来自远程传感观测在南大平原上的对流参数
1Department of Physics, University of Maryland, Baltimore County (UMBC), Baltimore, MD 21250, USA.
这项研究表明,遥感可以使用连续数据准确测量大气不稳定性 (CAPE) 和抑制 (CIN). 像AERI这样的主动和被动传感器,在天气预报方面,比传统的每天两次的无线电探测器提供了更高的准确性.
科学领域:
- 大气科学 大气科学
- 遥感 遥感 遥感 遥感
- 气象学 天气学
背景情况:
- 流动可用潜在能量 (CAPE) 和流动抑制 (CIN) 对于估计大气不稳定性和流动潜力至关重要.
- 传统方法依赖于不经常的射电探测器发射和模型数据,限制时间分辨率.
- 持续的大气概况分析为操作预测提供了潜在的改进.
研究的目的:
- 评估被动和主动遥感系统在CAPE和CIN.推导中的性能.
- 为了比较远程传感衍生的CAPE/CIN值与现场射电探测测量.
- 评估不同类型传感器对CAPE和CIN计算准确性的影响.
主要方法:
- 使用大气发射辐射干扰仪 (AERI),微波辐射仪 (MWR),拉曼LiDAR和差分吸收LiDAR (DIAL) 的数据计算了CAPE和CIN.
- 通过将遥感衍生的值与射电探测器数据进行比较来评估性能.
- 来自活跃LiDAR系统的水蒸气概况被纳入评估其影响.
主要成果:
- 与无线电探测器相比,被动传感器显示AERI提供了比MWR更准确的CAPE和CIN.
- 积极的LiDAR系统与被动传感器相结合,提高了CAPE的准确性.
- 活跃LiDAR对CIN准确性的影响不如CAPE的影响.
结论:
- 遥感为不断推导大气不稳定性和抑制指标提供了一种可行的方法.
- 在CAPE/CIN估计中,AERI在被动传感器中表现出卓越的性能.
- 集成活跃的LiDAR数据增强了CAPE计算,为更好地了解水分传输和云发展铺平了道路.
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