Spatio-temporal Rainfall Distribution and Markov Chain Analogue Year Stochastic Daily Rainfall Model in Ethiopia

This paper aims at the spatiotemporal distribution of rainfall in Ethiopia and developing stochastic daily rainfall model. Particularly, in this study, we used a Markov Chain Analogue Year (MCAY) model that is, Markov Chain with Analogue year (AY) component is used to model the occurrence process of daily rainfall and the intensity or amount of rainfall on wet days is described using Weibull, Log normal, mixed exponential and Gamma distributions. The MCAY model best describes the occurrence process of daily rainfall, this is due to the AY component included in the MC to model the frequency of daily rainfall. Then, by combining the occurrence process model and amount process model, we developed Markov Chain Analogue Year Weibull model (MCAYWBM), Markov Chain Analogue Year Log normal model (MCAYLNM), Markov Chain Analogue Year mixed exponential model (MCAYMEM) and Markov Chain Analogue Year gamma model (MCAYGM). The performance of the models is assessed by taking daily rainfall data from 21 weather stations (ranging from 1 January 1984-31 December 2018). The data is obtained from Ethiopia National Meteorology Agency (ENMA). The result shows that MCAYWBM, MCAYMEM and MCAYGM performs very well in the simulation of daily rainfall process in Ethiopia and their performances are nearly the same with a slight difference between them compared to MCAYLNM. The mean absolute percentage error (MAPE) in the four models: MCAYGM, MCAYWBM, MAYMEM and MCAYLNM are 2.16%, 2.27%, 2.25% and 11.41% respectively. Hence, MCAYGM, MCAYWBM, MAYMEM models have shown an excellent performance compared to MCAYLNM. In general, the light tailed distributions: Weibull, gamma and mixed exponential distributions are appropriate probability distributions to model the intensity of daily rainfall in Ethiopia especially, when these distributions are combined with MCAYM.     

On the Sun’s distance from the center and the shape of the inner halo in the Galaxy: Gaia EDR3, HST and literature globular clusters

A statistical method is used to derive both the Sun’s distance $r_0$ from the Galactic Center (GC) and the 3D geometry of the inner ($<$ 25 kpc) halo. The spatial distribution of the 138 Gaia EDR3 globular clusters (GCs) with distances established on a combination of HST and literature data of Baumgardt and Vasiliev (2021) is explored. An estimate by using these ancient objects of the pressure-supported subsystem of the Galaxy with newly derived distances leads to the mean $r_0=7.81\pm 0.14$ kpc. The distribution of GCs within 25 kpc is almost spherically symmetric, and has the shape of an ellipsoid with a major axis of its symmetry slightly elongated toward the Sun and two minor axes of almost the same length. The obtained scale-length ratio of the major axis to the minor axis in the plane and to the vertical axis of the ellipsoid is $\approx$ 1:0.8:0.7. Based on the papers of a series, for practical use we argue to employ the following Sun’s distances from the GC and the plane: $r_0=8.15\pm 0.15$ kpc and $z_0=15\pm 5$ pc.     

El Nino衰减年西北太平洋热带气旋活动特征的差异性北大核心

El Nino衰减年西北太平洋热带气旋(Tropical cyclone,TC)活动表现出多样性,给TC活动的气候预测带来挑战。采用美国联合台风预警中心的热带气旋最佳路径数据和欧洲中期预报中心提供的ERA-5再分析资料,对1970—2018年的El Nino衰减年7—10月的西北太平洋TC生成频数进行合成分析,发现其与气候态没有显著的差异,但在单个年份,存在着较大的正、负异常。为此,将El Nino衰减年分为TC生成频数偏少(负异常)和偏多(正异常)两种情形,对比两种情形的TC活动和大尺度环境要素特征。结果表明,TC生成频数偏少的情形,TC生成频数的异常减少主要发生在西北太平洋东部海域,即(15°~25°N,140°~150°E)和(5°~25°N,150°~170°E),与垂直风切变增大、对流层中层相对湿度和低层绝对涡度减少有关;TC生成频数偏多的情形,TC生成频数的异常增加主要发生在南海和菲律宾群岛附近,即(15°~25°N,110°~120°E)和(5°~25°N,120°~130°E),对流层中层相对湿度增加的贡献最大,其次是上升运动增强和绝对涡度增大;对比两种情形发现,TC生成频数偏多的情形,广东和福建沿岸的东南风异常引导气流有利于菲律宾群岛附近生成的TC登陆中国大陆。     

江淮流域夏半年日照时数气候特征及趋势分析

基于江淮流域逐月日照时数观测资料,利用旋转正交函数(REOF)、线性趋势分析、Mann-Kendall突变检验以及Morlet小波分析等方法,对江淮流域夏半年(5—10月)日照时数进行了统计分析,结果表明:江淮流域夏半年日照时数普遍在1000～1200 h之间,呈现由南向北递增的空间分布特点,但受地形等因素影响又存在区域性差异。同时发现其标准差与平均日照时数呈现并不一致的分布规律。进一步将江淮流域日照时数分为4个区,分别为北部区Ⅰ、东北区Ⅱ、西南区Ⅲ和东南区Ⅳ,每个区都表现出显著的下降趋势,但在线性趋势、突变时段以及周期特征上,各个区域又存在显著的差异。