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Better 'Nowcasting' Can Reveal What Weather is About To Hit Within 500 Meters (technologyreview.com)
Weather forecasting is impressively accurate given how changeable and chaotic Earth's climate can be. It's not unusual to get 10-day forecasts with a reasonable level of accuracy. But there is still much to be done. One challenge for meteorologists is to improve their "nowcasting," the ability to forecast weather in the next six hours or so at a spatial resolution of a square kilometer or less.
From a report: In areas where the weather can change rapidly, that is difficult. And there is much at stake. Agricultural activity is increasingly dependent on nowcasting, and the safety of many sporting events depends on it too. Then there is the risk that sudden rainfall could lead to flash flooding, a growing problem in many areas because of climate change and urbanization. That has implications for infrastructure, such as sewage management, and for safety, since this kind of flooding can kill. So meteorologists would dearly love to have a better way to make their nowcasts. Enter Blandine Bianchi from EPFL in Lausanne, Switzerland, and a few colleagues, who have developed a method for combining meteorological data from several sources to produce nowcasts with improved accuracy.
Their work has the potential to change the utility of this kind of forecasting for everyone from farmers and gardeners to emergency services and sewage engineers. Current forecasting is limited by the data and the scale on which it is gathered and processed. For example, satellite data has a spatial resolution of 50 to 100 km and allows the tracking and forecasting of large cloud cells over a time scale of six to nine hours. By contrast, radar data is updated every five minutes, with a spatial resolution of about a kilometer, and leads to predictions on the time scale of one to three hours. Another source of data is the microwave links used by telecommunications companies, which are degraded by rainfall.
Their work has the potential to change the utility of this kind of forecasting for everyone from farmers and gardeners to emergency services and sewage engineers. Current forecasting is limited by the data and the scale on which it is gathered and processed. For example, satellite data has a spatial resolution of 50 to 100 km and allows the tracking and forecasting of large cloud cells over a time scale of six to nine hours. By contrast, radar data is updated every five minutes, with a spatial resolution of about a kilometer, and leads to predictions on the time scale of one to three hours. Another source of data is the microwave links used by telecommunications companies, which are degraded by rainfall.
I have this already. I call it a "window".
It is completely unusual to get a ten-day forecast with any level of accuracy.
I live on the edge of a small town with farms around. It seems like we've often had in the past couple years a lot of months where we got the northern edge of one storm, the southern edge of the next and end up without much rain overall compared to everyone around us. As a result the farmers have to start getting out the huge sprinklers for their crops, and the next day a storm hits us head on while the farmers are sprinkling. Seems like it could save a lot of gallons of irrigation, or alternately crop damage knowing if weather than day is actually going to rain here or miss again.
"It's not unusual to get 10-day forecasts with a reasonable level of accuracy"
A UK 10-day forecast consists of the words "The sun is likely to come up; you may or may not be able to see it."
5-day forecasts are generally little better than flipping a coin to see whether it will rain or not. 3-day isn't too bad and 1-day forecasts are reasonably good for much of the summer and winter; in spring and autumn they're pretty rough.
None of which prevents the Met Office from showing weather maps with a ludicrous level of precision completely unmatched by their accuracy.
"Encyclopedia" is to "Wikipedia" what "Library" is to "Some people at a bus stop"
This story is nonsense. I'm a meteorologist and I do severe storms research. There are a number of factual errors present, even in the summary. Nowcasting is a short term forecast, generally in the 0-6 hour time frame. That's one of the few things this story got right.
Forecasters rely heavily on numerical models to make predictions. On a regional scale, these models numerically integrate a number of partial differential equations forward on a 3D grid. Many of these models are different configurations of the Weather Research & Forecasting (WRF) model. WRF can be run across many cores with shared memory (OpenMP) or distributed memory (MPI). Domains with very large numbers of grid points can be run across thousands of cores. If the spatial size of the domain size remains the same, adding grid points means decreasing the space between each grid point. Not only does this increase the processing requirements because of more grid points, but also the time step of the numerical integration generally has to decrease. High resolution domains require very large amounts of computing resources in order to produce a forecast in a reasonable amount of time.
The highest resolution model that's regularly run operationally in the US is the High Resolution Rapid Refresh (HRRR) model, and is a specific configuration of WRF. The HRRR is run hourly and has a horizontal grid spacing of 3 km. This is well above the supposed precision of 500 meters. Furthermore, even if the HRRR was run at 500 m, it doesn't mean the forecast would be accurate on such small spatial scales. The big difference between the 3 km HRRR and coarser resolution models like the 13 km RAP (also, WRF-based) is that the HRRR doesn't parameterize convection. That means it runs at a high enough resolution that it can directly simulate phenomena like thunderstorms.
The resolution of radar data in the US is about 500 m, and has been for roughly the past decade. The best weather satellite right now is GOES-16, with a resolution of 500 m-2 km, depending on the type of product. That's a huge difference from what's described in the summary. Forecasts that rely on extrapolating radar and satellite data might be accurate for 30 minutes or perhaps even an hour or two. Beyond that, numerical models are going to produce better forecasts.
The radar and satellite data, along with a lot of other data sources, are assimilated into models like the RAP and HRRR. Assimilation basically means updating the state of the 3D domain based on the new observations. Data assimilation of conventional observations like winds, temperature, pressure, and humidity generally produces good results. However, assimilating radar and satellite data isn't as simple.
