pyPhenology.models.FallCooling

class pyPhenology.models.FallCooling(parameters={})

Fall senesence model

A model for fall senesence. Essential a Thermal Time model, but instead of accumulating warming above a base temperature, it accumulates cooling below a max temperature.

Event happens on \(DOY\) when the following is met:

\[\sum_{t=t_{1}}^{DOY}R_{f}(T_{i})\geq F^{*}\]

where:

\[R_{f}(T_{i}) = max(threshold-T_{i}, 0)\]

This is a simplified version of the model in Delpierre et al. 2009. The full version also has a photoperiod compoenent.

Parameters:

t1 : int

\(t_{1}\) - The DOY which forcing accumulating beings

default : (182,365)

T : int

\(T\) - The threshold below which cooling accumulates

default : (-25,25)

F : int, > 0

\(F^{*}\) - The total cooling units required

default : (0,1000)

Notes:

Delpierre, N., Dufrêne, E., Soudani, K., Ulrich, E., Cecchini, S., Boé, J., & François, C. (2009). Modelling interannual and spatial variability of leaf senescence for three deciduous tree species in France. Agricultural and Forest Meteorology, 149(6–7), 938–948. http://doi.org/10.1016/j.agrformet.2008.11.014

__init__(parameters={})

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([parameters])	Initialize self.
fit(observations, predictors[, …])	Estimate the parameters of a model
get_params()	Get the fitted parameters
predict([to_predict, predictors])	Make predictions
save_params(filename[, overwrite])	Save the parameters for a model
score([metric, doy_observed, to_predict, …])	Evaluate a prediction given observed doy values