8 ms·

U.S. Daily Temperature Anomalies 1964-2013

206 points by dandelany 13y ago

keelhaule 13y ago
I think the solution for such issue is not at the MacroEconomical level, but at micro-behavioral level of our culture and life habits, if we solve it, all the macro factors will adapt accordingly
gooddelta 13y ago
Really awesome visualization, but I didn't read the text because the columns were insanely wide on my 24" monitor. Might want to constrain the width a bit, chaps.
- dandelany 13y ago
  Thanks for the feedback! Just pushed an update with a max-width.
noir_lord 13y ago
I'm probably been blind but where is the units for the Y axis on the top graph?
- dandelany 13y ago
  You aren't blind :) We just had trouble fitting a y-scale on the top chart that was both clean and readable and didn't get in the way of the time slider... However this is just supposed to be an overview of the trend - the proportional bar chart further down the page is the same data, plotted in more depth and explained further.
sigil 13y ago
Absolutely beautiful visualization. A couple cautions about drawing conclusions from this data though: 1. A trend in the outliers of a distribution does not imply the same trend in the mean values of the distribution. Although I'm sure there's an upward trend in the mean values, it's not good science to encourage people to jump to that second conclusion. (Not without the supporting data at least.) 2. What about sampling bias? Intuitively, it seems like the reporting weather stations would not be uniformly distributed geographically, but would rather show a higher concentration near urban areas, which store and release extra heat. How large is this effect, and how could we correct for it? For anyone interested, you can also get at the raw data without signing up for engima.io: http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/ http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/
- dandelany 13y ago
  Thanks for the excellent comment. Your first point is very well taken - we also urge caution in drawing too many conclusions regarding an overall trend in mean temperatures. However, I think our conclusion - that we are having more hot outlier days now than ever before - is interesting in and of itself. Your second point is an interesting one, and I too would be curious to look further into the correlation between proximity to a city and temperature. However, to look for outliers, we created a long-running distribution of seasonal temperatures for each station individually - so in some sense the map is already corrected for this effect. Each anomaly you see is an anomaly for that station alone - meaning if an urban station regularly gets higher temperatures than a rural one, it will take a proportionally higher temperature to trigger an anomaly on the former than on the latter. Furthermore, NOAA has been good about getting good national distribution of these stations so it's less of a concern than you might think. That said, urban stations may still show artifacts compared to rural ones, eg. when there is an extreme warm outlier, cities may be more likely to have another warm outlier the following day due to the heat storage effect you mention. I'm not sure.
  - jsyedidia 13y ago
    About the second point, the U.S. population has been growing (from 179 million in 1960 to 308 million in 2010 according to the US Census). So a particular station that was in the same location in 2014 as it was in 1964 could well have a more urban surrounding in 2014. In fact, one knows that surely on average this will be the case. Since more urban surroundings lead to higher temperatures, this must be a biasing factor. Does anybody have any idea how large this biasing factor is? Is there any literature on that issue?
    - cromulent 13y ago
      Apparently the factor has been recognized and analyzed. http://www.grida.no/publications/other/ipcc_tar/?src=/climate/ipcc_tar/wg1/052.htm http://www.grida.no/publications/other/ipcc_tar/?src=/climat... "However, over the Northern Hemisphere land areas where urban heat islands are most apparent, both the trends of lower-tropospheric temperature and surface air temperature show no significant differences. In fact, the lower-tropospheric temperatures warm at a slightly greater rate over North America (about 0.28°C/decade using satellite data) than do the surface temperatures (0.27°C/decade), although again the difference is not statistically significant. "
Govannon 13y ago
Loved It! One comment I might have is that your model assumes the average temperature on a given day of the year is constant across years. I would have to spend some time thinking of how to control for it, but have you considered the impact of climactic oscillation? Your data seems to reflect these patterns to some degree, and removing/reducing them might make the overall shift clearer. http://en.wikipedia.org/wiki/Effects_of_the_El_Ni%C3%B1o%E2%80%93Southern_Oscillation_in_the_United_States http://en.wikipedia.org/wiki/Effects_of_the_El_Ni%C3%B1o%E2%...
