NASA数据集——NASA 标准二级（L2）暗目标（DT）气溶胶产品每 6 分钟在全球范围内对陆地和海洋上空的气溶胶光学厚度（AOT）产品

2024-05-04 08:48:20 浏览数 (3)

VIIRS/NOAA20 Dark Target Aerosol 6-Min L2 Swath 6 km

简介

NOAA-20（前身为联合极地卫星系统-1（JPSS-1））--可见红外成像辐射计套件（VIIRS）NASA 标准二级（L2）暗目标（DT）气溶胶产品每 6 分钟在全球范围内对陆地和海洋上空的气溶胶光学厚度（AOT）及其特性以及海洋上空的光谱 AOT 及其尺寸参数进行卫星衍生测量。VIIRS 的 DT 气溶胶产品是基于相同的 DT 算法开发的，该算法用于从 Terra 和 Aqua 任务的中型成像分光仪 (MODIS) 仪器中获取产品。目前有两种不同的 DT 算法。一种算法有助于检索海洋上空的气溶胶信息（可见光和较长波段为暗色），另一种算法则有助于检索植被覆盖/暗色土壤覆盖的陆地上空的气溶胶信息（可见光波段为暗色）。这个轨道级产品（简称：AERDT_L2_VIIRS_NOAA20）在天底的分辨率为 6 千米 x 6 千米，由于传感器的扫描几何形状和地球曲率，在远离天底的地方分辨率会逐渐增加。换个角度看，该产品的分辨率可容纳 8 x 8 原始 VIIRS 中等分辨率（M 波段）像素，这些像素的水平像素尺寸大约为 750 米。因此，二级暗目标气溶胶光学厚度数据产品在 6 分钟的采集过程中包含了 64 个（750 米）像素。这套第 2 版产品是首次收集 NOAA-20 VIIRS 来源的第 2 级暗目标气溶胶数据。因此，有必要概述 NOAA-20 VIIRS 与 Suomi National Polar-orbiting Partnership (SNPP) VIIRS 得出的产品之间的差异。Level-2 暗目标气溶胶： NOAA-20 VIIRS v2.0 改进版--NOAA-20 VIIRS v2.0 产品使用了更高分辨率的云掩模，该掩模源自 375 米图象波段红波长，可在减少云污染的情况下进行更近距离的近云检索。这种改进后的掩膜在海洋上空尤为明显，许多高 AOD 值都被向下修正。- NOAA-20 VIIRS v2.0 产品使用 NASA 全球建模和同化办公室（GMAO）的输入作为辅助气象数据源，而不是之前 NOAA 全球数据同化系统（GDAS）的数据源。- NOAA-20 VIIRS v2.0 产品使用更新的 VIIRS Level-1B 反射率，其校准比前一版本有所改进。- NOAA-20 VIIRS v2.0 产品现在报告所有七个波段的陆地平均反射率和标准偏差，而 v1.1 产品仅报告海洋反射率。 L2 netCDF 产品包含以下 37 个科学数据集 (SDS) 图层：

  1. Aerosol_Cldmask_Land_Ocean
  2. Aerosol_Cloud_Fraction_Land
  3. Aerosol_Cloud_Fraction_Ocean
  4. Aerosol_Type_Land
  5. Angstrom_Exponent_1_Ocean
  6. Angstrom_Exponent_2_Ocean
  7. Asymmetry_Factor_Average_Ocean
  8. Average_Cloud_Pixel_Distance_Land_Ocean
  9. Backscattering_Ratio_Average_Ocean
  10. Cloud_Pixel_Distance_Land_Ocean
  11. Corrected_Optical_Depth_Land
  12. Effective_Optical_Depth_Average_Ocean
  13. Effective_Radius_Ocean
  14. Error_Flag_Land_And_Ocean
  15. Fitting_Error_Land
  16. Image_Optical_Depth_Land_And_Ocean
  17. Land_Ocean_Quality_Flag
  18. Land_Sea_Flag
  19. Least_Squares_Error_Ocean
  20. Mass_Concentration_Land
  21. Mass_Concentration_Ocean
  22. Mean_Reflectance_Land
  23. Mean_Reflectance_Ocean
  24. Number_Pixels_Used_Land
  25. Number_Pixels_Used_Ocean
  26. Optical_Depth_By_Models_Ocean
  27. Optical_Depth_Land_And_Ocean
  28. Optical_Depth_Large_Average_Ocean
  29. Optical_Depth_Ratio_Small_Land
  30. Optical_Depth_Ratio_Small_Ocean_0p55micron
  31. Optical_Depth_Small_Average_Ocean
  32. PSML003_Ocean
  33. STD_Reflectance_Land
  34. STD_Reflectance_Ocean
  35. Surface_Reflectance_Land
  36. Topographic_Altitude_Land
  37. Wind_Speed_Ncep_Ocean

