Temporal and spatial variations of global solar radiation over the Qinghai–Tibetan Plateau during the past 40 years

Global solar radiation is of great significance to the balance of ground surface radiation, the energy exchange between the Earth’s surface and atmosphere, and the development of weather and climate systems in various regions. In this study, the monthly global radiation recorded at 23 stations over the Qinghai–Tibetan Plateau (QTP) was utilized to estimate global solar radiation (Q) from sunshine duration and to obtain improved fits to the variation coefficients of the monthly Angström–Prescott model (APM). The modeling results were evaluated by calculating the statistical errors, including mean bias error, mean absolute error, root mean square error, and mean relative error. We demonstrate that the monthly Q values can be predicted accurately by APM over the QTP. We also assess the variations of Q values at 116 meteorological stations by APM over the QTP during 1961–2000. The analysis shows that the annual mean sunshine duration amounted to more than 3,000 h over the whole plateau, implying promising prospects for economic applications of solar energy. During the past 40 years, the mean global solar radiation has been relatively high in the western QTP, extending northward to the Inner Mongolian Plateau. Although its decadal variations in the QTP and surrounding regions were inconsistent, the anomaly values of global solar radiation were generally positive during the 1960s and 1970s, indicating that the QTP’s global solar radiation has increased during those periods. The anomaly values were negative during the 1980s and 1990s, showing that the plateau’s global solar radiation has decreased during those periods. Global solar radiation over the QTP is negatively proportional to latitude but positively proportional to altitude and relative sunshine duration. Three factors, the sunshine duration, latitude, and altitude, exert great influence on global surface radiation, of which sunshine duration is most significant. A high-variation-coefficient zone of global solar radiation occurred in the western part of the QTP but, on average, the variation coefficient of the plateau’s global solar radiation was only 0.031, suggesting that the variation in global radiation was relatively stable over the whole QTP.     

国家级极端高温短期气候预测系统的研制及应用

目前,国家级旬、月极端高温预测的业务工作尚未展开,国家级极端高温短期气候预测系统的研制为中国高温预测业务提供了一个有效平台.该系统以百分位相对阈值和35°C、38°C绝对阈值作为高温阈值指标,应用月动力预测模式、动力预测与统计降尺度相结合、物理统计相似三种不同的方法,预测未来1～40天的旬、月极端高温发生概率及高温日数,定期滚动发布预测产品.并以相关系数为衡量指标,应用交叉检验方法对三种方法的预测效果进行分析,结果表明不同方法高相关区的空间分布存在差异,在进行高温预测时,应综合各方法高相关区的预测结果给出综合预测意见.对2007年7月极端高温预测个例分析表明三种方法均有一定的预测技巧.     

60～70oS臭氧总量的QBO和ENSO信号

本文利用Ｎｉｍｂｕｓ－７上搭载的臭氧总量观测光谱仪（ＴＯＭＳ）得到的６０～７０ｏＳ纬圈中臭氧总量资料,分析研究了该地区臭氧总量准两年振荡（ＱＢＯ）和ＥＮＳＯ信号的纬向分布,指出在该纬圈臭氧总量的长期变化中包含着的ＱＢＯ和ＥＮＳＯ信号。同时,本文还分析研究了沿纬圈分布的大气臭氧总量季节变化和长期变化趋势,指出在该纬圈各个季节中臭氧总量呈下降趋势,以６０～１００ｏＷ十月份的下降最大,达到－９．３ＤＵ／ａ。研究同时表明：臭氧总量季节变化、长期变化趋势、以及ＱＢＯ信号的纬向分布都在西南极上空出现异常。本文对此进行了讨论,认为这是西南极海陆分布调整大气环流及大气波动造成对臭氧总量分布和变化的影响     

对大连历年汛期起止日期的客观判定

根据大连市 195 1～ 1998年的逐日降水量资料 ,应用扫描 t检验方法对每年入汛期和出汛期进行了判定和分析 ,并与目前使用的经验方法划定的日期作了比较。结果表明 ,t检验方法能更客观、准确地判定汛期的开始日期和结束日期。     

