diff --git a/.readthedocs.yaml b/.readthedocs.yaml index cdd5a58e67..9e1ea1d8cf 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -11,3 +11,7 @@ build: sphinx: configuration: conf.py + +python: + install: + - requirements: guide/requirements.txt diff --git a/CHANGELOG.rst b/CHANGELOG.rst index b7ddc8a552..20689760e4 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -22,6 +22,20 @@ individual files. The changes are now listed with the most recent at the top. +**October 5 2023 :: WRF-DART tutorial diagnostic section. Tag v10.8.5** + +- Improvements: + + - Added a more complete diagnostics section to the WRF-DART Tutorial. + - Developer test for Mersenne twister random number generator. + +- Bug-fix: + + - 1D location subsetting fixed for obs_sequence_tool. + + *contributed by Henry Santer* + + **September 18 2023 :: Fluxnet observation converter and obs_def_rttov13_mod.f90 bug-fixes. Tag v10.8.4** Fluxnet obs converter: diff --git a/conf.py b/conf.py index 7e5f834bae..e0485f6320 100644 --- a/conf.py +++ b/conf.py @@ -21,7 +21,7 @@ author = 'Data Assimilation Research Section' # The full version, including alpha/beta/rc tags -release = '10.8.4' +release = '10.8.5' root_doc = 'index' # -- General configuration --------------------------------------------------- diff --git a/guide/images/WRF_tutorial_evolution1.png b/guide/images/WRF_tutorial_evolution1.png new file mode 100644 index 0000000000..cdbd3c7eea Binary files /dev/null and b/guide/images/WRF_tutorial_evolution1.png differ diff --git a/guide/images/WRF_tutorial_evolution2.png b/guide/images/WRF_tutorial_evolution2.png new file mode 100644 index 0000000000..99631e3cce Binary files /dev/null and b/guide/images/WRF_tutorial_evolution2.png differ diff --git a/guide/images/WRF_tutorial_linkobs1.png b/guide/images/WRF_tutorial_linkobs1.png new file mode 100644 index 0000000000..c2d0fbae5e Binary files /dev/null and b/guide/images/WRF_tutorial_linkobs1.png differ diff --git a/guide/images/WRF_tutorial_linkobs2.png b/guide/images/WRF_tutorial_linkobs2.png new file mode 100644 index 0000000000..fca2003e2b Binary files /dev/null and b/guide/images/WRF_tutorial_linkobs2.png differ diff --git a/guide/images/WRF_tutorial_ncview1.png b/guide/images/WRF_tutorial_ncview1.png new file mode 100644 index 0000000000..a89c1b4905 Binary files /dev/null and b/guide/images/WRF_tutorial_ncview1.png differ diff --git a/guide/images/WRF_tutorial_ncview2.png b/guide/images/WRF_tutorial_ncview2.png new file mode 100644 index 0000000000..1898991e43 Binary files /dev/null and b/guide/images/WRF_tutorial_ncview2.png differ diff --git a/guide/images/WRF_tutorial_oneline1.png b/guide/images/WRF_tutorial_oneline1.png new file mode 100644 index 0000000000..a0e6b980c8 Binary files /dev/null and b/guide/images/WRF_tutorial_oneline1.png differ diff --git a/guide/images/WRF_tutorial_oneline2.png b/guide/images/WRF_tutorial_oneline2.png new file mode 100644 index 0000000000..a648ab7bd8 Binary files /dev/null and b/guide/images/WRF_tutorial_oneline2.png differ diff --git a/guide/images/WRF_tutorial_profile1.png b/guide/images/WRF_tutorial_profile1.png new file mode 100644 index 0000000000..aef98f2436 Binary files /dev/null and b/guide/images/WRF_tutorial_profile1.png differ diff --git a/guide/images/WRF_tutorial_profile2.png b/guide/images/WRF_tutorial_profile2.png new file mode 100644 index 0000000000..bf040cee53 Binary files /dev/null and b/guide/images/WRF_tutorial_profile2.png differ diff --git a/guide/images/WRF_tutorial_radiosonde_obs.png b/guide/images/WRF_tutorial_radiosonde_obs.png new file mode 100644 index 0000000000..a51caed4d7 Binary files /dev/null and b/guide/images/WRF_tutorial_radiosonde_obs.png differ diff --git a/guide/images/WRF_tutorial_surface_obs.png b/guide/images/WRF_tutorial_surface_obs.png new file mode 100644 index 0000000000..107b549c7e Binary files /dev/null and b/guide/images/WRF_tutorial_surface_obs.png differ diff --git a/guide/requirements.txt