数据信息

Shortname:

AERDT_L2_VIIRS_NOAA20

Platform:

NOAA-20

Instrument:

VIIRS

Processing Level:

Level-2

File Size (MB):

7 - 12 MB

Data Format:

netCDF4

Spatial Resolution:

6km

Temporal Resolution:

6 minute

Spatial Coverage:

Global (daytime only)

ArchiveSets:

5200

Collection:

NPP and JPSS1 VIIRS data 2.0 (ArchiveSet 5200)

Production Frequency:

~130 files/day

Data Authors:

R.C. Levy, S. Mattoo, V. Sawyer, L.A. Munchak

Dataset Originator/Creator:

Dark Target aerosol team, Climate and Radiation Laboratory, NASA Goddard Space Flight Center

PGE Number:

NONE

File Naming Convention:

Example: AERDT_L2_VIIRS_NOAA20.A2019218.1818.001.2019291174906.nc Syntax: ESDT.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.Format ESDT = Earth Science Data Type or ShortnameA = AcquisitionYYYYDDD = Data acquisition year and Day-of-yearHHMM = Acquisition Hour and MinuteCCC = Version ID of the data collectionYYYYDDDHHMMSS = Processing year, Day-of-year, UTC time (hour, minutes, seconds)Format = File format suffix, which in the above case represents netCDF4

Citation:

Please cite the use of this data set in publications using the following references: Sawyer, V., R.C. Levy, S. Mattoo, G. Cureton, Y. Shi, and L.A. Remer (2020), Continuing the MODIS Dark Target Aerosol Time Series with VIIRS. Remote Sens. 2020, 12, 308; https://doi.org/10.3390/rs12020308 Levy, R.C., L. A. Munchak, S. Mattoo, F. Patadia, L. A. Remer, and R. E. Holz (2015), Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance, Atmos. Meas. Tech., 8, 4083–4110.

Keywords:

SNPP VIIRS, L2 Swath, 6-Minute, Dark Target Aerosol Optical Thickness

  • ESDT = Earth Science Data Type or Shortname
  • A = Acquisition
  • YYYYDDD = Data acquisition year and Day-of-year
  • HHMM = Acquisition Hour and Minute
  • CCC = Version ID of the data collection
  • YYYYDDDHHMMSS = Processing year, Day-of-year, UTC time (hour, minutes, seconds)
  • Format = File format suffix, which in the above case represents netCDF4

Citation:Please cite the use of this data set in publications using the following references: Sawyer, V., R.C. Levy, S. Mattoo, G. Cureton, Y. Shi, and L.A. Remer (2020), Continuing the MODIS Dark Target Aerosol Time Series with VIIRS. Remote Sens. 2020, 12, 308; https://doi.org/10.3390/rs12020308 Levy, R.C., L. A. Munchak, S. Mattoo, F. Patadia, L. A. Remer, and R. E. Holz (2015), Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance, Atmos. Meas. Tech., 8, 4083–4110.Keywords:SNPP VIIRS, L2 Swath, 6-Minute, Dark Target Aerosol Optical Thickness

代码

代码语言：javascript复制
!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="AERDT_L2_VIIRS_NOAA20",
    cloud_hosted=True,
    bounding_box=(-180.0, -90.0, 180.0, 90.0),
    temporal=("2000-01-01", "2024-04-26"),
    count=-1,  # use -1 to return all datasets
    return_gdf=True,
)
 
 
gdf.explore()
 
#leafmap.nasa_data_download(results[:5], out_dir="data")

数据链接

VIIRS/NOAA20 Dark Target Aerosol 6-Min L2 Swath 6 km - LAADS DAAC

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