search for: winds

Hello, I have a statistical problem that I am using R for, but I am not making sense of the results. I am trying to use multiple regression to explore which variables (weather conditions) have the greater effect on a local atmospheric variable. The data is taken from a database that has 20391 data points (Z1). A simplified version of the data I'm looking at is given below, but I have a

Aloha all, I love using ggplot. It took a while to get used to the grammar of graphics, but it is starting to get easy now that I am thinking in a more structured way. A question. I'm making a wind rose that I'd like to be oriented with due north straight up. I've discovered that the orientation is sensitive to how north is represented. When north is represented as 0,

...have the season, frequency, strength and direction of the wind from 10 different locations, the coverage of the area that I am interested in is not 100% there are small gaps in my coverage due to the location of the weather stations. I am trying to create a series of wind maps e.g. the Prevailing Winds, the maximum seasonal wind, etc. Could any body recommend any R-packages that would cover this type problem/issue? xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Any views expressed in this message are those of the individual sender, except where the sender specifically...

Hi all, Very surprising (to me!) and mystifying result from predict.glm(): the predictions vary depending on whether or not I use ns() or splines::ns(). Reprex follows: library(splines) set.seed(12345) dat <- data.frame(claim = rbinom(1000, 1, 0.5)) mns <- c(3.4, 3.6) sds <- c(0.24, 0.35) dat$wind <- exp(rnorm(nrow(dat), mean = mns[dat$claim + 1], sd = sds[dat$claim + 1])) dat <-

A wind rose plot omits time information. Your request is simply not possible. On October 30, 2024 3:48:03 AM PDT, javad bayat <j.bayat194 at gmail.com> wrote: >Dear all; >I am searching for a way to extract wind direction and speed from a wind >rose plot. I have a graph and I want to make a dataframe of 5 years with >hourly intervals. > >> start_date <-

...ncy, strength and direction of the wind from 10 > different locations, the coverage of the area that I am interested in is > not 100% there are small gaps in my coverage due to the location of the > weather stations. > > I am trying to create a series of wind maps e.g. the Prevailing Winds, the > maximum seasonal wind, etc. > > Could any body recommend any R-packages that would cover this type > problem/issue? Hi David, While there are several packages that include plotting routines for wind roses, it looks to me as though you want to define a small number of vectors rep...

Dear all; I am searching for a way to extract wind direction and speed from a wind rose plot. I have a graph and I want to make a dataframe of 5 years with hourly intervals. > start_date <- as.POSIXct("2019-01-01 00:00:00") > end_date <- as.POSIXct("2023-12-31 23:00:00") > time_sequence <- seq(from = start_date, to = end_date, by = "hour") > df

Probably a stupid question, but I don't seem to be able to find the answer I'm looking for from any of the R literature. Basically I have a matrix with several thousand rows and 20 columns(weather stations) of wind direction data. I am wanting to extract a matrix which contains data for all columns conditional on column 20 having a value of _either_ less than 45 or greater than 315. (ie I

R-help, I'm using the "update" command for a multiple regression model and it is just not working: > update(model1, . ~ . – temp:wind:rad,data=ozone.pollution) Error: unexpected input in "model2<-update(model1, . ~ . –" > summary(model1) Call: lm(formula = ozone ~ temp * wind * rad + I(rad^2) + I(temp^2) + I(wind^2), data = ozone.pollution) Residuals:

Hi I'm using polygon to delimit an area on a plot. However my intention is to "superpose" the outside area of the polygon (I want to cover an extrapolation of contour(interp(...)). Is there an easy way of doing it ? Thanks EJ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hello, are there people outside who use R for analysis of wind-measurement data (meteorological or for planning of wind power stations)? Are there already scripts/modules available for analysing and displaying/plotting wind data in the way it is done in projection/planning of wind power stations? If not, would it be of interest to use R for this, and therefore adapt data-logger output to R (by

Hi Just to clarify, I think this IS a problem with grid.path() as well as polypath(). For the example you give, grid.path() diverts to drawing a polygon (because there is no 'id' specified), and the NAs in 'x' generate two separate polygons, which get drawn one on top of the other. The correct analogy to the polypath() example is ... x2 <- matrix(x[!is.na(x)], ncol=2)

...000000 0.0000000 0.0000000 0.000000 0.000000 [,8] [1,] 0.1468429 [2,] 12.9221733 [3,] 2.2026432 [4,] 0.0000000 [5,] 0.0000000 The problem is when plotting the wind rose, it is always scaled to 30%. In my case, the north limb is out of scale in the graph since it represent the 59% of winds. The command does't have and scale argument, So I can't change the default scale settings. Any tip? Thanks in advance A. [[alternative HTML version deleted]]

Hi All, This is a question not directly related to R itself, it's about how to deal with missing data. I want to build wind roses i.e. circular histograms of wind directions and associated speeds to look for trends or changes in the wind patterns over several decades for some meteo stations. The database I have contains hourly records of wind direction and speed over the past 50

> library(reshape2) > x = melt(airquality, id=c('month', 'day')) With reshape I can cast with multiple functions: > library(reshape) > cast(x, month+variable~., c(mean,sd)) month variable mean sd 1 5 ozone 23.615385 22.224449 2 5 solar.r 181.296296 115.075499 3 5 wind 11.622581 3.531450 4 5 temp 65.548387

On Thu, 4 Aug 2016 at 17:53 Michael Sumner <mdsumner at gmail.com> wrote: > On Thu, 4 Aug 2016 at 11:17 Paul Murrell <paul at stat.auckland.ac.nz> wrote: > >> Hi >> >> Just to clarify, I think this IS a problem with grid.path() as well as >> polypath(). >> >> > Hi, oh dear - sorry about that > > I appreciate the deeper explanation, I

Hi, I see different results in png() and pdf() for polypath() on Windows when using the "winding" rule ## overlapping, both clock-wise x <- cbind(c(.1, .1, .6, .6, NA, .4, .4, .9, .9), c(.1, .6, .6, .1, NA, .4, .9, .9, .4)) pfun <- function() { plot(x) polypath(x * 0.8 + 0.2, rule = "winding", col = "#BEBEBE80") polypath(x, rule =

hi R users: I have a dataset including u wind in x-axis and v wind in y-axis. How can I plot the u,v wind data in vector or barb figure? which command ? thank you . -- TANG Jie [[alternative HTML version deleted]]

Hi, I'm dealing with wind data and I'd like to model their distribution in order to simulate data to fill-in missing values. Wind direction are typically following a vonmises distribution and wind speeds follow a weibull distribution. I'd like to build a joint distribution of directions and speeds as a VonMises-Weibull bivariate distribution. First is this a stupid question? I'm

I have a problem that deals with correlating wind velocity to seed collection data. The problem lies in that I have a wind data set that is contains 2000+ data points and weed collection data on the order of a couple hundred. Both data sets were collected for the same time period, but there is not a one-to-one wind velocity->seed location match. My understanding of correlation is that you