b/guide/requirements.txt new file mode 100644 index 0000000000..254085495f --- /dev/null +++ b/guide/requirements.txt @@ -0,0 +1,2 @@ +Sphinx==6.2.1 +sphinx-rtd-theme==1.2.2 diff --git a/models/clm/readme.rst b/models/clm/readme.rst index be100d6a08..6c9fa0ab9a 100644 --- a/models/clm/readme.rst +++ b/models/clm/readme.rst @@ -495,7 +495,7 @@ Inflation has been shown to be quite useful in our experience of DA with CLM and DART. The model is strongly influenced by the atmospheric forcing and will cause the CLM ensemble to relax to a state consistent with the forcing when the assimilation -stops. [5]_ Depending on the forecast length between assimilations, and +stops. Depending on the forecast length between assimilations, and sometimes just to restore the variance lost during an assimilation, inflation should be used. @@ -744,49 +744,49 @@ References The `CTSM Documentation `__ -is THE reference for CLM. +is THE reference for CLM. Below are a list of CLM-DART scientific publications: -.. [1] Zhang, Y.-F., T. J. Hoar, Z.-L. Yang, J. L. Anderson, A. M. Toure and M. Rodell, 2014: + Zhang, Y.-F., T. J. Hoar, Z.-L. Yang, J. L. Anderson, A. M. Toure and M. Rodell, 2014: Assimilation of MODIS snow cover through the Data Assimilation Research Testbed and the Community Land Model version 4. *Journal of Geophysical Research: Atmospheres*, **142** 1489-1508, `doi:10.1002/2013JD021329 `__ -.. [2] Lin, P., J. Wei, Z. -L. Yang, Y. Zhang, K. Zhang, 2016: + Lin, P., J. Wei, Z. -L. Yang, Y. Zhang, K. Zhang, 2016: Snow data assimilation‐constrained land initialization improves seasonal temperature prediction. *Geophysical Research Letters* **43** (21), 11,423-11,432 `doi:10.1002/2016GL070966 `__ -.. [3] Zhao, L., Z. -L. Yang and T. J. Hoar, 2016: + Zhao, L., Z. -L. Yang and T. J. Hoar, 2016: Global soil moisture estimation by assimilating AMSR-E brightness temperatures in a coupled CLM4-RTM-DART system. *Journal of Hydrometeorology*, **17**, 2431-2454, `doi:10.1175/JHM-D-15-0218.1 `__ -.. [4] Kwon, Y., Z. -L. Yang, T. J. Hoar and A. M. Toure, 2017: + Kwon, Y., Z. -L. Yang, T. J. Hoar and A. M. Toure, 2017: Improving the radiance assimilation performance in estimating snow water storage across snow and land-cover types in North America. *Journal of Hydrometeorology*, **18**, 651-668, `doi:10.1175/JHM-D-16-0102.1 `__ -.. [5] Fox, A. M., Hoar, T. J., Anderson, J. L., Arellano, A. F., Smith, W. K., Litvak, M. E., et al., 2018: + Fox, A. M., Hoar, T. J., Anderson, J. L., Arellano, A. F., Smith, W. K., Litvak, M. E., et al., 2018: Evaluation of a data assimilation system for land surface models using CLM4.5. *Journal of Advances in Modeling Earth Systems*, **10**, 2471–2494, `doi.org/10.1029/2018MS001362 `__ -.. [6] Ling, X. L., Fu, C. B., Yang, Z. L., & Guo, W. D., 2019: + Ling, X. L., Fu, C. B., Yang, Z. L., & Guo, W. D., 2019: Comparison of different sequential assimilation algorithms for satellite-derived leaf area index using the Data Assimilation Research Testbed (version Lanai). *Geoscientific Model Development*, 12(7), 3119-3133. `doi.org/10.5194/gmd-12-3119-2019 `__ -.. [7] Bian, Q., Xu, Z., Zhao, L., Zhang, Y. F., Zheng, H., Shi, C., … & Yang, Z. L., 2019: + Bian, Q., Xu, Z., Zhao, L., Zhang, Y. F., Zheng, H., Shi, C., … & Yang, Z. L., 2019: Evaluation and intercomparison of multiple snow water equivalent products over the Tibetan Plateau. *Journal of Hydrometeorology*, 20(10), 2043-2055. `doi.org/10.1175/JHM-D-19-0011.1 `__ -.. [8] Raczka, B., Hoar T.J., Duarte H.F., Fox A.M., Anderson J.L., Bowling D.R., & Lin J.C., 2021 + Raczka, B., Hoar T.J., Duarte H.F., Fox A.M., Anderson J.L., Bowling D.R., & Lin J.C., 2021 Improving CLM5.0 Biomass and Carbon Exchange across the Western US Using a Data Assimilation System. *Journal of Advances in Modeling Earth Systems*, `doi.org/10.1029/2020MS002421 `__ diff --git a/models/wrf/tutorial/README.rst b/models/wrf/tutorial/README.rst index b3491df001..e0be016ec1 