VIIRS-CALIOP Collocation Index (2013 - 2017)

This is an introduction to the collocated data of VIIRS and CALIOP over the years 2013 to 2017. The data files are saved in the format of Hierarchical Data Format, version 5.

Table of Contents

• File structure

• File Names and Sizes

• Data Generation Process

• List of Variables

• References

File Structure

This dataset contains five compressed folders: 

• 2013.tar.gz
• 2014.tar.gz
• 2015.tar.gz
• 2016.tar.gz
• 2017.tar.gz

File structure after decompression:

calipso_index_new/                                  # Root directory

├── 2013/                                             # Year directory (2013-2017)

│   ├── 001/                                           # Day directory (1-365)

│   │   ├── matchviirscaliop*.h5            # Layer 3: Index data file

│   │   └── …

│   └── 002/ 

│   │   └── …

│   ├── …       

└── 2014/

    └── ...

File Names and Sizes

Time range: year 2013 - 2017

Number of VIIRS-CALIOP collocated data: Below are the number and the size of HDF5 files contained in each folder

• Total - 14.2GB

• 2013 - 26367 - 3.1 GB

• 2014 - 25537 - 2.9 GB 

• 2015 - 26042 - 3.0 GB

• 2016 - 24091 - 2.8 GB

• 2017 - 20727 - 2.4 GB

Name formatting:

• Example: matchviirscaliop.vnp2014002t2000.cal2014002t1929.hdf

• Matchviirscaliop: Fixed filename prefix

• vnpxxxxxx: year-DayOfYear-t-HourMinute (The VIIRS time)

• cal2017002t2250: Year-DayOfYear-t-HourMinute (The CALIOP time)

Data Generation Process

1. Download source data

   1. Source: Earth Data NASA GOV 

   2. Search for product name: 

   1. CALIPSO Lidar Level 2 1 km Cloud Layer (CLayer), V4-20

   2. CALIPSO Lidar Level 2 5 km Cloud Layer (CLayer), V4-20

   3. Input start time and end time, and then download files directly or using a generated bash script.

   1. Source: Earth Data NASA GOV

   2. Search for product name:

   1. VIIRS/NPP Moderate Resolution Terrain-Corrected Geolocation L1 6-Min Swath 750 m

   2. VNP02MOD | VIIRS/NPP Moderate Resolution 6-Min L1B Swath 750 m

1. Download CALIPSO data

2. Download VIIRS data

2. Execute code for index generation

1. Using the downloaded CALIPSO and VIIRS data as inputs, and run this code from GitHub: https://github.com/AI-4-atmosphere-remote-sensing/satellite_collocation/blob/main/examples/collocate_viirs_calipso_local_execution/main.py 

List of Variables

Please see variable_list.txt for the full list of variables

References

Software of VIIRS-CALIPSO collection: https://github.com/AI-4-atmosphere-remote-sensing/satellite_collocation/tree/main/examples