Net Radiation and Daily Upscaling Remote Sensing in Python

This Python package implements the net radiation and daily upscaling methods described in Verma et al 2016.

Gregory H. Halverson (they/them)
gregory.h.halverson@jpl.nasa.gov
Lead developer
NASA Jet Propulsion Laboratory 329G

Installation

This package is distributed using the pip package manager as verma-net-radiation with dashes.

Usage

Import this package as verma_net_radiation with underscores.

This module provides functions to calculate instantaneous net radiation and its components, integrate daily net radiation, and process radiation data from a DataFrame. Below is a detailed explanation of each function and how to use them.

process_verma_net_radiation

Description:
Calculates instantaneous net radiation and its components based on input parameters.

Parameters:

• SWin (Union[Raster, np.ndarray]): Incoming shortwave radiation (W/m²).
• albedo (Union[Raster, np.ndarray]): Surface albedo (unitless, constrained between 0 and 1).
• ST_C (Union[Raster, np.ndarray]): Surface temperature in Celsius.
• emissivity (Union[Raster, np.ndarray]): Surface emissivity (unitless, constrained between 0 and 1).
• Ta_C (Union[Raster, np.ndarray]): Air temperature in Celsius.
• RH (Union[Raster, np.ndarray]): Relative humidity (fractional, e.g., 0.5 for 50%).
• cloud_mask (Union[Raster, np.ndarray], optional): Boolean mask indicating cloudy areas (True for cloudy).

Returns: A dictionary containing:

• "SWout": Outgoing shortwave radiation (W/m²).
• "LWin": Incoming longwave radiation (W/m²).
• "LWout": Outgoing longwave radiation (W/m²).
• "Rn": Instantaneous net radiation (W/m²).

Example:

results = process_verma_net_radiation(
    SWin=SWin_array,
    albedo=albedo_array,
    ST_C=surface_temp_array,
    emissivity=emissivity_array,
    Ta_C=air_temp_array,
    RH=relative_humidity_array,
    cloud_mask=cloud_mask_array
)

daily_Rn_integration_verma

Description:
Calculates daily net radiation using solar parameters.

Parameters:

• Rn (Union[Raster, np.ndarray]): Instantaneous net radiation (W/m²).
• hour_of_day (Union[Raster, np.ndarray]): Hour of the day (0-24).
• doy (Union[Raster, np.ndarray], optional): Day of the year (1-365).
• lat (Union[Raster, np.ndarray], optional): Latitude in degrees.
• sunrise_hour (Union[Raster, np.ndarray], optional): Hour of sunrise.
• daylight_hours (Union[Raster, np.ndarray], optional): Total daylight hours.

Returns:

• Raster: Daily net radiation (W/m²).

Example:

daily_Rn = daily_Rn_integration_verma(
    Rn=Rn_array,
    hour_of_day=hour_of_day_array,
    doy=day_of_year_array,
    lat=latitude_array,
    sunrise_hour=sunrise_hour_array,
    daylight_hours=daylight_hours_array
)

---

process_verma_net_radiation_table

Description:
Processes a DataFrame containing inputs for Verma net radiation calculations and appends the results as new columns.

Parameters:

• verma_net_radiation_inputs_df (DataFrame): A DataFrame containing the following columns:
  • Rg: Incoming shortwave radiation (W/m²).
  • albedo: Surface albedo (unitless, constrained between 0 and 1).
  • ST_C: Surface temperature in Celsius.
  • EmisWB: Surface emissivity (unitless, constrained between 0 and 1).
  • Ta_C: Air temperature in Celsius.
  • RH: Relative humidity (fractional, e.g., 0.5 for 50%).

Returns:

• DataFrame: A copy of the input DataFrame with additional columns for the calculated radiation components:
  • SWout: Outgoing shortwave radiation (W/m²).
  • LWin: Incoming longwave radiation (W/m²).
  • LWout: Outgoing longwave radiation (W/m²).
  • Rn: Instantaneous net radiation (W/m²).

Example:

output_df = process_verma_net_radiation_table(input_df)

References

Verma, M., Fisher, J. B., Mallick, K., Ryu, Y., Kobayashi, H., Guillaume, A., Moore, G., Ramakrishnan, L., Hendrix, V. C., Wolf, S., Sikka, M., Kiely, G., Wohlfahrt, G., Gielen, B., Roupsard, O., Toscano, P., Arain, A., & Cescatti, A. (2016). Global surface net-radiation at 5 km from MODIS Terra. Remote Sensing, 8, 739. Link