100644 --- a/models/wrf/tutorial/README.rst +++ b/models/wrf/tutorial/README.rst @@ -878,73 +878,479 @@ continue to cycle until the final analysis time has been reached. -Step 6: Check your results --------------------------- +Step 6: Diagnosing the assimilation results +------------------------------------------- -Once you have run the analysis system, it is time to check if things ran -well or if there are problems that need to be addressed. DART provides +Once you have successfully completed steps 1-5, it is important to +check the quality of the assimilation. In order to do this, DART provides analysis system diagnostics in both state and observation space. -Check to see if the analysis system actually changed the state. You -should find a file in the *$BASE_DIR/output/* directory called -*analysis_increment.nc* which is the change in the ensemble mean state -from the background to the analysis after running *filter*. Use a tool, -such as *ncview*, to look at this file. You should see spatial patterns -that look something like the meteorology of the day. These should be -places where the background (short ensemble forecast) was adjusted based -on the set of observations provided. Please become familiar with the +As a preliminary check, confirm that the analysis system actually updated +the WRF state. Locate the file in the ``$BASE_DIR/output/*`` directory called +``analysis_increment.nc`` which is the difference of the ensemble mean state +between the background (prior) and the analysis (posterior) after running +``filter``. Use a tool, such as **ncview**, to look at this file as follows: + +:: + + cd $BASE_DIR/output/datefnl + module load ncview + ncview analysis_increment.nc + + + +The ``analysis_increment.nc`` file includes the following atmospheric variables: +``MU, PH, PSFC, QRAIN, QCLOUD, QGRAUP, QICE, QNICE, QSNOW, QVAPOR, T`` and ``T2``. +The example figure below shows the increments for temperature (T) only. You can +use **ncview** to advance through all 11 atmospheric pressure levels. You should +see spatial patterns that look something like the meteorology of the day. + ++--------------------------+--------------------------------+ +| |ncview1| | |ncview2| | ++--------------------------+--------------------------------+ + + +For more information on how the increments were calculated, we recommend +(but do not require to complete the tutorial) that you review the :doc:`Diagnostics Section <../../../guide/checking-your-assimilation>` -of the DART Documentation. - -The *driver.csh* script also ran the *diagnostics_obs.csh* which runs -the -`obs_diag <../../../assimilation_code/programs/obs_diag/threed_sphere/obs_diag.html>`__ -program to investigate the observation space analysis statistics. You'll -find the results of this in -``$BASE_DIR/output//obs_diag_output.nc``. There are many Matlab -scripts in the ``$DART_DIR/diagnostics/matlab`` directory that help -explore the effectiveness of the assimilation. Look for their examples -in the :doc:`Observation-Space -Diagnostics <../../../guide/matlab-observation-space>` -section. - -The additional files enable plotting the time series of recently -assimilated observations once multiple cycles have been run. Be sure to -check that a high percentage (> 90%) of available observations were -assimilated. Low assimilation rates typically point to a problem with -the background analysis, observation quality, and/or observation error -specification which are important to address before using system results -for science. - -Additional statistics can be evaluated using the converted final -observation sequence file in netcdf format from the -`obs_seq_to_netcdf <../../../assimilation_code/programs/obs_seq_to_netcdf/obs_seq_to_netcdf.html>`__ -tool. This file has a name like *obs_epoch_029.nc*, where the number in -the file is largest in the most recent set of observations processed. -There are Matlab tools to explore where and why the