近30a龙羊峡水库周边地区沙漠化遥感监测

在RS和GIS支持下,选取4期遥感数据,采用室内解译和野外检验修正的方法,获得龙羊峡水库周边地区不同时期土地沙漠化数据库.结果显示,在过去30 a中,龙羊峡水库周边地区土地的沙漠化在时间上经历了一般发展到正在逆转两个阶段;2000年以后,极重度沙漠化土地和重度沙漠化土地变化最为明显,均呈现逆转趋势,其中极重度沙漠化逆转为其他类型的总面积为145.90 km2,重度沙漠化土地逆转为中度沙漠化面积为146.44km2;在沙漠化土地的空间分布上,过去30 a里,沙漠化土地主要集中分布在龙羊峡两岸的塔拉滩和木格滩地区;研究区内沙漠化的逆转主要是由重度和极重度沙漠化土地转变为中度和轻度沙漠化土地.1975-1989年,研究区的降水呈增加趋势,但是由于这一时期人为因素的影响,沙漠化呈不断加剧的态势;1989-2000年,研究区的气候趋向于暖干化,加上过度放牧等人为因素,重度和极重度沙漠化土地持续发展;2000年以后,研究区的气候趋向于暖湿化,政府实施了一系列生态环境保护、恢复计划,沙化土地呈现逆转的态势.     

再分析资料和陆面数据同化资料土壤湿度产品在中国北方地区的适用性评估

土壤湿度是地球系统模拟的重要参数之一,准确获得其时空分布和变化特征是研究陆-气相互作用的基础。再分析资料和陆面数据同化资料均可提供全球或区域高分辨率土壤湿度产品,但在使用前需要对其进行评估分析。利用土壤湿度观测数据,计算ERA5、ERA5-Land、NCEP-DOE R2、CRA40再分析资料和GLDAS-Noah、GLDAS-CLSM、CLDAS陆面数据同化资料土壤湿度产品与观测数据的中位数、模拟偏差、相关系数等统计指标,并分季节和气候区讨论不同土壤湿度产品在中国北方地区的模拟效果。结果表明：整体来看,CRA40与观测值的相关性最好,ERA5和ERA5-Land分别对干中心、湿中心模拟效果更好,GLDAS-Noah对于较干土壤地区模拟略偏湿,CLDAS对较湿土壤地区模拟结果以系统性偏干为主,NCEP-DOE R2和GLDAS-CLSM模拟效果较差;ERA5、ERA5-Land、NCEP-DOE R2、GLDAS-Noah和CLDAS在所有季节均为模拟正偏差,春季模拟效果较好的是CRA40、ERA5-Land,夏季和秋季ERA5-Land、ERA5和CRA40与观测值相关性较好,不同产...     

新疆夜雨和昼雨的空间分布和长期变化

基于云南省1977—2017年124个测站逐小时降水资料,运用时空平均等统计方法,分析了云南地区夜雨率、夜雨频次和夜雨强度的基本气候特征。结果表明：（1）云南夜雨占日降水量的比例较大,各个季节大部分地区夜雨率均能超过50%,且具有显著的区域性差异。多年平均夜雨率逐候变化呈现复杂和特殊的三峰型变化。（2）云南夜雨年频次呈现东部和西部多,而中部少的特征。主要是因为春、冬季云南东部和西部受南支西风系统、昆明准静止锋及云南地形的共同影响,是典型夜雨高频区。（3）云南北部和南部边缘在全年多数时段为夜雨强度的大值区,而中部常年夜雨强度相对较弱。云南大部地区夏、秋季夜雨强度大于春、冬季,但云南西北部边缘夜雨强度春、冬季高于夏、秋季。

     

台风灿鸿造成浙江东北部大暴雨地形作用的数值模拟研究

利用中尺度非静力数值模式WRF V3.6.1对台风灿鸿(1509)进行了高分辨率数值模拟,模式较好地再现了台风灿鸿的发展演变过程和在浙江东北部产生的强降水。观测资料显示台风接近浙江期间,在东北气流下,浙东北地形的摩擦辐合及抬升作用使得大量的对流云团汇集在台风西北侧,对流系统活跃,是浙江东北部产生强降水的重要原因。控制试验也模拟出了在台风接近陆地时,内核区西北侧存在有组织的、切向分布的小尺度对流系统,由地形强迫产生的降雨量和地形走向一致,迎风坡降雨量增加。通过升降地形,改变土地类型和将杭州湾水体用陆地替换等敏感性试验发现:(1)地形的影响对台风降雨量的增幅最为明显。通过降低地形,台风西北侧小尺度雨带明显减弱,浙江东北地区降水也明显减少。可见地形会影响这些中小尺度系统的结构和演变,引起降水异常变化。(2)大暴雨期间,台风一直维持较强的对称性,具有典型的眼墙和暖心结构。     

