Calculating BC with LabRadar. It works!

ptosis

Member
Joined
Nov 24, 2020
Messages
23
Location
.ch
Just like you can take absolute pressure and change it to sea level, if you have the sea level pressure, and know the altitude you're at, you can change that to absolute pressure. So none of the atmos data you got was useless. Just do the math and correct it to what you need.

Like the 1011 hPa at 800m would be 918 hPa absolute.
Formula - Station pressure * ((1 - 2.25577*10^-5)*(height))^5.25588
Pressure in Pascals, height in meters.
Yep.

Indeed, knowing QNH and alt., it is possible to calculate QFE.

For the sake of completeness, there are several, more or less erroneous, pressure reduction formulae (cf. https://www.wmo.int/pages/prog/www/IMOP/meetings/SI/ET-Stand-1/Doc-10_Pressure-red.pdf), but for shooting applications the error is typically negligible (most of the time, pocket barometers just interpolate QNH from standard atmosphere tables).

In practice, however, if I don't have a barometer at hand, I just pull the QFF (where real conditions on site are used for the correction rather than ISO standard conditions) from the nearest Meteosuisse station, take the difference as compared to the standard 1013.25, and apply the same difference to the standard pressure for the altitude I am at. When compared to Kestrel station pressure readings, the difference is within 2 Hpa (and I am not even sure which one is more precise), so for all practical purposes this works just fine.

The biggest source of errors when converting QNH to QFE is altitude. Altitude should be taken at the shooting station (using GPS or a detailed map). As practice shows when walking (or driving) up and down the mountain slopes, pressure-based altimeters can drift away pretty significantly.
 

akmtnhnt

Well-Known Member
Joined
Nov 21, 2021
Messages
53
Location
Anchorage, AK
Yep.

Indeed, knowing QNH and alt., it is possible to calculate QFE.

For the sake of completeness, there are several, more or less erroneous, pressure reduction formulae (cf. https://www.wmo.int/pages/prog/www/IMOP/meetings/SI/ET-Stand-1/Doc-10_Pressure-red.pdf), but for shooting applications the error is typically negligible (most of the time, pocket barometers just interpolate QNH from standard atmosphere tables).

In practice, however, if I don't have a barometer at hand, I just pull the QFF (where real conditions on site are used for the correction rather than ISO standard conditions) from the nearest Meteosuisse station, take the difference as compared to the standard 1013.25, and apply the same difference to the standard pressure for the altitude I am at. When compared to Kestrel station pressure readings, the difference is within 2 Hpa (and I am not even sure which one is more precise), so for all practical purposes this works just fine.

The biggest source of errors when converting QNH to QFE is altitude. Altitude should be taken at the shooting station (using GPS or a detailed map). As practice shows when walking (or driving) up and down the mountain slopes, pressure-based altimeters can drift away pretty significantly.
If you need to get that precise and you're using a pressure sensing altimeter, don't forget to correct for temperature and height above the station you got the QNH from as well, assuming it's not 15C minus the lapse rate where you are(standard).
If it's super hot or cold that could be worth up to 300-400m or so in the Density altitude that you're calculating.
 

ssgross

New Member
Joined
Jan 6, 2022
Messages
1
Location
Virginia
I assumed as much too, and strangely, for some of the downrange calculated velocities (i.e. at the distances you set in the software), this is the case, but the V0 velocity is often way off the line for some reason.
I stumbled upon this playing data from my labradar, thought I would give my 2 cents. The reason why you and others get different results is that you are doing a simple linear regression. You need to do a weighted linear regression, with weights computed from the signal to noise ratio (SNR). I can get within +- 1fps across all distances after a weighted regression combined with maybe tossing out some points with super small SNR.
 
Top