observations were -rejected. *plot_obs_netcdf.m* and *link_obs.m* are particularly useful. +of the DART Documentation. There are seven sections within the diagnostics +section including 1) Checking your initial assimilation, 2) Computing +filter increments and so on. Be sure to advance through all the sections. + +The existence of increments proves the model state was adjusted, however, +this says nothing about the quality of the assimilation. For example, +how many of the observations were assimilated? Does the posterior state +better represent the observed conditions of the atmosphere? These questions +can be addressed with the tools described in the remainder of this section. +All of the diagnostic files (**obs_epoch*.nc** and **obs_diag_output.nc**) +have already been generated from the tutorial. +(**driver.csh* executes **diagnostics_obs.csh**). Therefore you are ready +to start the next sections. + + +Visualizing the observation locations and acceptance rate +--------------------------------------------------------- + +An important assimilation diagnostic is whether observations were accepted +or rejected. Observations can be rejected for many reasons, but the two most common +rejection modes in DART are: 1) **violation of the outlier threshold**, meaning the +observations were too far away from the prior model estimate of the observation or +2) **forward operator failure**, meaning the calculation to generate the expected +observation failed. A full list of rejection criteria are provided +:doc:`here. <../../../guide/dart-quality-control>` Regardless of the reason for +the failure, a successful simulation assimilates the vast majority of observations. +The tools below provide methods to visualize the spatial patterns, statistics and +failure mode for all observations. + +The observation diagnostics use the **obs_epoch*.nc** file as input. This file is +automatically generated by the **obs_diagnostic.csh** script within Step 5 of this +tutorial. + +The **obs_epoch*.nc** file is located in the output directory of each time step. +In some cases there could be multiple obs_epoch*.nc files, but in general, the user +should use the obs_epoch file appended with the largest numeric value as it +contains the most complete set of observations. The diagnostic scripts used here +are included within the DART package, and require a license of Matlab to run. The +commands shown below to run the diagnostics use NCAR's Cheyenne, but a user could +also run on their local machine. + +First explore the obs_epoch*.nc file and identify the variety of observations included +in the assimilation including aircraft, surface, satelllite and radiosonde types. + + +:: + + ncdump -h $BASEDIR/output/datefnl/obs_epoch_029.nc + + .. + .. + RADIOSONDE_U_WIND_COMPONENT + RADIOSONDE_V_WIND_COMPONENT + RADIOSONDE_TEMPERATURE + RADIOSONDE_SPECIFIC_HUMIDITY + ACARS_U_WIND_COMPONENT + ACARS_V_WIND_COMPONENT + ACARS_TEMPERATURE + MARINE_SFC_U_WIND_COMPONENT + MARINE_SFC_V_WIND_COMPONENT + MARINE_SFC_TEMPERATURE + MARINE_SFC_SPECIFIC_HUMIDITY + LAND_SFC_U_WIND_COMPONENT + LAND_SFC_V_WIND_COMPONENT + LAND_SFC_TEMPERATURE + LAND_SFC_SPECIFIC_HUMIDITY + SAT_U_WIND_COMPONENT + SAT_V_WIND_COMPONENT + RADIOSONDE_SURFACE_ALTIMETER + MARINE_SFC_ALTIMETER + LAND_SFC_ALTIMETER + METAR_ALTIMETER + METAR_U_10_METER_WIND + METAR_V_10_METER_WIND + METAR_TEMPERATURE_2_METER + METAR_SPECIFIC_HUMIDITY_2_METER + METAR_DEWPOINT_2_METER + RADIOSONDE_DEWPOINT + LAND_SFC_DEWPOINT + RADIOSONDE_RELATIVE_HUMIDITY + LAND_SFC_RELATIVE_HUMIDITY + .. + .. + +The example below uses the **plot_obs_netcdf.m** script to visulaize +the observation type: ``RADIOSONDE_TEMPERATURE`` which includes both horizontal +and vertical coverage across North America. We recommend to view the script's +contents with a text editor, paying special attention to the beginning of the file +which is notated with a variety of examples. Then to run the example do the +following: + +:: + + cd $DARTROOT/diagnostics/matlab + module load matlab + matlab -nodesktop + +Within Matlab declare the following variables, then run the script +**plot_obs_netcdf.m** as follows below being sure to modify the +``fname`` variable for your specific case. + +:: + + >> fname = '$BASEDIR/output/2017042712/obs_epoch_029.nc'; + >> ObsTypeString = 'RADIOSONDE_TEMPERATURE'; + >> region = [200 330 0 90 -Inf Inf]; + >> CopyString = 'NCEP BUFR observation'; + >> QCString = 'DART quality control'; + >> maxgoodQC = 2; + >> verbose = 1; % anything > 0 == 'true' + >> twoup = 1; % anything > 0 == 'true' + >> plotdat = plot_obs_netcdf(fname, ObsTypeString, region, CopyString, QCString, maxgoodQC, verbose, twoup); + +Below is an example of the figure produced by **plot_obs_netcdf.m**. +Note that the top panel includes both the 3-D location of all possible +``RADIOSONDE_TEMPERATURE`` observations, which are color-coded based upon +the temperature value. The bottom panel, on the other hand, provides only +the location of the observations that were rejected by the assimilation. +The color code indicates the reason for the rejection based on the +:doc:`DART quality control (QC). <../../../guide/dart-quality-control>` +In this example observations were rejected based on violation of the +outlier threshold (QC = 7), and forward operator failure (QC = 4). +Text is included within the figures that give more details regarding the +rejected observations (bottom left of figure), and percentage of observations +that were rejected (flagged, located within title of figure). + + ++-------------------------------------------------------------+ +| |radiosonde_obs| | ++-------------------------------------------------------------+ + +.. Tip:: + The user can manually adjust the appearance of the data by accessing the + 'Rotate 3D' option either by clicking on the top of the figure or through + the menu bar as Tools > Rotate 3D. Use your cursor to rotate the map to the + desired orientation. + + +For the next figure (below) the same steps are taken as described +above, however, the observation type (``ObsTypeString``) is set to +``METAR_TEMPERATURE_2_METER``. Notice in this case the observations +are limited to near the land surface. This is because the vertical location +of this observation type was defined to be at the land surface +(VERTISSURFACE), as opposed to the ``RADIOSONDE_TEMPERATURE`` observation +in which the vertical location was defined as pressure (VERTISPRESSURE). The +vertical coordinate system is defined in the ``obs_seq.out`` file and +`documented here. `__ + ++-------------------------------------------------------------+ +| |surface_obs| | ++-------------------------------------------------------------+ + + +Next we will demonstrate the use of the **link_obs.m** script which +provides visual tools to explore how the observations impacted the +assimilation. The script generates 3 different figures which includes +a unique linking feature that allows the user to identify the features +of a specific observation including physical location, QC value, and +prior/posterior estimated values. In the example below the 'linked' +observation appears 'red' in all figures. To execute **link_obs.m** do the +following within Matlab being sure to modify ``fname`` for your case: + +:: + + >> clear all + >> close all + >> fname = '$BASEDIR/output/2017042712/obs_epoch_029.nc'; + >> ObsTypeString = 'RADIOSONDE_TEMPERATURE'; + >> region = [200 330 0 90 -Inf Inf]; + >> ObsCopyString = 'NCEP BUFR observation'; + >> CopyString = 'prior ensemble mean'; + >> QCString = 'DART quality control'; + >> global obsmat; + >> link_obs(fname, ObsTypeString, ObsCopyString, CopyString, QCString, region) + + + ++-----------------------------------+------------------------------+ +| |linkobs1| | |linkobs2| | ++-----------------------------------+------------------------------+ + + +.. Tip:: + To access the linking feature, click near the