(Exercise) Will it snow?

This is an exercise for an advanced analytics task, involving multiple steps.

Given

• Actual (Air) Temperature T in °C
• Dew Point Temperature T_d in °C

Derive

• Actual vapor pressure e in hPa (from T)
• Saturated vapor pressure e_s in hPa (from T_d)
  • Transfer formula from temperature t to vapor pressure e is e = 6.11 \times 10^{\frac{7.5 t}{237.3 + t}}
• Relative Humidity rh in percent, rh = \frac{e}{e_s} \times 100
• Wet bulb temperature T_w in °C, T_w =T \times arctan(0.151977 \sqrt{rh + 8.313659}) + 0.00391838 \sqrt{rh^3} arctan(0.023101 rh) - arctan(rh - 1.676331) + arctan(T + rh) - 4.686035

Evaluate

• On which days is snow possible or even likely? What would be its quality for winter sports?

T_w in °F ⚠	Snow Quality
x > 28	no snow possible
28 ≥ x ≥ 27	wet snow, snowy rain
27 > x ≥ 23	marginal snow
23 > x ≥ 20	good snow
20 > x	great snow

• Combine the possible snow quality with the precipitation data to find likely days with snow fall

Plot

• Plot T_w over time. Mark the thresholds for snow in the plot and highlight sections in which snow was possible, select stronger highlights for better quality.
• Put a timeline below the plot marking full days in which snow was possible and precipitation happened.