黄淮平原农业干旱预警系统研究

采用区域气候模式与土壤水分模型相结合的技术,建立黄淮平原农业干旱预警系统。系统的气候模式采用NCAR的区域气候模式(RegCM2),为土壤水分模型提供所需的气象要素场数值预报。土壤水分模型采用适合于黄淮平原冬小麦、夏玉米等作物的土壤水分平衡方程。试运行结果表明,利用区域气候模式和土壤水分模型构建的区域性土壤水分模型,土壤水分预报的平均相对误差在15%以下,可以较好地模拟出土壤水分变化和干旱分布状况,可用于土壤水分预报和干旱监测。     

1951-2003年中国气温和降水变化及其对干旱的影响

利用1951-2003年606个台站的气象观测资料,对中国53 a来的气候变化和干旱特征进行了分析。结果表明：我国的干旱面积在气候变暖背景下总体上趋于增加,但变化趋势不显著。干旱变化的区域差异较大,东北、华北和西北东部干旱呈显著增加的趋势。降水量是我国干旱变化的最主要的因素。     

高空资料质量问题的原因分析

分析了山东省高空资料审核中出现的问题及原因,并对特殊情况和异常数据提出了处理办法.     

江西大岗山负离子浓度与气象因子之间的响应关系

利用江西大岗山森林生态地面标准气象观测场内2019年度空气负离子和气象监测数据,分析了负离子浓度与气象因子之间的响应关系.结果表明:1)该地区年均负离子浓度1411.5个/cm3.夏季负离子浓度和温度呈负相关、和湿度呈正相关,在其余季节负离子浓度和温度呈正相关、与湿度呈负相关.2)无雨天与日降雨量少于50 mm的雨天,负离子浓度与温度呈负相关,与湿度呈正相关;暴雨天负离子浓度与温度呈正相关,与湿度呈较弱的负相关.3)不同季节,温度、湿度的大幅变化常伴随着负离子浓度的大幅变化,而温度、湿度变化较小时,负离子浓度的变化幅度也较小,说明温度、湿度的变化对负离子浓度的影响很大.4)暴雨过程中,负离子浓度随降水量的增加(减少)而增大(减小);暴雨发生时,负离子浓度急剧增大.     

海南岛西部山区人工催化暖底积云随机化效果检验

2015—2016年在海南省昌江县霸王岭开展地面暖云烟炉随机化人工催化效果检验,共取得催化和未催化试验样本34个。利用TITAN风暴追踪系统结合自动雨量资料进行统计和物理效果分析。结果表明:催化样本影响区平均增雨量为3.36mm/2h,未催化样本平均增雨量为2.97mm/2h,催化比未催化样本平均增加雨量0.39mm,相对增加11.4%,显著性分析差异显著;对于增长阶段的积雨云,催化样本反射率增强、含水量增大、回波顶高升高;处于减弱阶段的积云,多数催化样本回波减弱趋势趋缓。     

The second order adjoint analysis: Theory and applications

Summary The adjoint method application in variational data assimilation provides a way of obtaining the exact gradient of the cost functionj with respect to the control variables. Additional information may be obtained by using second order information. This paper presents a second order adjoint model (SOA) for a shallow-water equation model on a limited-area domain. One integration of such a model yields a value of the Hessian (the matrix of second partial derivatives, ² J) multiplied by a vector or a column of the Hessian of the cost function with respect to the initial conditions. The SOA model was then used to conduct a sensitivity analysis of the cost function with respect to distributed observations and to study the evolution of the condition number (the ratio of the largest to smallest eigenvalues) of the Hessian during the course of the minimization. The condition number is strongly related to the convergence rate of the minimization. It is proved that the Hessian is positive definite during the process of the minimization, which in turn proves the uniqueness of the optimal solution for the test problem. Numerical results show that the sensitivity of the response increases with time and that the sensitivity to the geopotential field is larger by an order of magnitude than that to theu andv components of the velocity field. Experiments using data from an ECMWF analysis of the First Global Geophysical Experiment (FGGE) show that the cost functionJ is more sensitive to observations at points where meteorologically intensive events occur. Using the second order adjoint shows that most changes in the value of the condition number of the Hessian occur during the first few iterations of the minimization and are strongly correlated to major large-scale changes in the reconstructed initial conditions fields.With 17 Figures