five

ASCOS-OOTI-ozone

收藏
Global Change Master Directory (GCMD)2026-04-25 收录
下载链接:
https://cmr.earthdata.nasa.gov/search/concepts/C1214595433-SCIOPS.html
下载链接
链接失效反馈
官方服务:
资源简介:
ASCOS was an interdisciplinary expedition to the central Arctic on the icebreaker Oden from 1 August to 9 September 2008. The expedition focused on processes relating to cloud formation in the summer Arctic and included observations of marine biology and chemistry, atmospheric chemistry, physical oceanography, aerosol chemistry and physics, and meteorology. OOTI (Out On The Ice) air analyzing platform was developed by Environment Canada scientists: Dr. Jan Bottenheim (Jan.Bottenheim@ec.gc.ca) and Dr. Stoyka Netcheva (Stoyka.Netcheva@ec.gc.ca). University of Toronto student Rachel Chang (rchang@chem.utoronto.ca) was in charge of the equipment set up in the field and its operation. OOTI instrument package is designed for in-situ measurement of ground level ozone and Gaseous elemental mercury, Bromine monoxide, ambient temperature and few quality control parameters over the ice by the ice breaker Oden on its ASCOS expedition. The package is battery powered and its operation was fully automated. OOTI was taken out on the ice for sampling different environmental conditions described into the ASCOS - OOTI -log file. The in-situ ozone data were collected at 40cm height. Raw ozone mixing ratio was recorded every 2 seconds and the data were averaged for 5 minutes sampling interval (running average). Ozone mixing ratio was measured by 2B Technologies dual beam ozone monitor Model 205. Ozone data (ASCOS-OOTI-ozone.csv) file contains ozone mixing ratio averaged over 5 minutes sampling interval. Data file format consists of 2 columns. The first one is Date and Time stamp: DD/MM/YYYY HH:MM ? it gives the beginning of averaged sampling interval in UTC. The second column contains ozone measured mixing ratio averaged over 5 minutes sampling each of them starting at the time indicated on the corresponding Date and Time column.
提供机构:
SCIOPS
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作