Celsius please. But besides that: Very nice, very clear and way better than supid sun and cloud icons with temperatures next to them over some vague areas.
I am proud of forecast.io for sticking with a 'normal' color palette here, rather than the non-standard purples they have chosen for radar; as a meteorologist the purple radar hurts my brain, but this map is completely cool.
Also there are definitely some quality control issues with the RTMA data, so you can bump into the garbage-in-garbage-out issue with it, but overall, this is a very nice start to something that could ultimately be quite useful.
Also: Validation is tricky, since we can't just compare the output to ground station observations, as we incorporate ground station data into the model. Eventually I want to generate alternative versions that randomly exclude specific stations so we can use them for comparison.
Instead, I think you'd need to find temperature measurements that are completely independent and use them for verification. Along this line, I'm not sure how refitting the data to ground stations would produce a better match anywhere except at those ground stations (overfitting). Or are you using ground stations that are truly independent?
When we compare it to RTMA, we leave out RTMA from the list of data sources. Likewise, eventually I'd like to do the same with a subset of the ground stations we use.
(The problem with finding completely independent measurements is that we'd want to use them as an input!)
Thank MapBox. If it were up to me, I'd do something funky like a blackbody-esque color palette and then get yelled at because it'd be hard to read. :-)
The color palette adjusts based on the zoom level in order to improve contrast. Roughly a bazillion people pointed out that it's "broken", so I guess that was a dumb call on my part!
Shouldn't it adjust based on the extremes (Or standard deviation) within the zoom area? In that case there would always be some purple, and should fix at least the specific problem the parent showed.
I was also impressed but concur that there seems to be significant loss when zoomed out. I'm not sure how they sample for the larger scales, but it seems very inaccurate.
This isn't a map. This is a simulation. You made a simulation, and are outputting the results.
This teaches you nothing whatsoever except that your model has pretty colors.
Next thing someone is going to take these results, use them as input data for a new model, then send the results of that new model back as data for the first.
What would a better map be? Is your point that they are doing interpolation on something that is already interpolated? Or are you implying that there is no way to create a map of temperature using only point measurements? I would like to know how well this data matches the raw station measurements (and verification measurements) but I think it's a decent visualization of likely real time temperature across a region.
Hmm, there are some superlatives ("highest resolution") in here I'm not sure about. Lots of groups create maps like this for modeling purposes. One for sea surface temperature is:
This is a blended product (i.e., multi-instrument, and gaps filled) with 1km resolution. There is also a 1km MODIS land surface temperature data product:
"Real-time" is the key. As far as we know, there isn't another real-time global data product that is this high resolution.
And while we actually use MODIS data as an input to our temperature correction model, it is, as you mentioned, land surface temperature, whereas our map represents near-surface air temperature (i.e., what you'd get in a normal weather report).
Just for the fun of it, for those of you in the bay area, here's a surface temperature forecast for today, 16:00 PST. It is from the forecast site that I've been maintaining for some time now - http://www.norcalsoaring.org/BLIP/BYRON/index.html
Most of China's 3million+ cities are on the east coast, the west is relative unpopulated. I was there in November and while the results of this map shouldn't have surprised me, considering the extreme city expansions I saw, I was still very surprised to see that half the country is at the same level as Saudi Arabia!
Having done a lot of real-time programming myself, it's really in the eye of the beholder. And there are snobs who think that nothing less than several kilohertz is real-time.
But historically, "real-time" means "not batch mode" - where batch jobs are executed whenever there are available resources, in an unpredictable manner.
Real-time is responding to real world input on some periodic schedule that is appropriate. In this case, one hour sounds fine for a world temperature map. Are you expecting to make minute-to-minute decisions based on the global temperature distribution?
Local temperature I'd expect to be updated faster, but really it's a matter of your use-case.
I wonder if they are aware of the super high resolution weather satellites that NOAA is putting up into orbit and will come on line, I believe, end of this year. I was talking to a high level NOAA official on the technical side and he was saying that it will essentially provide a remarkable, i.e., revolutionary increase in prediction accuracy and be able to provide on the ground climate level predictions.