Reflectivity and radial velocity are generally assimilated from radar data. Radial velocity is generally assimilated in areas where there isn't precipitation, and is a lot like assimilating wind data. Reflectivity is the amount of power that's scattered back to the radar, and is generally larger if there's heavier precipitation. It's not nearly so simple to assimilate reflectivity because you also need to update variables like temperature, wind, humidity, and pressure in the 3D domain, even though the radar isn't directly measuring them. Those variables are going to be quite a bit different inside a thunderstorm than they are outside it. If you want to update the position and strength of thunderstorms in a model, you need to update quite a few variables in the model that you probably aren't measuring at all in those areas. If you want accurate forecasts of thunderstorms, you need to update the model based on radar reflectivity data.
There are techniques like the Ensemble Kalman Filter (EnKF) that update unobserved variables based on measurements of variables that are observed. However, even with the best EnKF techniques at present, assimilating reflectivity data often doesn't really improve the forecast beyond an hour or two. Perhaps more observations and better techniques will im
resolution of around 4 km. But after 40 minutes or so, any forecasting ability is lost, say Bianchi and co. And with a greater resolution of around 1 km, the forecasting ability drops to less than 15 minutes.
One way to improve these forecasts is to correlate the radar images with rainfall measurements on the ground.
When this assumption is correct, Bianchi and co say, their nowcasts produce accurate forecasts more than 20 minutes into the future at a scale of as little as 500 meters. That’s impressive.
But the assumption of Lagrangian persistence isn’t always true. Sometimes the atmosphere undergoes unexpected changes—sudden heating events that cause convection cells, for example. And when this happens, the accuracy of the forecasts drops dramatically. “In the case of convective events, the performance of the nowcast algorithm decreases rapidly after 15 min
Improving to 6 hours as described in the summary and in the article seems pretty unlikely. At least, in scientific/practical terms and by taking as reference what appears to be the current state of the art as defined by the quotes above. For the marketer/MBA-holder/you-do-the-science-&-I-do-the-thinking-who-will-probably-not-get-this-joke considering that saying 6 hours was the best way to improve their chances to get the next round of funding, it is certainly possible (because what is the difference between 15 mins. and 6 hours? It is just a matter of time! Scale it up! Move to quantum mode! Put more scientific thingies in!). LOL.
Custom Solvers 2.0 = Alvaro Carballo Garcia = varocarbas.
For this reason, God sends them a powerful delusion(operation of wandering)(planet) so that they will believe the lie.
What is Winter Sunlight?
Is there a Winter Moonlight?
"Weather forecasting is impressively accurate given how changeable and chaotic Earth's climate can be."
There's a reason for that. It's because WEATHER AND CLIMATE ARE NOT THE SAME THING.
Just because your models predict weather well does not mean they can predict climate well, and indeed not a single climate model can account for the historical record without throwing out or even falsifying MASSIVE amounts of data.
This whole climate fraud needs to stop.
I've been impressed with the amount of information you get during a Tornado, especially the big ones. Of course, you have spotters on the ground and air along with a very clear radar signature ( when there is a debris ball involved ). They can forecast down to the city/block level at almost sub-minute resolution. Go and watch youtube videos of the Moore OK tornado and the coordination between everyone involved ( spotters, meteorologists, TV/Radio ) was pretty impressive given the circumstances.
I came to the datacenter drunk with a fake ID, don't you want to be just like me?
Winter sunlight is incident sunlight during meteorological winter (December 1 through February 28 or 29, as meteorological seasons lead solstices and equinoxes by 3 weeks). Some key characteristics of winter sunlight:
1. Noontime angle of incidence is farthest from overhead.
2. Daily duration of sunlight is shortest.
3. Snow albedo: Accumulated snow reflects much of the light rather than allowing the ground to absorb it.
I don't subscribe to MIT Technology Review. But more accurate hourly forecasts are useful to pedestrians and cyclists, as they can make a trip earlier or later to avoid hazardous weather.
Headline: This thing is true now
Body: People have some ideas and are hoping to eventually get to where this thing is true
#DeleteChrome
Indeed. That's why they don't even bother with 11 days or 12 days. By the time you get 10 days out, you're mostly looking at the average for this time of year. Current conditions, existing weather patterns, don't tell you much about 10 days from now.
Seven days out you can say "there is a higher than average chance of rain" or "it may be warmer than normal".
There was a company in Chico, CA (the area that is burning right now) that was doing this in 1980. They could even send weather maps to Apple ][e computers over a 300 baud modem. Oddly enough the name of the company was "Nowcasting".
I have a link to the local radar feed on my phone. It shows a three hour color coded animation with updates every ten minutes. I can guess with excellent accuracy how long till a storm system will hit where I am, you can usually see it coming hours away, how hard it is raining or snowing, if there is hail or it is likely, how long it will take to pass over, or if it is going to be a long term thing, etc. It is not 100 percent, sometimes a storm will veer off or break up at the last minute, occasionally they will form seemingly out of nowhere, but I would say I can tell with about 90 percent accuracy the state of precipitation where I am an hour or two from now. That combined with the daily forecast for temperature and wind is all I need to feel pretty comfortable when I am out biking, boating, golfing, etc.
Here's a challenge for you armchair scientists: Make a weather prediction every day, just before the news channel produces their forecast. Write it down. Write the official forecast down, then check up who is right how often.
It makes up what it wants the summary to say, then claims what they made up is wrong, but blames the summary writer for it.
Why should that be modded up?
You presume that because that is what you WANT to be true. It isn't. Instead of assuming, go fucking test. It requires work and ill show you you are wrong, neither of which you want to accept so will not put the effort in to.
I apologise you did not find anything better to try. Give it another go. Maybe the neurons will spark next time.