- dandelany 13y ago
  Yeah, that is an interesting point and highlights the difference between "weather" and "climate" - it also brings up a tension between two different objectives of the chart: to visualize weather patterns over time intuitively, and to draw general conclusions about climate trends. In the context of the first intention, climatic oscillations like El Niño are interesting signals - you can see how they affect weather throughout the country in unexpected ways. But in the context of the latter goal, they are noise which should be filtered out/corrected for.
  - Govannon 13y ago
    That makes sense; my only thought was that if you are graphing "anomalies" you might want to filter out non-anomalous behavior. Higher highs or lower lows are actually to some degree expected in those years. I suppose it could be best not to control for oscillatory behavior though as the affect of any climate shift on those oscillations is possibly not insignificant.
RA_Fisher 13y ago
I'd be curious to see maximum and minimum temperatures modeled with an extreme value distribution. Might do it myself.
autokad 13y ago
strange coincidence, temperatures started going up after the EPA declared war on sulfur.
ToastyMallows 13y ago
Is the data not loading for anyone else? It's been 10 minutes for me an all I get it "Loading data". EDIT: Not working in Chrome, but it works in IE.
- dandelany 13y ago
  Hmm, that's odd - it was developed in Chrome and I haven't seen any Chrome-related issues after testing on several computers. Could be due to a badly-behaving browser extension? Let me know if you see any JS errors on the console, or if you figure out what was causing this...
  - ToastyMallows 13y ago
    A-ha! Looks like HTTPS-Everywhere was messing it up. After loading it Incognito it worked.
D9u 13y ago
Too bad the graphics only show the lower 48 states. Sure, some will claim that, "Alaska is always cold, and Hawai'i is always hot," which is a typical fallacy. People surf in Alaska, and it snows in Hawai'i. (We just had a hailstorm a few weeks ago.) http://www.hawaiinewsnow.com/story/25102371/flash-flood-watch-issued-for-oahu-until-sunday-morning-showers-and-thunderstorms-possible http://www.hawaiinewsnow.com/story/25102371/flash-flood-watc... Back in the 1970's I remember seeing snow fall halfway down the slopes of 13,796 foot Mauna Kea, something we don't see too often anymore.
- dandelany 13y ago
  Click and drag to pan the map - Alaska, Hawaii and Puerto Rico all have data :)
  - D9u 13y ago
    Thank you... Not sure why I didn't notice this initially. (blames outdated mobile device)
- aidenn0 13y ago
  Hail is not the same as snow. When I lived in the mid-atlantic region, we got hail almost exclusively in the summer, as it was typically caused by thunderstorms.
- CanSpice 13y ago
  Little known fact: Hawaii's record high temperature (100F) is the same as Alaska's record high temperature (100F), and both are the lowest record high temperatures for the 50 states. Alaska's record low (-80F) is a little bit colder than Hawaii's record low (15F) though.
  - batmansbelt 13y ago
    I'd love to live in Hawaii. It sounds like heaven on Earth.
    - 13y ago
dpierce9 13y ago
Wouldn't it be better to use a rolling window rather than monthly distribution for anomaly detection? One might expect more anomalies in the shoulder months using the monthly distribution.
- dandelany 13y ago
  Yes, this would be a good improvement to the data pipeline. I only built the front-end so I can't speak to exactly what difficulties would be involved, but I agree.
- abelsonlive 13y ago
  Yes, that's a good point. It would be better to create one distribution for each day of the year, with the values drawn from the 2-3 weeks before / after that day, but we chose a month to minimize the computational complexity. Presumably these artifacts wouldn't affect the aggregate trend over time, only the appearance of more outliers at the beginning of March / October, etc. each year. We also were drawing inspiration from NOAA's Climate Extremes Index which uses monthly data: https://www.ncdc.noaa.gov/extremes/cei/ https://www.ncdc.noaa.gov/extremes/cei/
crazy1van 13y ago
Great looking graphs. But, its hard to take the data seriously when the y-axis is rarely labeled...
bernardom 13y ago
I couldn't find the answer to this (perhaps I missed it): what is defined as an outlier?
- nymph 13y ago
  It's "dataviz", bro. Not data science.
  - nymph 13y ago
