MTD: Run

MTD: Run cindyhg Tue, 06/25/2019 - 08:16

MTD: Run

First, we need to prepare our observations by putting 1-hourly StageII precipitation forecasts into 3-hourly buckets. Create an output directory:

mkdir -p sample_obs/ST2ml_3h

Run the following PCP-Combine commands to prepare the observations:

pcp_combine -sum 00000000_000000 01 20050807_030000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080703V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml
pcp_combine -sum 00000000_000000 01 20050807_060000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080706V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml
pcp_combine -sum 00000000_000000 01 20050807_090000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080709V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml
pcp_combine -sum 00000000_000000 01 20050807_120000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080712V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml
pcp_combine -sum 00000000_000000 01 20050807_150000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080715V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml
pcp_combine -sum 00000000_000000 01 20050807_180000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080718V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml
pcp_combine -sum 00000000_000000 01 20050807_210000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080721V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml
pcp_combine -sum 00000000_000000 01 20050808_000000 03 \
sample_obs/ST2ml_3h/sample_obs_2005080800V_03A.nc \
-pcpdir ${METPLUS_DATA}/met_test/data/sample_obs/ST2ml

Rather than listing 8 input forecast and observation files on the command line, we will write them to a file list first. Since the 0-hour forecast does not contain 3-hourly accumulated precip, we will exclude that from the list. We will use the 3-hourly APCP output from PCP-Combine that we prepared above:

ls -1 ${METPLUS_DATA}/met_test/data/sample_fcst/2005080700/wrfprs* | egrep -v "_00.tm00" > fcst_file_list
ls -1 sample_obs/ST2ml_3h/sample_obs* > obs_file_list

Next, run the following MTD command:

mtd \
-fcst fcst_file_list \
-obs obs_file_list \
-config MTDConfig_tutorial \
-outdir . \
-v 2

Just as with MODE, MTD applies a convolution operation to smooth the data. However, there are two important differences. In MODE, the convolution shape is a circle (radius = conv_radius). In MTD, the convolution shape is a square (width = 2*conv_radius+1) and for time t, the values in that square are averaged for times t-1, t, and t+1. Convolving in space plus time enables MTD to identify more continuous space-time objects.

If your data has high enough time frequency that the features at one timestep overlap those at the next timestep, it may be well-suited for MTD.