NASA数据集——GES DISC 的 AIRS-CloudSat 云掩模、雷达反射率和云分类匹配 V3.2 (AIRS_CPR_MAT)

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发布于 2024-05-24 09:31:54

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发布于 2024-05-24 09:31:54

AIRS-AMSU variables-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRSM_CPR_MAT) at GES DISC

GES DISC 的 AIRS-CloudSat 云掩模、雷达反射率和云分类匹配 V3.2 (AIRS_CPR_MAT)

简介

这是 NetCDF-4 格式的 AIRS-CloudSat 定位子集。这些数据包括AIRS 1b 级辐射光谱、CloudSat 雷达反射率和 MODIS 云掩模。这些数据是在 MEaSUREs 项目框架内创建的。

其基本任务是汇集来自多个 "A-train "仪器（AIRS、AMSR-E、MODIS、AMSU、MLS、CloudSat）的水汽和云层属性检索数据，利用云层信息对每个 "场景"（仪器外观）进行分类，并按云层类别分层建立大气水汽随高度变化的合并多传感器气候学。这是一个大型科学分析项目，需要使用 SciFlo 技术来发现和组织所有数据集，根据需要移动和缓存数据集，找到成对仪器之间的空间/时间 "匹配"，并处理多年的卫星数据以生成气候数据记录。

该数据集的简称为 AIRS_CPR_MAT

具体信息

Resource Type	Dataset
Metadata Created Date	November 12, 2020
Metadata Updated Date	December 6, 2023
Publisher	NASA/GSFC/SED/ESD/GCDC/GESDISC
Maintainer	GERALD MANIPON
Identifier	C1236224153-GES_DISC
Data First Published	2006-06-15
Language	en-US
Data Last Modified	2012-12-14
Category	MEaSUREs, geospatial
Public Access Level	public
Bureau Code	026:00
Metadata Context	https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID	https://data.nasa.gov/data.json
Schema Version	https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby	https://project-open-data.cio.gov/v1.1/schema/catalog.json
Citation	Eric Fetzer, Brian Wilson, and Gerald Manipon. 2013-07-01. AIRS_CPR_MAT. Version 3.2. AIRS-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2. Greenbelt, MD, USA. AIRS_CPR_MAT_3.2. Archived by National Aeronautics and Space Administration, U.S. Government, Goddard Earth Sciences Data and Information Services Center (GES DISC). https://doi.org/10.5067/MEASURES/WVCC/DATA203. https://disc.gsfc.nasa.gov/datacollection/AIRS_CPR_MAT_3.2.html. Digital Science Data.
Creator	Eric Fetzer, Brian Wilson, and Gerald Manipon
Data Presentation Form	Digital Science Data
Graphic Preview File	https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/AIRS_CPR_MAT_3.2.png
Harvest Object Id	05e26f18-33dc-42b9-a62c-51e9aab0d02b
Harvest Source Id	58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title	NASA Data.json
Issue Identification	AIRS_CPR_MAT_3.2
Homepage URL	https://doi.org/10.5067/MEASURES/WVCC/DATA203
Metadata Type	geospatial
Old Spatial	-180.0 -90.0 180.0 90.0
Program Code	026:001
Release Place	Greenbelt, MD, USA
Series Name	AIRS_CPR_MAT
Source Datajson Identifier	True
Source Hash	3a8b1f5c7a329194d6bbfb4266a1669f2331cf655cb1d3bd7dea5330feae2ed2
Source Schema Version	1.1
Spatial
Temporal	2006-06-15T00:00:00Z/2012-12-14T23:59:59.999Z
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代码

!pip install leafmap
!pip install pandas
!pip install folium
!pip install matplotlib
!pip install mapclassify
 
import pandas as pd
import leafmap
 
url = "https://github.com/opengeos/NASA-Earth-Data/raw/main/nasa_earth_data.tsv"
df = pd.read_csv(url, sep="\t")
df
 
leafmap.nasa_data_login()
 
 
results, gdf = leafmap.nasa_data_search(
    short_name="AIRSM_CPR_MAT",
    cloud_hosted=True,
    bounding_box=(-180, -90, 180, 90),
    temporal=("2020-12-20", "2023-12-08"),
    count=-1,  # use -1 to return all datasets
    return_gdf=True,
)
 
 
gdf.explore()
 
#leafmap.nasa_data_download(results[:5], out_dir="data")