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  • PALM-4U THF Forest Study - Overview

    Aim of the Study

    This study aims to understand the thermal influence of an urban forest tree canopy using the LES model PALM. The study analyses different spatial densities of tree spacing to assess which density brings most daytime/ nighttime cooling/ heating due to the shading of the tree canopy and the evapotranspiration effect. 


    PALM-4U Simulation Domain

    Tempelhofer Feld Simulation Domain

  • COSMO Weather Data


    COSMO Data Acquisition

    The COSMO D2 analysis data that was use to produce the dynamic_driver data for PALM was obtained via the online Pamore API service.


    "-flow" data request:

    The command: pamore -d 2018080600 -de 2018081100 -model cd2_ana -lt ass -suffix "-flow"


    Retrieved the following data:

    QNV-request oflxd21.8cc8427d6b8026c1a7dc59f0a595bff0003 ended successfully

    command: pamore -d 2018080600 -de 2018081100 -model cd2_ana -lt ass -suffix "-flow"

    location of the data - host:            download.dwd.de
                           directory:       pub/Pamore/oflxd21.8cc8427d6b8026c1a7dc59f0a595bff0003
                           available until: 17.10.2023

                           link:            https://download.dwd.de/pub/Pamore/oflxd21.8cc8427d6b8026c1a7dc59f0a595bff0003

    ACCOUNTING of QNV-DATABASE-REQUEST
    ----------------------------------
    req-ID                                      user           sended              execute       realtime dbreq  gribs    MByte pamore-command
    ------------------------------------------- -------- ------------------- ------------------- -------- ----- ------ -------- --------------
    oflxd21.8cc8427d6b8026c1a7dc59f0a595bff0003 xxxxxxxx 09.10.2023 16:43:09 12.10.2023 03:25:12      169   121  92969    79153 '-d 2018080600 -de 2018081100 -model cd2_ana -lt ass -suffix "-flow"'

      

    "-soiltype" Data Request

    The command: pamore -d 2018080600 -hstop 0 -ee SOILTYP -model cd2 -lt ass -suffix "-soiltype"


    Retrieved the following data:

    QNV-request oflxd21.76cd14673b8dcbb1fdf43903aa38345e000 ended successfully

    command: pamore -d 2018080600 -hstop 0 -ee SOILTYP -model cd2 -lt ass -suffix "-soiltype"

    location of the data - host:            download.dwd.de
                           directory:       pub/Pamore/oflxd21.76cd14673b8dcbb1fdf43903aa38345e000
                           available until: 16.10.2023

                           link:            https://download.dwd.de/pub/Pamore/oflxd21.76cd14673b8dcbb1fdf43903aa38345e000

    ACCOUNTING of QNV-DATABASE-REQUEST
    ----------------------------------
    req-ID                                      user           sended              execute       realtime dbreq  gribs    MByte pamore-command
    ------------------------------------------- -------- ------------------- ------------------- -------- ----- ------ -------- --------------
    oflxd21.76cd14673b8dcbb1fdf43903aa38345e000 xxxxxxxx 09.10.2023 16:12:17 11.10.2023 02:29:32        2     1      1        0 '-d 2018080600 -hstop 0 -ee SOILTYP -model cd2 -lt ass -suffix "-soiltype"'


    "-hhl" Data Request

    The command: pamore -d 2018080600 -hstop 0 -ee SOILTYP -model cd2 -lt ass -suffix "-soiltype"


    Retrieved the following data:

    QNV-request oflxd21.46795a029091707a73ac2458292f83e9002 ended successfully
    command: pamore -d 2018080600 -ee HHL -model cd2 -lt ass -suffix "-hhl"

    location of the data - host:            download.dwd.de
                           directory:       pub/Pamore/oflxd21.46795a029091707a73ac2458292f83e9002
                           available until: 14.10.2023

                           link:            https://download.dwd.de/pub/Pamore/oflxd21.46795a029091707a73ac2458292f83e9002

    ACCOUNTING of QNV-DATABASE-REQUEST
    ----------------------------------
    req-ID                                      user           sended              execute       realtime dbreq  gribs    MByte pamore-command
    ------------------------------------------- -------- ------------------- ------------------- -------- ----- ------ -------- --------------
    oflxd21.46795a029091707a73ac2458292f83e9002 xxxxxxxx 06.10.2023 14:06:32 09.10.2023 09:16:42        3     2    132      138 '-d 2018080600 -ee HHL -model cd2 -lt ass -suffix "-hhl"'


    INIFOR Data Processing

    The data was then processed using the INIFOR pre-processor native to PALM


    The following command produced the thf_base_2018080700_dynamic file:

    inifor --path /mnt/d/phd/thf/data/cd2_ana/download/nc/flow --date 2018080700 --init-mode profile --soil-init-mode volume -s /mnt/d/phd/thf/data/cd2_ana/download/nc/flow/soil.nc -t /home/joshuabl/palm/current_version/JOBS/thf_base/INPUT/thf_base_static -n /home/joshuabl/palm/current_version/JOBS/thf_base/inifor/namelist -o /home/joshuabl/palm/current_version/JOBS/thf_base/INPUT/thf_forest_5m_dynamic.nc --soil-prefix laf_ --input-prefix laf_


    Generate the Validation Plot

    Below shows a comparison of air temperature values for the PALM baseline simulation, DWD weather data, and PALM dynamic_driver (COSMO D2 analysis) Here is the file the reproduce the plot below: thf_forest_dwd_validation.ipynb 


    Air temperature validation plot with dynamic_driver data added.

