Aquarius Official Release Level 3 Ancillary Reynolds Sea Surface Temperature Standard Mapped Image Descending Seasonal Climatology Data V5.0
简介
水瓶座 3 级辅助海面温度 (SST) 标准映射图像数据是水瓶座校准用于盐度反演的辅助海面温度数据。它们只是雷诺兹国家气候数据中心 (NCDC) 0.25 度数据集中的每日海面温度数据，使用水瓶座 L2-L3 处理方案进行网格化和平均，空间分辨率为 1 度，时间间隔为每日、7 天、每月、每季和每年，与水瓶座 L3 标准盐度和风速产品相同。该特定数据集是与水瓶座数据集 5.0 版本相关的季节性气候学降序辅助海面温度产品，该版本是 AQUARIUS/SAC-D 任务正式结束任务后发布的公开数据。
摘要
Additional Metadata
Resource Type Dataset
Metadata Created Date April 11, 2025
Metadata Updated Date September 19, 2025
Publisher Aquarius Project NASA/OBPG, Reynolds & Smith NOAA/NCDC;NASA/JPL/PODAAC
Maintainer
Earthdata Forum
Identifier 10.5067/AQR50-3RVDS
Data Last Modified 2025-09-10
Category Earth Science
Public Access Level public
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id a7890f0a-a706-4f8e-aa46-e1e4f099de5f
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL https://podaac.jpl.nasa.gov/CitingPODAAC
Old Spatial {"EastBoundingCoordinate":180.0,"NorthBoundingCoordinate":90,"SouthBoundingCoordinate":-90,"WestBoundingCoordinate":-180.0},"CARTESIAN"
Program Code 026:000
Source Datajson Identifier True
Source Hash 145a639441ca42adf92eecfcca7cbcab50d97ebf9801c231fe777a00e187d3a6
Source Schema Version 1.1
Spatial
Temporal 2011-08-25/2011-08-25
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"
df = pd.read_csv(url, sep="\t")
df
leafmap.nasa_data_login()
results, gdf = leafmap.nasa_data_search(
short_name="AQUARIUS_L3_ANCILLARY_SST_SMI_SEASONAL-CLIMATOLOGY_V5",
cloud_hosted=True,
bounding_box=(-180.0, -90, 180.0, 90),
temporal=("2011-08-25", "2015-06-07"),
count=-1, # use -1 to return all datasets
return_gdf=True,
)
gdf.explore()
leafmap.nasa_data_download(results[:5], out_dir="data")
