CPT based SubSeasonal Forecasting Scripts NOAAs CPC International
CPT based Sub-Seasonal Forecasting Scripts NOAA’s CPC International Desks NOAA-USAID 11 ITWCVP - Ankara, Turkey, 15 – 26 April 2019
Outline q Download the CFS (NCEP) S 2 S Data from the IRIDL server q Generate maps of Raw forecast and associate skill q Produced the calibrated forecast o Make the data ready for CPT o Calibrated using CPT: Maps of calibrated Forecast and associate skill maps q Generate map of observed anomalies for eye ball verification The current version is valid only for the precipitation. Future release will include temperature
Copying and Unpacking 1. Make sure that you have copy of S 2 S_CPT_FCST. tar. gz file in your cygwin/linux home folder. A copy is available at following address: https: //ftp. cpc. ncep. noaa. gov/International/11 ITWCVP_Ankara 2019/S 2 S_CPT_FRCST. tar. gz 2. From your cygwin/Linux terminal, uncompress the file: tar -xzvf S 2 S_CPT_FCST. tar. gz 3. Go to the folder S 2 S_CPT_FCST : cd S 2 S_CPT_FCST 4. List to see his content : ls
Download the NCEP CFS S 2 S data (forecast, hindcast) and the historical observed data bash get_S 2 S_data. sh idate tgtprd obsbse § idate - Forecast initiation date in the format YYYYMMDD (eg. 20190211) § tgtprd - Forecast target period. It can be "5 days" "10 days" "week 1" "week 2" "week 34" § obsbse - Source’s name of the observed data. Valid option are "cpcuni" or "arc 2" The downloaded data (forecast, hindcast, historical observed) are in the folder : S 2 S_DATA/idate/trgtprd/grads_data The processing time depends on your internet connection speed and your computer processor speed.
Make the data ready for CPT : Converting from binary to cpt format bash Convert_S 2 S_bin 2 cpt. sh idate tgtprd obsbse ylat. S ylat. N ylon. W ylon. E § § § § idate tgtprd obsbse ylat. S ylat. N ylon. W ylon. E - Forecast initiation date in the format YYYYMMDD (eg. 20190211) Forecast target period. It can be "5 days" "10 days" "week 1" "week 2" "week 34" Source’s name of the observed data. Valid option are "cpcuni" or "arc 2" Southern boundary of the area of interest - Northern boundary of the area of interest Western boundary of the area of interest Eastern boundary of the area of interest The converted data (forecast, hindcast, historical observed) are in the folder : S 2 S_DATA/idate/trgtprd/cpt_data Files names are : model_fcst_trgtprd. tsv model_hdcst_trgtprd. tsv obs_hist_trgtprd. tsv They can be used within windows version of CPT
Make the data ready for CPT (cntd): Converting from binary to cpt format (Examples) bash Convert_S 2 S_bin 2 cpt. sh 20190211 10 days cpcuni -59. 75 -179. 75 bash Convert_S 2 S_bin 2 cpt. sh 20190211 week 1 cpcuni -59. 75 -179. 75 bash Convert_S 2 S_bin 2 cpt. sh 20190211 week 2 cpcuni -59. 75 -179. 75 bash Convert_S 2 S_bin 2 cpt. sh 20190211 week 34 cpcuni -59. 75 -179. 75
Calibrating CFS S 2 S forecast using CPT : bash CPT_S 2 S_Calib. sh idate tgtprd mthds obsbse ylat. S ylat. N ylon. W ylon. E xlat. S xlat. N xlon. W xlon. E idate - Forecast initiation date in the format YYYYMMDD (eg. 20190211) tgtprd - Forecast target period. It can be "5 days" "10 days" "week 1" "week 2" "week 34" mthds - The calibration method. Valid option are "GCM", "CCA" or "PCR" obsbse - Source’s name of the observed data. Valid option are "cpcuni" or "arc 2" ylat. S , ylat. N, ylon. W , ylon. E are respectively the extend of the predictand ie the geographical coordinates of the area of interest § xlat. S , xlat. N, xlon. W , xlon. E are respectively the extend of the predictor ie the geographical coordinates of the domain to consider for the model § § § The calibrated forecast map and the associated skill map are in the folder : Figures_Sub. X_Frcst_Calib/init_idate/By_mthds Under the name : NCEP_trgtprd_fcst_mthds_calib. png ; the map of calibrated forecast (probabilistic) PC_skill_map_trgtprd_fcst_mthds_calib. png ; the associate Pearson Correlation skill map
Calibrating CFS S 2 S forecast using CPT (cntd): Examples 1. bash CPT_S 2 S_Calib. sh 20190211 week 2 GCM cpcuni -59. 75 -179. 75 -90 90 0 360 2. bash CPT_S 2 S_Calib. sh 20190211 week 2 CCA cpcuni -59. 75 -179. 75 -90 90 0 360 Case 1 Case 2 Figures_Sub. X_Frcst_Calib/init_20190211/By_GCM Figures_Sub. X_Frcst_Calib/init_20190211/By_CCA NCEP_week 2_fcst_GCM_calib. png PC_skill_map_week 2_fcst_GCM_calib. png NCEP_week 2_fcst_CCA_calib. png PC_skill_map_week 2_fcst_CCA_calib. png