    Yo, downvoter: In case it wasn't apparent to you, there were a number of fairly obvious (let's call them "junior") errors of reasoning embedded in the original posting. As in, the kinds of things we would have readily lost points for in that undergraduate-level "quantitative reasoning" course we crammed through on the way to fulfilling our social science degree. Wholly independent, mind you, of all the fancy-schmancy talk about generalized linear models and whatnot. Which, while being quite nice-sounding, serve only to distract from the more basic (and glaring) errors of inference in the surrounding text. Which, in turn, is why the label "dataviz" is a more than appropriate description of the otherwise quite fun and entertaining HTML5 demo provided by the Enigma team. "Data science", however, it is not.
- dandelany 13y ago
  From the page: "Armed with this refined dataset, we computed the historical range of low and high temperatures for each station for each month of the year. We then compared each station's daily temperatures to its corresponding monthly distribution. If one or both of these measurements fell in the bottom or top 2% on a given day, we labeled it an "anomaly" according to the typology above."
mixonic 13y ago
Neat visualization, 100 megabytes of ram consumption! Sometimes as much as 8 meg GC during a JavaScript frame, making the frame bloat to over 50ms of running time. I bet there are some cheap wins you can find in there OP! Keep up the good work.
- dandelany 13y ago
  You should've seen it before we found all the cheap wins :) Seriously though, I'd be interested to hear any ideas you have - it has already been optimized quite a bit but it's just a lot of data (3 million rows over 50 years). It uses canvas and throws away all the circle references every day so that helps a lot.
guscost 13y ago
Nice work, really cool method for visualizing this data. I don't agree with the decision to include a political argument in the writeup, but I suppose that's to be expected.
deleted 13y ago
[deleted]
adaml_623 13y ago
Would it be very hard to do this for a sample of all the stations world wide? The US centered view is kind of odd considering the subject matter.
- dandelany 13y ago
  Theoretically no, the database we used contains weather station data from all over the world. However during our analysis we found that the quality of data from international stations was a lot more varied - as measured by many factors such as geographical distribution of stations, regularity of measurements and number of implausible outliers. I would still like to come back to this eventually & try to iron out as many of those issues as possible - but for the scope of this project it was much easier to just use US data as it is extremely well-curated.
jstalin 13y ago
Is it the raw, original weather station data, or the data the NOAA has been "adjusting" over and over to make the past cooler?
- dandelany 13y ago
  AFAIK this is based on raw, original weather station data.
- insensible 13y ago
  Joe D'Aleo, the first director of meteorology at the Weather Channel who now works with WeatherBELL, is explaining to anyone who will listen that NOAA did exactly that. http://icecap.us/images/uploads/NOAAroleinclimategate.pdf http://icecap.us/images/uploads/NOAAroleinclimategate.pdf Closing line: "The NOAA, NASA and the Hadley Center press releases should be ignored. The reason which is expanded on with case studies in the full report is that the surface based data sets have become seriously flawed and can no longer be trusted for climate trend or model forecast assessment in decision making by congress or the EPA."
sadfnjksdf 13y ago
Can't wait to see 2014. Right up there with... hmm, maybe not.
tomc1985 13y ago
What kind of data is available for prior 1964? It'd be foolish to draw conclusions with only 50 years' data. Pre-industrial-revolution readings could be a useful control...
kf5jak 13y ago
I was wanting to do something just like this recently. Very visualizing and pleasing to watch. Now we just need some slow building dramatic melody to watch as our planet melts away!
QuantumChaos 13y ago
You have to ask yourself this question: If I saw a webpage like this, but with the opposite trend (or no trend), would I consider this to be strong evidence against global warming, or would I dismiss it as cherry picked data, a statistical artifact, etc.?
vvvnnnnvvv 13y ago
Gorgeous visualization! Takes a really long time to watch though, even after clicking the "up" on speed a bunch of times, and so it's hard to get the same sense from watching the points on the map as you get instantly from the chart under the map. Have you considered aggregating a little more, so that years move by faster?
Smachine 13y ago
There hasn't been any warming for 17 years. How can the graph point up? I'm sure I will get lambasted. But there hasn't been any warming for 17 years.

