The Nitrogen
and Phosphate Models take input from a weather file each time they are run. The
Internet version of the Models have access to a series
of weather files from different sites throughout the World (prepared as
described below). The Internet user of the Models selects a climatic region and
a corresponding weather file is automatically selected for input to the chosen
Model. At the same time, if the user has opted for 'Advanced Input', he/she is
presented with rainfall data from the selected weather file. The user can then
alter this rainfall data so that when he/she commands the Model to run, a new
weather file containing the user's rainfall modifications will be automatically
created and input to the Model instead of the file originally selected. This
automatic selection of weather files and the modification procedures outlined
below are all carried out by programs within the Web System which supports the
Model programs on a server computer.
USER MODIFICATION OF RAINFALL
Because the
weather files contain daily data and the user only modifies monthly averages,
his/her modifications must be expanded to provide daily values of rain. This
expansion depends on a set of rules which are intended to preserve as much
realism as possible within the modified weather files. They are based on the
evidence in the APPENDIX. The rules are as follows.
PREPARATION OF STANDARD WEATHER FILES
These were
produced so as to approximate to the average weather at each of many sites
throughout the world. The crop response model requires daily values of the mean
air temperature (degrees C), precipitation (rainfall in mm)and
potential evaporation from an open water surface in mm.
Sites in
different parts of the world outside the UK
These values
were prepared at all sites, with the exception of those in the
First, for each
site a file was produced of the mean monthly values of precipitation and the
number of days on which precipitation occurred and also of the average monthly
daily maximum and daily minimum temperature. The data was obtained from the
booklets, details of which are given in the REFERENCES under Meteorological
Office in the REFERENCE Section at the end of this document .
Although the data was old it generally summarized measurements over a period of
at least 30 years.
Daily values of
maximum and minimum temperatures had to be generated for each day throughout
the year. They were generated from the cosine model described in Peiris & McNicol (1996). The
model was calibrated for each site with the monthly data by fitting, using an
option in GENSTAT (Genstat5 Committee, 1987) for non uniform errors. These
values together with altitude and the latitude of the site were used to
generate daily values of evaporation from an open water surface (pan
evaporation). The procedure is described by Linacre (1977). If, however, the
average temperature was less than 4 degrees C the model was, according to the
author and our experience, unsatisfactory. At these low temperatures, daily
potential evaporation was set to 0.01 mm.
Daily rainfall
in each month was generated from the total rainfall for that month and the number
days in the month when rain fell. The procedure was method 2 described in EPIC(1997) with the X parameter set at 1.3 a value that has
been found to be usually satisfactory in the
Sites in the
With the
exception of daily potential evaporation from an open water surface the
standard weather files for the IK were generated as described above. These were
calculated from the average values over a 47 year period at Wellesbourne (near
the centre of England) by assuming that potential evaporation during any month
in the UK is approximately proportional to the ratio of average monthly
temperature at the site divided by that at Wellesbourne.. (
See APPENDIX for the reasoning behind the approach.)
APPENDIX
Modification of rainfall.
Methods of
adjusting daily rainfall for user inputs of monthly rainfall were based on
analysis of following data:
The
data for (a i & ii) and for (b i & ii) were obtained from (Meteorological Office, 1972 ,0.856c ). The data for (a iv)
were kindly provided by A Walker of HRI.
For each of the
(a) data sets total rainfall was far better correlated with rain per rainfall
day than with number of rain days. Regression of total rainfall versus rainfall
per rain day removed 83% of the variance in (ai)
whereas regression against number of rain days removed only 46%.
The entire data
set in (b) showed that rainfall was far better correlated with number of rain
days than with rainfall per day. Regression of total rain v number of rain days
removed 72% of the variance in (bi) whereas regression against rainfall per day
only removed 16%.
Thus in the
wetter regions total monthly rainfall is much better correlated with rainfall
per day than with number of rain days while the converse holds in the drier
regions. The change-over seems to take place at about 13 days.
Generation of
The
procedure was devised because it appeared to give a better estimate of
REFERENCES
EPIC (1997)Documentation\precipitation
- method 2 equation 99- at Internet site:
http://brcsunO.tamu.edu/epic/documentation/precipitation.html
Genstat 5 Committee (1987) Reference Manual, Clarendon Press,
Linacre (1977) A simple formula for estimating evaporation rates in various
climates using temperature data alone. Agricultural Meteorology 18,
409-424
Meteorological
Office
(1958) M.O.617a Tables of temperature , relative
humidity, and precipitation for the world . Part 1
Meteorological
Office
(1958) M.O.617b Tables of temperature , relative
humidity, and precipitation for the world . Part 2 Central and
Meteorological
Office
(1972) Met 0.856c Tables of temperature,relative
humidity, precipitation and for sunshine for the world. part
3
Meteorological
Office
(1958) M.O.617d Tables of temperature, relative humidity, and precipitation for
the world. Part 4
Meteorological
Office
(1958) M.O.617e Tables of temperature, relative humidity, and precipitation for
the world. Part 5
Meteorological
Office
(1958) M.O.617f Tables of temperature , relative
humidity, and precipitation for the world . Part 6
Peiris D R & McNicol J W (1996) Modelling daily weather with multivariate time series. Agriculture
and