Forecasts ========= With the method described by :cite:t:`marchesiello_mercator_2008`, CROCO can be used to downscale global forecasts in order to provide higher resolution forecasting. .. warning:: This method is only available with Matlab croco_tools It is advised to start from building a regional configuration following the dedicated tutorials and testing it with climatological or interannual forcing. Then, specifically for the forecast system, you will need to set the forecast parameters in ``crocotools_param.m``, define cpp key ``ROBUST_DIAG`` in cppdefs.h and recompile the model using jobcomp, then edit ``croco_forecast.in``. Finally, run the script ``run_croco_forecast.bash`` that will download global forecast (ocean and atmosphere), create specific forcing files using the Forecast_tools Matlab package, then run croco for the current period. Strategy of Forecast_tools -------------------------- CROCO_TOOLS allows running both inter-annual and real-time simulations. In the latter case, we rely on operational global ocean circulation models for the initial and lateral boundary conditions and operational global atmospheric models (introduced through bulk formulations) for surface forcing. In order to limit the volume of data transferred over the Internet, we use OPeNDAP (Matlab) or the Copernicus Marine Service Toolbox (Python) and extract only the necessary subgrid. We use the U.S. NCEP/NOAA data base for atmospheric forcing and the European CMEMS data for oceanic forcing. In a regional domain with low intrinsic variability where the circulation is directly forced by surface fluxes (away from fronts and eddies), initialization is of lower importance. However, if oceanic intrinsic variability with low predictability is dominant (e.g., mesoscale eddies with monthly time-scale), the model may well provide a statistically reliable image of the eddy field, but out of phase at any given time. An initialization method is therefore needed to bring ocean fields into phase with real time. Here, we do not perform data assimilation, but rely on the global CMEMS forecast products, which assimilates satellite altimetry and in-situ data. Newtonian nudging is used to adjust CMEMS data to CROCO dynamics in a downscaling procedure. The strategy for a hindcast/forecast cycle is as follows. The simulation starts at t0-hdays (hdays=1, t0 being the present time) and ends at t0+fdays (fdays=3). The model is run using interpolated data from CMEMS for lateral boundary conditions and NCEP for surface forcing. CMEMS data or a CROCO restart file (from a previous forecast) is used for initialization at t0-1, while nudging assimilates CMEMS data in the interior domain (with a nudging time-scale of about 10 days). A Shell script (run_croco_forecast.bash) manages the whole procedure: download and pre-processing, forecast simulations, post-processing (plot_forecast_croco.m), data storage and preparation of the next forecast cycle. Set forecast parameters ----------------------- #. Edit ``crocotools_param.m`` In section 7 Make sure that ``OGCM=mercator`` and set your login/password (http://marine.copernicus.eu) to access CMEMS data through the python Copernicus Marine Service Toolbox in Forecast_tools directory. :: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % 8 - Parameters for the forecast system % % --> select OGCM name above (mercator ...) % --> select Aforc name (GFS) % --> don't forget to define in cppdefs.h: % - ROBUST_DIAG % - CLIMATOLOGY % - BULK_FLUX % - TIDES if you choose so, but without TIDERAMP %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % FRCST_dir = [FORC_DATA_DIR,'Forecast/']; % path to local OGCM data directory % % % Number of hindcast / forecast days % hdays=1; fdays=3; % % Local time= UTC + timezone % timezone = +2; % % Add tides % add_tides_fcst = 1; % 1: add tides % % MERCATOR cases (See Section 7): % ============= % if strcmp(OGCM,'mercator') if mercator_type==3 % ======================== % 3 -> For Global Forecast PSY4 % ======================== product_id={'cmems_mod_glo_phy_anfc_0.083deg_P1D-m' ... 