# Exploiting Domain Knowledge to Address Class Imbalance in Meteorological Data Mining
## 3 Datasets  
### ERA-40 Dataset  
The European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 40-years dataset (ERA-40) is a global atmospheric analysis of many conventional observations and satellite data streams for the period of September 1957 to August 2002. Reanalysis products are used increasingly in many fields that require an observational record of the state of either the atmosphere or its underlying land and ocean surfaces. There are numerous data products that are separated into dataset series based on resolution, vertical coordinate reference, and likely research applications. In this study, we used the ERA-40 2.5 degree latitude-longitude gridded upper air analysis on pressure surfaces. This dataset contains 11 variables on 23 pressure surfaces on an equally spaced global 2.5 degree latitude-longitude grid. All variables are reported four times a day at 00, 06, 12 and 18 UTC for the entire period [17].  
We created our initial dataset choosing the values of 10 variables on 7 pressure surfaces on one node. We used only the data from the node with geographical coordinates 40\({}^{\circ}\) N latitude and 22.5\({}^{\circ}\) E longitude, which is the closest node to the Meteorological Station of Micra, Thessaloniki, Greece located at 40.52\({}^{\circ}\) N, 22.97\({}^{\circ}\) E and altitude of 4m. We omitted the 11 th variable of the Ozone mass mixing ratio. The 1000 hPa, 925 hPa, 850 hPa, 700 hPa, 500 hPa, 300 hPa and 200 hPa are the 7 pressure surfaces we chose, because these are the ones that are mainly used by the meteorology forecasters operationally. In addition, the values of the barometric pressure on mean sea level in Pa supplement the initial dataset that consists of 71 variables.  
Furthermore, the initial values of most of the variables for each pressure surface and the pressure on mean sea level were transformed to make them easier to understand or to express them in the same metric units as used operationally by the meteorologists. More specifically, specific humidity initially expressed in kg\(\cdot\)kg\({}^{-1}\) was converted to g\(\cdot\)kg\({}^{-1}\) and vertical velocity in Pa\(\cdot\)s\({}^{-1}\) to hPa\(\cdot\)h\({}^{-1}\). The relatively small values of both vorticity (relative) in s\({}^{-1}\) and divergence also in s\({}^{-1}\) were multiplied by 10\({}^{6}\), and the value of potential vorticity in K\(\cdot\)m\({}^{2}\cdot\)kg\({}^{-1}\cdot\)s\({}^{-1}\) by 10\({}^{8}\). Regarding the wind, wind direction in azimuth degrees and wind speed in knots were calculated using the U and V velocities in m\({}^{-1}\). Also, the azimuth degrees for the wind direction were assigned into the eight discrete values of north (N), northeast (NE), etc., used in meteorology. The geopotential in m\({}^{2}\cdot\)s\({}^{-2}\) was divided by the World Meteorological Organization (WMO) defined gravity constant of 9.80665 m\(\cdot\)s\({}^{-2}\), thus, it was transformed to geopotential height in gpm. Finally, the values of barometric pressure on mean sea level were expressed in hPa, and only the values of temperature in K and relative humidity as percentage (%) on pressure surfaces remained unchanged.