The Climate Profiles graph gives the user the opportunity to observe at a glance the distribution of the data in the EPW file for four key variables and their variation between day and night.
The Climate Profiles graph are Violin Plots. They show the probability density of the data at different values, usually smoothed by a kernel density estimator. Wider sections of the violin plot represent a higher probability that members of the population will take on the given value; the skinnier sections represent a lower probability.
On mouse hover, they display various statistical properties of the data:
maximum value
minimum value
mean
median
1st quartile
3rd quartile
you might want to start understanding what degree days are here:
Degree days are calculated as the integral of the difference between the outside air temperature and a base temperature over time.
If you can define a base temperature (the outside temperature above which a building needs no heating or cooling) then you can use this to estimate degree days. The building requires heating if the outside air temperature falls below the heating base temperature, and the heating degree days accrue; if the outside air temperature rises above the cooling base temperature, the structure requires cooling, and the cooling degree days accumulate.
The base temperature does not necessarily correspond to the desired building internal temperature, but is the homeostatic temperature between the interior and exterior. Base temperature might depend, among other factors, upon the use of the building, the internal heat gains and the level of insulation.
The top section of the page provides information about the selected location such as longitude, latitude, and Koppen-Geiger climate zone. Via this page, the user can also download the EPW data and the Clima Dataframe used to generate the plots, as shown below.
The bottom section of the page comprises the heating and cooling degree day chart and four violin plots showing the distribution of the dry-bulb air temperature (Tdb), relative humidity (RH), Global Horizontal Irradiance (GHI), and wind speed (U).
Learn more about the Climate Summary tab by watching the following video.
Clima calculates new variables and creates a new dataframe containing the variables already inside the original EPW files and other we calculate. Users can overlay all the variables on the sun path, on the psychometric chart, and on the customizable graphs in the data explorer.
All the variables in the new Clima dataframe are listed below.