河北大茂山碘化银地面发生器增雪作业影响分析

利用常规气象资料、MICAPS资料和NECP/NCAR再分析资料,结合高斯模拟,分析了2012年11月10日唐县大茂山地基碘化银发生器增雪作业的作业条件。结果发现,此次天气背景为自西南向东北移动的冷涡云系,根据帕斯奎尔(Pasquill)稳定度分类法得出作业时间段大气处于中性层结状态;高斯模式模拟得出,有效的AgI浓度向上扩散范围高达3.0 km;作业点作业时段上空至3.2 km均处于上升气流区,计算出作业点发生器出口温度1.0℃。因冬季人工观测云底高度多为2.5~3.0 km,综合分析认为,该作业点的选址是合适的,此次作业条件较好,可以将催化剂输送到云中,起到催化作用。     

Recent Advances in Predictability Studies in China （1999-2002）

Since the last International Union of Geodesy and Geophysics (IUGG) General Assembly (1999), the predictability studies in China have made further progress during the period of 1999-2002. Firstly, three predictability sub-problems in numerical weather and climate prediction are classified, which are concerned with the maximum predictability time, the maximum prediction error, and the maximum allowable initial error, and then they are reduced into three nonlinear optimization problems. Secondly, the concepts of the nonlinear singular vector (NSV) and conditional nonlinear optimal perturbation (CNOP) are proposed,which have been utilized to study the predictability of numerical weather and climate prediction. The results suggest that the nonlinear characteristics of the motions of atmosphere and oceans can be revealedby NSV and CNOP. Thirdly, attention has also been paid to the relations between the predictability and spatial-temporal scale, and between the model predictability and the machine precision, of which the investigations disclose the importance of the spatial-temporal scale and machine precision in the study of predictability. Also the cell-to-cell mapping is adopted to analyze globally the predictability of climate,which could provide a new subject to the research workers. Furthermore, the predictability of the summer rainfall in China is investigated by using the method of correlation coefficients. The results demonstrate that the predictability of summer rainfall is different in different areas of China. Analysis of variance, which is one of the statistical methods applicable to the study of predictability, is also used to study the potential predictability of monthly mean temperature in China, of which the conclusion is that the monthly mean temperature over China is potentially predictable at a statistical significance level of 0.10. In addition,in the analysis of the predictability of the T106 objective analysis/forecasting field, the variance and the correlation coefficient are calculated to explore the distribution characteristics of the mean-square errors.Finally, the predictability of short-term climate prediction is investigated by using statistical methods or numerical simulation methods. It is demonstrated that the predictability of short-term climate in China depends not only on the region of China being investigated, but also on the time scale and the atmospheric internal dynamical process.     

Effect of Stochastic MJO Forcing on ENSO Predictability

Within the frame of the Zebiak-Cane model,the impact of the uncertainties of the Madden-Julian Oscillation(MJO) on ENSO predictability was studied using a parameterized stochastic representation of intraseasonal forcing.The results show that the uncertainties of MJO have little effect on the maximum prediction error for ENSO events caused by conditional nonlinear optimal perturbation(CNOP);compared to CNOP-type initial error,the model error caused by the uncertainties of MJO led to a smaller prediction uncertainty of ENSO,and its influence over the ENSO predictability was not significant.This result suggests that the initial error might be the main error source that produces uncertainty in ENSO prediction,which could provide a theoretical foundation for the data assimilation of the ENSO forecast.     

北京地区公众气象服务需求分析

2006年7、8月份在北京地区开展了一次大范围的公众气象服务需求调查,本文在对回收的有效问卷进行统计分析的基础上,从公众对气象信息的关注程度、公众对气象服务的意愿付费情况及对气象服务改进的需求3个方面进行了研究,并运用行为经济学的理论对公众的气象信息需求进行分析阐述,揭示出其规律性.结果反映出公众对气象信息及其价值的认识还比较有限,气象部门有必要加强宣传和引导.最后从用户需求的角度,对如何有效提高公众气象服务质量提出了建议.     

The Combined Effect of Initial Error and Model Error on ENSO Prediction Uncertainty Generated by the Zebiak-Cane Model

Initial errors and model errors are the source of prediction errors. In this study, the authors compute the conditional nonlinear optimal perturbation （CNOP）-type initial errors and nonlinear forcing singular vector （NFSV）- type tendency errors of the Zebiak-Cane model with respect to El Nifio events and analyze their combined effect on the prediction errors for E1 Nino events. The CNOP- type initial error （NFSV-type tendency error） represents the initial errors （model errors） that have the largest effect on prediction uncertainties for E1 Nifio events under the perfect model （perfect initial conditions） scenario. How- ever, when the CNOP-type initial errors and the NFSV- type tendency errors are simultaneously considered in the model, the prediction errors caused by them are not am- plified as the authors expected. Specifically, the predic- tion errors caused by the combined mode of CNOP-type initial errors and NFSV-type tendency errors are a little larger than those caused by the NFSV-type tendency er- rors. This fact emphasizes a need to investigate the opti- mal combined mode of initial errors and tendency errors that cause the largest prediction error for E1 Nifio events.