vegperiod {vegperiod} | R Documentation |
Determine vegetation period
Description
Calculate start and end date of vegetation periods based on daily average air temperature and the day of the year (DOY). The sum of day degrees within the vegetation period is included for convenience.
Usage
vegperiod(
dates,
Tavg,
start.method,
end.method,
Tsum.out = FALSE,
Tsum.crit = 0,
species = NULL,
est.prev = 0,
check.data = TRUE
)
Arguments
dates |
vector of calendar dates (objects of class |
Tavg |
vector of daily average air temperatures in degree Celsius.
Same length as |
start.method |
name of method to use for vegetation start. One of
|
end.method |
name of method to use for vegetation end. One of
|
Tsum.out |
boolean. Return the sum of daily mean temperatures above
|
Tsum.crit |
threshold for sum of day degrees. Only daily mean temperatures
|
species |
name of tree species (required if Must be one of |
est.prev |
number of years to estimate previous year's chill
days for the first year (required if
|
check.data |
Performs plausibility checks on the temperature data to ensure that the temperatures have not been multiplied by ten. Plausible range is -35 to +40°C. |
Details
Common methods for determining the onset and end of thermal vegetation
periods are provided, for details see next sections. Popular choices with
regard to forest trees in Germany are Menzel
and vonWilpert
. Climate
change impact studies at NW-FVA are frequently conducted using Menzel
with
"Picea abies (frueh)" and NuskeAlbert
for all tree species; with tree
species specifics accounted for in subsequent statistical models.
Start methods:
The method Menzel
implements the algorithm described in
Menzel (1997). The method is parameterized for 10 common tree species. It
needs previous year's chill days. ETCCDI
resp.
StdMeteo
is a simple threshold based procedure as defined by the
Expert Team on Climate Change Detection and Indices (cf. ETCCDI 2009, Frich
et al. 2002, Zhang et al. 2011) leading to quite early vegetation starts.
This method is widely used in climate change studies. The method
Ribes uva-crispa
is based on leaf-out of gooseberry (Janssen
2009). It was developed by the Germany's National Meteorological Service
(Deutscher Wetterdienst, DWD) and is more robust against early starts than
common simple meteorological procedures.
End methods:
The end method vonWilpert
is based on von Wilpert (1990). It
was originally developed for Picea abies in the Black Forest but is
commonly used for all tree species throughout Germany. As usual, the rules
regarding the soilmatrix are neglected in this implementation.
LWF-BROOK90
is -for the sake of convenience- a
reimplementation of the LWF-BROOK90 VBA (version 3.4) variant of "vonWilpert"
(Hammel and Kennel 2001). Their interpretation of von Wilpert (1990) and the
somewhat lower precision of VBA was mimicked. NuskeAlbert
provide a very simple method which is inspired by standard climatological
procedures but employs a 7 day moving average and a 5 °C threshold (cf.
Walther and Linderholm 2006). ETCCDI
resp. StdMeteo
is a simple threshold based procedure as defined by the Expert Team on
Climate Change Detection and Indices (cf. ETCCDI 2009, Frich et al. 2002,
Zhang et al. 2011) leading to quite late vegetation ends.
Value
A data.frame with year and DOY of start and end day of
vegetation period. If Tsum.out=TRUE
, the data.frame contains an
additional column with the sum of day degrees within vegetation periods.
References
ETCCDI (2009) Climate Change Indices: Definitions of the 27 core indices. http://etccdi.pacificclimate.org/list_27_indices.shtml
Frich, P., Alexander, L., Della-Marta, P., Gleason, B., Haylock, M., Klein Tank, A. and Peterson, T. (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate Research, 19, 193–212. doi:10.3354/cr019193.
Hammel, K. and Kennel, M. (2001) Charakterisierung und Analyse der Wasserverfügbarkeit und des Wasserhaushalts von Waldstandorten in Bayern mit dem Simulationsmodell BROOK90. Forstliche Forschungsberichte München.
Janssen, W. (2009) Definition des Vegetationsanfanges. Internal Report, Deutscher Wetterdienst, Abteilung Agrarmeteorologie.
Menzel, A. (1997) Phänologie von Waldbäumen unter sich ändernden Klimabedingungen - Auswertung der Beobachtungen in den Internationalen Phänologischen Gärten und Möglichkeiten der Modellierung von Phänodaten. Forstliche Forschungsberichte München.
von Wilpert, K. (1990) Die Jahrringstruktur von Fichten in Abhängigkeit vom Bodenwasserhaushalt auf Pseudogley und Parabraunerde: Ein Methodenkonzept zur Erfassung standortsspezifischer Wasserstreßdispostion. Freiburger Bodenkundliche Abhandlungen.
Walther, A. and Linderholm, H. W. (2006) A comparison of growing season indices for the Greater Baltic Area. International Journal of Biometeorology, 51(2), 107–118. doi:10.1007/s00484-006-0048-5.
Zhang, X., Alexander, L., Hegerl, G. C., Jones, P., Tank, A. K., Peterson, T. C., Trewin, B. and Zwiers, F. W. (2011) Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdisciplinary Reviews: Climate Change, 2(6), 851–870. doi:10.1002/wcc.147.
Examples
data(goe)
vegperiod(dates=goe$date, Tavg=goe$t,
start.method="Menzel", end.method="vonWilpert",
species="Picea abies (frueh)", est.prev=5)
# take chill days from first year, which is then dropped
vegperiod(dates=goe$date, Tavg=goe$t, start="Menzel", end="vonWilpert",
species="Picea abies (frueh)", est.prev=0)
# add column with sum of day degrees in vegetation periods
vegperiod(dates=goe$date, Tavg=goe$t, Tsum.out=TRUE,
start="StdMeteo", end="StdMeteo")