Help for package climatrends

Type:

Package

Title:

Climate Variability Indices for Ecological Modelling

Version:

0.5

URL:

https://agrdatasci.github.io/climatrends/

BugReports:

https://github.com/agrdatasci/climatrends/issues

Description:

Supports analysis of trends in climate change, ecological and crop modelling.

License:

MIT + file LICENSE

Encoding:

UTF-8

LazyData:

true

Depends:

R (≥ 3.5.0), methods

Imports:

stats, nasapower

Suggests:

ag5Tools, chirps, knitr, rmarkdown, sf, testthat

Language:

en-GB

RoxygenNote:

7.2.1

VignetteBuilder:

knitr

NeedsCompilation:

Packaged:

2023-01-06 12:28:44 UTC; kauefeitosadiasdesousa

Author:

Kauê de Sousa

[aut, cre], Jacob van Etten

[ctb, ths], Svein Ø. Solberg

[ctb, ths]

Maintainer:

Kauê de Sousa <desousa.kaue@gmail.com>

Repository:

CRAN

Date/Publication:

2023-01-06 15:40:06 UTC

Climate Variability Indices for Ecological Modelling

Description

Supports analysis of trends in climate change, ecological and crop modelling.

Author(s)

Kauê de Sousa and Jacob van Etten and Svein Ø. Solberg

Reference evapotranspiration

Description

Reference evapotranspiration using the Blaney-Criddle method. This is general theoretical method used when no measured data on pan evaporation is available locally.

Usage

ETo(object, ..., Kc = 1)

## Default S3 method:
ETo(object, tmin, ..., Kc = 1, lat = NULL, month = NULL)

## S3 method for class 'data.frame'
ETo(object, day.one, ..., Kc = 1)

## S3 method for class 'array'
ETo(object, day.one, ..., Kc = 1, lat = NULL, p = 0.27)

## S3 method for class 'sf'
ETo(object, day.one, ..., Kc = 1, as.sf = TRUE)

Arguments

object

a numeric vector with the maximum temperature, or a data.frame with geographical coordinates (lonlat), or an object of class sf with geometry 'POINT' or 'POLYGON', or an array with two dimensions containing the maximum and minimum temperature, in that order. See details

...

additional arguments passed to methods. See details

Kc

a numeric value for the crop factor for water requirement

tmin

a numeric vector with the minimum temperature

lat

a vector for the latitude (in Decimal degrees), used to compute mean daily percentage of annual daytime hours based on the latitude and month. This is extracted automatically in the sf method. See details

month

an integer for the reference month of daylight percentage

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

p

optional if lat is given, a numeric for the mean daily percentage of annual daytime hours (p = 0.27 by default)

as.sf

logical, to return an object of class 'sf'

Details

When lat is provided, it is combined with the month provided in day.one to call for the system data daylight to find the correct value for p which represents the daily percentage of daytime hours in the given month and latitude. Otherwise p is set to 0.27 as default.

The array method assumes that object contains climate data available in your R section; this requires an array with two dimensions, 1st dimension contains the day temperature and 2nd dimension the night temperature, see help("temp_dat", package = "climatrends") for an example on input structure.

The data.frame method and the sf method assumes that the climate data will be fetched from a remote (cloud) source that be adjusted using the argument data.from.

Additional arguments:

last.day: an object (optional to span) of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the last day of the time series

span: an integer (optional to last.day) or a vector with integers (optional if last.day is given) for the length of the time series to be captured

data.from: character for the source of climate data. Current remote data is: 'nasapower'

pars: character vector for the temperature data to be fetched. If data.from is 'nasapower'. The temperature can be adjusted to 2 m, the default, c("T2M_MAX", "T2M_MIN") or 10 m c("T10M_MAX", "T10M_MIN")

days.before: optional, an integer for the number of days before day.one to be included in the timespan.

Value

The evapotranspiration in mm/day

References

Brouwer C. & Heibloem M. (1986). Irrigation water management: Irrigation water needs. Food and Agriculture Organization of The United Nations, Rome, Italy. https://www.fao.org/3/S2022E/s2022e00.htm

Examples

# the default method
set.seed(78)
tmax <- runif(50, 37, 47)
set.seed(79)
tmin <- runif(50, 31, 34)

ETo(tmax, tmin, lat = 22, month = 10)

###############################################

# the array method
data("temp_dat", package = "climatrends")

ETo(temp_dat, 
    day.one = "2013-10-28",
    span = 10,
    Kc = 0.92)

Growing degree-days

Description

This a heuristic tool in phenology that measures heat accumulation and is used to predict plant and animal development rates. Growing degree-days are calculated by taking the integral of warmth above a base temperature.