206 points by dandelany 13y ago

I think the solution for such issue is not at the MacroEconomical level, but at micro-behavioral level of our culture and life habits, if we solve it, all the macro factors will adapt accordingly

gooddelta 13y ago

Really awesome visualization, but I didn't read the text because the columns were insanely wide on my 24" monitor. Might want to constrain the width a bit, chaps.

dandelany 13y ago
Thanks for the feedback! Just pushed an update with a max-width.

noir_lord 13y ago

I'm probably been blind but where is the units for the Y axis on the top graph?

dandelany 13y ago
You aren't blind :) We just had trouble fitting a y-scale on the top chart that was both clean and readable and didn't get in the way of the time slider... However this is just supposed to be an overview of the trend - the proportional bar chart further down the page is the same data, plotted in more depth and explained further.

sigil 13y ago

Absolutely beautiful visualization. A couple cautions about drawing conclusions from this data though: 1. A trend in the outliers of a distribution does not imply the same trend in the mean values of the distribution. Although I'm sure there's an upward trend in the mean values, it's not good science to encourage people to jump to that second conclusion. (Not without the supporting data at least.) 2. What about sampling bias? Intuitively, it seems like the reporting weather stations would not be uniformly distributed geographically, but would rather show a higher concentration near urban areas, which store and release extra heat. How large is this effect, and how could we correct for it? For anyone interested, you can also get at the raw data without signing up for engima.io: http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/ http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/

dandelany 13y ago
Thanks for the excellent comment. Your first point is very well taken - we also urge caution in drawing too many conclusions regarding an overall trend in mean temperatures. However, I think our conclusion - that we are having more hot outlier days now than ever before - is interesting in and of itself. Your second point is an interesting one, and I too would be curious to look further into the correlation between proximity to a city and temperature. However, to look for outliers, we created a long-running distribution of seasonal temperatures for each station individually - so in some sense the map is already corrected for this effect. Each anomaly you see is an anomaly for that station alone - meaning if an urban station regularly gets higher temperatures than a rural one, it will take a proportionally higher temperature to trigger an anomaly on the former than on the latter. Furthermore, NOAA has been good about getting good national distribution of these stations so it's less of a concern than you might think. That said, urban stations may still show artifacts compared to rural ones, eg. when there is an extreme warm outlier, cities may be more likely to have another warm outlier the following day due to the heat storage effect you mention. I'm not sure.
- jsyedidia 13y ago
  About the second point, the U.S. population has been growing (from 179 million in 1960 to 308 million in 2010 according to the US Census). So a particular station that was in the same location in 2014 as it was in 1964 could well have a more urban surrounding in 2014. In fact, one knows that surely on average this will be the case. Since more urban surroundings lead to higher temperatures, this must be a biasing factor. Does anybody have any idea how large this biasing factor is? Is there any literature on that issue?
  - cromulent 13y ago
    Apparently the factor has been recognized and analyzed. http://www.grida.no/publications/other/ipcc_tar/?src=/climate/ipcc_tar/wg1/052.htm http://www.grida.no/publications/other/ipcc_tar/?src=/climat... "However, over the Northern Hemisphere land areas where urban heat islands are most apparent, both the trends of lower-tropospheric temperature and surface air temperature show no significant differences. In fact, the lower-tropospheric temperatures warm at a slightly greater rate over North America (about 0.28°C/decade using satellite data) than do the surface temperatures (0.27°C/decade), although again the difference is not statistically significant. "

Govannon 13y ago

Loved It! One comment I might have is that your model assumes the average temperature on a given day of the year is constant across years. I would have to spend some time thinking of how to control for it, but have you considered the impact of climactic oscillation? Your data seems to reflect these patterns to some degree, and removing/reducing them might make the overall shift clearer. http://en.wikipedia.org/wiki/Effects_of_the_El_Ni%C3%B1o%E2%80%93Southern_Oscillation_in_the_United_States http://en.wikipedia.org/wiki/Effects_of_the_El_Ni%C3%B1o%E2%...

