Merge pull request #49 from thijsheus/notebook_thijs

Path fix and MicroHH tutorial

_toc.yml

@@ -35,6 +35,7 @@ parts:
         - file: tutorials/xarray/xwrf-xarray-intro
         - file: tutorials/comble/comble-mip-tutorial
         - file: tutorials/emc2/InstrumentSimulatorsForModelEvaluation.ipynb
+        - file: tutorials/microhh/run_microhh
         - file: tutorials/microhh/analyze_microhh
         - file: tutorials/machine_learning/ARM_DQO_Spike_Detection
         - file: tutorials/pyart/sail_qpe_grid

tutorials/microhh/analyze_microhh.ipynb

@@ -44,7 +44,7 @@
    "outputs": [],
    "source": [
     "# locate the folder where the data is stored\n",
-    "basedir = '/data/lasso/SGP/SGP_20160611/'\n",
+    "basedir = '/data/project/ARM_Summer_School_2024_Data/summerschool_microhh/'\n",
     "basename = 'SGP'\n",
     "NC_arr = [10, 50, 80, 100, 200, 400, 800]\n"
    ]

tutorials/microhh/run_microhh.md

@@ -0,0 +1,63 @@
+Running MicroHH
+-------
+
+MicroHH is a computational fluid dynamics code made for Direct Numerical Simulation (DNS) and Large-Eddy Simulation of turbulent flows in the atmospheric boundary layer. The code is written in C++.
+
+A tutorial and documentation is available at: https://microhh.readthedocs.io/en/latest/.
+
+MicroHH is described in detail in [Van Heerwaarden et al. (2017)](http://www.geosci-model-dev-discuss.net/gmd-2017-41/#discussion).
+
+Downloading the code
+--------------------
+General information to download the code from GitHub can be found here:
+    https://github.com/microhh/microhh/blob/main/README.md
+
+For this tutorial, we will use Thijs' fork, and in particular the `lagtraj` branch:
+        git clone --recurse-submodules https://github.com/thijsheus/microhh.git
+
+More details on how to compile and setup the code on your own can be found in the main README
+
+Logging in to OSC
+-----------------
+
+To run this tutorial, we first log in on the Ohio Super Computer through:
+    ondemand.osc.edu
+and log in with the username that you got before the workshop.
+
+From the side bar, select the *Ascend Desktop* to get in-browser access to the supercomputer.
+
+Give the app a moment to start up, open it, and open a VNC window.
+
+Quick Start to Running MicroHH
+------------------------------
+
+At the desktop, open a terminal and navigate to the summerschool folder:
+
+    cd /fs/project/PFS0220/summerschool
+make your own folder, and copy all relevant data to your own folder:
+
+    cp template/* <yourname>/
+and move to your own folder.
+
+To submit a quick simulation to the supercomputer, you can submit a job to the queue:
+    sbatch SGP.slurm
+
+
+Changing the input parameters
+-----------------------------
+The input parameters are in `SGP.ini`. Feel free to browse through and look at what can be easily changed. More info on individual options is available on 
+https://microhh.readthedocs.io/en/latest/
+
+
+After the simulation is done, you can evaluate the results, for instance with the `analyze_microhh.ipynb` script.
+
+Selecting particular ERA5 use cases (Advanced and Experimental):
+---------------------
+The eulerian_lagtraj.py code is based on the lagtraj Python package and pulls ERA5 data to drive the LES model. This is a bit too time consuming for the current tutorial, but the gist is as follows:
+
+1. Open `config.yaml` to set the location, time, name, etc. Note that you can elect to use a Eulerian (fixed in space) setup, or a Lagrangian (moving along with the atmospheric flow) setup. A Lagrangian setup over land is not recommended.
+1. Open `SGP.ini.base` to setup the case properties, such as domain size, grid points, etc. You can fill out `None` for anything that you want the system to decide
+1. Run the python script: `python eulerian_lagtraj.py`
+1. Initialize MicroHH following the instructions above.
+
+