2011~2013年中国冻雨、冻毛毛雨和冻雾的特征分析

研究冰冻天气的特征对于更好的认识冰冻天气,提高此类天气的预警预报能力,从而达到防灾减灾有重要意义。利用2011~2013年间中国民航机场的一小时或半小时一次的例行观测和特殊观测资料,分析了冻雨、冻毛毛雨和冻雾天气的时空分布、持续时间和气象条件等特征。研究结果表明:我国大部分地区均会发生冰冻天气。冻雨和冻毛毛雨的频发区与其持续时间较长区比较一致,而冻雾的少发区,其持续时间也可能较长。我国冰冻天气最容易在冬季(12~2月)发生,在1月出现的比例最高;在凌晨[00~07时(当地时间,下同)]出现频率相对较高,午后(13~14时)出现频率最低。一次冰冻天气的持续时间一般不超过2个小时。温度在-3~-1℃,露点温度在-4~-1℃,温度露点差在0~1℃时冰冻天气发生的频率最大。出现冰冻天气时的风向以东北风和北风为主,而平均风速在2~3.9 m s-1时冻雨和冻毛毛雨发生的频率最大。我国冻雨和冻毛毛雨发生时,同时常会有雾或轻雾;冻雾出现时,一般不会伴随其他天气。     

邛崃山生态环境及生物多样性遥感监测评价

为了解邛崃山生态保护红线区生态环境及生物多样性维护状况,利用卫星遥感和地形数据,运用主成分分析法,建立遥感生态指数和生物多样性维护功能指数模型,对邛崃山生态保护红线区2000~2019年生态环境状况和生物多样性状况开展监测评估。结果表明：就遥感生态指数而言,近20a区域平均值为0.642~0.680,红线区南部多为高值区,北部多为低值区,评价等级为优的区域面积呈明显上升趋势,东北部及西南部的低值区略有扩大,呈弱恶化趋势;就生物多样性维护功能指数而言,近20a区域平均值为0.482~0.522,红线区南部多为高值区,北部多为低值区,多样性功能整体表现为缓慢增强,其中功能评价等级为强的区域面积呈显著增长趋势,而东北部功能等级改善效果不明显;邛崃山生态保护红线区生态环境状况整体较好,南部优于北部,生态环境状况和生物多样性大部分区域有所提升,小部分区域有所下降。     

A Positivity-preserving Conservative Semi-Lagrangian Multi-moment Global Transport Model on the Cubed Sphere

A positivity-preserving conservative semi-Lagrangian transport model by multi-moment finite volume method has been developed on the cubed-sphere grid. Two kinds of moments(i.e., point values(PV moment) at cell interfaces and volume integrated average(VIA moment) value) are defined within a single cell. The PV moment is updated by a conventional semi-Lagrangian method, while the VIA moment is cast by the flux form formulation to assure the exact numerical conservation. Different from the spatial approximation used in the CSL2(conservative semi-Lagrangian scheme with second order polynomial function) scheme, a monotonic rational function which can effectively remove non-physical oscillations is reconstructed within a single cell by the PV moments and VIA moment. To achieve exactly positive-definite preserving, two kinds of corrections are made on the original conservative semi-Lagrangian with rational function(CSLR)scheme. The resulting scheme is inherently conservative, non-negative, and allows a Courant number larger than one.Moreover, the spatial reconstruction can be performed within a single cell, which is very efficient and economical for practical implementation. In addition, a dimension-splitting approach coupled with multi-moment finite volume scheme is adopted on cubed-sphere geometry, which benefitsthe implementation of the 1 D CSLR solver with large Courant number.The proposed model is evaluated by several widely used benchmark tests on cubed-sphere geometry. Numerical results show that the proposed transport model can effectively remove nonphysical oscillations and preserve the numerical nonnegativity, and it has the potential to transport the tracers accurately in a real atmospheric model.     

