Newer
Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CST_Analogs.R
\name{Analogs}
\alias{Analogs}
\title{Search for analogs based on large scale fields.}
\usage{
Analogs(expL, obsL, time_obsL, expVar = NULL, obsVar = NULL,
criteria = "Large_dist", lon_local = NULL, lat_local = NULL,
region = NULL, nAnalogs = 1, return_list = FALSE)
}
\arguments{
\item{expL}{variable for the Large scale in the model (same variable
might be used in the local scale for criteria 2)}
\item{obsL}{variable for the large scale in the observations}
\item{expVar}{variable for the local scale in the model usually different
to the variable in expL}
\item{obsVar}{variable for the local scale in the observations usually
different to the variable in obsL}
\item{criteria}{different criteria to be used for the selection of analogs
if criteria = "Large_dist"
if criteria ="Local_dist"
if criteria ="Local_cor"}
\item{lon_local}{longitude in the local scale}
\item{lat_local}{latitude in the local scale}
\item{region}{region for the local scale}
\item{nAnalogs}{number of Analogs to be selected to apply the criterias (this
is not the necessary the number of analogs that the user can get)}
\item{return_list}{TRUE if you want to get a list with the best analogs FALSE
if not.}
}
\value{
list list with the best analogs (time, distance)
values values of a certain variable
}
\description{
This function search for days with similar large scale
conditions or similar large and local scale conditions.
The large scale and the local scale regions are defined by the user.
The large scale is usually given by atmospheric circulation as sea level
pressure or geopotential height (Yiou et al, 2013) but the function gives the
possibility to use another field. For the local scale the user can select
any variable.
The analogs function will find the best analogs based in three criterias:
(1) Minimal distance in the large scale pattern (i.e. SLP)
(2) Minimal distance in the large scale pattern (i.e. SLP) and minimal
distance in the local scale pattern (i.e. SLP).
(3) Minimal distance in the large scale pattern (i.e. SLP), minimal
distance in the local scale pattern (i.e. SLP) and maxima correlation in the
local variable to find the analog (i.e Precipitation).
Once the search of the analogs is complete, and in order to used the
three criterias the user can select a number of analogs nAnalogs to restrict
the selection of the best analogs in a short number of posibilities, the best
ones. By default this parameter will be 1.
This function has not constrains of specific regions, variables to find the
analogs, or data to be used (seasonal forecast data, climate projections
data, reanalyses data).
The input data might be interpolated or not.
The function is an adapted version of the method of Yiou et al 2013.
}
\references{
Yiou, P., T. Salameh, P. Drobinski, L. Menut, R. Vautard,
and M. Vrac, 2013 : Ensemble reconstruction of the atmospheric column
from surface pressure using analogues. Clim. Dyn., 41, 1419-1437.
\email{pascal.yiou@lsce.ipsl.fr}
}
\author{
Carmen Alvarez-Castro, \email{carmen.alvarez-castro@cmcc.it}
Nuria Perez-Zanon \email{nuria.perez@bsc.es}
}