基于NLCCA的中国夏季降水与东亚夏季风关系的探讨

运用一种基于人工神经网络的非线性典型相关分析方法(NLCCA),对中国夏季降水与东亚夏季风之间的非线性关系进行了分析。结果表明,夏季降水对东亚夏季风的响应具有一定的非线性,当夏季风较强与较弱时,对应的中国夏季降水异常分布呈现明显的不对称性。夏季降水与夏季风之间的关系可分离为线性响应和非线性响应,其中非线性响应部分占总方差贡献的52.1%,说明我国夏季降水异常分布与东亚夏季风相互之间的关系既有线性特征也有非线性特征,非线性响应略显重要。     

沈阳市降水概率预报服务系统

沈阳市降水概率预报服务系统是在日本数值预报的基础上应用多种统计方法建立MOS预报方程,对其预报结果应用概率回归集成制作降水概率预报。TS评分结果表明:MOS预报的降水确率高于日本数值预报,MOS集成预报的结果在各种MOS预报结果平均偏上的水平。概率预报的Brier评分结果表明:在MOS综合基础上的概率回归(REEP)方法得出的概率预报结果较为理想。     

Global thermal and dynamical perturbations due to Cretaceous mantle avalanche

The numerical models of mantle convection agree to depict avalanches behaviour according to the level of endothermicity of the spinel → perovskite phase change. Their potential effects on the global thermal and dynamical states of the mantle have been computed thanks to a numerical code, which takes into account both the 400-km exothermic and the 660-km endothermic phase changes. The cycle followed by the avalanches is: local layering, destabilization of the 660-km thermal layer, travelling and spreading on the core, and reappearing of the local layering. Therefore, mantle convection is characterized by quiet periods of partial layering embedded in catastrophic events. During the avalanche, the amplitude of the surface velocity is multiplied by two, which would imply an enhanced plate tectonic and ridge activities. The global thermal effects of the avalanche are compatible with a high mantle temperature and an acceleration of Earth's rotation during the Cretaceous. They also offer a coherent explanation to locate the origin of mantle plumes both within the CMB and just below the transition zone.     

A cluster-optimizing regression-based approach for precipitation spatial downscaling in mountainous terrain

Precipitation temporal and spatial variability often controls terrestrial hydrological processes and states. Common remote-sensing and modeling precipitation products have a spatial resolution that is often too coarse to reveal hydrologically important spatial variability. A statistical algorithm was developed for downscaling low-resolution spatial precipitation fields. This algorithm auto-searches precipitation spatial structures (rain-pixel clusters), and orographic effects on precipitation distribution without prior knowledge of atmospheric setting. It is composed of three components: rain-pixel clustering, multivariate regression, and random cascade. The only required input data for the downscaling algorithm are coarse-pixel precipitation map and a topographic map. The algorithm was demonstrated with 4 km × 4 km Next Generation Radar (NEXRAD) precipitation fields, and tested by downscaling NEXRAD-aggregated 16 km × 16 km precipitation fields to 4 km × 4 km pixel precipitation, which was then compared to the original NEXRAD data. The demonstration and testing were performed at both daily and hourly temporal resolutions for the northern New Mexico mountainous terrain and the central Texas Hill Country. The algorithm downscaled daily precipitation fields are in good agreement with the original 4 km × 4 km NEXRAD precipitation, as measured by precipitation spatial structures and the statistics between the downscaling and the original NEXRAD precipitation maps. For three daily precipitation events, downscaled precipitation map reproduces precipitation variance of the disaggregation field, and with Pearson correlation coefficients between the downscaled map and the NEXRAD map of 0.65, 0.71, and 0.80. The algorithm does not perform as well on downscaling hourly precipitation fields at the examined scale range (from 16 km to 4 km), which underestimates precipitation variance of the disaggregation field. For a scale range from 4 km to 1 km, the algorithm has potential to perform well at both daily and hourly precipitation fields, indicated from good regression performance.     

