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Supercomputer quietly puts U.S. weather resources back on top

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Re: Supercomputer quietly puts U.S. weather resources back on top

#61

Post by khm »

matt2000 wrote: post #2

Is there anyone here who works on weather models who would be able to explain why custom supercomputers are still needed vs. large commodity clusters? Thanks!

There is no such thing as a 'large commodity cluster.' You can order a pile of commodity parts and spend the next five years fiddling with it as you watch your metrics fall into the toilet, or you can contract with a systems integrator with domain experience to make sure that you can actually accomplish the work you set out to do. When you're moving an established set of software from a known environment into a new cluster, it helps to have a wide array of technical experts and SLAs in place to ensure that the environment -- here meaning the physical compute infrastructure, storage service, and software installation -- is reliable and maintainable, so that your team can focus on their core mission -- in this case, the modeling software.

"Chaos monkey" works fine when you're dealing with random cloudstuff and you are in a position to duck-punch your production code. When you have a large dataset that you need to process reliably and predictably, the mantra shifts to "fail never", and that requires engineering up front in combination with carefully-planned maintenance.

Full disclosure: I've worked on this specific supercomputer. While I'm not on the admin team in question, I do work with them occasionally and I have a lot of respect for them -- their job is not an easy one.

Re: Supercomputer quietly puts U.S. weather resources back on top

#62

Post by mrow84 »

Sniffnoy wrote: post #32

I'm bothered by how the article says "three years ago European models delivered a blow to the U.S. weather apparatus". Better models by Europeans do not make the models by Americans any worse. Improved models help everyone.

You are correct, and I don't think there is much more of a collaborative than a competitive spirit between the various organisations. However, it is not only the model that is important in weather forecasting, but also the data assimilation system. This is an active area of research with a lot of "art" involved, or, perhaps more realistically, very educated guesswork, about how best to set up and tune any given system. ECMWF have been developing their 4D-VAR system in the atmosphere for quite a long time now, and it is very successful. I think the Americans might be using an ensemble Kalman filter, which has a whole range of tuning issues, so that will probably take them a while to get right. There is an interesting paper that interprets the effects of these two systems that I still don't fully comprehend [0]. The Met Office also uses a 4D-VAR system, but I'm not really clear on the key differences between it an the ECMWF system.

Another important topic is coupling ocean and atmosphere models, and how you handle the data assimilation across your coupling - again, this is an active area of research, with lots of subtlety.

Of course, the model dynamics and physics are also very important, as is the resolution. This last issue is one of the places where bigger computers have really direct benefits, the other being increasing the size of an ensemble.

It's also important to realise that the various systems tend to be better suited to certain things, so whilst the ECMWF system is better in key global metrics, it doesn't (on average) provide better forecasts of all quantities in all situations.

[0] http://onlinelibrary.wiley.com/doi/10.1034/j.1600-0870.2001....

Re: Supercomputer quietly puts U.S. weather resources back on top

#63

Post by mrow84 »

nether wrote: post #47
oh_sigh wrote: post #39

Earlier quoted context omitted.

No one in the foreseeable future is going to use cellphones as parallel processors. First of all, the communication latencies are way too large to coordinate anything usefully. Second of all, users are already upset about the lack of battery life available for their phones.

It's not exactly parallel processing, but the Dark Sky app already does its forecasting calculations on the iPhone: http://jackadam.github.io/2011/how-dark-sky-works/ > The reason we encode velocity data as an image is so we can pass it off to the GPU on the iPhone and iPad. Both the storm prediction and the smooth animations are calculated on the device itself, rather than the server, and all the magic happens direc…

In case anyone starts wondering, in the article it says that they're assuming that atmospheric motion is linear, which they justify (reasonably) because they're only looking over short time scales. So, although it is a forecast, it's a pretty simple one ;-).

Re: Supercomputer quietly puts U.S. weather resources back on top

#65

Post by barney54 »

akie wrote: post #49
Sniffnoy wrote: post #32

I'm bothered by how the article says "three years ago European models delivered a blow to the U.S. weather apparatus". Better models by Europeans do not make the models by Americans any worse. Improved models help everyone.

I talked to a (very) senior scientist at the World Meteorological Organization not too long ago. He was of the opinion that the U.S. weather models were about 5 to 10 years behind on the European models, and that this was caused by structural underfunding over longer periods of time (i.e. past decades). As I understood it these weather models are basically humongous software programs that are developed in house, but…

He is correct. The European model still outperforms the US (GFS) model: https://twitter.com/RyanMaue/status/700216724067586049

Re: Supercomputer quietly puts U.S. weather resources back on top

#66

Post by mrow84 »

avar wrote: post #53
nradov wrote: post #25

Earlier quoted context omitted.

