usEstUstarThreshold.RdEstimate the Ustar threshold by aggregating the estimates for seasonal and temperature subsets.
usEstUstarThreshold(ds, seasonFactor = usCreateSeasonFactorMonth(ds$sDateTime),
yearOfSeasonFactor = usGetYearOfSeason(seasonFactor,
ds$sDateTime), ctrlUstarEst = usControlUstarEst(),
ctrlUstarSub = usControlUstarSubsetting(),
fEstimateUStarBinned = usEstUstarThresholdSingleFw2Binned,
isCleaned = FALSE, isInBootstrap = FALSE)data.frame with columns "sDateTime", "Ustar", "NEE", "Tair", and "Rg"
factor for subsetting times (see details)
named integer vector: for each seasonFactor level, get the year (aggregation period) that this season belongs to
control parameters for estimating uStar on a single binned series,
see usControlUstarEst
control parameters for
subsetting time series (number of temperature and Ustar classes ...),
see usControlUstarSubsetting
function to
estimate UStar on a single binned series,
see usEstUstarThresholdSingleFw2Binned
set to TRUE, if the data was cleaned already,
to avoid expensive call to usGetValidUstarIndices.
set to TRUE if this is called from
sEddyProc_sEstimateUstarScenarios to avoid further
bootstraps in change-point detection
The threshold for sufficiently turbulent conditions u * (Ustar)
is estimated for different subsets of the time series.
From the estimates for each season (each value in seasonFactor)
the maximum of all seasons of one year is reported as estimate for this year.
Within each season the time series is split by temperature classes.
Among these Ustar estimates, the median is reported as season value.
In order to split the seasons, the uses must provide a vector with argument
seasonFactor.
All positions with the same factor, belong to
the same season. It is conveniently generated by one of the following functions:
usCreateSeasonFactorMonth
(default DJF-MAM-JJA-SON with December from previous to January of the year)
usCreateSeasonFactorMonthWithinYear
(default DJF-MAM-JJA-SON with December from the same year)
usCreateSeasonFactorYday
for a refined specification of season starts.
usCreateSeasonFactorYdayYear
for specifying different seasons season between years.
The estimation of Ustar on a single binned series can be selected argument
fEstimateUStarBinned.
This function is called by
sEddyProc_sEstUstarThold which stores the result
in the class variables (sUSTAR and sDATA).
sEddyProc_sEstUstarThresholdDistribution which
additionally estimates median and confidence intervals for each year
by bootstrapping the original data within seasons.
For inspecting the NEE~uStar relationship plotting is provided by
sEddyProc_sPlotNEEVersusUStarForSeason
A list with entries data.frame with columns "aggregationMode", "seasonYear", "season", "uStar" with rows for "single": the entire aggregate (median across years) , "seasonYear": each year (maximum across seasons or estimate on pooled data) , "season": each season (median across temperature classes)
data.frame listing results for year with columns "seasonYear" , "uStarMaxSeason" the maximum across seasonal estimates within the year , "uStarPooled" the estimate based on data pooled across the year (only calculated on few valid records or on uStarMaxSeason was nonfinite) , "nRec" number of valid records (only if the pooled estimate was calculated) , "uStarAggr" chosen estimate, corresponding to uStarPooled if this was calculated, or uStarMaxSeason or uStarTh across years if the former was non-finite
data.frame listing results for each season , "nRec" the number of valid records , "uStarSeasonEst" the estimate for based on data within the season (median across temperature classes) , "uStarAggr" chose estimate, corresponding to uStarSeasonEst, or the yearly seasonYear$uStarAggr, if the former was non-finite
numeric matrix (nTemp x nAggSeason): estimates for each temperature subset for each season
columns
season, tempBin and uStarBin
for each record of input ds
reporting classes of similar environmental conditions
that the record belongs to.
Ustar filtering following the idea in Papale, D. et al. (2006) Towards a standardized processing of net ecosystem exchange measured with eddy covariance technique: algorithms and uncertainty estimation. Biogeosciences 3(4): 571-583.