dandelany 13y ago
Yeah, that is an interesting point and highlights the difference between "weather" and "climate" - it also brings up a tension between two different objectives of the chart: to visualize weather patterns over time intuitively, and to draw general conclusions about climate trends. In the context of the first intention, climatic oscillations like El Niño are interesting signals - you can see how they affect weather throughout the country in unexpected ways. But in the context of the latter goal, they are noise which should be filtered out/corrected for.
- Govannon 13y ago
  That makes sense; my only thought was that if you are graphing "anomalies" you might want to filter out non-anomalous behavior. Higher highs or lower lows are actually to some degree expected in those years. I suppose it could be best not to control for oscillatory behavior though as the affect of any climate shift on those oscillations is possibly not insignificant.

RA_Fisher 13y ago

I'd be curious to see maximum and minimum temperatures modeled with an extreme value distribution. Might do it myself.

autokad 13y ago

strange coincidence, temperatures started going up after the EPA declared war on sulfur.

ToastyMallows 13y ago

Is the data not loading for anyone else? It's been 10 minutes for me an all I get it "Loading data". EDIT: Not working in Chrome, but it works in IE.

dandelany 13y ago
Hmm, that's odd - it was developed in Chrome and I haven't seen any Chrome-related issues after testing on several computers. Could be due to a badly-behaving browser extension? Let me know if you see any JS errors on the console, or if you figure out what was causing this...
- ToastyMallows 13y ago
  A-ha! Looks like HTTPS-Everywhere was messing it up. After loading it Incognito it worked.

D9u 13y ago

Too bad the graphics only show the lower 48 states. Sure, some will claim that, "Alaska is always cold, and Hawai'i is always hot," which is a typical fallacy. People surf in Alaska, and it snows in Hawai'i. (We just had a hailstorm a few weeks ago.) http://www.hawaiinewsnow.com/story/25102371/flash-flood-watch-issued-for-oahu-until-sunday-morning-showers-and-thunderstorms-possible http://www.hawaiinewsnow.com/story/25102371/flash-flood-watc... Back in the 1970's I remember seeing snow fall halfway down the slopes of 13,796 foot Mauna Kea, something we don't see too often anymore.

dandelany 13y ago
Click and drag to pan the map - Alaska, Hawaii and Puerto Rico all have data :)
- D9u 13y ago
  Thank you... Not sure why I didn't notice this initially. (blames outdated mobile device)
aidenn0 13y ago
Hail is not the same as snow. When I lived in the mid-atlantic region, we got hail almost exclusively in the summer, as it was typically caused by thunderstorms.
CanSpice 13y ago
Little known fact: Hawaii's record high temperature (100F) is the same as Alaska's record high temperature (100F), and both are the lowest record high temperatures for the 50 states. Alaska's record low (-80F) is a little bit colder than Hawaii's record low (15F) though.
- batmansbelt 13y ago
  I'd love to live in Hawaii. It sounds like heaven on Earth.
  - 13y ago

dpierce9 13y ago

Wouldn't it be better to use a rolling window rather than monthly distribution for anomaly detection? One might expect more anomalies in the shoulder months using the monthly distribution.

dandelany 13y ago
Yes, this would be a good improvement to the data pipeline. I only built the front-end so I can't speak to exactly what difficulties would be involved, but I agree.
abelsonlive 13y ago
Yes, that's a good point. It would be better to create one distribution for each day of the year, with the values drawn from the 2-3 weeks before / after that day, but we chose a month to minimize the computational complexity. Presumably these artifacts wouldn't affect the aggregate trend over time, only the appearance of more outliers at the beginning of March / October, etc. each year. We also were drawing inspiration from NOAA's Climate Extremes Index which uses monthly data: https://www.ncdc.noaa.gov/extremes/cei/ https://www.ncdc.noaa.gov/extremes/cei/

crazy1van 13y ago

Great looking graphs. But, its hard to take the data seriously when the y-axis is rarely labeled...

bernardom 13y ago

I couldn't find the answer to this (perhaps I missed it): what is defined as an outlier?