Usage

GDD(object, ..., tbase = 10)

## Default S3 method:
GDD(object, tmin, ..., tbase = 10)

## S3 method for class 'data.frame'
GDD(object, day.one, ..., tbase = 10)

## S3 method for class 'array'
GDD(object, day.one, ..., tbase = 10)

## S3 method for class 'sf'
GDD(object, day.one, ..., tbase = 10, as.sf = TRUE)

Arguments

object

...

additional arguments passed to methods. See details

tbase

an integer for the minimum temperature for growth

tmin

a numeric vector with the minimum temperature

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

as.sf

logical, to return an object of class 'sf'

Details

Additional arguments:

equation character to specify the equation to be used, one of "default", "a", "b" or "c". See Equations below

tbase_max optional, the maximum tbase temperature, required if equation = "c"

return.as character (one of, the default, "acc" or "daily", "ndays") to select if the function returns the accumulated gdd, or the daily values of gdd across the series, or the number of days required to reach a certain number of degree.days

degree.days an integer for the accumulated degree-days required by the organism. Optional if return.as = "daily" or return.as = "acc"

last.day: an object (optional to span) of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the last day of the time series. For data.frame, array and sf methods

span: an integer (optional to last.day) or a vector with integers (optional if last.day is given) for the length of the time series to be captured. For data.frame, array and sf methods

S3 Methods:

The data.frame and sf methods assumes that the climate data will e fetched from a remote (cloud) source that be adjusted using the argument data.from

Equations:

"default": GDD = ((tmax + tmin) / 2) - tbase

"a": adjust tmean = tbase if tmeam < tbase

"b": adjust tmin = tbase if tmin < tbase, adjust tmax = tbase if tmax < tbase

"c": adjust tmin = tbase if tmin < tbase, adjust tmax = tbase_max if tmax < tbase_max

Value

The number of days to reach the accumulated degree.days or the daily degree-days as defined with the argument return.as

References

Prentice I. C., et al. (1992) Journal of Biogeography, 19(2), 117.

Baskerville, G., & Emin, P. (1969). Ecology, 50(3), 514-517. doi:10.2307/1933912

Examples

data("innlandet", package = "climatrends")

# use the default equation
GDD(innlandet$tmax, innlandet$tmin, tbase = 2)

# set the equation "b", which is a better option for this case
# tmin = tbase if tmin < tbase 
# tmax = tbase if tmax < tbase
GDD(innlandet$tmax, innlandet$tmin, tbase = 2, equation = "b")


#####################################################

# return as the number of days required to reach a certain accumulated GDD
# use equation "c", which adjusts tmax base on a tbase_max
data("temp_dat", package = "climatrends")

GDD(temp_dat, 
    day.one = "2013-10-27", 
    degree.days = 90, 
    return.as = "ndays", 
    tbase_max = 32,
    equation = "c")

Example of input data using local data

Description

Input example from disk data. See details

Format

an array with two layers (temp_dat) a matrix (rain_dat), a data.frame (innlandet), a sf object (lonlatsf), a list ("commonbean")

Details

commonbean: a list with three data sets 1) on-farm variety performance data, 2) chirps data, and 3) modis data.

rain_dat: matrix with precipitation from CHIRPS. An excerpt to represent an example of the input data in rainfall() or

get_timeseries() when a matrix is provided.

rain_dat: matrix with precipitation from CHIRPS. An excerpt to represent an example of the input data in rainfall() or get_timeseries() when a matrix is provided.

innlandet: a data.frame with maximum and minimum temperature for a random point in the Innlandet county in Norway, spanning from "2019-01-01" to "2019-07-01"

lonlatsf: a 'sf' object with 'POINT' geometry with five random points around the municipality of Sinop, Brazil

temp_dat and rain_dat, rows represents the coordinates for the given lonlat provided in raster::extract() and colunms represents the dates from the observed precipitation/temperature.