    COSMO Data Download:


    • Simulation Setup


      Domain Size

      Number of grid cells=nx, ny, nz
      Grid cell size=dx, dy, dz


      Parent domain:

      &initialization_parameters
          nx = 399,
          ny = 399,
          nz = 40,
          dx = 10.0,
          dy = 10.0,
          dz = 10.0,
          dz_stretch_level = 130.0,
          dz_stretch_factor = 1.1,
          dz_max = 50.0,


      Child Domain:

      &initialization_parameters
          nx = 199,
          ny = 199,
          nz = 50,
          dx = 2.0,
          dy = 2.0,
          dz = 2.0,

      Different Tree Spacing Cases

      Below is a list of all the case scenarios of urban forest that were generated for the study. The naming convention of the files doesn't actually match the target spacing due to a logic in the tree placement script. This will be updated in the final dataset.

      1. thf_base_2018080700 = the original case scenario (no trees added to the static_driver file)
      2. thf_forest_05m = 10m spacing trunk to trunk
      3. thf_forest_10m = 15m spacing trunk to trunk
      4. thf_forest_25m = 20m spacing trunk to trunk
      5. thf_forest_30m = 25m spacing trunk to trunk
      6. thf_forest_35m = 30m spacing trunk to trunk
      7. thf_forest_40m = 35m spacing trunk to trunk

      Plant Canopy Model Setup - Tree placing script

      A Python script was made that adds tree based on a i,j (x,y) coordinate. 

      Here is the modify_static_driver_JBL.py Python script

      Here is the palm_csd_canopy_generator.py dependency needed to run modify_static_driver_JBL.py.


      Below show the first three lines of a CSV data array for tree locations and tree parameters to be added to the static_driver file:


      Parent domain:

      i,j,height,type,tree_dia,trunk_dia,tree_lai
      123,229,20,82,10,1,3
      123,227,20,82,10,1,3
      123,226,20,82,10,1,3

      Here is a Python Notebook to calculate the LAI form LAD values in the static_driver file: calculate_lai_from_lad_values.ipynb
      The total LAI for tree ID 15935 is: 3.138277292251587
      The average LAI per contributing grid cell for tree ID 15935 is: 1.5691386461257935

      Child domain:

      i,j,height,type,tree_dia,trunk_dia,tree_lai
      111,4,20,82,10,1,3
      110,11,20,82,10,1,3
      106,4,20,82,10,1,3

      Here is a Python Notebook to calculate the LAI form LAD values in the static_driver file: calculate_lai_from_lad_values.ipynb
      The total LAI for tree ID 180 is: 28.538515090942383
      The average LAI per contributing grid cell for tree ID 180 is: 0.3658783986018254

      Parent Domain


      thf_forest_static_gif

      # Define the spacing and the corresponding number of tree points
      spacing = [5, 10, 15, 20, 25, 30, 35, 40]  # in meters
      tree_points = [16450, 7391, 4161, 2664, 1880, 1376, 1069, 835]


      Child Domain (N02)


      thf_forest_static_N02_gif


      # Define the spacing and the corresponding number of tree points
      spacing = [5, 10, 15, 20, 25, 30, 35, 40]  # in meters
      tree_points = [627, 288, 156, 107, 72, 57, 40, 34]


      • Validation

        Weather Station vs PALM Simulation 

        Air temperature validation of DWD weather station data:


        station_id
        dataset parameter date value quality from_date to_date height latitude longitude name state
        00433
        temperature_air
        temperature_air_mean_200
        2018-08-07 00:00:00+00:00
        293.55 3.0 1951-01-01 00:00:00+00:00
        2024-01-31 00:00:00+00:00 48.0 52.4676
        13.402
        Berlin-Tempelhof
        Berlin

         

        Validation Plot

        The following figure shows air temperature (degrees celsius) over two duranial cycles from the date 2018-08-07 00:00:00+00:00 to 2018-08-09 00:00:00+00:00. Here is a link to the Python code to reproduce the plot: thf_forest_dwd_validation.ipynb. The PALM NetCDF file used in the validation plot can be downloaded here: thf_base_2018080700_av_3d_merged.nc

        Spatial Details of the horizontal slice

        latitude = 52.4676
        longitude = 13.402

        x_index = 191 # Grid Cells
        y_index = 138 # Grid Cells
        z_index = 3   # Grid Cells (first vertical grid cell above the ground due to terrain)

        Air temperature validation of DWD weather station data vs PALM simulation

        Air temperature validation plot with dynamic_driver data added.

