About

weathergen generates time-varying weather profiles using a synthesis of in-situ observations and satellite reanalysis estimates of meteorological parameters, and is able to recreate weather patterns allowing for the simulation frameworks like maria to simulate climatologically-accurate ground-based astronomical observations.

Usage

Install the package using pip:

pip install weathergen

Import the package and instantiate a `Weather` object, and pass it an array of times to the `generate` function. For example, to simulate hourly weather for Princeton, New Jersey between June 1st and September 1st we would write

import numpy as np
from datetime import datetime
import weathergen

t0 = datetime(2022,6,1).timestamp() # June 1, 2022
t1 = datetime(2022,9,1).timestamp() # August 1, 2022

gen_times = np.arange(t0, t1, 3600) # three months of hourly data

weather = weathergen.Weather(region='princeton', seasonal=True, diurnal=True)
weather.generate(time=gen_times, mode='random')

Specified times should be supplied in Unix time. The weather parameters are contained in the attributes of the weather object, e.g. weather.temperature or weather.pressure. The values are typically two-dimensional with shape (n_height, n_time), where weather.height and weather.time describe the time and height of each dimension, in Unix time and meters above sea level. Single-level parameters are described by a single number for each time and do not have a height dimension.

Note that the supplied year is arbitrary; the underlying model considers only seasonal and diurnal climatological variations. All available regions are outlined in the dataframe weathergen.regions.