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Frost Prediction

Discussion and questions about Cumulus weather station software version 1. This section is the main place to get help with Cumulus 1 software developed by Steve Loft that ceased development in November 2014.
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nking
Posts: 813
Joined: Thu 17 Dec 2009 2:03 pm
Weather Station: W-8681
Operating System: Windows 10
Location: Hurstpierpoint, West Sussex, UK
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Re: Frost Prediction

Post by nking »

There is a difference, take a look at this link http://www.bbc.co.uk/weather/features/u ... rost.shtml or http://weatherfaqs.org.uk/node/26

When white crystals are seen on grass on a cold morning it is called a 'hoar frost'.
If the air temperature (measured at 1.25 m above ground) falls below freezing, it is called an 'air frost'.
If the ground temperature falls below freezing, it is called a 'ground frost'.
Wind speed does affect the severity of frost.

So it all comes down to the height you have your transmitter/temp. sensor at ;)
wd40
Posts: 448
Joined: Thu 05 Aug 2010 10:02 pm
Weather Station: WS2080
Operating System: W7
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Re: Frost Prediction

Post by wd40 »

One point I would like to make is the only advantage this frost prediction over your normal weather service frost prediction is taking into account your local sensor readings so the range of the frost forecast is limited to the area near your station.

This page is one of the better pages describing the difference in frost and is the source for the centigrade formula I provided earlier.

http://www.metservice.com/learning/frost

I tried this formula and it seems to perform better under low humidity conditions.

It would be good if several people could run these simple calculations after a frost to see how accurate they can be. If we can verify it usefulness or lack there off, it would verify if frost prediction is useful or not.

As Steve noted a forecast tool that is hit and miss could be detrimental to the confidence in Cumulus.

Randy

Randy
wd40
Posts: 448
Joined: Thu 05 Aug 2010 10:02 pm
Weather Station: WS2080
Operating System: W7
Location: GA, USA
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Re: Frost Prediction

Post by wd40 »

As I continue to dig into frost prediction, there are many methods and formula to give a real good guess. Each has been fine tuned by organizations in the local area where they are applied and each is predicated on the evening sensor reading the day before the frost event. It is this fine tuning that may make a Cumulus frost forecast less appealing.

Most often it is some sort of agricultural product like grapes or peaches that pushes researchers to improve frost forecast.

However our stations offer us the ability to calculate a micro forecast that can account for local deviations from the national of regional forecast.

One interesting observation I have made is how close the Apparent Temperature may track a frost event. I say may because I only noticed it on the graph from the last frost. Here is a local calculator to predict frost that uses a similar approach to the Apparent Temperature formula listed below.

http://fawn.ifas.ufl.edu/tools/minimum_temperature/


From: Norms of apparent temperature in Australia, Aust. Met. Mag., 1994, Vol 43, 1-16

About the formula for the apparent temperature
The formula for the AT used by the Bureau of Meteorology is an approximations of the value provided by a mathematical model of heat balance in the human body. It can include the effects of temperature, humidity, wind-speed and radiation. Two forms are given, one including radiation and one without. On this site we use the non-radiation version.

Version including the effects of temperature, humidity, and wind:
AT = Ta + 0.33×e − 0.70×ws − 4.00

Version including the effects of temperature, humidity, wind, and radiation:
AT = Ta + 0.348×e − 0.70×ws + 0.70×Q/(ws + 10) − 4.25
where:
Ta
= Dry bulb temperature (°C)
e
= Water vapour pressure (hPa) [humidity]
ws
= Wind speed (m/s) at an elevation of 10 meters
Q
= Net radiation absorbed per unit area of body surface (w/m2)

The vapour pressure can be calculated from the temperature and relative humidity using the equation:
e = rh / 100 × 6.105 × exp ( 17.27 × Ta / ( 237.7 + Ta ) )
where:
rh
= Relative Humidity [%]
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