小浪底水库蓄水前后雷暴气候变化特征分析

利用小浪底库区及周边地区具有代表性的12个气象站蓄水前后共20 a逐日雷暴资料,采用数理统计方法对各站雷暴日数、初日、终日及其空间分布特征等进行统计,结果表明:小浪底水库蓄水后,因水域面积增大,对小浪底库区及周边雷暴气候特征等有较大影响,库区和周边东部年雷暴日数和初终间日数呈增加趋势,周边南部呈减少趋势;雷暴日数秋季增加,夏季减少;库区和周边雷暴初日均呈明显的提前趋势,终日多呈推迟趋势。     

1981-2005年中国东北榆树物候变化特征及模拟研究

探讨了1980－2005年中国东北榆树物候的时空变化与气候因子的关系。结果表明：近26 a,东北地区13个站点榆树的展叶期和枯黄期变化趋势较大,13个物候时间系列,展叶初期显著提前趋势占54%,枯黄初期显著推后趋势占38%;榆树物候与气温呈显著相关关系：展叶期与3－4月平均气温呈显著的负相关关系,与平均展叶期的积温呈显著的负相关关系;各站点枯黄期与8－9月平均气温关系不显著,整个东北地区呈显著的正相关关系。研究表明,榆树物候与降水、日照关系不显著。以日平均气温最高日为界,枯黄期积温值可分为呈线性关系的两段,从日平均气温最高日开始,连续10 d积温值低于固定值时,植物开始枯黄。     

全球1.5℃和2.0℃升温对中国小麦产量的影响研究

采用部门间影响模式比较计划（ISI-MIP）的气候模式,确定全球升温1.5℃和2.0℃出现的时间,并结合农业技术转移决策支持系统（DSSAT）模型模拟小麦的产量,最终选取4套数据对比研究中国小麦区温度和降水变化特征以及各区域小麦产量变化趋势,综合评价了不同升温情景对中国小麦产量的影响。结果表明：(1)在全球升温1.5℃和2.0℃背景下,我国小麦生育期内温度相对于工业革命前分别升高1.17℃和1.81℃。两种升温情景下我国春麦区升温幅度大于冬麦区升温幅度。春麦区中新疆春麦区升温幅度最大,西北春麦区升温幅度最小;冬麦区中温度变化最大和最小的麦区分别为西南冬麦区和黄淮冬麦区。(2)在全球升温1.5℃和2.0℃情景下,我国小麦生育期内降水相对于历史时段(1986—2005年)分别增加9.1%和11.3%。从各麦区来看,两种升温情景下春麦区降水增加幅度略大于冬麦区的增加幅度。所有麦区中只有新疆春麦区降水低于历史时段降水。春麦区降水增加幅度最大的麦区为北部春麦区。冬麦区中降水增加较大的麦区为北部冬麦区和黄淮冬麦区,降水增加较小的麦区为华南冬麦区和西南冬麦区。(3)两种升温情景下,我国小麦单产相对于历史时段(1986—2005年)平均减产分别为5.2%和4.6%,两种升温情景对中国小麦产量并没有显著的差异。在全球升温大背景下我国春小麦主要呈现增产趋势,冬小麦主要呈现减产趋势。减产幅度较大的麦区为华南冬麦区和青藏春麦区,增产幅度最大的麦区为西北春麦区。从各麦区产量减产面积比例上看,我国各麦区减产面积所占比例趋势为从北向南由多变少再变多,其中华南冬麦区减产面积所占比例最大,北部冬麦区最小。     

基于EEMD的黄河中上游夏季降水预报方法的研究

传统的统计方法难以很好的对气候系统这一集非线性、非平稳性为一身的多层次系统进行处理。因此集层次化处理和平稳化处理的集合正交经验模态分解技术(EEMD)的提出,为解决上述问题提供了有效的途径。本文选取黄河中上游24个气象观测站的逐月降水资料,结合组合预报和集合预报思路,基于EEMD建立了统计预报模型。其中对降水序列中的高频部分进行了二次平稳化处理,实现对2008—2013年6—8月的降水预报,并用预报评分检测预报效果。结果表明:EEMD模型对黄河中上游夏季降水有着较强的预报能力,在该区域与气候模式和传统的统计方法相比具有更高的精度和更好的应用前景。     

Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.     

湖北省未来30年气温和降水量变化趋势预测

使用国家气候中心的区域气候模式对1961～1990、2001～2030年湖北省逐月气温、降水量的预估值(格点0.5°×0.5°,A2情景),以1961～1990年湖北省平均温度和平均降水量为基准,计算并分析未来30年(2001～2030年)及每10年年平均气温、降水量变化趋势。结果表明:(1)未来30年湖北省年平均气温普遍呈上升趋势,上升幅度在0.19～0.39℃之间,平均0.27℃,鄂南增温比鄂北快,其中2021～2030年增幅最大,2001～2010年增幅最小;(2)年平均降水量湖北省大部呈减少趋势,表现出南增北减、东增西减的特点,2001～2010年变化不大,2011～2020年绝大多数站点均有不同幅度增加,2021～2030年全省各地呈一致的下降趋势,湖北省南涝北旱趋势将有所加剧。