Application of Backward Nonlinear Local Lyapunov Exponent Method to Assessing the Relative Impacts of Initial Condition and Model Errors on Local Backward Predictability

Initial condition and model errors both contribute to the loss of atmospheric predictability. However, it remains debatable which type of error has the larger impact on the prediction lead time of specific states. In this study, we perform a theoretical study to investigate the relative effects of initial condition and model errors on local prediction lead time of given states in the Lorenz model. Using the backward nonlinear local Lyapunov exponent method, the prediction lead time,also called local backward predictability limit(LBPL), of given states induced by the two types of errors can be quantitatively estimated. Results show that the structure of the Lorenz attractor leads to a layered distribution of LBPLs of states. On an individual circular orbit, the LBPLs are roughly the same, whereas they are different on different orbits. The spatial distributions of LBPLs show that the relative effects of initial condition and model errors on local backward predictability depend on the locations of given states on the dynamical trajectory and the error magnitudes. When the error magnitude is fixed, the differences between the LBPLs vary with the locations of given states. The larger differences are mainly located on the inner trajectories of regimes. When the error magnitudes are different, the dissimilarities in LBPLs are diverse for the same given state.     

三种非线性回归逐时气温预报比较订正

选取ECMWF和T639的2013年1月至2014年12月的数值预报场构造预报因子,基于神经网络、支持向量机和构造函数的非线性方法,预报地面逐时气温。试验结果显示,在单个方法预报误差较大时,3种方法的偏差订正集成方法更利于减小误差,通过偏差订正,3种非线性方法预报效果良好,平均绝对误差减小了0.5 ℃。在近1年独立样本的预报检验中,集成方法、神经网络、支持向量机和构造函数预报的平均绝对误差分别为1.5 ℃、1.7 ℃、1．8 ℃和1．4 ℃,总体上构造函数预报更为准确。     

GM(1, 1)模型的建模条件

GM(1,1)模型是灰色系统理论的核心预测模型,对GM(1,1)模型的建模条件进行研究是提高模拟精度的基础.采用理论证明和数值算例相结合的方法对GM(1,1)模型的建模条件进行研究,拓展了经典灰色预测模型的级比判定条件.结果表明:当原始序列的累加序列值都相等时,发展系数不存在;提高原始序列光滑度不是提高模拟精度的充分条件.     

测站降雹和区域降雹气候特征对比分析

应用1960～2001年测站降雹和区域降雹(包括非测站资料)两种资料,对山东省降雹气候特征进行了对比分析,计算分析了山东省两种降雹资料气候图的相似离度。分析结果表明,区域降雹比测站降雹明显偏多,但时间和空间分布趋势基本一致,相似度在86％%以上,应用测站降雹资料制作的气候图具有86％的代表性。     

雷达资料在云南一次强降水过程中的三维变分同化试验

鉴于云南观测信息相对不足、局地强降水突出的现状,利用WRF(Weather Research and Forecasting)模式及其变分同化系统进行雷达反射率因子和反演风场的三维变分同化试验。通过对2012年9月12日00:00—13日00:00发生在云南的一次强降水过程进行数值模拟和对比分析,结果表明,同时同化雷达反演风场和基本反射率因子,对区域模式同化系统中风矢量、相对湿度、位势高度几个基本分析量都有明显影响。雷达资料的同化,有利于区域模式初始场中强降水区域的上游中低层空气湿度增加、水汽输送增强和强降水发生区域的风场辐合加强,从而改善区域模式对强降水落区、强度的预报质量。对于切变线等天气尺度系统影响下的强降水过程,雷达资料的同化持续时间选取3 h、同化间隔为1 h较适宜。另外,雷达反演风场和基本反射率因子的同化均对降水预报改善有明显贡献,且多种资料的同化效果好于单一资料同化。     

气象要素对太阳能电池板温度的影响

温度升高会引起光伏电池发电效率下降,电池板温度是确定温度折减系数的必要条件,目前我国尚没有充足的外场实测电池板温度数据。该文基于北京南郊太阳能试验站2010年全年逐时电池板温度、气温、地表温度、斜面和水平辐照度实测数据,分析了电池板温度随时间的变化及其与各气象要素的关系。结果表明:电池板温度与气温和斜面辐照度的综合相关或与地表温度的线性相关最好,但实测数据不易获得;电池板温度与气温的线性相关较好,数据较易获得且质量有保证,从现实可行性考虑,是推算电池板温度最实用的相关方程;电池板温度与气温和水平辐照度的综合相关可以作为辅助方程,用于推算气温较高情况下的电池板温度。基于2010年电池板温度实测数据和加权计算的方法,得到北京地区年平均光伏发电温度折减系数约为2%,最高可达到13.3%。