近54年渭干河流域径流变化特征及影响因素分析

基于1960-2013年渭干河流域逐月径流量观测资料及逐日气象数据,采用Kruskal-Wallis阶段转换检验、R/S分析、集合模态分解分析（EEMD）等方法研究了近54年渭干河流域径流量的年内、年际变化特征及其影响因素。结果表明：（1）近54年渭干河流域Cv、Cr较大,径流量年内分配不均衡,径流量夏季〉秋季〉春季〉冬季,未来这种趋势会更加明显。（2）径流年际变化特征可分为三个阶段,1960-1976年的枯水期、1976-1993年的平水期和1994-2013的丰水期。（3）径流量总体呈现增加趋势,其中夏季增长最为显著,其次是春秋季,冬季径流量有轻微减少。未来近期内,渭干河径流量还会继续保持增加。（4）流域气温和降水量亦呈增加趋势,突变点在1970s末和1990s初,与径流变化特征吻合,两者呈正相关关系。其中夏季径流量变化主要受降水影响,秋冬季径流量变化主要受气温影响。

1961—2017年成都市降水变化特征分析

本文选取1961—2017年成都市月降水量数据,利用线性回归分析、Mann-Kendall突变分析和EEMD周期分析等数理统计方法,研究了成都市近57年降水量的变化特征,为其水资源检测、评估和气象灾害防治提供一定的理论依据和基础。结果表明,成都市近57年平均年降水量为892.6mm,呈逐渐下降的趋势且无突变现象发生,以3年和5年的年际周期振荡变化为主。降水主要集中在夏、秋两季,累计降水量超过年降水量的80%,其中夏季降水量呈减少趋势,不存在突变,包含2年和7年的周期;秋季降水量存在2个突变点,变化周期以准3年和11年为主。春季降水量占全年降水量的16%,有多个突变点,存在2年和9年的周期。冬季降水量仅占3%,呈缓慢上升趋势,存在多个突变点,周期为2年和准6年。

西南地区夏季降水量的多尺度变化特征

为了更好地分析中国西南地区近60年来夏季降水的变化特征,利用1961~2017年西南地区76个气象站点的降水量资料和NCEP/NCAR再分析月平均资料,主要运用经验正交函数分解(EOF)、Morlet小波分析、集合经验模态分解(EEMD)等方法对该地区近60年夏季降水量的空间分布特征以及时间变化特征进行研究。结果表明:1) 西南地区近60年来夏季降水量空间分布不均匀,大体呈现东多西少,南多北少的变化趋势。2) EOF分析表明:第1模态显示西南地区夏季降水呈全区一致型;第2模态显示夏季降水在西北–东南有“正–负–正”的分布类型;第3模态显示夏季降水呈全区一致型。3) 小波分析表明:夏季降水主要有2年、3~7年、8年以及12~22年的变化周期。4) EEMD分解表明:夏季降水具有2.85年、6年、16.28年、28.5年的变化周期,且在整个时间尺度上呈下降趋势。5) 西南地区趋势系数正值区和负值区交错分布,年平均降水的相对变率不大,从西南到东北由正转负。

Combined filter method for weakening GNSS multipath error

A filter method that combines ensemble empirical modal decomposition(EEMD)and wavelet analysis methods was proposed to separate and correct the global navigation satellite system(GNSS)multipath error more effectively.In this method,the GNSS signal is first decomposed into several intrinsic mode functions(IMFs)and a residual through EEMD.Then,the IMFs and residual are classified into noise terms,mixed terms,and useful terms according to a combined classification criterion.Finally,the mixed term denoised by wavelet and the useful term are reconstructed to obtain the multipath error and thus enable an error correction model to be built.The measurement data provided by the Curtin GNSS Research Center were used for processing and analysis.Results show that the proposed method can separate multipath error from GNSS data to a great extent,thereby effectively addressing the defects of EEMD and wavelet methods on multipath error weakening.The error correction model established with the separated multipath error has a higher accuracy and provides a certain reference value for research on related signal processing.

西南雨季降水时空变化特征

为研究西南雨季降水的时空变化特征,利用1960~2022年西南地区81个气象站点的逐日气象降水量观测资料,通过EOF分解、Morlet小波分析和EEMD分析等方法,对西南地区雨季降水量的多尺度变化特征进行了详细研究。结果表明:1) 西南地区63年来雨季降水量空间分布不均匀,大体有由东向西逐渐递减,以及由南向北逐渐递减的变化趋势。川西高原为降水量低值区,雅安、峨眉以及云南南部为降水量高值区。西南地区趋势系数正值区和负值区交错分布,正值区主要在川西高原以及川东和贵州,负值区在云南地区。2) EOF分析表明:西南地区雨季降水量第1模态为全区一致型,大值中心位于云南地区以及四川中南部。西南地区雨季降水量第2模态显示为北负南正型,正值大值中心位于云南地区,负值大值区位于川西和川东。西南地区雨季降水量第3模态显示为东北到西南正负交错的分布类型。西南地区雨季降水量第4模态为西负东正的分布类型。西南地区雨季降水量第5模态显示为东北到西南呈正负交错的分布类型。3) 小波分析表明西南地区雨季降水量主要有3~4年、7~8年、10~14年、15~23年的变化周期;EEMD分解表明西南地区雨季降水量主要有2.66年、5.33年、10年、21.3年的变化周期。由此可知,西南地区主要存在4年、8年和20年左右的周期。In order to study the spatio-temporal variation of rainy season precipitation in Southwest China, the multi-scale variation of rainy season precipitation in Southwest China was studied in detail by means of EOF decomposition, Morlet wavelet analysis and EEMD analysis, based on the daily meteorological precipitation observation data of 81 meteorological stations in Southwest China during 1960~2022. The results show that: 1) The spatial distribution of rainy season precipitation in Southwest China in the past 63 years is uneven, with a gradual decline from east to west and from south to north. The West Sichuan Plateau has a low precipitation value, while Ya’an, E’mei and southern Yunnan have a high precipitation value. The positive and negative regions of the trend coefficient in Southwest China are interleaved, the positive regions are mainly in the west Sichuan Plateau, the east Sichuan and Guizhou, and the negative regions are in Yunnan. 2) The EOF analysis shows that the first mode of precipitation in the rainy season in southwest China is the uniform type in the whole region, and the large value center is located in Yunnan and central and southern Sichuan. The second mode of rainy season precipitation in Southwest China shows that the north is negative and the south is positive. The positive value center is located in Yunnan, and the negative value area is located in west and east Sichuan. The third mode of precipitation in the rainy season in Southwest China shows the distribution type of positive and negative interleaving from northeast to southwest. The fourth mode of precipitation in the rainy season in Southwest China is the distribution type of west negative and east positive. The fifth mode of precipitation of rainy season in Southwest China shows the distribution type of positive and negative from northeast to southwest. 3) Wavelet analysis shows that the rainy season precipitation in Southwest China mainly has a change cycle of 3~4 years, 7~8 years, 10-14 years and 15~23 years. The EEMD decomposition shows that the rainy season precipitation in Southwest China mainly has a change cycle of 2.66 years, 5.33 years, 10 years and 21.3 years. It can be seen that there are cycles of about 4 years, 8 years and 20 years in Southwest China.