        Discussion 

        As you can see there is an acceptable fit between the Tempelhofer Feld weather station and the PALM baseline simulation. Note that the DWD weather (orange line)  contains one extra timestep at the start of the time series 2018-08-07 00:00:00+00:00 compared with the PALM baseline simulation (blue line). This is due to the fact that PALM was set to output data after the first time step, in this case 2018-08-07 01:00:00+00:00 (1am). 

        The PALM simulation displays some latency behind the DWD weather data. This could be due to an a spatial temporal difference as the PALM domain contains a 10m terrain step near the site of the weather station. However, the sensor is upwind from the terrain step in the simulation domain and should not have any significant influence on the results. Another explanation could be due to insufficient surface spinup time (48hrs) of the PALM model surfaces. Therefore introducing some latency to reach real world temperatures. 


        OUTPUT Files:

        • Results

          Comparison Plot

          Please be aware that only case "thf_base_2018080700" contains the OUTPUT data directory. This is due to the size of each case (64G) and data storage constraints. However validation analysis can be undertaken using the "thf_base_2018080700" case.


          The following figure shows air temperature (degrees celsius) over two duranial cycles from the date 2018-08-07 00:00:00+00:00 to 2018-08-09 00:00:00+00:00. This time all tree spacing cases have been included in the plot to cross compare the results. 

          Here is a link to the Python code to reproduce the plot: thf_forest_ta_case_comparison.ipynb

          The location of the validation point was set to (DWD weather station):

          x_index = 191 # Grid Cells
          y_index = 138 # Grid Cells
          z_index = 3   # Grid Cells

          A comparison plot of air temperature again the DWD weather data and PALM simulations

          Discussion

          This result must be taken with much caution as full validation of the PALM Plant Canopy Model (PMC) has not yet been validated. The following discussion is just speculation based on preliminary results. I encourage the PALM developers involved in the PMC to engage in this discussion to help validate the result. 

          The results show that increasing tree density lowers nighttime temperature and increases daytime temperatures, compared with the baseline (blue line) and weather station data (grey line). Some explanation for the exponential nighttime cooling effect, for example the low temperatures at 08-08-00, case 05m (10m tree spacing trunk to trunk - pink line), in comparison to the other cases might be due to the exponential increase in trees, thus more shading and evapotranspiration effect as can be seen by the exponential curve of trees added at each density in following figure:



          Potential Sources of Error

          One potential issue that might cause hightended cooling of nighttime air temperature in the tree canopy is the following setting in the p3d file: 

           &bulk_cloud_parameters
              cloud_scheme = 'kessler',
              cloud_water_sedimentation = .T.,
           
          Another case without the cloud model is needed to be run in order to rule out this possible cause of unrealistically low air temperatures.

          Another source of error could be due to using the single trees in a domain with large grid spacing (10m in this case). It is recommended in the PALM documentation to only use single tree with LAD and BAD profiles when the level of detail (LOD1) is less than a 1m grid resolution. Although, the same air temperatures can be found in the child domain (N02). Suggesting that grid sensitivity to the single trees in PALM is not the main cause of error. This cannot be proven until another case is run with a 1m grid resolution in the child domain.

          Specifying the full range of tree options via the palm_csd Python script is needed to make sure the trees in the study are specified correctly. Below is a list of possible single tree options available:

          Index |=Species Shape Crown height/width ratio(*) Crown diameter (m) Height (m) LAI summer(*) LAI winter(*) Height of maximum LAD (m)(*) LAD/BAD ratio(*) DBH (m)
          0 Default 1.0 1.0 4.0 12.0 3.0 0.8 0.6 0.025 0.35
          1 Abies 3.0 1.0 4.0 12.0 3.0 0.8 0.6 0.025 0.80
          2 Acer 1.0 1.0 7.0 12.0 3.0 0.8 0.6 0.025 0.80


          Currently only the following tree options have been switched on as you can see in this example CSV array:

          i,j,height,type,tree_dia,trunk_dia,tree_lai
          123,229,20,82,10,1,3

          Crown height/width ratio(*), DBH, Height of maximum LAD (m)(*), LAD/BAD ratio(*) and DBH (m) are still yet to be utilised!

          Feedback from the PALM developers and personnel responsible for maintaining the PALM Plant Canopy Model and palm_csd Python Processor would be most welcome. I believe that a thorough investigation and validation of the PMC would also be beneficial to the PALM community and scientific users.


          • Case Download

            Download Files

            All the data for this study is openly available via the following links for reproducibility:

            Please be aware that only case "thf_base_2018080700" contains the OUTPUT data directory. This is due to the size of each case (64G) and data storage constraints. However validation analysis can be undertaken using the "thf_base_2018080700" case.