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4dvar- instructions. Atmospheric Transport Model Parameterized Chemical Transport Model (PCTM; Kawa, et al, 2005) –Driven by reanalyzed met fields from.

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Presentation on theme: "4dvar- instructions. Atmospheric Transport Model Parameterized Chemical Transport Model (PCTM; Kawa, et al, 2005) –Driven by reanalyzed met fields from."— Presentation transcript:

1 4dvar- instructions

2 Atmospheric Transport Model Parameterized Chemical Transport Model (PCTM; Kawa, et al, 2005) –Driven by reanalyzed met fields from NASA/Goddard’s GEOS-DAS3 scheme –Lin-Rood finite volume advection scheme –Vertical mixing: diffusion plus a simple cloud convection scheme –Exact adjoint for linear advection case Basic resolution 2  x 2.5 , 25  layers,  t  30 min, with ability to reduce resolution to –4  x 5 ,  t  60 min –6  x 10 ,  t  120 min <  we’ll use this in the example –12  x 15 ,  t  180 min Measurements binned at  t resolution

3 Data Assimilation Experiments Monday: Test performance of 4DVar method in a simulation framework, with dense data (6°x10°, lowest level of model, every  t, 1 ppm (1  ) error) –Case 1 -- no data noise added, no prior –Case 2 -- w/ data noise added, no prior –Case 3 -- w/ data noise added, w/ prior –Case 4 -- no data noise added, w/ prior Tuesday: with Case 3 above, do OSSEs for –Case 5 -- dense data, but OCO column average –Case 6 -- OCO ground track and column average –Case 7 -- extended version of current network –Case 8 -- current in situ network Possibilities for projects: examine the importance of –Data coverage and accuracy vs. targeted flux resolution –Prior error pattern and correlation structures –Measurement correlations in time/space –Errors in the setup assumptions (“mistuning”) –Effect of biases in the measurements

4 How to run the 4D-Var code Home directory: /project/projectdirs/m598/dfb/4DVar_Example/scripts/case1/BFGS Work directories: /scratch/scratchdirs/dfb/case1/work_fwd & /scratch/scratchdirs/dfb/case1/work_adj Submit batch job by typing ‘llsubmit runBFGS2_LL’ while in /project/projectdirs/m598/dfb/4DVar_Example/scripts/case1/BFGS/ This executes the main driver script, found in BFGSdriver4d.F, in same directory, which controls setting up all the files and running FWD and ADJ inside the minimization loop The scripts that execute the FWD and ADJ runs of the model are found in …/4DVar_Example/scripts/case1/, named run.co2.fvdas_bf_fwd(adj)_trupri997_hourly Check progress of job by typing ‘llqs’ Jobs currently set up to do a 1 year-long run (360 days), solving for the fluxes in 5-day long chunks, at 6.4  x10  resolution, with  t =2 hours

5 How to monitor job while running In /scratch/scratchdirs/dfb/case1/work_fwd/costfuncval_history/temp –Column 1 -- measurement part of cost function –Column 2 -- flux prior part of cost function –Column 4 -- total cost function value –Column 10 -- weighted mismatch from true flux –Column 11 -- unweighted mismatch from true flux Columns 4, 10, and 11 ought to be decreasing as the run proceeds Columns X and Y give the iteration count and 1-D search count

6 How to view detailed results A results file in netCDF format written to: /scratch/scratchdirs/dfb/case1/work_fwd/estim_truth.nc sftp this to davinci.nersc.gov (rename it, so that you don’t overwrite another group’s file) Pull up an X-window to davinci and ssh -X davinci.nersc.gov On davinci, ‘module load ncview’ Then ‘ncview estim_truth.nc’ Click on a field to look at it Hint: set ‘Range’ to +/- 2e-8 for most fields

7 Other code details The code for the FWD and ADJ model is in../4DVar_Example/src_fwd_varres and src_adj_varres Measurement files are located in /scratch/scratchdirs/dfb/case1/meas Two files controlling the tightness of the prior and whether or not noise is added to the measurements are /scratch/scratchdirs/dfb/case1/work_fwd/ferror and /scratch/scratchdirs/dfb/case1/work_fwd/measnoise_on.dat

8 Monday’s Experiment 2-hourly measurements in the lowest model level at 6.4  x 10 , 1 ppm error (1  ) Iterate 30 descent steps, 1-year-long run, starts 1/1 4 cases –Case 1 -- No measurement noise added, no prior –Case 2 -- Add measurement noise added, no prior –Case 3 -- Add noise, and apply a prior –Case 4 -- No noise, but apply a prior Designed to test the method and understand the impact of data errors and the usefulness of the prior Case 3 is the most realistic and will be used to do OSSEs for several possible future networks for Tuesday’s problem set

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10 Tuesday’s Experiment Use Case 3 from above to test more-realistic measurement networks: –Current in situ network –Extended version of current network –OCO satellite –Hourly 6.4  x 10  column measurements Essentially an “OSSE” (observing system simulation experiment) -- tells you how well your instrument should do in constraining the fluxes. Only gives the random part of the error, not biases

11 OCO Groundtrack, Jan 1st (Boxes at 6  x 10  ) Across 1 day 5 days 2 days


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