CSLS_daily_met: Given CSLS lake and method, calculate daily evaporation

Description Usage Arguments Value Examples

View source: R/CSLS_daily_met.R

Description

This function calculates daily evaporation for a CSLS lake given the desired method and lake name. While this function can use any of the methods availaible in evaporation, it is currently hardwired to load input data from the CSLS field campaign (as available in CSLSdata) and analysis is restricted to dates with available weather, lake surface temperature, and lake level data (via CSLS_find_common_dates) regardless of the requirements of the chosen method.

Usage

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CSLS_daily_met(
  method = "McJannet",
  use_lst = TRUE,
  Lz = 90,
  wind_elev = 3,
  z0 = 0.02,
  no_condensation = FALSE
)

Arguments

method

denotes which evaporation method to use ("FAO", "McJannet", or "Hamon").

use_lst

logical defaults to TRUE to use available lake surface temperature data.

Lz

longitude of location's measurement timezone (degrees west of Greenwich). For example, Lz = 75, 90, 105 and 120° for measurement times based on the Eastern, Central, Rocky Mountain and Pacific time zones (United States).

wind_elev

height at which wind is measured (m), default: 3

z0

aerodynamic roughness of weather measurement site (m), default: 0.2

no_condensation

defaults to FALSE. If TRUE, forces negative evapotranspiration values (i.e., condensation) to zero

Value

weather, a data frame with daily weather information including:

date

day of each weather observation POSIXct

atmp_min

minimum air temperature for the day (deg C)

atmp_max

maximum air temperature for the day (deg C)

RH_min

minimum relative humidity for the day (percent)

RH_max

maximum relative humidity for the day (percent)

P

total precipitation for the day (mm)

E

total lake evaporation for the day (mm)

Examples

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daily_met <- CSLS_daily_met("McJannet")
daily_met <- CSLS_daily_met("McJannet", use_lst = FALSE)
daily_met <- CSLS_daily_met("Hamon")

WDNR-Water-Use/CSLSevap documentation built on April 9, 2021, 1:35 a.m.