Estimate Surface Temperature Using Energy Balance Model

Estimate Surface Temperature Using Energy Balance Model

Usage

estimate_surface_temperature(
  df,
  depth,
  init_temp = NULL,
  f_mix = 0.2,
  rho_w = 1000,
  cp_w = 4186,
  dt = 86400,
  alpha_sw = 0.07,
  ch = 0.0013,
  ce = 0.0013,
  relax_tau = 3 * 86400
)

Arguments

df

data frame with meteorological and observed surface temperature data. Must include columns: - Date: Date of observation - MET_tmpair: Air temperature (°C) - MET_wndspd: Wind speed (m/s) - MET_radswd: Downward shortwave radiation (W/m²) - MET_radlwd: Downward longwave radiation (W/m²) - MET_prvapr: Vapor pressure (mb) - HYD_temp: Observed surface temperature (°C), - T5avg: 5-day average air temperature (°C)

depth

Lake depth (m)

init_temp

Initial surface temperature (°C). If NULL, uses first available observation or air temperature.

f_mix

Fraction of lake involved in surface mixing. Defaults to 0.2

rho_w

Water density (kg/m³)

cp_w

Heat capacity of water (J/kg/K)

dt

Timestep (s)

alpha_sw

Shortwave albedo. Defaults to 0.07

ch

Bulk sensible heat coefficient. Defaults to 1.3e-3

ce

Bulk latent heat coefficient. Defaults to 1.3e-3

relax_tau

Relaxation timescale to observations (s)

Value

Data frame with estimated surface temperature added as column sst