Classification of wind events
Sorry, please put my last post aside. I mis-read your question. I agree with Jim's comments.
On Sun, May 17, 2020 at 9:52 PM Abby Spurdle <spurdle.a at gmail.com> wrote:
Hi Stefano, I don't have any specific suggestions, but... If you could convert your (character) direction vector into a (numeric) time-ordered direction vector giving radians or degrees, and provide the corresponding speed vector... (i.e. North -> 90 degrees). I'd be happy to try and plot the data in a variety of ways... ...and see if there's any obvious relationships, or anything else useful. On Sat, May 16, 2020 at 10:23 PM Stefano Sofia <stefano.sofia at regione.marche.it> wrote:
Dear Jim and Jeff,
thank you for your comments. You are right, it is quite difficult to detect this process through a single observation point, I am awre of it.
I need to set up an automatic algorithm to filter 20 years of data, and I have to find an easy way to do it.
I know quite well my automatic stations, the wind direction is very stable during these situations, and therefore I would like to start from it. (I should use also wind speed, relative humidity and temperature, but I will introduce them only once I will be able to manage the direction).
In the case of the example below reported, I know that the directions of this particular automatic station must be only SW or WSW.
My biggest problem, obviously, is to find the beginning and the end of each event, when there is a change in the main direction.
Thinking about categorical data in general, is there a way to detect periods when one particular category is more frequent?
Here I reproduce a real example 24 hours long, where these Foehn condition start between 09 and 10 and finish after 19:
first_day_POSIX <- as.POSIXct("2020-02-19-00-00", format="%Y-%m-%d-%H-%M")
last_day_POSIX <- as.POSIXct("2020-02-20-00-00", format="%Y-%m-%d-%H-%M")
mydf <- data.frame(data_POSIX=seq(first_day_POSIX, last_day_POSIX, by="10 min"))
mydf$main_dir <- c(WSW, WSW, SW, SW, W, WSW, WSW, WSW, W, W, SW, WSW, SSW, S, SW, SW, WSW, WNW, W, WSW, WSW, SE, SE, SE, NW, NNE, ENE, SE, NNW, NW, NW, NW, NW, NW, NW, NE, NW, NW, NW, NW, NW, N, WNW, NW, NNW, NNW, NW, NW, NW, WNW, ESE, W, WSW, SW, SW, SW, WSW, SW, S, S, SSW, SW, WSW, WSW, WSW, WSW, WSW, WSW, WSW, SW, WSW, WSW, WSW, WSW, SW, SW, WSW, WSW, WSW, WSW, WSW, SW, SW, SW, SW, SW, SW, SW, SW, SW, WSW, WSW, WSW, WSW, SW, SW, SW, SW, WSW, SW, SW, SW, SW, SW, WSW, SW, SW, W, WSW, WSW, SSW, S, WNW, SW, W, WSW, WSW, SE, SE, SE, NW, NNE, ENE, SE, NNW, NW, NW, NW, NW, NW, NW, NE, NW, NW, NW, NW, NW, N, WNW, NW, NNW, NNW, NW, NW, NW)
mydf$max_speed <- c(4.60, 4.60, 3.40, 3.10, 4.80, 4.20, 4.10, 4.50, 4.70, 4.30, 2.40, 2.30, 2.20, 2.10, 2.90, 2.80, 1.80, 2.70, 4.30, 3.30, 2.30, 2.30, 3.20, 3.20, 2.90, 2.30, 1.50, 1.80, 2.90, 2.40, 1.80, 2.40, 2.30, 2.60, 1.80, 2.30, 1.90, 2.20, 2.80, 2.40, 1.00, 1.10, 1.60, 2.30, 2.50, 3.30, 3.40, 3.20, 4.50, 3.90, 3.10, 2.40, 6.00, 7.80, 6.30, 7.80, 8.10, 6.10, 7.40, 9.50, 8.90, 9.10, 10.10, 10.50, 11.10, 10.10, 10.90, 11.30, 13.40, 13.50, 12.80, 11.50, 13.10, 13.50, 11.10, 10.50, 8.50, 10.10, 10.70, 13.60, 11.90, 14.90, 10.90, 10.90, 12.80, 12.10, 9.10, 8.30, 8.80, 7.40, 8.40, 10.30, 10.00, 7.00, 8.50, 8.40, 8.60, 6.70, 7.30, 6.20, 5.90, 5.90, 5.10, 5.80, 5.60, 6.50, 6.60, 11.70, 11.30, 8.70, 7.10, 6.90, 4.30, 3.80, 4.30, 3.30, 2.30, 2.30, 3.20, 3.20, 2.90, 2.30, 1.50, 1.80, 2.90, 2.40, 1.80, 2.40, 2.30, 2.60, 1.80, 2.30, 1.90, 2.20, 2.80, 2.40, 1.00, 1.10, 1.60, 2.30, 2.50, 3.30, 3.40, 3.20, 4.50)
Thank you for your attention
Stefano
(oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia at regione.marche.it
---Oo---------oO----------------
________________________________________
Da: Jim Lemon [drjimlemon at gmail.com]
Inviato: mercoled? 13 maggio 2020 11.01
A: Stefano Sofia; r-help mailing list
Oggetto: Re: [R] Classification of wind events
Hi Stefano,
Given only one observation point you will find it difficult. If your
automatic weather station is in the low area where the foehn wind is
felt, it can only be distinguished from a dry katabatic wind if the
upwind conditions are known. There is a similar but milder version of
this in eastern Australia, but it is usually of the latter sort. There
may be a way to measure turbulence above the peak of the high ground
with radar or something, but I'm not familiar with that.
Jim
On Tue, May 12, 2020 at 6:13 PM Stefano Sofia
<stefano.sofia at regione.marche.it> wrote:
Dear R list users,
I am aware that this question is not strictly related, at the present moment, to R code and it is more general. Please forgive me, but I need to share my thoughts with you.
Foehn conditions on the southern slope of Alps happen with strong northerly flows that impact perpendicularly over the Apls. This situation triggers strong northerly leeward winds.
Given a single automatic weather station, I would like to identify these periods starting from wind direction and wind intensity data. Frequency of data is quarter of hour.
I would really find difficult to detect the moving windows of these events:
- I can't analyse data day by day;
- at the beginning and at the end of each event, when the process is not at full speed yet, the rotation is not always perfectly identifiable;
- I cannot claim in principle that the direction of each consecutive observation is costantly and strictly from the chosen direction.
Does anybody have a clue on how to start to build this process in the right way?
Thank you for your attention and your help
Stefano
(oo)
--oOO--( )--OOo----------------
Stefano Sofia PhD
Civil Protection - Marche Region
Meteo Section
Snow Section
Via del Colle Ameno 5
60126 Torrette di Ancona, Ancona
Uff: 071 806 7743
E-mail: stefano.sofia at regione.marche.it
---Oo---------oO----------------
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