nymph 13y ago
It's "dataviz", bro. Not data science.
- nymph 13y ago
  Yo, downvoter: In case it wasn't apparent to you, there were a number of fairly obvious (let's call them "junior") errors of reasoning embedded in the original posting. As in, the kinds of things we would have readily lost points for in that undergraduate-level "quantitative reasoning" course we crammed through on the way to fulfilling our social science degree. Wholly independent, mind you, of all the fancy-schmancy talk about generalized linear models and whatnot. Which, while being quite nice-sounding, serve only to distract from the more basic (and glaring) errors of inference in the surrounding text. Which, in turn, is why the label "dataviz" is a more than appropriate description of the otherwise quite fun and entertaining HTML5 demo provided by the Enigma team. "Data science", however, it is not.
dandelany 13y ago
From the page: "Armed with this refined dataset, we computed the historical range of low and high temperatures for each station for each month of the year. We then compared each station's daily temperatures to its corresponding monthly distribution. If one or both of these measurements fell in the bottom or top 2% on a given day, we labeled it an "anomaly" according to the typology above."

mixonic 13y ago

Neat visualization, 100 megabytes of ram consumption! Sometimes as much as 8 meg GC during a JavaScript frame, making the frame bloat to over 50ms of running time. I bet there are some cheap wins you can find in there OP! Keep up the good work.

dandelany 13y ago
You should've seen it before we found all the cheap wins :) Seriously though, I'd be interested to hear any ideas you have - it has already been optimized quite a bit but it's just a lot of data (3 million rows over 50 years). It uses canvas and throws away all the circle references every day so that helps a lot.

guscost 13y ago

Nice work, really cool method for visualizing this data. I don't agree with the decision to include a political argument in the writeup, but I suppose that's to be expected.

deleted 13y ago

[deleted]

adaml_623 13y ago

Would it be very hard to do this for a sample of all the stations world wide? The US centered view is kind of odd considering the subject matter.

dandelany 13y ago
Theoretically no, the database we used contains weather station data from all over the world. However during our analysis we found that the quality of data from international stations was a lot more varied - as measured by many factors such as geographical distribution of stations, regularity of measurements and number of implausible outliers. I would still like to come back to this eventually & try to iron out as many of those issues as possible - but for the scope of this project it was much easier to just use US data as it is extremely well-curated.

jstalin 13y ago

Is it the raw, original weather station data, or the data the NOAA has been "adjusting" over and over to make the past cooler?

dandelany 13y ago
AFAIK this is based on raw, original weather station data.
insensible 13y ago
Joe D'Aleo, the first director of meteorology at the Weather Channel who now works with WeatherBELL, is explaining to anyone who will listen that NOAA did exactly that. http://icecap.us/images/uploads/NOAAroleinclimategate.pdf http://icecap.us/images/uploads/NOAAroleinclimategate.pdf Closing line: "The NOAA, NASA and the Hadley Center press releases should be ignored. The reason which is expanded on with case studies in the full report is that the surface based data sets have become seriously flawed and can no longer be trusted for climate trend or model forecast assessment in decision making by congress or the EPA."

sadfnjksdf 13y ago

Can't wait to see 2014. Right up there with... hmm, maybe not.

tomc1985 13y ago

What kind of data is available for prior 1964? It'd be foolish to draw conclusions with only 50 years' data. Pre-industrial-revolution readings could be a useful control...

kf5jak 13y ago

I was wanting to do something just like this recently. Very visualizing and pleasing to watch. Now we just need some slow building dramatic melody to watch as our planet melts away!

QuantumChaos 13y ago

You have to ask yourself this question: If I saw a webpage like this, but with the opposite trend (or no trend), would I consider this to be strong evidence against global warming, or would I dismiss it as cherry picked data, a statistical artifact, etc.?

vvvnnnnvvv 13y ago

Gorgeous visualization! Takes a really long time to watch though, even after clicking the "up" on speed a bunch of times, and so it's hard to get the same sense from watching the points on the map as you get instantly from the chart under the map. Have you considered aggregating a little more, so that years move by faster?

Smachine 13y ago

There hasn't been any warming for 17 years. How can the graph point up? I'm sure I will get lambasted. But there hasn't been any warming for 17 years.