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I was checking the weather forecast just now, and it is showing that it "feels like -999 °C". I never heard or saw -999 °C before. I searched other weather channels, and they were showing that it feels like 2 °C. What is the meaning of -999 °C, irrespective of the weather?

Gimelist
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eLg
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1 Answers1

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The value -999 is likely the "fill value" used in the dataset when data is missing or is not being properly filtered or handled when displayed. In the specific case on the website you cite, it is likely a problem with the algorithm for wind chill (the "feels like" temperature this time of year).

It isn't a physical value and only means the value is missing. Furthermore, -999°C is not a possible value because absolute zero is –273.15°C, and it's not possible to be colder than this (at least not in any meaningful way, and certainly not because of wind chill). The coldest recorded temperature on earth is around –90°C.

f.thorpe
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casey
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    Personally, I prefer -9e99 (or 9e99) as a dubious (and obvious) fill value. But yes, this is almost certainly what this is. – David Hammen Dec 16 '14 at 00:07
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    NASA often uses -9999... just to be sure they put the extra 9 – f.thorpe Dec 16 '14 at 05:33
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    the data on that page comes from weather underground, see http://www.wunderground.com/weather/api/d/docs?d=resources/phrase-glossary 'values will = -9999 or -999 for Null or Non applicable (NA) variables' I also suspect that 'feels like' is the heat index value, not the wind chill, which is why it's undefined ( you're not going to get heat stroke there at the moment ) – Pete Kirkham Dec 16 '14 at 19:43
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    @PeteKirkham "feels like" is typically heat index in the warm season and wind chill in the cold season. Some provides use additional factors in their algorithm as well. – casey Dec 16 '14 at 19:45
  • Stupid languages that don't have an NA numeric value >:/ – naught101 Jan 12 '15 at 03:28
  • No, it isn't stupid. For analytical purposes spreadsheets necessarily have a numerical field, so we have to insert a 'stupid' number that we can recognize as spurious, and filter out when it comes to statistical analysis. – Gordon Stanger Mar 04 '17 at 05:14