Smart phones are good at collecting live barometric pressure data but not much else. Temperature sensors aren't very useful because they are poorly calibrated, you can't reliably tell whether someone is outdoors, and the reading can be thrown off by the heat generated by the device or the person holding it. UV sensors are seldom pointed in the right direction. And I haven't seen a phone with a wind speed or precipita…

I genuinely don't mean to sound passive aggressive when I ask, do you know anything about this subject or are you just guessing? I don't know anything about it, but I can think of numerous ways to mitigate the issues you mention. E.g.: * Does it actually matter that the absolute value of temperature sensors is inaccurate, or is it enough that they have good relative accuracy (do they?) * Do you really need to tell if…

I also know nothing about the limitations of the temperature sensors on smartphones (I don't even know of any phones that have temperature sensors).

What I do know is that whilst teasing signals out of noisy data is achievable when the data are unbiased, the possibility of biases makes it significantly harder, especially when you don't know what the biases might be. This can be a significant problem with all sorts of data that you might think were fairly good, including both in-situ and satellite measurements.

Re: Supercomputer quietly puts U.S. weather resources back on top

#67

Post by NickNameNick »

avar wrote: post #53
nradov wrote: post #25

Earlier quoted context omitted.

Smart phones are good at collecting live barometric pressure data but not much else. Temperature sensors aren't very useful because they are poorly calibrated, you can't reliably tell whether someone is outdoors, and the reading can be thrown off by the heat generated by the device or the person holding it. UV sensors are seldom pointed in the right direction. And I haven't seen a phone with a wind speed or precipita…

I genuinely don't mean to sound passive aggressive when I ask, do you know anything about this subject or are you just guessing? I don't know anything about it, but I can think of numerous ways to mitigate the issues you mention. E.g.: * Does it actually matter that the absolute value of temperature sensors is inaccurate, or is it enough that they have good relative accuracy (do they?) * Do you really need to tell if…

I'm not sure how useful the usual techniques for normalising sensors would be for moving sensors.

Fixed weather stations have corrective mappings associated with them. For example the station at the airport might be assumed to be 1 degree warmer than the generalised temperature for your city. It might be known to collect 5% more rain when the wind is northerly, and 8% less for southerly. These mappings are very important, because they let you shut-down a weather station, and build a new one in a different location, and compare the data from the two.

if the weather stations aren't in consistent locations, with discoverable local behaviors, then converting the raw data into generalised data about the area is going to be very difficult.

Re: Supercomputer quietly puts U.S. weather resources back on top

#68

Post by mturmon »

akie wrote: post #49
Sniffnoy wrote: post #32

I'm bothered by how the article says "three years ago European models delivered a blow to the U.S. weather apparatus". Better models by Europeans do not make the models by Americans any worse. Improved models help everyone.

I talked to a (very) senior scientist at the World Meteorological Organization not too long ago. He was of the opinion that the U.S. weather models were about 5 to 10 years behind on the European models, and that this was caused by structural underfunding over longer periods of time (i.e. past decades). As I understood it these weather models are basically humongous software programs that are developed in house, but…

I believe this reflects the community consensus. Perhaps partly money, partly communication/coordination, partly technique. It's embarrassing, and comments nearby saying "we have something to learn" are too complacent. US predictions over CONUS should be at least on par with ECMWF predictions.

Re: Supercomputer quietly puts U.S. weather resources back on top

#69

Post by superpc »

paulmd wrote: post #7
matt2000 wrote: post #2

Is there anyone here who works on weather models who would be able to explain why custom supercomputers are still needed vs. large commodity clusters? Thanks!

Modern supercomputers essentially are large commodity clusters. Nobody builds a single fast machine ala Cray-1 anymore. It's just not scaleable past a certain point and we're long since past that. However, they still like to give them fancy names as marketing, because they cost tens of millions of dollars. The main differentiation vs a standard datacenter is low-latency high-throughput interconnects, often with a spe…

Does this count, just curious. It is a large single machine not cluster. https://www.sgi.com/pdfs/4555.pdf

Re: Supercomputer quietly puts U.S. weather resources back on top

#70

Post by knappe »

bannus wrote: post #60
knappe wrote: post #36

Earlier quoted context omitted.

I was in the south Everglades last week. We went over a pass that was _1_ ft tall. Coming from Colorado, the sign advertising the "pass" was just bizarre.

For the similarly curious -- I assume this is referring to Rock Reef Pass: http://www.jessstryker.com/national-parks/everglades/rock-re...

That's it! Thanks, the picture was on my gf's phone and I couldn't reference it.
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