top of the figure such + that a list of icons appear. Next click on the 'brush data' icon then + click on a data point you wish to link. It will appear red. Alternatively + you can access the brush tool through the menu bar (Tools > Brush). + + +Another useful application of the **link_obs.m** script is to visually identify +the improvement of the model estimate of the observation through the 1:1 plot. +One way to do this is to compare the prior and posterior model estimate of the +either the ensemble mean or a single ensemble member. In the example figures below, +a 1:1 plot was generated for the prior and posterior values for ensemble member 3. +(Left Figure: ``CopyString = 'prior ensemble member 3'`` and Right Figure: +``CopyString = posterior ensemble member 3'``). Note how the prior member +estimate (left figure) compares less favorably to the observations as compared +to the posterior member estimate (right figure). The improved alignment +(blue circles closer to 1:1 line) between the posterior estimate and the observations +indicates that the DART filter update provided an improved representation of the +observed atmospheric state. + ++-------------------------+-------------------------+ +| |oneline1| | |oneline2| | ++-------------------------+-------------------------+ + +So far the example figures have provided primarily qualitative estimates +of the assimilation performance. The next step demonstrates how to apply more +quantitative measures to assess assimilation skill. + + +Quantification of model-observation mismatch and ensemble spread +---------------------------------------------------------------- + +The **plot_rmse_xxx_profile.nc** script is one of the best tools to evaluate +assimilation performance across a 3-D domain such as the atmosphere. +It uses the **obs_diag_output.nc** file as an input to generate RMSE, +observation acceptance and other statistics. Here we choose the ensemble +‘total spread’ statistic to plot alongside RMSE, however, you can choose +other statistics including 'bias', 'ens_mean' and 'spread'. For a full +list of statistics perform the command ``ncdump -v CopyMetaData obs_diag_output.nc``. + +:: + + >> fname ='$BASEDIR/output/2017042712/obs_diag_output.nc'; + >> copy = 'totalspread'; + >> obsname = 'RADIOSONDE_TEMPERATURE'; + >> plotdat = plot_rmse_xxx_profile(fname,copy,'obsname',obsname) + + ++-------------------------------------------------------------+ +| |profile1| | ++-------------------------------------------------------------+ + +Note in the figure above that the prior RMSE and total spread values +(solid black and teal lines) are significantly greater than the posterior +values (dashed black and teal lines). This is exactly the behavior we would +expect (desire) because the decreased RMSE indicates the posterior model +state has an improved representation of the atmosphere. It is common for +the introduction of observations to also reduce the ‘total spread’ because +the prior ensemble spread will compress to better match the observations. +In general, it is preferable for the magnitude of the total spread to be +similar to the RMSE. If there are strong departures between the total spread +and RMSE this suggests the adaptive inflation settings may need to be adjusted +to avoid filter divergence. Note that these statistics are given for each +pressure level (1-11) within the WRF model. Accompanying each level is also +the total possible (pink circle) and total assimilated (pink asterisk) observations. +Note that for each level the percentage of assimilated observations is +quite high (>90%). This high acceptance percentage is typical of a high-quality +assimilation and consistent with the strong reduction in RMSE. + + +The same plot as above is given below except for the observation type: +``RADIOSONE_SPECIFIC_HUMIDITY``. + ++-------------------------------------------------------------+ +| |profile2| | ++-------------------------------------------------------------+ + + + +Although the plot_rmse_xxx_profile.m script is valuable for visualizing +vertical profiles of assimilation statistics, it doesn’t capture the temporal +evolution. Temporal evolving statistics are valuable because the skill of an +assimilation often begins poorly because of biases between the model and observations, +which should improve with time. Also the quality of the assimilation may change +because of changes in the quality of the observations. In these cases the +**plot_rmse_xxx_evolution.m** script is used to illustrate temporal changes in +assimilation skill. To generate the figures below the following matlab commands were used: + +:: + + >> fname = '$BASEDIR/output/2017042712/obs_diag_output.nc'; + >> copy = 'totalspread'; + >> obsname = 'RADIOSONDE_TEMPERATURE'; + >> plotdat = plot_rmse_xxx_evolution(fname,copy,'obsname',obsname,'level',3); + +.. NOTE:: + The figures below only evaluate two different assimilation + cycles (hour 6 and hour 12 on 4/27/17), thus it is difficult to evaluate the + temporal progression of the assimilation statistics. This is given purely as an + example. Real world assimilations generally span for months and years thus + evaluating temporal evolution of statistics is more straightforward. The x-axis was + also manually adjusted in the figure below. To do this + **plot_rmse_xxx_evolution.m** was edited such that the ``bincenters`` were replaced + with ``datenum`` values when defining ``axlims`` as: + + axlims = [datenum(2017,4,27,2,0,0) datenum(2017,4,27,14,0,0) plotdat.Yrange]; + ++-------------------------------------------------------------+ +| |evolution1| | ++-------------------------------------------------------------+ + +The above figure is evaluated at model level 850hPa ('level',3), whereas +the figure below is generated in the same way except is evaluated at +300 hPa ('level',7) using: +plotdat = plot_rmse_xxx_evolution(fname,copy,'obsname',obsname,'level',7) + + ++-------------------------------------------------------------+ +| |evolution2| | ++-------------------------------------------------------------+ + + +.. Important:: + The example diagnostics provided here are only a subset of the diagnostics + available in the DART package. Please see the web-based diagnostic + :doc:`documentation. <../../../guide/matlab-observation-space>` or + `DART LAB and DART Tutorial `__ + for more details. + + + +Generating the obs_diag_output.nc and obs_epoch*.nc files manually **[OPTIONAL]** +--------------------------------------------------------------------------------- + +This step is optional because the WRF-DART Tutorial automatically generates +the diagnostic files (obs_diag_output.nc and obs_epoch_*.nc). However, these +files were generated with pre-set options (e.g. spatial domain, temporal bin size etc.) +that you may wish to modify. Also, it is uncommon to generate these diagnostics +files automatically for a new assimilation application. Therefore this section +describes the steps to generate the diagnostic files directly from the DART scripts +by using the WRF Tutorial as an example. + + +Generating the obs_epoch*.nc file +------------------------------------ + +:: + + cd $DARTROOT/models/wrf/work + +Generate a list of all the **obs_seq.final** files created by the assimilation +step (filter step). This command creates a text list file. + +:: + + ls /glade/scratch/bmraczka/WRF_DART_Tut4/output/2017*/obs_seq.final > obs_seq_tutorial.txt + +The DART exectuable **obs_seq_to_netcdf** is used to generate the obs_epoch +type files. Modify the ``obs_seq_to_netcdf`` and ``schedule`` namelist settings +(using a text editor like `vi`) with the **input.nml** file to specify the spatial domain +and temporal binning. The values below are intended to include the entire time +period of the assimilation. + +:: + + &obs_seq_to_netcdf_nml + obs_sequence_name = '' + obs_sequence_list = 'obs_seq_tutorial.txt', + lonlim1 = 