est_ustar_thr: Estimate ustar threshold
In grahamstewart12/tidyflux:

Description Usage Arguments Details References

Estimate the ustar threshold by aggregating the estimates for seasonal and temperature subsets. Original name: usEstUstarThreshold.

1
2
3

est_ustar_thr(data, sf = create_sf(data$timestamp), sf_yr,
  ctrl_est = control_ustar(), ctrl_sub = subset_ustar(),
  binned_fun = est_ustar_fw2, cleaned = FALSE)

`data`	Data frame with columns "timestamp", "ustar", "NEE", "Tair", and "Rg".
`sf`	Factor for subsetting times (see details).
`ctrl_est`	Control parameters for estimating ustar on a single binned series, see `control_ustar`.
`ctrl_sub`	Control parameters for subsetting time series (number of temperature and ustar classes), see `subset_ustar`.
`binned_fun`	Function to estimate ustar on a single binned series, see `est_ustar_fw2`.
`cleaned`	Set to TRUE if the data was cleaned already (avoids expensive call to `get_ustar_indices`.

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 sf) 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, a vector with argument sf must be provided. All positions with the same factor belong to the same season. It is generated by one of the methods in the function create_sf: * create_sf(type = "month") (default DJF-MAM-JJA-SON with December from previous to January of the year) * create_sf(type = "ymonth") (default DJF-MAM-JJA-SON with December from the same year) * create_sf(type = "yday") for a refined specification of season starts. * create_sf(type = "year") for specifying different seasons between years.

The estimation of ustar on a single binned series can be selected argument est_ustar_binned: * est_ustar_fw1 * est_ustar_fw2 (default)

This function is called by:

get_ustar_thr 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.

Inspecting the NEE~uStar relationship plotting is provided by sEddyProc_sPlotNEEVersusUStarForSeason

Add index columns to locate which season / tempClass / uStarBin each record belongs. Cannot directly change sDATA, in EddyProcC, because will be overwritten in each bootstrap.

change point detection (CPT) method: With specifying ctrl_est = control_ustar(diff_temp = TRUE) change point detection is applied instead of the moving point test (e.g. with Fw2Binned). The sometimes sensitive binning of uStar values within a temperature class is avoided. Further, possible spurious thresholds are avoided by testing that the model with a threshold fits the data better than a model without a threshold using a likelihood ratio test. In addition, with CPT seasons are excluded where a threshold was detected in only less than ctrl_est$min_prop (default 20 method often gives higher estimates of the ustar threshold.

One-big-season fallback: If there are too few records within one year, or when no season yielded a finite ustar threshold estimate, then the yearly ustar threshold is estimated by pooling the data from seasons within one seasonYear. The user can suppress using pooled data on few records by providing option ctrl_sub$one_season = FALSE (see subset_ustar)

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.

grahamstewart12/tidyflux documentation built on June 4, 2019, 7:44 a.m.