pwsFWI is now a bit more than a year old and has proven its value : it relates very well to the existing indices and the EFFIS Current Situation viewer. This means that the note : Behavioural testing still under way! will be removed from the pwsFWI page at the end of the European fire season (21 September).
Having said that, I have noticed that some users have reverted to the FWI calculations and graphs as shown by FWIcalc as if that one is better than pwsFWI.
In my previous blog I described why and how the predictions on pwsFWI were implemented. Also I promised a short analysis:
We’re now in version 1.8.3 and it seems all to be working OK. The testing is back on the meteorological level, trying to find out how much a two day ahead prediction will differ from the actual calculation when the day has past.
In this blog I will show the results and try to interpret them.
Please note that this is not a scientific or even a full analysis as I am lacking the resources and the data for that.
One of the goals of the current implementation of pwsFWI is to see its behaviour under all conditions. It is therefore very interesting to see that behaviour in the two stations in semi-arid zones (in Australia and in Spain) where long dry periods may suddenly alternate with rain after which the drought returns. Continue reading
Now that version 0.9.0 of my Fire Weather Index for personal weather stations (pwsFWI) has been released in the context of CumulusUtils (I may separate it later into an independent program), it is time to look at formula corrections.
In An effort for a Simpler Fire Weather Index I described my new FWI and the theory behind it. In short, this pwsFWI (as I have baptised it) is meant to be a generic FWI, valid everywhere and independent of geology and vegetation.
The pwsFWI is a (not too) complex measure of local meteorology, an indicator composed of humidity, wind speed and temperature. It fluctuates under ‘normal’ conditions and if it becomes dryer (a longer period without rain, the number becomes higher. As soon as it starts raining, the value starts dropping.
In this blog I will propose a fire weather index for PWSs. The goal is to get fuel parameters out of the equation. This means that species, litter type or geography, will not play a role as they do in the Canadian FWI. As such, it connects with a recent new development described by Goodrick et.al. 2 .
I will describe the Canadian FWI as it appears in (scientific) literature. The basic reason for describing this complex fire-weather index is, that it is heavily used in some big countries, notably Canada, France, Australia and New Zealand and that the description of the method of calculation is not readily available.
The FWI also has been introduced in 2007 [1] as the method to assess the fire danger level in a harmonized way throughout Europe.
Some extensive studies have been made, to measure its performance and its relevance. FWI also contains most parameters relevant to estimating the danger level of the weather in relation to nature fires. In short: the FWI is an important tool for estimating and studying fire weather and fire spreading, with a huge knowledge base spanning almost 100 years. Continue reading
Please note, that this blog is one in a series culmination in an argument for a new Fire Weather Index for Personal Weather Stations developed by me. The articles in this blog often are not standalone but related. To appreciate this please check out the tags FWI or pwsFWI (more specific).
The Ångström index and the FMI index are highly similar indices in understanding, functioning and behaviour using only two meteorological parameters: temperature and humidity.
These indices are interesting because they are historically important, they are still in use and because, in discussing these indices, they shed some light on the understanding of the what and how of trying to understand estimating fire weather danger. Continue reading
One of the practical applications of meteorology is the objectivation of nature fire risks on the basis of different meteorological parameters (actual or from the past). Rainfall, humidity, temperature and windspeed are typically parameters to calculate a number indicating the risk on nature fire.