0.0 + lonlim2 = 360.0 + latlim1 = -90.0 + latlim2 = 90.0 + verbose = .false. + / + + &schedule_nml + calendar = 'Gregorian', + first_bin_start = 1601, 1, 1, 0, 0, 0, + first_bin_end = 2999, 1, 1, 0, 0, 0, + last_bin_end = 2999, 1, 1, 0, 0, 0, + bin_interval_days = 0, + bin_interval_seconds = 21600, + max_num_bins = 1000, + print_table = .true + / + +Finally, run the exectuable: + +:: + + ./obs_seq_to_netcdf + + +Generating the obs_diag_output.nc file +----------------------------------------- + +:: + + cd $DARTROOT/models/wrf/work + +The DART exectuable **obs_diag** is used to generate the obs_diag_output +files. Modify the ``obs_diag`` namelist settings +(using a text editor like `vi`) with the **input.nml** file to specify the spatial domain +and temporal binning. Follow the same steps to generate the **obs_seq_tutorial.txt** +file as described in the previous section. + +:: + + &obs_diag_nml + obs_sequence_name = '', + obs_sequence_list = 'obs_seq_tutorial.txt', + first_bin_center = 2017, 4, 27, 0, 0, 0 , + last_bin_center = 2017, 4, 27, 12, 0, 0 , + bin_separation = 0, 0, 0, 6, 0, 0 , + bin_width = 0, 0, 0, 6, 0, 0 , + time_to_skip = 0, 0, 0, 0, 0, 0 , + max_num_bins = 1000, + Nregions = 1, + lonlim1 = 0.0, + lonlim2 = 360.0, + latlim1 = 10.0, + latlim2 = 65.0, + reg_names = 'Full Domain', + print_mismatched_locs = .false., + verbose = .true. + / + +Finally, run the exectuable: + +:: + + ./obs_diag + + If you encounter difficulties setting up, running, or evaluating the system performance, please consider using the `GitHub Issue `__ facility or feel free to contact us at dart(at)ucar(dot)edu. -Agenda from the 22 Jan 2014 tutorial ------------------------------------- +Additional materials from previous in-person tutorials +------------------------------------------------------ -- Introduction (Anderson) - `DART Lab +- Introduction - `DART Lab materials <../../../guide/DART_LAB/DART_LAB.html>`__ -- WRF/DART basic building blocks (Romine) +- WRF/DART basic building blocks -`slides `__ (some material is outdated) -- Computing environment support (Collins) +- Computing environment support -`slides `__ -- WRF/DART application examples (Romine) +- WRF/DART application examples -`slides `__ (some material is outdated) -- Observation processing (Collins) +- Observation processing -`slides `__ -- DART diagnostics (Hoar) - :doc:`observation diagnostics <../../../guide/matlab-observation-space>` +- DART diagnostics - :doc:`observation diagnostics <../../../guide/matlab-observation-space>` More Resources @@ -958,4 +1364,51 @@ More Resources MATLAB `__ to use with DART. - `WRF model users page `__ -- Need help? e-mail dart (at) ucar (dot) edu + +.. |ncview1| image:: ../../../guide/images/WRF_tutorial_ncview1.png + :height: 300px + :width: 100% + +.. |ncview2| image:: ../../../guide/images/WRF_tutorial_ncview2.png + :height: 300px + :width: 100% + +.. |radiosonde_obs| image:: ../../../guide/images/WRF_tutorial_radiosonde_obs.png + :height: 300px + :width: 100% + +.. |surface_obs| image:: ../../../guide/images/WRF_tutorial_surface_obs.png + :height: 300px + :width: 100% + +.. |linkobs1| image:: ../../../guide/images/WRF_tutorial_linkobs1.png + :height: 300px + :width: 100% + +.. |linkobs2| image:: ../../../guide/images/WRF_tutorial_linkobs2.png + :height: 300px + :width: 100% + +.. |oneline1| image:: ../../../guide/images/WRF_tutorial_oneline1.png + :height: 300px + :width: 100% + +.. |oneline2| image:: ../../../guide/images/WRF_tutorial_oneline2.png + :height: 300px + :width: 100% + +.. |profile1| image:: ../../../guide/images/WRF_tutorial_profile1.png + :height: 300px + :width: 100% + +.. |profile2| image:: ../../../guide/images/WRF_tutorial_profile2.png + :height: 300px + :width: 100% + +.. |evolution1| image:: ../../../guide/images/WRF_tutorial_evolution1.png + :height: 300px + :width: 100% + +.. |evolution2| image:: ../../../guide/images/WRF_tutorial_evolution2.png + :height: 300px + :width: 100%