This documentation teaches how to run the rain-snow separation component of JGrass-NewAge

1. Bancheri and Formetta
LINKERS
JGrass-NewAGE: RainSnowSeparation
component
Marialaura Bancheri*†
and Giuseppe Formetta†
*
Correspondence:
marialaura.bancheri@unitn.it
Dipartimento di Ingegneria Civile
Ambientale e Meccanica, Trento,
Mesiano di Povo, Trento, IT
Full list of author information is
available at the end of the article
†
Code Author
Abstract
These pages teach how to run the rain-snow separation component inside the OMS 3
console. Some preliminary knowledge and installation of OMS is mandatory (see @Also
useful). This component deals with the detection of the rainfall and snowfall in the
total precipitation. It uses the approach proposed by Kavetski et al. (2006), based on a
smoother filter for thresholds on temperature. The component can be used with both
raster inputs and punctual inputs. It is perfectly integrated in the system and its
outputs can be the inputs of different components, e.g. the snow component (1)
@Version:
0.1
@License:
GPL v. 3
@Inputs:
• Total precipitation (mm);
• Air temperature (◦
C);
• αr (−);
• αs (−);
• m1 (−);
@Outputs:
• Rainfall (mm);
• Snowfall (mm).
@Doc Author: Marialaura Bancheri
@References:
• See References section below
Keywords: OMS; JGrass-NewAGE Component Description; rain-snow separation

2. Bancheri and Formetta Page 2 of 6
Code Information
Executables
This link points to the jar file that, once downloaded can be used in the OMS console:
https://github.com/GEOframeOMSProjects/OMS_Project_RainSnowSep/tree/master/
lib
Developer Info
This link points to useful information for the developers, i.e. information about the code
internals, algorithms and the source code
https://github.com/geoframecomponents
Also useful
To run JGrass-NewAGE it is necessary to know how to use the OMS console. Information
at: ”How to install and run the OMS console”,
https://alm.engr.colostate.edu/cb/project/oms).
JGrasstools are required for preparing some input data (information at:
http://abouthydrology.blogspot.it/2012/11/udig-jgrasstools-resources-in-italian.
html
To visualize results you need a GIS. Use your preferred GIS, following its installation
instructions. To make statistics on the results, you can probably get benefits from R:
http://www.r-project.org/ and follow its installation instruction.
To whom address questions
marialaura.bancheri@unitn.it
Authors of documentation
Marialaura Bancheri (marialaura.bancheri@unitn.it)
This documentation is released under Creative Commons 4.0 Attribution International

3. Bancheri and Formetta Page 3 of 6
Component Description
Usually only precipitation totals and air temperature are available from meteorological
stations. A common procedure for separating rain and snow is to use a threshold air
temperature Ts: all the precipitation is considered snow if the air temperature for the
time interval is less than or equal to Ts; all the precipitation is considered to be rain if air
temperature is greater than Ts. As proposed in Kavetski et al. (2006), to avoid problems
for parameter calibration, a smoother filter for thresholds is applied, and the algorithm
to discriminate between rainfall and snowfall can be described as follows:
Pr = αr ·
P
π
· arctan
T − Ts
m1
+
P
2
(1)
Ps = αs(P − Pr) (2)
where P (mm) is measured precipitation,Pr (mm) is the rainfall,Ps (mm) is the snow-
fall,Ts (C) (C stands for Celsius degree) is the threshold temperature, and m1 (–) is the
parameter controlling the degree of smoothing (if m1=0 threshold behavior is simulated).
The two coefficients αr and αs adjust for measurement errors for rain and snow. Because
different values for different climate regions have been found in prior studies the two
coefficients are considered parameters in the model and are therefore calibrated.
Detailed Inputs description
General description
The input file is a .csv file containing a header and one or more time series of input data,
depending on the number of stations involved. Each column of the file is associated to a
different station.
The file must have the following header:
• The first 3 rows with general information such as the date of the creation of the file
and the author;
• the fourth and fifth rows contain the IDs of the stations (e.g. station number 8:
value 8, ID, ,8);
• the sixth row contains the information about the type of the input data (in this
case, one column with the date and one column with double values);
• the seventh row specifies the date format (YYYY-MM-dd HH:mm).
All this information shown in the figure 1.

