<p>If we could have some 3d data of clouds (shape, water concentration, temperature) linked with the data on land (luminosity, rain level, wind...), could we train a machine learning model that could better predict local weather ? And could we use this data to better understand the inner working of clouds in order to predict better the weather ?</p>
<h2>Technical part</h2>
<p>In order to capture the 3d shape of clouds, we could use some stereoscopic videos of the sky with for example 3 cameras on land taking videos of the sky, and some satellite data of the sky from above. Them, we could use the the paper of <a href="https://guanjunwu.github.io/4dgs/" rel="nofollow noreferrer">&quot;4D Gaussian Splatting&quot;</a> in order to recreate the 3d cloud.</p>
<p>We could then have two machine learning model. The first one could learn to predict the evolution of the 3D shape of the cloud in the future. The second Machine learning model could learn the relation between the cloud shape and the land weather.</p>
<p>Thus we could have a local weather predictor. (With better local accuracy ideally)</p>

CC BY-SA 4.0
2024-12-10T21:51:12.540Z
3d-scanning of clouds is done via (rain) radar, both stationary as well as required to be installed in commercial airliners. I believe most weather apps do have this kind of forecast for the next few hours based on the cloud and wind information in the last ~60 minutes or so.
planetmaker
CC BY-SA 4.0
2024-12-14T02:39:07.607Z
@planetmaker Note that radar doesn't scan at power return resolution great enough for clouds (as far as I know), but only larger droplet sizes -> precipitation.  And it's not showing you where the cloud is, but at what levels there's precipitation falling (so you can only use vertical differences as a hint of what levels have precipitation particles are higher in the layer above... and even then you can have significant evaporation/condensation "clouding" results).  It generally won't, for example, show you the bottom of the cloud, because precipitation continues to fall.
JeopardyTempest
CC BY-SA 4.0
2024-12-14T02:41:45.663Z
And as far as I know, there's no typical radar that resolves clouds that don't have droplets of precipitation size [generally mm in size], which tends to eliminate the use the asker seems to be asking about.
JeopardyTempest
CC BY-SA 4.0
2024-12-14T02:54:54.623Z
But Arthur, I believe we already have some fair 3d data on clouds, firstmost from [satellites](https://eos.org/research-spotlights/using-multiple-satellites-gives-a-fuller-view-of-cloud-structure) (ok, they're technically radars planetmaker! though not the ones you're talking about used on airplanes/rain radars), plus lasers [cloud height indicators are installed on at least all ASOS in the US, not sure about wider usage, though the one shortfall is it's only location-point vertical structure observations]... so that probably negates the need for stereoscoping...
JeopardyTempest
CC BY-SA 4.0
2024-12-14T03:00:37.613Z
...and such data generally should already be ingested into weather models. Now could AI use just that data and prove worthwhile, an interesting question. Though often storms and clouds and such will develop from no cloud to clouds in minutes to hours, so I doubt cloud data would be great in prediction itself. The vertical temperature structure [and to some degree moisture structure] of the atmosphere is much more important, as it's the instability that dictates cloud formation [add in wind and you have the other key ingredient of forcing mechanisms, and the missing factor to movement]
JeopardyTempest
<clouds><data-analysis><machine-learning>
Could scanning clouds help us predict local wheather and the physics of the sky?
Arthur Delannoy
# Could scanning clouds help us predict local wheather and the physics of the sky?

(Asked by: username_0 on 2024-12-10)

If we could have some 3d data of clouds (shape, water concentration, temperature) linked with the data on land (luminosity, rain level, wind...), could we train a machine learning model that could better predict local weather ? And could we use this data to better understand the inner working of clouds in order to predict better the weather ?

## Technical part

In order to capture the 3d shape of clouds, we could use some stereoscopic videos of the sky with for example 3 cameras on land taking videos of the sky, and some satellite data of the sky from above. Them, we could use the the paper of ["4D Gaussian Splatting"](https://guanjunwu.github.io/4dgs/) in order to recreate the 3d cloud.

We could then have two machine learning model. The first one could learn to predict the evolution of the 3D shape of the cloud in the future. The second Machine learning model could learn the relation between the cloud shape and the land weather.

Thus we could have a local weather predictor. (With better local accuracy ideally)

**Tags:** clouds, data-analysis, machine-learning

> **Comments:**
> **username_1**: 3d-scanning of clouds is done via (rain) radar, both stationary as well as required to be installed in commercial airliners. I believe most weather apps do have this kind of forecast for the next few hours based on the cloud and wind information in the last ~60 minutes or so.  
> **username_2**: @username_1 Note that radar doesn't scan at power return resolution great enough for clouds (as far as I know), but only larger droplet sizes -> precipitation.  And it's not showing you where the cloud is, but at what levels there's precipitation falling (so you can only use vertical differences as a hint of what levels have precipitation particles are higher in the layer above... and even then you can have significant evaporation/condensation "clouding" results).  It generally won't, for example, show you the bottom of the cloud, because precipitation continues to fall.  
> **username_2**: And as far as I know, there's no typical radar that resolves clouds that don't have droplets of precipitation size [generally mm in size], which tends to eliminate the use the asker seems to be asking about.  
> **username_2**: But username_0, I believe we already have some fair 3d data on clouds, firstmost from [satellites](https://eos.org/research-spotlights/using-multiple-satellites-gives-a-fuller-view-of-cloud-structure) (ok, they're technically radars username_1! though not the ones you're talking about used on airplanes/rain radars), plus lasers [cloud height indicators are installed on at least all ASOS in the US, not sure about wider usage, though the one shortfall is it's only location-point vertical structure observations]... so that probably negates the need for stereoscoping...  
> **username_2**: ...and such data generally should already be ingested into weather models. Now could AI use just that data and prove worthwhile, an interesting question. Though often storms and clouds and such will develop from no cloud to clouds in minutes to hours, so I doubt cloud data would be great in prediction itself. The vertical temperature structure [and to some degree moisture structure] of the atmosphere is much more important, as it's the instability that dictates cloud formation [add in wind and you have the other key ingredient of forcing mechanisms, and the missing factor to movement]  

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## 0 answers

