS)均超过70分,距平相关系数(ACC)均为正值。研究表明土壤湿度因子中包含了对我国夏季降水有用的预测信号,可以考虑将土壤湿度应用于夏季降水的预测业务中。     

基于大气降水的华北地区土壤湿度预测模型

基于引入随机变量的机理性模型方法,利用华北地区2000—2008年气象台站观测数据,以大气降水为随机变量,并考虑其延迟效应,利用回归方法建立了预测时效为1旬的土壤相对湿度预测模型。利用预测率和干旱等级预报精度两个评价指标,结合2009年土壤湿度实际观测数据,验证了预测模型预报率均在90%以上,绝大部分站点的干旱等级预报精度均在70%以上,得出该预测模型在华北地区应用的合理性,从而建立了一套客观、动态的土壤湿度预测方法,有利于及时掌握农田旱情程度和分布,主动采取防旱、抗旱应对措施。     

农业气象产量预测业务系统的研制

农业气象产量预测业务系统（The Agrometeorological Yield Forecasting Operational System，简称AYFOS）使用Quick BASIC、MS-C和汇编语言混合编写而成，采用下拉式和弹出式中文菜单提示、彩色光（亮）条选择的人机界面，提供在线帮助。系统软件结构合理，操作方便、灵活，容错性好，产品图文并茂。系统功能齐全，包括数据管理、组建预测模型、预测模型思路记忆、模型实时预测与预测集成、产品输出管理和系统维护等主要功能模块。系统在某些方面具有自己的软件特色     

基于小波分解和最小二乘支持向量机的大气臭氧含量时间序列预测

基于小波分解(WT)和最小二乘支持向量机(LSSVM)理论,建立了将二者相结合的大气臭氧含量时间序列预测模型。采用香河等4个观测站的月平均臭氧总量观测样本,经小波分解为不同频段的子序列,将这些子序列分别进行LSSVM预测,最后经小波重构得到月平均臭氧总量时间序列预测结果。实验表明该方法能有效预测大气臭氧含量,与支持向量机(SVM)以及人工神经网络(ANN)的预测结果相比,该方法具有较高的预测精度。     

利用BP神经网络模拟预测夏季降水场

利用人工神经网络(ANN-Artificial Neural Network)的反向传播(BP-Back-Propagation)模型,对永州市夏季(6～8)降水场进行模拟及预测,取得了较好的效果,并建立了永州市降水场的人工神经网络BP预测模型,为降水趋势预测提供了一种研究方法。     

流域年均含沙量的B—P网络预测模型及其效果检验

应用误差反向传播算法的人工神经网络，建立了流域年均含沙量的预测模型，该模型用于某流域年均含沙量预测的拟合率达９０％以上，预留检验预报的准确率为７５％。     

热带气旋路径人工神经元预报方法对比试验研究

分别对具有动量项BP、LM、RBF人工神经网络建立36、48、60、72小时的热带气旋路径预测模型,各用100个独立样本进行预测检验,分析了网络"学习好,预报差"的原因,解决这一问题的关键是选择合适的网络结构参数、相应的学习算法和合适的预报因子,并总结了合理应用人工神经网络建立预测模型的经验.针对人工神经网络模型不具有自动选取因子的功能,给实际应用造成困难,提出了基于RBF的逐步选取因子的算法,并进行了对比试验,表明该方法具有较高的实用价值.     

四川旱涝震灾害的人工神经网络外推预测

选取旱，涝，震灾害之间的一步转移概率作为Ｂ－Ｐ人工神经网络训练样本的输入信息，建立了四川旱，涝，震的人工神经网络灾型预测模型。Ｂ－Ｐ网络模型应用于实侧预测结果与用主分量分析法的趋势预测结果精度接近。     

我国粮食产量综合预测系统

介绍了我国粮食产量综合预测方法及其预测系统的结构与特性。系统的模型体系包括气象预测模型、社会经济因素预测模型、社会经济和气象因子综合预测模型,通过实例分析了这３个不同预测模型的历史拟合情况和预报效果。结果表明,综合模型的预测效果比单一模型好,但其业务化程度较低,需要进一步改进。     

基于概念模型的麦田土壤水分动态模拟研究

农田土壤水分模拟是农业用水管理的重要依据。以根区土体水量平衡方程为依据,考虑根区下界面水分通量,构建了农田土壤水分变化模拟模型,该模型由作物蒸散量模型、根区下界面水分通量模型以及水量平衡方程等组成。采用山西水利职业技术学院试验基地2007年和2008年2个年度冬小麦试验资料,确定了模型参数。结果表明,土壤储水量模拟计算值与实测值有较好的一致性,其相关系数达到0.9555;F检验结果达到极显著水平,所建立的麦田土壤水分动态模型可用于作物蒸散量、根区下界面水分通量和田间土壤水分的模拟计算;计算精度平均达到3%～11%。表明该模型可较好地描述农田士壤水分转化过程。     

陆面生态过程的一维数值模拟

建立了一个研究大气、植被、土壤相互作用的传播模式。模式是由多层大气模式、多层土壤模式和植被模式通过界面上能量、水汽传输平衡方程耦合而成。对植被和土壤的不同性质,进行了一系列的数值试验。结果表明,不同的植被覆盖以及降水等因子会对大气、植被、地表界面上能量、水汽传输以及热状态产生显著的影响。此模式还可以耦合进中尺度模式用以研究非均匀区域陆面过程和大气的相互作用。     