4. Bancheri and Formetta Page 4 of 6
Figure 1 Heading of the .csv input file
Total precipitation
The total precipitation is given in time series or raster maps of (mm) values.
Air temperature
The air temperature is given in time series or raster maps of (◦
C).The conversion in (◦
K) is directly done by the component.
αr
αr is the adjustment parameter for the rainfall measurements errors in eq. 1.
αs
αs is the adjustment parameter for the snow measurements errors eq. 2.
m1
m1 is the parameter controling the degree of smoothing in eq. 1.
Detailed Outputs description
Rainfall and snowfall
The detected rainfall and snowfall are given as time series at a given point as raster maps.
Their units are (mm). Figure 2 shows the results of a rain-snow separation simulation.

5. Bancheri and Formetta Page 5 of 6
0 5000 10000 15000
0510152025
Rain-snow separation
Time [h]
Totalprecipitation[mm]
Rain [mm]
Snow [mm]
Figure 2 Time series of clearness index
Examples
The following .sim file is customized for the use of the rain-snow separation component.
The .sim file can be downloaded from here:
https://github.com/GEOframeOMSProjects/OMS_Project_RainSnowSep/tree/master/
simulation
import static oms3.SimBuilder.instance as OMS3
def home = oms_prj
// start and end date of the simulation
def startDate= "1994 -01 -01 00:00"
def endDate="1996 -01 -01 00:00"
OMS3.sim {
resource "$oms_prj/lib"
model(while: " reader_data_precip .doProcess" ) {
components {
// components to be called : reader input data , lwrb and writer
output data
" reader_data_precip " "org.jgrasstools .gears.io.
timedependent . OmsTimeSeriesIteratorReader "
" reader_data_temp " "org.jgrasstools.gears.io.
timedependent . OmsTimeSeriesIteratorReader "
" rainSnowSep " " rainSnowSperataion .
RainSnowSeparationPointCase "
" writer_snow " "org. jgrasstools .gears.io
. timedependent . OmsTimeSeriesIteratorWriter "
" writer_rain " "org. jgrasstools .gears.io
. timedependent . OmsTimeSeriesIteratorWriter "
}
parameter{
// parameter of the reader components
" reader_data_precip .file" "${home }/ data/
interpolated_rainfall .csv"
" reader_data_precip .idfield" "ID"
" reader_data_precip .tStart" "${startDate}"
" reader_data_precip .tEnd" "${endDate}"

6. Bancheri and Formetta Page 6 of 6
" reader_data_precip .tTimestep" 60
" reader_data_precip . fileNovalue " " -9999"
" reader_data_temp .file" "${home }/ data/ Temperature.csv"
" reader_data_temp .idfield" "ID"
" reader_data_temp .tStart" "${startDate}"
" reader_data_temp .tEnd" "${endDate}"
" reader_data_temp .tTimestep" 60
" reader_data_temp .fileNovalue" " -9999"
" rainSnowSep .alfa_r" 1.08
" rainSnowSep .alfa_s" 1.05
" rainSnowSep . meltingTemperature " 1.94
// parameter of the writing component
" writer_snow .file" "${home }/ output/snow.csv"
" writer_snow .tStart" "${startDate}"
" writer_snow .tTimestep" 60
" writer_rain .file" "${home }/ output/rain.csv"
" writer_rain .tStart" "${startDate}"
" writer_rain .tTimestep" 60
}
connect {
" reader_data_precip .outData" "rainSnowSep.
inPrecipitationValues "
" reader_data_temp .outData" "rainSnowSep.
inTemperatureValues "
" rainSnowSep . outRainfallHM " "writer_rain.inData"
" rainSnowSep . outSnowfallHM " "writer_snow.inData"
}
}
}
Data and Project
The following link is for the download of the input data necessaries to execute the CI
component (as shown in the .sim file in the previous section ) :
https://github.com/GEOframeOMSProjects/OMS_Project_RainSnowSep/tree/master/
data
The following link is for the download of the OMS project for the component:
https://github.com/GEOframeOMSProjects/OMS_Project_RainSnowSep
%
References
1. Formetta, G., Kampf, S.K., David, O., Rigon, R.: Snow water equivalent modeling components in newage-jgrass.
Geoscientific Model Development 7(3), 725–736 (2014)