Re: another online prediction tool


What is it doing when you tell it to run more than 1 prediction? or 50 or 400?

The Original Rolling Ball Clock
Idle Tyme

On 3/28/2017 9:40 AM, 'L. Paul Verhage' nearsys@... [GPSL] wrote:

So I wonder if we could create a good landing zone prediction by varying the ascent rate and burst altitudes by plus or minus some percent. Say 10%. Then use a combination of these variations to map out a recovery ellipse (I assume it would an ellipse shape with the major axis aligned along the overall flight path).

On Mar 28, 2017 8:35 AM, "Jerry Gable jerrygable@... <mailto:jerrygable@...> [GPSL]" <GPSL-noreply@... <mailto:GPSL-noreply@...>> wrote:

[Attachment(s) <#m_-4471659708677056433_TopText> from Jerry Gable
included below]

To me it looks like their tool takes in variances in the weather
data but my experience has been human caused variances such as
fill and burst altitude.

Here is my correlation from GPSL last year. After the flights I
ran a prediction with the actual ascent, decent, and burst. I
used the preflight weather data and they all came out pretty close.


Image via Dropbox


Jerry Gable
Balloon Flight Prediction tools <>

*From:* "Mark Conner mconner1@...
<mailto:mconner1@...> [GPSL]" <GPSL-noreply@...
*Cc:* GPSL list <GPSL@... <mailto:GPSL@...>>
*Sent:* Monday, March 27, 2017 1:29 PM
*Subject:* Re: [GPSL] another online prediction tool

Not only are U and V covariant with each other to some degree, but
there is covariance with height. Each wind level is not
independent of the levels adjacent to it - in fact they are highly
correlated. If you have winds at 180/25 at 250 mb, they will be
very close to that value at 240 and 260 mb.

Below is a heat map for my planned Saturday launch. I think it
underestimates the left/right uncertainty in the track, and
probably the distance as well. It certainly underestimates the
overall uncertainty in using a 120-hour forecast versus, say, a
24-hour forecast.

Don't get me wrong, doing a Monte Carlo approach is a good way to
get a peek at uncertainty. But I'm not sure if this is a full
measure of the overall uncertainty in the landing site prediction.

73 de Mark N9XTN

Inline image 1

On Mon, Mar 27, 2017 at 11:40 AM, Mark Conner <mconner1@...
<mailto:mconner1@...>> wrote:

The model treats it as U and V. The model is on a Cartesian
grid but "knows" it's on a sphere (the physics account for that).

It's more a statistical exercise in the wind errors. Is it
better to treat U and V errors independently, or is there
covariance? Does that covariance change as the vector
magnitudes change? Winds aren't truly random, so Gaussian
statistics may not apply.

So is it better to assume that U has a standard deviation of n
m/sec and V has a SD of y m/sec, or is it better to assume
that direction has a standard deviation of q degrees and speed
a SD or r m/sec? The "r" part would not be Gaussian because
it could not be negative, so some other distribution would
have to be assumed.

Something I'd like to explore in the literature more. Someday.

- Mark

On Mon, Mar 27, 2017 at 11:17 AM, 'L. Paul Verhage'
nearsys@... <mailto:nearsys@...> [GPSL]
<mailto:GPSL-noreply@...>> wrote:

Interesting, they describe the transition at Hank's Knee
as the Drag Crisis Band. The paper looks very interesting
in my brief and cursory look. It appears the Reynold's
Number of the balloon makes a gradual descrease during the
entire ascent.
Mark's comment makes me wonder now how the GFS model
generates wind profiles. Is it in the north-south
direction and the east-west direction or does it generate
speed and direction directly. I guess this could be
referred to as generating wind profiles in Cartesian or
Polar coordinates. As we will recall from high school,
each can be converted into the other. But which is easier
to compute for supercomputers generating the GFS model
(enquiring minds want to know)?
Still, all kidding aside, the paper and the questions it
brings to mind are interesting. I'll find some time to
read it in more detail. For example, I'd like to learn
what percentage of variation it puts into the data for
each prediction.
On Mar 27, 2017 10:03 AM, "Mark Conner mconner1@...
<mailto:mconner1@...> [GPSL]"
<mailto:GPSL-noreply@...>> wrote:

The full paper describing the methodology is here:

The Reynolds number transition, mentioned in an EOSS
presentation at GPSL several years ago, is modeled
here. For others with balloon flight forecasting
tools, there are some concepts here that could be

The treatment of wind uncertainty is interesting. Most
models, including this one, treat the uncertainty
independently in the u (east/west) and v (north/south)
vector components. I've always thought, without
anything to really back it up, that uncertainties
should be handled in direction and speed space and
then taken back to u/v for computations. But I don't
know if that will produce numerically different
results in the end.

73 de Mark N9XTN

On Sun, Mar 26, 2017 at 4:43 PM, 'L. Paul Verhage'
nearsys@... <mailto:nearsys@...> [GPSL]
<mailto:GPSL-noreply@...>> wrote:

This is much quicker than running several
predictions with various input parameters. I think
this form of modeling a landing zone can be called
the Monte Carlo method.
On Mar 26, 2017 10:42 AM, "Mark Conner
mconner1@... <mailto:mconner1@...>
[GPSL]" <GPSL-noreply@...
<mailto:GPSL-noreply@...>> wrote: uk/

This one is interesting in that it will run
numerous predictions with variations in the
launch parameters and return a heat map
showing the likely landing zone. I did one for
our NSTAR 17-A launch from Lincoln scheduled
for next Saturday.

Inline image 1

Around 50 simulations seems to be enough to
generate a reasonable map. I tried 50 and 150
for this flight and the heat map did not
change very much.

73 de Mark N9XTN

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