Bancheri and Formetta

LINKERS

JGrass-NewAGE: RainSnowSeparationcomponentMarialaura 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 3console. Some preliminary knowledge and installation of OMS is mandatory (see @Alsouseful). This component deals with the detection of the rainfall and snowfall in thetotal precipitation. It uses the approach proposed by Kavetski et al. (2006), based on asmoother filter for thresholds on temperature. The component can be used with bothraster inputs and punctual inputs. It is perfectly integrated in the system and itsoutputs 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

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

Bancheri and Formetta Page 3 of 6

Component DescriptionUsually 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 − Tsm1

)+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.

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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 descriptionRainfall 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.

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0 5000 10000 15000

05

1015

2025

Rain-snow separation

Time [h]

Tota

l pre

cipi

tatio

n [m

m]

Rain [mm]Snow [mm]

Figure 2 Time series of clearness index

ExamplesThe 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 OMS3def home = oms_prj

// start and end date of the simulationdef 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 writeroutput 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}"

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"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 ProjectThe 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

%

References1. 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)