<p>I have a time series of snow and temperature and I want to analyze changes over time for a specific period of time: 15 April - 15 June. In the perpetual calendar April 15 is the day 105 and in a leap year is 106. How should I handle/correct for leap years? Should I subtract one day on leap years? Is there a bias in the data because of leap years? </p>

<p>thanks for you answers!</p>

CC BY-SA 3.0
2017-09-08T02:22:28.917Z
Figure out what physical characteristic you think matters to your data -- the equinox? -- and choose the time period that is constant w.r.t. that physical characteristic.
cphlewis
CC BY-SA 3.0
2017-09-08T02:36:05.030Z
Day of year is appropriate for some data.  Month by month is appropriate for others.  Really depends on what you are trying to do with the data.
f.thorpe
CC BY-SA 3.0
2017-09-08T04:00:30.150Z
Try both, see if it makes a difference. If yes, ask yourself if you are analyzing the right thing in the first place
Christoph
<temperature><snow><time>
How to handle leap years when working with environmental conditions time series?
MSS
# How to handle leap years when working with environmental conditions time series?

(Asked by: username_0 on 2017-09-08)

I have a time series of snow and temperature and I want to analyze changes over time for a specific period of time: 15 April - 15 June. In the perpetual calendar April 15 is the day 105 and in a leap year is 106. How should I handle/correct for leap years? Should I subtract one day on leap years? Is there a bias in the data because of leap years?

thanks for you answers!

**Tags:** temperature, snow, time

> **Comments:**
> **username_1**: Figure out what physical characteristic you think matters to your data -- the equinox? -- and choose the time period that is constant w.r.t. that physical characteristic.  
> **username_2**: Day of year is appropriate for some data.  Month by month is appropriate for others.  Really depends on what you are trying to do with the data.  
> **username_3**: Try both, see if it makes a difference. If yes, ask yourself if you are analyzing the right thing in the first place  

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