安徽省地基GPS大气可降水量时空演化特征分析及应用研究 |
| |
引用本文: | 王根,邱康俊,刘惠兰,谢伟. 安徽省地基GPS大气可降水量时空演化特征分析及应用研究[J]. 中国农学通报, 2018, 34(33): 107-114 |
| |
作者姓名: | 王根 邱康俊 刘惠兰 谢伟 |
| |
作者单位: | 安徽省气象信息中心 安徽省大气科学与卫星遥感重点实验室,安徽省气象信息中心 安徽省大气科学与卫星遥感重点实验室,安徽省气象信息中心 安徽省大气科学与卫星遥感重点实验室,安徽省气象信息中心 安徽省大气科学与卫星遥感重点实验室 |
| |
基金项目: | 公益性行业(气象)科研专项“作物湿渍害星地一体化检测与预警技术研究及应用示范”(GYHY201406028);安徽省自然科学基金项目“广 义变分同化AIRS水汽通道亮温及在安徽强对流天气预报中的应用研究”(1708085QD89);中国气象局沈阳大气环境研究所开放基金课题“基于非高 斯模型的AIRS 水汽通道同化初步研究”(2016SYIAE14);淮河流域气象开放研究基金“基于地面和卫星观测反演的江淮流域降水资料融合算法研 究”(HRM201407)。 |
| |
摘 要: | 安徽地处梅雨区域,研究此区域的大气可降水量(PWV)时空分布和演化特征对理解水汽相关过程如降雨、蒸发和对流活动等起到重要的作用。笔者分析了安徽地区两个时间段(2012年6月—2012年9月和2014年6月—2014年9月)逐时GPS/PWV资料,揭示了GPS/PWV平均值和地形高度变化存在正相关。相应的GDAS资料积分得到的GDAS/PWV揭示了本区域上层大气中的PWV变化主要集中在地表到700 hPa区间。基于快速傅里叶变换(FFT)得到安徽地区6—9月份PWV具有季节性周期,13.0035天~准2周振荡等多尺度特征。进一步根据季节变化特征得出7月底是GPS/PWV值的关键转折点。最后给出了GPS/PWV和GDAS/PWV在天气预报分析中的应用研究,PWV资料对降水预报能力提高、人工影响天气、空中水资源等分析研究奠定了基础。
|
关 键 词: | GPS/PWV GDAS/PWV 快速傅里叶变换 多尺度特征 天气预报分析 |
收稿时间: | 2017-08-11 |
修稿时间: | 2017-09-05 |
Precipitable Water Vapor Derived from Ground-based GPS in Anhui Province: Temporal-Spatial Evolution Characteristics and Application Research |
| |
Abstract: | Anhui Province is one of the most typical Meiyu areas, the study of spatial distribution and temporal evolution characteristics of the atmospheric precipitable water vapor (PWV) in this area is important for our understanding of water vapor related processes, such as rainfall, evaporation and convective activity. With hourly GPS/PWV data in two periods (June to September 2012 and June to September 2014), it is revealed that a positive correlation exists between the averaged value of GPS/PWV and local terrain height. The variation of PWV in the upper atmosphere results from the water vapor variation from surface to 700 hPa, which is integrated on Global Data Assimilation System (GDAS). Based on fast Fourier transform (FFT), it is found that there is a seasonal feature with PWV in Anhui area from June to September, which includes 13.0035 days toquasi-two-week oscillation. According to the variation characteristics of seasonal change, we conclude that the end of July is a critical turning point of GPS/PWV value. Finally, the application of GPS/PWV and GDAS/PWV in weather forecast is also presented, which shows that PWV data lay a foundation for the improvement of rainfall forecast capability, weather artificial modification and water resource analysis. |
| |
Keywords: | GPS/PWV GDAS/PWV Fast Fourier transform Multi-scale features Weather forecast analysis |
本文献已被 CNKI 等数据库收录! |
| 点击此处可从《中国农学通报》浏览原始摘要信息 |
|
点击此处可从《中国农学通报》下载全文 |
|