Source

Funk, C. et al. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific Data, 2, 150066. doi:10.1038/sdata.2015.66

van Etten, J. et. al. (2019). PNAS 116(10) 4194-4199 doi:10.1073/pnas.1813720116

Wan Z, Hook S, Hulley G (2015) MYD11A1 MODIS/Aqua Land Surface Temperature/Emissivity 8-Day L3 Global 1km SIN Grid V006 doi:10.5067/MODIS/MYD11A2.006.

Crop sensitive indices

Description

Compute crop sensitive indices. These indices are designed to capture the changes in temperature extremes during key phenological stages (e.g. anthesis), but can also be applied to other phenological stages.

Usage

crop_sensitive(object, ...)

## Default S3 method:
crop_sensitive(object, tmin, ...)

## S3 method for class 'data.frame'
crop_sensitive(object, day.one, ...)

## S3 method for class 'array'
crop_sensitive(object, day.one, ...)

## S3 method for class 'sf'
crop_sensitive(object, day.one, ..., as.sf = TRUE)

Arguments

object

...

additional arguments passed to methods. See details

tmin

a numeric vector with the minimum temperature

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

as.sf

logical, to return an object of class 'sf'

Details

The function uses pre-defined threshold to compute the indices. For hts_mean (32, 35, 38 Celsius), for hts_max (36, 39, 42 Celsius), for hse (31 Celsius), for cdi_mean (22, 23, 24 Celsius), for cdi_max (27, 28, 29 Celsius) and for lethal (43, 46, 49 Celsius).

Additional arguments:

The thresholds can be adjusted using the arguments hts_mean.threshold, hts_max.threshold, hse.threshold, cdi_mean.threshold, cdi_max.threshold and lethal.threshold which are a numeric (or vector of numeric)

span: an integer (optional to last.day) or a vector with integers (optional if last.day is given) for the length of the time series to be captured. For data.frame, array and sf methods

Value

A dataframe with crop sensitive indices with n colunms depending on the number of thresholds passed to each index:

hts_mean

high temperature stress using daily MEAN temperature, and given as percentage number of days a certain threshold is exceeded

hts_max

high temperature stress using daily MAX temperature, and given as percentage number of days a certain threshold is exceeded

hse

heat stress event, and given as percentage number of days a a certain threshold is exceeded for at least two consecutive days

hse_ms

heat stress event, and given the maximum number of days a certain threshold is exceeded for at least two consecutive days

cdi_mean

crop duration index using daily MEAN temperature, and given as max(Tmean - threshold, 0)

cdi_max

crop duration index using daily MAX temperature, and given as max(Tmax - threshold, 0)

lethal

lethal temperatures, defined as percentage of days during the timeseries where daily MEAN temperature exceeds a given threshold

References

Challinor et al. (2016). Nature Climate Change 6(10):6954-958 doi:10.1038/nclimate3061

Trnka et al. (2014). Nature Climate Change 4(7):637–43. doi:10.1038/nclimate2242

Examples

# the default method
set.seed(78)
tmax <- runif(50, 37, 47)
set.seed(79)
tmin <- runif(50, 31, 34)

crop_sensitive(tmax, tmin)

###############################################

# the array method
data("temp_dat", package = "climatrends")

# use the default thresholds
crop_sensitive(temp_dat,
               day.one = "2013-10-27",
               last.day = "2013-11-04")

# or change the thresholds based on the crop physiology
crop_sensitive(temp_dat,
               day.one = "2013-10-27",
               last.day = "2013-11-04",
               hts_mean.threshold = c(24),
               hts_max.threshold = c(31, 33))

Cumulative sum of dry days

Description

Returns a vector with the cumulative sum of the maximum length of dry spell (MLDS)

Usage

cumdrought(x)

Arguments

x

a numeric vector

Value

a vector with the cumulative sum of MLDS

Examples


rain <- c(0,0.2,0.4,0.1,0.4,5.1,1.5,1.6,0.1,0,7,6,4,6,0.1,1.2,0.5,0)

cumdrought(rain)

Cumulative sum of rainfall days

Description

Returns a vector with the cumulative sum of the maximum length of wet spell (MLWS)

Usage

cumrain(x)

