Ground-Based Networks Examples¶

These examples configure downloads from ground-based photometer, spectrometer, in-situ, radar, and lidar measurement networks.

NASA AERONET¶

Built-in example: aeronet/aeronet_aod_inversions.yaml
Run directly: gathering run example:aeronet/aeronet_aod_inversions.yaml | Copy locally: gathering examples copy aeronet/aeronet_aod_inversions.yaml .

Demonstrates downloading Level 1.5/2.0 spectral Aerosol Optical Depth (AOD) and Almucantar retrieval products (size distribution, single scattering albedo):

# ==============================================================================
# NASA AERONET — Aerosol Optical Depth (AOD) & Almucantar Inversions
# ==============================================================================

logging:
  level: INFO

tasks:
  # Task 1: Level 1.5 & Level 2.0 Spectral AOD
  - source: aeronet
    site: Granada
    start_date: "2023-07-01"
    end_date: "2023-07-05"
    product:
      - AOD15   # Level 1.5 Cloud-screened AOD
      - AOD20   # Level 2.0 Quality-assured AOD
    overwrite_cache: false

  # Task 2: Almucantar Inversions (Size distribution, Single Scattering Albedo)
  - source: aeronet
    site: Granada
    start_date: "2023-07-01"
    end_date: "2023-07-05"
    product:
      - ALM15   # Level 1.5 Almucantar Inversion
      - ALM20   # Level 2.0 Almucantar Inversion
      - SDA20   # Level 2.0 Spectral Deconvolution Algorithm (Fine/Coarse mode AOD)
    overwrite_cache: false

Pandonia Global Network (PGN)¶

Built-in example: pandonia/pandonia_trace_gases.yaml
Run directly: gathering run example:pandonia/pandonia_trace_gases.yaml | Copy locally: gathering examples copy pandonia/pandonia_trace_gases.yaml .

Demonstrates downloading Pandora spectrometer total and tropospheric column trace gases ($NO_2$, $O_3$, $HCHO$):

# ==============================================================================
# Pandonia Global Network (PGN / Pandora) — Atmospheric Trace Gases
# ==============================================================================

source: pandonia

# --- Authentication (Optional inline; alternatively use PANDONIA_API_KEY or credentials.yaml) ---
# api_key: "your_pandonia_api_key"

# Station name (e.g. 'Innsbruck', 'Granada', 'Madrid', 'Rome-TorVergata')
station: "Innsbruck"

# Instrument identifier (optional, auto-resolved if omitted)
instrument_id: "Pandora45"

# Observation date range
start_date: "2023-07-01"
end_date: "2023-07-03"

# Products to download
product:
  - "fnvh3"   # Nitrogen Dioxide (NO2)
  - "fzo3"    # Ozone (O3)
  - "fvh3"    # Formaldehyde (HCHO)

# Processing level & spectrometer
level: "L2Fit"
spectrometer: "1"

overwrite_cache: false

ACTRIS ARES¶

Built-in example: actris/actris_ares_insitu_lidar.yaml
Run directly: gathering run example:actris/actris_ares_insitu_lidar.yaml | Copy locally: gathering examples copy actris/actris_ares_insitu_lidar.yaml .

Demonstrates downloading in-situ aerosol optical properties ($PM_{10}$ scattering/absorption) and remote sensing vertical Lidar profiles:

# ==============================================================================
# ACTRIS ARES — In-situ Aerosol, Trace Gases & Remote Sensing (Lidar)
# ==============================================================================

logging:
  level: INFO

tasks:
  # Task 1: In-situ Aerosol Optical Properties (e.g. nephelometer, aethalometer)
  - source: actris_ares
    station: "gra"                      # Station code (e.g. 'gra' for Granada, 'hpb' for Hohenpeissenberg)
    data_type: "aer_opt"                # Options: aer_opt, aer_phys, aer_chem, trac_gas, voc, lidar_prof
    start_date: "2023-06-01"
    end_date: "2023-06-05"
    matrix: "pm10"                      # Sample matrix (e.g. 'pm10', 'pm2.5', 'pm1', 'air')
    format: "nasa_ames"                 # Data format: 'nasa_ames' or 'netcdf'
    overwrite_cache: false

  # Task 2: Aerosol Remote Sensing Lidar Profiles
  - source: actris_ares
    station: "gra"
    data_type: "lidar_prof"
    start_date: "2023-06-01"
    end_date: "2023-06-05"
    format: "netcdf"
    overwrite_cache: false

ACTRIS Cloudnet¶

Built-in example: actris/actris_cloudnet_profiles.yaml
Run directly: gathering run example:actris/actris_cloudnet_profiles.yaml | Copy locally: gathering examples copy actris/actris_cloudnet_profiles.yaml .

Demonstrates downloading Cloudnet cloud/aerosol vertical profiling products (categorize classification, iwc ice water content):

# ==============================================================================
# ACTRIS Cloudnet — Cloud & Aerosol Profiling (Radar, Lidar, Categorize)
# ==============================================================================

logging:
  level: INFO

tasks:
  # Task 1: Cloudnet Target Classification / Categorize
  - source: actris_cloudnet
    site: "granada"                     # Site name (e.g. 'granada', 'juelich', 'palaiseau', 'leipzig')
    product: "categorize"               # Options: 'categorize', 'classification', 'radar', 'lidar', 'mwr', 'iwc', 'lwc'
    start_date: "2023-06-01"
    end_date: "2023-06-03"
    overwrite_cache: false

  # Task 2: Cloud Water Content (IWC / LWC)
  - source: actris_cloudnet
    site: "granada"
    product: "iwc"                      # Ice Water Content
    start_date: "2023-06-01"
    end_date: "2023-06-03"
    overwrite_cache: false