Generating the raw forecast maps – Any differences with the Calibrated forecasts? converting deterministic forecast into probabilistic map using model climatology bash plot_S 2 S_Raw_frcst. sh idate tgtprd obsbse ylat. S ylat. N ylon. W ylon. E § § § § idate - Forecast initiation date in the format YYYYMMDD (eg. 20190211) tgtprd - Forecast target period. It can be "5 days" "10 days" "week 1" "week 2" "week 34" obsbse - Source’s name of the observed data. Valid option are "cpcuni" or "arc 2" ylat. S - Southern boundary of the area of interest ylat. N - Northern boundary of the area of interest ylon. W - Western boundary of the area of interest ylon. E - Eastern boundary of the area of interest This will generate two maps under the Folder: Figures_Sub. X_Frcst_Calib/init_idate/RAW_FCST 1 - NCEP_trgtprd_RAW_FCST. png 2 - PC_skill_map_trgtprd_RAW_FCST. png : the raw forecast probabilistic map : the associate Pearson Correlation skill map
Generating the raw forecast maps – Any differences with the Calibrated forecasts? (cntd) : Examples converting deterministic forecast into probabilistic map using model climatology bash plot_S 2 S_Raw_frcst. sh 20190211 week 2 cpcuni -59. 75 The above command line will generate two file under the Folder: Figures_Sub. X_Frcst_Calib/init_20190211/RAW_FCST Those files are : NCEP_week 2_RAW_FCST. png PC_skill_map_week 2_RAW_FCST. png 59. 75 -179. 75
Plotting observed anomalies for verification bash plot_obs_for_verif. sh idate tgtprd obsbse ylat. S ylat. N ylon. W ylon. E § § § § idate - Forecast initiation date in the format YYYYMMDD (eg. 20190211) tgtprd - Forecast target period. It can be "5 days" "10 days" "week 1" "week 2" "week 34" obsbse - Source’s name of the observed data. Valid option are "cpcuni" or "arc 2" ylat. S - Southern boundary of the area of interest ylat. N - Northern boundary of the area of interest ylon. W - Western boundary of the area of interest ylon. E - Eastern boundary of the area of interest This action will generate the containing file the observed anomalies map. It can be found in the folder : Figures_Sub. X_Frcst_Calib/init_idate The file name would look like: obsbse_anom_obs_trgtprd. png The processing time depends on your internet connection speed
Plotting observed anomalies for verification (cntd) – Examples bash plot_obs_for_verif. sh 20190211 week 2 cpcuni -59. 75 -179. 75 This action will generate the containing file the observed anomalies map. It can be found in the folder : Figures_Sub. X_Frcst_Calib/init_20190211 The file name is : cpcuni_anom_obs_week 2. png
CPT based Sub-Seasonal Forecasting Scripts – Summary 1. cd S 2 S_CPT_FCST 2. bash get_S 2 S_data. sh idate tgtprd obsbse 3. bash plot_S 2 S_Raw_frcst. sh idate tgtprd obsbse ylat. S ylat. N ylon. W ylon. E 4. bash Convert_S 2 S_bin 2 cpt. sh idate tgtprd obsbse ylat. S ylat. N ylon. W ylon. E 5. bash CPT_S 2 S_Calib. sh idate tgtprd mthds obsbse ylat. S ylat. N ylon. W ylon. E xlat. S xlat. N xlon. W xlon. E 6. bash plot_obs_for_verif. sh idate tgtprd obsbse ylat. S ylat. N ylon. W ylon. E Where: § idate - Forecast initiation date in the format YYYYMMDD (eg. 20190211) § tgtprd - Forecast target period. It can be "5 days" "10 days" "week 1" "week 2" "week 34" § mthds - The calibration method. Valid option are "GCM", "CCA" or "PCR" § obsbse - Source’s name of the observed data. Valid option are "cpcuni" or "arc 2" § ylat. S , ylat. N, ylon. W , ylon. E are respectively the extend of the predictand ie the geographical coordinates of the area of interest § xlat. S , xlat. N, xlon. W , xlon. E are respectively the extend of the predictor ie the geographical coordinates of the domain to consider for the model The processing time depends on your internet connection speed and your computer processor speed. The current version is valid only for the precipitation. Future releases will include temperature
Hands on Tools : Practice CPT based Sub-seasonal Forecasting (1) Depending on your geographical belonging produce the forecast maps using the parameters described in the table below. Initiation date Target period Calibration Method Observed data Target area (Predictand domain) Model area (Predictor domain) Africa, Europe and Middle East [40 S-60 N / 20 W-60 E] Feb 11, 2019 10 days, week 1, week 2, week 34 GCM, CCA, PCR cpcuni Asia and Maritime Continent [40 S-60 N / 60 E-179. 75 E] [60 S-60 N / 0 -360 E] Central and South America [60 S-30 N / 120 W-30 W] For this initiation date the data are already provide. So on regarding slide 13, skip step 2 and proceed accordingly with the others steps.
Hands on Tools : Practice CPT based Sub-seasonal Forecasting (2) Depending on your geographical belonging produce the forecast maps using the parameters described in the table below. Initiation date Pick a start date in the past. Just make sure that the target period is in the past so you can plot the observed anomalies. Target period Calibration Method Observed data Target area (Predictand domain) Model area (Predictor domain) Africa, Europe and Middle East [40 S-60 N / 20 W-60 E] 10 days, week 1, week 2, week 34 GCM, CCA, PCR cpcuni Asia and Maritime Continent [40 S-60 N / 60 E-179. 75 E] [60 S-60 N / 0 -360 E] Central and South America [60 S-30 N / 120 W-30 W] In this case you will need to run all the steps as described on slide 13.
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