Arguments

x

a numeric vector

Value

a vector with the cumulative sum of MLWS

Examples


# Example 1

rain <- c(0,0.2,1.4,6.1,1.4,5.1,1.5,1.6,0.1,0,7,6,4,6,1.1,1.2,1.5,0)

cumrain(rain)

# should return this vector
# raincum <- c(0,0,1,2,3,4,5,6,6,6,6,6,6,6,6,6,7,7)

# Example 2

rain2 <- c(1,0,1,1,0,0,1,1,1,0,0,1,1)

cumrain(rain2)

# should return this 
# raincum2 <- c(1,1,1,2,2,2,2,2,3,3,3,3,3)

Time series climate data

Description

General functions and methods to concatenate climate data across a time series

Usage

get_timeseries(object, day.one, ...)

## Default S3 method:
get_timeseries(
  object,
  day.one,
  span = NULL,
  last.day = NULL,
  as.matrix = FALSE,
  data.from = "nasapower",
  ...
)

## S3 method for class 'matrix'
get_timeseries(object, day.one, span = NULL, last.day = NULL, ...)

## S3 method for class 'array'
get_timeseries(object, day.one, span = NULL, last.day = NULL, ...)

Arguments

object

a data.frame (or any other object that can be coerced to data.frame) with geographical coordinates (lonlat), or an object of class sf with geometry 'POINT' or 'POLYGON', or a named matrix with climate data, or an array with two dimensions for max and min temperature. See details.

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

...

additional arguments passed to methods. See details.

span

an integer or a vector with integers (optional if last.day is given) for the length of the time series to be captured

last.day

optional to span, an object of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the last day of the time series

as.matrix

logical, optional, to return a matrix or array instead of a data.frame

data.from

character, for the source of climate data. See details.

Details

The default method and the sf method assumes that the climate data will be fetched from an remote (cloud) data.from.

The matrix method assumes that the climate data was previously handled and will be inputted in the format of a named matrix. See help("modis", "climatrends") for examples.

Available remote sources to pass data.from: "nasapower"

Additional arguments:

pars: character vector of solar, meteorological or climatology parameters to download. See help("parameters", "nasapower") when data.from = "nasapower".

days.before: an integer for the number of days before day.one to be included in the timespan.

Value

A list with class clima_ls with data.frame(s) with the class clima_df

Examples


# Using local sources
# an array with temperature data
data("temp_dat", package = "climatrends")

set.seed(9271)
span <- as.integer(runif(10, 6, 15))

get_timeseries(temp_dat, "2013-10-28", span = span)

# matrix with precipitation data
data("rain_dat", package = "climatrends")

get_timeseries(rain_dat, "2013-10-28", span = span)


# data can be returned as matrix
library("sf")
# Fetch data from NASA POWER using 'sf' method
data("lonlatsf", package = "climatrends")

g <- get_timeseries(object = lonlatsf,
                    day.one = "2018-05-16",
                    last.day = "2018-05-30",
                    pars = c("PRECTOTCORR", "T2M"),
                    as.matrix = TRUE)

Late spring frost

Description

Compute late spring frost, which is a freezing event occurring after a substantial accumulation of warmth

Usage

late_frost(object, ..., tbase = 4, tfrost = -2)

## Default S3 method:
late_frost(object, tmin, ..., tbase = 4, tfrost = -2)

## S3 method for class 'data.frame'
late_frost(object, day.one, ..., tbase = 4, tfrost = -2)

## S3 method for class 'array'
late_frost(object, day.one, ..., tbase = 4, tfrost = -2)

## S3 method for class 'sf'
late_frost(object, day.one, ..., tbase = 4, tfrost = -2)

Arguments

object

...

additional arguments passed to methods. See details

tbase

an integer for the minimum temperature for growth

tfrost

an integer for the freezing threshold

tmin

a numeric vector with the minimum temperature

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

Details

Additional arguments:

equation: character to specify the equation to be used, "b" is set by default. See GDD()

dates: a character (or Date or numeric) vector for the dates of tmax and tmin in the default method

last.day: an object (optional to span) of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the last day of the time series

span: an integer (optional to last.day) or a vector with integers (optional if last.day is given) for the length of the time series to be captured

