This tutorial demonstrates how to generate a single plume trajectories trajectory with FLEXPART and how to visualise the results in various ways.
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Please enter folder 'plume_trtrajectory' to start working. |
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In this example we will generate a forward trajectories trajectory by releasing atmospheric tracers from Newcastle. |
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This says that the release will happen over a 3 h period between heights in the lower 500 m at Newcastle and we will release 1000 kg of material in total.
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#Run flexpart (asynchronous call!) r = flexpart_run( output_path : "result_tr", input_path : "../data", starting_date : 20120517, starting_time : 12, ending_date : 20120519, ending_time : 12, output_field_type : "none", output_trajectory : "on", output_area : [40,-25,66,10], output_grid : [0.25,0.25], output_levels : 500, release_species : 1, releases : rel_ncastle print(r) |
Here we defined both the input and output path and specified the simulation period , and the output grid as well. We also told FLEXPART to only generate plume trajectories on output..
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The actual species that will be released is defined as an integer number (for details about using the species see here). With the default species settings number 1 stands for atmospheric tracer. |
If we run this macro (or alternatively right-click execute
the FLEXPART Run icon) the results resulting CSV file, 'tr_r1.csv', will be available (after a minute or so) will be available in folder 'result_tr'. The computations actually took place in a temporary folder then Metview copied the results to the output folder. If we open folder 'result_tr' we will see the 'tr_r1. csv' CSV file containing the plume trajectories. For details about the FLEXPART trajectory outputs click here.
Step 1 - Plotting the mean track
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First, we read the CSV file .using a Table Reader:
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#The input file
dIn="result_tr_single"
inFile=dIn & "/tr_r1.csv"
#Read table (CSV) data
tbl=read_table(table_filename: inFile,
table_header_row: "2",
table_meta_data_rows: "1") |
Next, we determine the trajectory (i.e. the release) start date and time from the table header:
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#Read runDate from table header runDate=date(metadata_value(tbl,"runDate")) runTime=number(metadata_value(tbl,"runTime")) runDate=runDate + hour(runTime/10000) #Read release start date from table header startSec=number(metadata_value(tbl,"start")) releaseDate=runDate + second(startSec) |
Next, we read the coordinates of the mean track and define an use Input Visualiser and Graph Plotting to plot it:
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#Read columns from table mLat=tolist(values(tbl,"meanLat")) mLon=tolist(values(tbl,"meanLon")) #visualiser iv_curve = input_visualiser( input_plot_type : "geo_points", input_longitude_variable : mLon, input_latitude_variable : mLat ) #line attributes graph_curve=mgraph(graph_line_colour: "red", graph_line_thickness: "3", graph_symbol: "on", graph_symbol_marker_index: 15, graph_symbol_height: 0.5, graph_symbol_colour: "white", graph_symbol_outline: "on" ) |
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The macro to use is 'plot_tr_step3.mv'.
First, we read the CSV file .using a Table Reader:
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#The input file dIn="result_tr_single" inFile=dIn & "/tr_r1.csv" #Read table (CSV) data tbl=read_table(table_filename: inFile, table_header_row: "2", table_meta_data_rows: "1") |
Next
The first difference is that we need to determine the middle of the release interval since the trajectory waypoint times are given in seconds elapsed since this date. The release date reading part needs to be modified like this:
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