'cmems_mod_glo_phy-cur_anfc_0.083deg_P1D-m', ... 'cmems_mod_glo_phy-thetao_anfc_0.083deg_P1D-m', ... 'cmems_mod_glo_phy-so_anfc_0.083deg_P1D-m'}; % elseif mercator_type==4 % ======================== % 4 -> For Mediterannean Forecast PSY4 4.2km % ======================== product_id={'cmems_mod_med_phy-ssh_anfc_4.2km_P1D-m', ... 'cmems_mod_med_phy-cur_anfc_4.2km_P1D-m', ... 'cmems_mod_med_phy-tem_anfc_4.2km_P1D-m', ... 'cmems_mod_med_phy-sal_anfc_4.2km_P1D-m'}; % elseif mercator_type==5 % ======================== % 5 -> For Mediterannean Forecast PSY4 4.2km (ssh detided) % ======================== product_id={'cmems_mod_med_phy-ssh_anfc_detided_4.2km_P1D-m', ... 'cmems_mod_med_phy-cur_anfc_4.2km_P1D-m', ... 'cmems_mod_med_phy-tem_anfc_4.2km_P1D-m', ... 'cmems_mod_med_phy-sal_anfc_4.2km_P1D-m'}; % else end end Make sure that ``OGCM=mercator`` (section 7), choose the hindcast/forecast period ``hdays/fdays`` (start with default), set your time zone and then your login/password (http://marine.copernicus.eu) to access CMEMS data through motuclient python package in Forecast_tools directory. .. warning:: CMEMS url and files may sometimes change name, resulting in system failure until we make the necessary adjustments. #. Edit ``croco_forecast.in`` if you want to adjust some default parameters like nudging coefficient to forecast data ( by default on the order of 15 days) :: nudg_cof: TauT_in, TauT_out, TauM_in, TauM_out [days for all] 1. 15. 1. 15. .. warning:: ``croco_forecast.in`` contains template variables for NTIMES, DT, NDTFAST, NRST,NWRT and NAVG Compiling --------- #. Edit ``cppdefs.h`` for defining forcing and nudging procedures: :: # define BULK_FLUX /* Lateral Forcing */ # define CLIMATOLOGY # ifdef CLIMATOLOGY # define ZCLIMATOLOGY # define M2CLIMATOLOGY # define M3CLIMATOLOGY # define TCLIMATOLOGY # define ZNUDGING # define M2NUDGING # define M3NUDGING # define TNUDGING # define ROBUST_DIAG # endif ``ROBUST_DIAG`` sets non-zero nudging coefficients tauT_out for nudging to CMEMS forecast (T,S) data. #. Re-compile the model: :: ./jobcomp > jobcomp_forecast.log Running the script ------------------ #. Copy run_croco_forecast.bash from SCRIPTS/Plurimonths_scripts to local directory. #. Edit run_croco_forecasts.bash. Check in particular the locations of matlab executable and loaddap library (used to extract NCEP atmospheric forecast data) :: export TOOLSDIR=$HOME/croco/croco_tools/Forecast_tools export RUNDIR=${PWD} export MATLAB=/usr/local/bin/matlab export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/loaddap-3.5.2/lib Check the forecast cycle options (default choice is generally fine but you may want to set RESTART=1 after the first forecast cycle) :: # Clean results of previous forecasts # export CLEAN=0 # # Get forcing files from DODS SERVER and process them for CROCO # PRE_PROCESS=1 ==> do the work (0 otherwise) # export PRE_PROCESS=1 # # Restart from previous forecast # export RESTART=0 # # Run hindcast/forecast # export RUN=1 # # # Make a few plots export PLOT=1 # #======================================================================= # Define time parameters (it will modify croco_forecast.in) #======================================================================= # # Model time step [seconds] DT=3600 # Number of barotropic time steps within one baroclinic time step [number] # NDTFAST in croco.in NFAST=60 # Hindcast depth [days] see crocotools_param (hdays/fdays) NDAYS_HIND=1 # Forecast depth [days] NDAYS_FCST=3 # Output frequency [hours] # average ND_AVG=24 # history (if = -1 set equal to NUMTIMES) ND_HIS=6 # restart (if = -1 set equal to NUMTIMES) ND_RST=24 #. Run the script (from Terminal or from Crontab) :: ./run_croco_forecast.bash