ACT-America: L3 Merged In Situ Atmospheric Trace Gases and Flask Data, Eastern USA
简介
该数据集提供了作为“大气碳和输送 - 美国”（ACT-America）项目的一部分，在美国中部和东部上空飞行期间获取的合并数据产品。NASA 兰利比奇 B200 空中国王和 NASA 戈达德太空飞行中心的 C-130H 大力神这两架飞机平台被用于收集各种大陆表面和大气条件下的高质量现场测量数据。合并数据产品由对大气二氧化碳 (CO2)、甲烷 (CH4)、一氧化碳 (CO)、臭氧 (O3) 和乙烷（C2H6，仅限 B200 飞机）的连续现场测量数据组成，这些测量数据被平均到均匀间隔，并与飞机导航和气象变量以及使用可编程烧瓶包 (PFP) 收集的离散烧瓶样本中的痕量气体浓度合并。这些合并数据产品提供了按间隔进行的综合测量，对建模界研究北美大气二氧化碳和甲烷的输送和通量非常有用。
本数据集共包含 1256 个文件。NetCDF (*.nc) 文件格式包含 628 个数据文件，ICARTT (*.ict) 文件格式也包含 628 个数据文件。需要注意的是，两种格式的文件包含相同的大气气体浓度数据，但 NetCDF 文件包含额外的变量（例如，元数据标记信息），并且变量名称在不同活动和飞机之间保持一致。
摘要
Data Product | Reporting Frequency | File Organization | Merge Protocol - Continuous | Merge Protocol Discrete |
Continuous one-second merge | 1-second | For both NetCDF and ICARTT file formats, files are organized by: aircraft (B-200 or C-130), flight date, revision number, and optionally flight segment (number) for flights with more than one segment. | L2 data from Picarro CRDS and ozone monitoring instruments (2B Technologies) were averaged to 1-second intervals | PFP sample results were added to the 1-second continuous reporting time observation that was nearest the middle of the flask sample collection period |
Continuous 5-second merge | 5-seconds | For both NetCDF and ICARTT file formats, files are organized by: aircraft (B-200 or C-130), flight date, revision number, and optionally flight segment (number) for flights with more than one segment. | L2 data from Picarro CRDS and ozone monitoring instruments (2B Technologies) were averaged to 5-second intervals | PFP sample results were added to the 5-second continuous reporting time observation that was nearest the middle of the flask sample collection period |
Discrete Flask-based Merge | Variable; total PFP fill time | For both NetCDF and ICARTT file formats, files are organized by: aircraft (B-200 or C-130), flight date, revision number, and optionally flight segment (number) for flights with more than one segment. | L2 data from Picarro CRDS and ozone monitoring instruments (2B Technologies) were averaged to the 15-second interval surrounding each flask sample | Flask samples are presented at their native temporal resolution |
代码
!pip install leafmap
!pip install pandas
!pip install folium
!pip install matplotlib
!pip install mapclassifyimport pandas as pd
import leafmapurl = "https://github.com/opengeos/NASA-Earth-Data/raw"
df = pd.read_csv(url, sep="\t")
dfleafmap.nasa_data_login()results, gdf = leafmap.nasa_data_search(short_name="ACTAMERICA_Merge_1593",cloud_hosted=True,bounding_box=(-106.49, 27.23, -72.66, 50.55),temporal=("2016-07-11", "2019-07-27"),count=-1, # use -1 to return all datasetsreturn_gdf=True,
)gdf.explore()#leafmap.nasa_data_download(results[:5], out_dir="data")