Value

A data.frame with the late frost events

id

the id generated using the indices for the rows in object

date

the first day of the event

gdd

the growing degree-days accumulated during the event

event

a factor for the observed event, frost, latent (where there is no frost event, but also there is no GDD), and warming (where GDD is accumulated)

duration

the number of days the event spanned

References

Trnka et al. (2014). Nature Climate Change 4(7):637–43. doi:10.1038/nclimate2242

Zohner et al. (2020). PNAS. doi:10.1073/pnas.1920816117

Examples

# default method
data("innlandet", package = "climatrends")

# equation b is set by default
# where tmin and tmax are adjusted if below tbase
late_frost(innlandet$tmax, 
           innlandet$tmin, 
           dates = innlandet$date, 
           tbase = 2, 
           tfrost = -2)

# slightly different series if equation a is used
late_frost(innlandet$tmax, 
           innlandet$tmin, 
           dates = innlandet$date, 
           tbase = 2,
           tfrost = -2,
           equation = "a")

#####################################################

# demo of the array method but no frost event is returned 
# because the data comes from the tropics
data("temp_dat", package = "climatrends")

late_frost(temp_dat, day.one = "2013-10-27")

Rainfall indices

Description

Methods to compute rainfall indices over a time series

Usage

rainfall(object, ...)

## Default S3 method:
rainfall(object, ..., timeseries = FALSE)

## S3 method for class 'data.frame'
rainfall(object, day.one, span = NULL, ..., timeseries = FALSE)

## S3 method for class 'matrix'
rainfall(object, day.one, span = NULL, ..., timeseries = FALSE)

## S3 method for class 'sf'
rainfall(object, day.one, span = NULL, ..., timeseries = FALSE, as.sf = TRUE)

Arguments

object

a numeric vector with precipitation data or a data.frame with geographical coordinates (lonlat), or an object of class sf with geometry 'POINT' or 'POLYGON', or a named matrix with precipitation data. See details.

...

additional arguments passed to methods. See details.

timeseries

logical, FALSE for a single point time series observation or TRUE for a time series based on intervals

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

span

an integer or a vector with integers (optional if last.day is given) for the length of the time series to be captured

as.sf

logical, to return an object of class 'sf'

Details

#' Additional arguments:

intervals: an integer (no lower than 5), for the days intervals when timeseries = TRUE

last.day: optional to span, an object of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the last day of the time series

dates: a character (or Date or numeric) vector for the dates of tmax and tmin in the default method

data.from: character for the source of remote data. Current remote source is: 'nasapower'

pars: character vector for the precipitation data to be fetched. If data.from is 'nasapower', the default precipitation parameter is "PRECTOTCORR".

days.before: optional, an integer for the number of days before day.one to be included in the timespan.

# S3 Methods

The matrix method assumes that object contains climate data available in your R section; see help("rain_dat", package = "climatrends") for an example on input structure.

The data.frame and the sf methods assumes that the climate data will e fetched from a remote (cloud) source that be adjusted using the argument data.from.

When timeseries = TRUE, an id is created, which is the index for the rownames of the inputted object.

Value

A dataframe with rainfall indices:

MLDS

maximum length of consecutive dry day, rain < 1 mm (days)

MLWS

maximum length of consecutive wet days, rain >= 1 mm (days)

R10mm

number of heavy precipitation days 10 >= rain < 20 mm (days)

R20mm

number of very heavy precipitation days rain >= 20 (days)

Rx1day

maximum 1-day precipitation (mm)

Rx5day

maximum 5-day precipitation (mm)

R95p

total precipitation when rain > 95th percentile (mm)

R99p

total precipitation when rain > 99th percentile (mm)

Rtotal

total precipitation (mm) in wet days, rain >= 1 (mm)

SDII

simple daily intensity index, total precipitation divided by the number of wet days (mm/days)

References

Aguilar E., et al. (2005). Journal of Geophysical Research, 110(D23), D23107. doi:10.1029/2005JD006119

Examples

# A vector with precipitation data
set.seed(987219)
rain <- runif(50, min = 0, max = 6)

rainfall(rain)

# Return as timeseries with intervals of 7 days
dates <- 17650:17699
rainfall(rain, dates = dates, timeseries = TRUE, intervals = 7)

######################################################

# the matrix method
data("rain_dat", package = "climatrends")

rainfall(rain_dat,
         day.one = "2013-10-28",
         span = 12)

Temperature indices

Description

Methods to compute temperature indices over a time series

Usage

temperature(object, ...)

