- Preciphysics is a Python library offering a bunch of meteological and numerical calculations.
- Apart from numerical calculations it offers some visualization plots such as meteogram, skew-T etc.
- This Python package is under development with an attempt to be taken onto further supportment.
Experimental work by an Undergraduate Student dedicated to the improvement of the meteorological implications and numerical modelling studies in Turkey.
- Calcsy offers a bunch of meteorological calculations. Fundamentally used equations in Thermodynamics and Precipitation physics are gathered in simply defined functions.
- Each equation function can take arrays of parameters.
- Calcsy is still in development.
- Using calcsy to calculate sensible heat in Joule(J) given the initial and final temperature in Celcius(°C) and Mass of air in (kg) with the help of sens_heat() function.
Input :
sense_heat(tmpi=20, tmpf=21, M=0.5)
# tmpi = Initial Temperature (C)
# tmpf = Final Temperature (C)
# M = Mass (kg)Output :
502.5
#Returns sensible heat in Joules in an array form.-
Meteogravis offers you to plot your Meteogram easily. There are two different functions in which the former plots the Temperature and MSLP Meteogram, while the latter plots the Visibility and the Precipitation Accumulation.
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It expects from you to enter individually preferred 4 parameters which are ;
- Latitude
Latitude on which the plotting will be performed- Longitude
Longitude on which the plotting will be performed- Days
Count of days that will be plotted- Time related- GFS Dataset
Meteogravis only accept GFS Dataset now but future improvements on the way in which other Datasets will also be accepted.
| preciphysics | Function Counts in use |
|---|---|
| Calcsy | 9 Functions in use |
| Meteogravis | 2 Functions in use |
by Berkay & Kutay DÖNMEZ