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Relationships Between Supermicrometer Sea Salt Aerosol and Marine Boundary Layer Conditions: Insights From Repeated Identical Flight Patterns
Journal of Geophysical Research: Atmospheres ( IF 3.8 ) Pub Date : 2020-05-25 , DOI: 10.1029/2019jd032346
Joseph S Schlosser 1 , Hossein Dadashazar 1 , Eva-Lou Edwards 1 , Ali Hossein Mardi 1 , Gouri Prabhakar 2 , Connor Stahl 1 , Haflidi H Jonsson 3 , Armin Sorooshian 1, 4
Affiliation  

The MONterey Aerosol Research Campaign (MONARC) in May–June 2019 featured 14 repeated identical flights off the California coast over the open ocean at the same time each flight day. The objective of this study is to use MONARC data along with machine learning analysis to evaluate relationships between both supermicrometer sea salt aerosol number (N>1) and volume (V>1) concentrations and wind speed, wind direction, sea surface temperature (SST), ambient temperature (Tamb), turbulent kinetic energy (TKE), relative humidity (RH), marine boundary layer (MBL) depth, and drizzle rate. Selected findings from this study include the following: (i) Near surface (<60 m) N>1 and V>1 concentration ranges were 0.1–4.6 cm−3 and 0.3–28.2 μm3 cm−3, respectively; (ii) four meteorological regimes were identified during MONARC with each resulting in different N>1 and V>1 concentrations and also varying horizontal and vertical profiles; (iii) the relative predictive strength of the MBL properties varies depending on predicting N>1 or V>1, with MBL depth being more highly ranked for predicting N>1 and with TKE being higher for predicting V>1; (iv) MBL depths >400 m (<200 m) often correspond to lower (higher) N>1 and V>1 concentrations; (v) enhanced drizzle rates coincide with reduced N>1 and V>1 concentrations; (vi) N>1 and V>1 concentrations exhibit an overall negative relationship with SST and RH and an overall positive relationship with Tamb; and (vii) wind speed and direction were relatively weak predictors of N>1 and V>1.

中文翻译:


超微米海盐气溶胶与海洋边界层条件之间的关系:来自重复相同飞行模式的见解



2019 年 5 月至 6 月的 MONterey 气溶胶研究活动 (MONARC) 在每个飞行日的同一时间从加利福尼亚海岸上空进行 14 次重复的相同飞行。本研究的目的是使用 MONARC 数据和机器学习分析来评估超微米海盐气溶胶数量 (N >1 ) 和体积 (V >1 ) 浓度与风速、风向、海面温度 (SST) 之间的关系)、环境温度 (T amb )、湍流动能 (TKE)、相对湿度 (RH)、海洋边界层 (MBL) 深度和毛毛雨率。本研究的选定结果包括以下内容: (i) 近表面(<60 id=93>>1 和 V >1浓度范围为 0.1–4.6 cm -3和 0.3–28。分别为2μm 3 cm -3 ; (ii) MONARC 期间确定了四种气象状况,每种气象状况导致不同的 N >1和 V >1浓度以及不同的水平和垂直剖面; (iii) MBL 属性的相对预测强度根据预测 N >1或 V >1而变化,预测 N >1时 MBL 深度排名更高,预测 V >1时 TKE 排名更高; (iv) MBL 深度 >400 m(<200 id=104>>1 和 V >1浓度;(v) 毛毛雨率增加与 N >1和 V >1浓度降低一致;(vi) N >1和 V % 3E1浓度与 SST 和 RH 总体呈负相关,与 T amb呈总体正相关;(vii) 风速和风向是 N >1和 V >1的相对较弱的预测因子。
更新日期:2020-05-25
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