## Default S3 method:
temperature(object, tmin, ..., timeseries = FALSE)

## S3 method for class 'data.frame'
temperature(object, day.one, span = NULL, ..., timeseries = FALSE)

## S3 method for class 'array'
temperature(object, day.one, span = NULL, ..., timeseries = FALSE)

## S3 method for class 'sf'
temperature(
  object,
  day.one,
  span = NULL,
  ...,
  timeseries = FALSE,
  as.sf = TRUE
)

Arguments

object

...

additional arguments passed to methods. See details

tmin

a numeric vector with the minimum temperature

timeseries

logical, FALSE for a single point time series observation or TRUE for a time series based on intervals

day.one

a vector of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the starting day to capture the climate data

span

an integer or a vector with integers (optional if last.day is given) for the length of the time series to be captured

as.sf

logical, to return an object of class 'sf'

Details

Additional arguments:

intervals: an integer (no lower than 5), for the days intervals when timeseries = TRUE

last.day: optional to span, an object of class Date or any other object that can be coerced to Date (e.g. integer, character YYYY-MM-DD) for the last day of the time series. For data.frame, array and sf methods

dates: a character (or Date or numeric) vector for the dates of tmax and tmin in the default method

data.from: character for the source of remote data. Current remote source is: 'nasapower'

pars: character vector for the temperature data to be fetched. If data.from is 'nasapower', the temperature can be adjusted to 2 m, the default, c("T2M_MAX", "T2M_MIN") or 10 m c("T10M_MAX", "T10M_MIN")

days.before: optional, an integer for the number of days before day.one to be included in the timespan.

# S3 Methods

The data.frame and the sf methods assumes that the climate data will be fetched from a remote (cloud) source that be adjusted using the argument data.from.

When timeseries = TRUE, an id is created, which is the index for the rownames of the inputted object.

Value

A dataframe with temperature indices:

maxDT

maximun day temperature (degree Celsius)

minDT

minimum day temperature (degree Celsius)

maxNT

maximun night temperature (degree Celsius)

minNT

minimum night temperature (degree Celsius)

DTR

diurnal temperature range (mean difference between DT and NT (degree Celsius))

SU

summer days, number of days with maximum temperature > 30 (degree Celsius)

TR

tropical nights, number of nights with maximum temperature > 25 (degree Celsius)

CFD

consecutive frosty days, number of days with temperature bellow 0 degree Celsius

WSDI

maximum warm spell duration, consecutive days with temperature > 90th percentile

CSDI

maximum cold spell duration, consecutive nights with temperature < 10th percentile

T10p

the 10th percentile of night tempeture (degree Celsius)

T90p

the 90th percentile of day tempeture (degree Celsius)

References

Aguilar E., et al. (2005). Journal of Geophysical Research, 110(D23), D23107. doi:10.1029/2005JD006119

Examples

# the default method
data("innlandet", package = "climatrends")

# a single temporal observation
temperature(innlandet$tmax, innlandet$tmin)

# return as timeseries with 30-day intervals
temperature(innlandet$tmax, 
            innlandet$tmin, 
            dates = innlandet$dates,
            timeseries = TRUE, 
            intervals = 30)

#####################################################

# array method
data("temp_dat", package = "climatrends")

temperature(temp_dat,
            day.one = "2013-10-28",
            span = 12)

Climate Variability Indices for Ecological Modelling

Description

Author(s)

See Also

Reference evapotranspiration

Description

Usage

Arguments

Details

Value

References

See Also

Examples

Growing degree-days

Description

Usage

Arguments

Details

Value

References

See Also

Examples

Example of input data using local data

Description

Format

Details

Source

Crop sensitive indices

Description

Usage

Arguments

Details

Value

References

See Also

Examples

Cumulative sum of dry days

Description

Usage

Arguments

Value

Examples

Cumulative sum of rainfall days

Description

Usage

Arguments

Value

Examples

Time series climate data

Description

Usage

Arguments

Details

Value

Examples

Late spring frost

Description

Usage

Arguments

Details

Value

References

See Also

Examples

Rainfall indices

Description

Usage

Arguments

Details

Value

References

Examples

Temperature indices

Description

Usage

Arguments

Details

Value

References

See Also