从MODIS资料提取土壤湿度信息的主成分分析方法

沿袭了遥感地物分类中K-L变换思想, 以归一化处理后的遥感数据, 结合地面土壤湿度观测数据, 应用主成分分析方法, 采用MODIS不同红外波段数据, 通过相关关系计算, 在监测结果中融合MODIS具有250 m分辨率的第2波段数据, 建立了青海省多维特征空间土壤湿度监测模型。模型的建立克服了热惯量法监测干旱需多时相遥感数据的缺陷, 经初步检验, 此模型可以在一定精度范围之内监测表层土壤湿度, 具有业务应用潜力。     

Numerical experiments of the effects of initial desert moisture on the climate change

A numerical model with the p-sigma incorporated coordinate system and primitive equations is used to simulate the effect of initial soil moisture in desert areas on the climate change. The results show that the present deserts have a tendency to expand. When the initial soil moisture in the desert regions increases, the desert areas will shrink but can not disappear. The small deserts may not remain any longer when there are sources of water vapour around. Both the land-sea contrast and the topography are the background conditions of the present desert distribution through the mechanism of the downdrafts and the rare precipitation over the desert regions. The increase of the initial desert soil moisture will weaken the summer monsoon circulation and, consequently, the monsoonal precipitation.     

华北干旱综合评估和预警技术研究

论述了根据热惯量理论,利用气象卫星ＡＶＨＲＲ资料,对华北平原的土壤墒情进行动态监测的方法。并在分析土壤墒情、降水量、气温和未来降水趋势对干旱综合影响的基础上,提出了适用华北地区农作物生长季节干旱的综合评估和预警指标。根据这种指标研制的干旱综合评估和预警系统其灵敏性和稳定性均有显著的提高。     

Possible Impacts of Climate Change on Soil Moisture Availability in the Southeast Anatolia Development Project Region (GAP): An Analysis from an Agricultural Drought Perspective

This paper presents probable effects of climate change on soil moisture availability in the Southeast Anatolia Development Project (GAP) region of Turkey. A series of hypothetical climate change scenarios and GCM-generated IPCC Business-as-Usual scenario estimates of temperature and precipitation changes were used to examine implications of climate change for seasonal changes in actual evapotranspiration, soil moisture deficit, and soil moisture surplus in 13 subregions of the GAP. Of particular importance are predicted patterns of enhancement in summer soil moisture deficit that are consistent across the region in all scenarios. Least effect of the projected warming on the soil moisture deficit enhancement is observed with the IPCC estimates. The projected temperature changes would be responsible for a great portion of the enhancement in summer deficits in the GAP region. The increase in precipitation had less effect on depletion rate of soil moisture when the temperatures increase. Particularly southern and southeastern parts of the region will suffer severe moisture shortages during summer. Winter surplus decreased in scenarios with increased temperature and decreased precipitation in most cases. Even when precipitation was not changed, total annual surplus decreased by 4 percent to 43 percent for a 2°C warming and by 8 percent to 91 percent for a 4°C warming. These hydrologic results may have significant implications for water availability in the GAP as the present project evaluations lack climate change analysis. Adaptation strategies – such as changes in crop varieties, applying more advanced dry farming methods, improved water management, developing more efficient irrigation systems, and changes in planting – will be important in limiting adverse effects and taking advantage of beneficial changes in climate.     

江苏省主要作物农田水分盈亏量的研究

利用江苏省1980～1992年土壤湿度资料，根据土壤水分平衡原理，运用运筹学中的优化技术，结合本省的自然条件和作物生长实际情况，提出有效降水量、下层水分补给量等计算方法，建立了旱地和稻田农田水分盈亏量的计算模式，以便应用实时降水和土壤湿度等资料，计算全省农田水分盈亏量，及时提供农业气象情报服务。     

Estimating Climate-Induced Change in Soil Moisture at the LandscapeScale: An Application to Five Areas of Ecological Interest in the U.K.

This paper presents an indication of the possible effects of climate change on monthly mean soil moisture at a fine spatial resolution (50 m) over the scale of a landscape (100–250 km²). Soil moisture is modelledusing daily time series of rainfall and potential evapotranspiration to drive a simple hydrological model operating on individual hillslopes and explicitly including, on a conceptual level, the lateral movement of water. Climate change is represented by the UKTR scenario and model results are provided at two time slices (the years 2030–2040 and 2060–2070) for five areasof ecological interest, forming a north-south transect across the U.K. The results are given in terms of the distribution of the monthly mean soil moisture change by soil type. The spread of values reflects the effect of the topographic control on the lateral movement of water. The results show a small increase in wetness at the Cairngorm site, a very slight decrease in summer soil moisture at the Moor House site and a very marked fall in soil moisture for the three more southerly sites. The importance of soil type in determining the availability of water to plants, the changing areal extent above specified soil moisture thresholds, and the implications for ecological change and conservation are discussed.     

Soil Moisture Retrieval from Satellite Images and Its Application to Heavy Rainfall Simulation in Eastern China

The soil water index (SWI) from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient (CORR), root-mean-square-error (RMSE) and bias (BIAS) shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture (NCEP) in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13–14 June, 18–22 June, and 21–26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21–26 July shows that the update of soil moisture initial conditions can improve the model’s performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13–14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy rainfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.