14 files changed, 927 insertions, 0 deletions
diff --git a/metchart/aggregator/__init__.py b/metchart/aggregator/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/metchart/aggregator/__init__.py
diff --git a/metchart/aggregator/dwd_icon.py b/metchart/aggregator/dwd_icon.py
new file mode 100755
index 0000000..ed5c149
--- /dev/null
+++ b/metchart/aggregator/dwd_icon.py
@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+
+import requests
+import datetime
+import pytz
+import requests
+import os
+
+from multiprocessing import cpu_count
+from multiprocessing.pool import ThreadPool
+
+import subprocess
+
+import xarray as xr
+
+from . import misc
+
+BASE='https://opendata.dwd.de/weather/nwp'
+
+def get_current_run():
+    # we allow up to 3h of slack for DWD to upload the latest run
+    tz = pytz.timezone('UTC')
+    now = datetime.datetime.now(datetime.timezone.utc)
+    corrected = now - datetime.timedelta(hours=3)
+
+    run = int(corrected.hour / 6) * 6
+
+    return (f'{run:02d}', corrected.strftime('%Y%m%d'))
+
+def download_url(args):
+    url, dest = args
+    r = requests.get(url)
+    try:
+        with open(dest, 'wb') as f:
+            f.write(r.content)
+        print(f'Downloaded {dest}')
+    except Exception as e:
+        print(f'Failed to download {dest}:\n', e)
+
+def unpack_bz2(dest):
+    res = subprocess.run(['bzip2', '-df', dest])
+    if res.returncode != 0:
+        print(f'There was an error unpacking {dest}:', res.stderr)
+
+def download_dwd_gribs(
+        date, run, target, output, model, steps, model_long,
+        pressure_level_parameters, parameter_caps_in_filename,
+        single_level_parameters, pressure_levels
+):
+    misc.create_output_dir(output)
+
+    to_download = []
+
+    for step in steps:
+        step_str = f'{step:03d}'
+
+        for parameter in pressure_level_parameters:
+            parameter2 = parameter.upper() if parameter_caps_in_filename else parameter
+
+            for level in pressure_levels:
+                filename = f'{model_long}_regular-lat-lon_pressure-level_{date}{run}_{step_str}_{level}_{parameter2}.grib2.bz2'
+                URL = f'{BASE}/{model}/grib/{run}/{parameter}/{filename}'
+
+                to_download.append((URL, os.path.join(output, filename)))
+
+        for parameter in single_level_parameters:
+            parameter2 = parameter.upper() if parameter_caps_in_filename else parameter
+            filename = f'{model_long}_regular-lat-lon_single-level_{date}{run}_{step_str}_{parameter2}.grib2.bz2'
+            URL = f'{BASE}/{model}/grib/{run}/{parameter}/{filename}'
+
+            to_download.append((URL, os.path.join(output, filename)))
+
+
+    for _ in ThreadPool(cpu_count()).imap_unordered(download_url, to_download):
+        pass
+
+    print('Done Downloading. Uncompressing...')
+
+    for _ in ThreadPool(cpu_count()).imap_unordered(unpack_bz2, [dest for _, dest in to_download]):
+        pass
+
+    downloaded_gribs = [dest.removesuffix('.bz2') for _, dest in to_download]
+
+    res = subprocess.run(['grib_copy'] + downloaded_gribs + [target])
+    if res.returncode != 0:
+        print('grib_copy failed with: ', res.stderr)
+
+    res = subprocess.run(['rm', '-f'] + downloaded_gribs)
+    if res.returncode != 0:
+        print('rm failed with: ', res.stderr)
+
+def clean_output_dir(directory, target):
+    to_delete = [f for f  in os.listdir(directory) if os.path.isfile(os.path.join(directory, f))]
+    if target in to_delete:
+        del to_delete[to_delete.index(target)]
+
+    for f in to_delete:
+        os.unlink(os.path.join(directory, f))
+
+def load_data(name, output, description = None, clean = False, force_filename = None, **kwargs):
+    target = force_filename
+
+    if target is None:
+        run, date = get_current_run()
+        filename = f'{name}_{date}_{run}.grib2'
+        target = os.path.join(output, filename)
+
+        if not os.path.exists(target):
+            download_dwd_gribs(date, run, target, output, **kwargs)
+        else:
+            print(f'{target} already exists. Using the cached version.')
+
+        if clean:
+            clean_output_dir(output, filename)
+
+    # we drop heightAboveGround to allow 2m and 10m values to be merged down to one dataset
+    ds = xr.load_dataset(target, engine='cfgrib', drop_variables='heightAboveGround')
+
+    if description is not None:
+        ds.attrs['_description'] = description
+    return ds
+
+
+debug_config = {
+    'output':'dwd_icon-eu',
+    'model':'icon-eu',
+    'model_long':'icon-eu_europe',
+    'clean': True,
+    'parameter_caps_in_filename':True,
+    'pressure_level_parameters': [
+        't',
+        'relhum',
+        'u',
+        'v',
+        'fi',
+        'clc'
+    ],
+    'single_level_parameters': [
+        'pmsl',
+        't_2m',
+        'relhum_2m'
+    ],
+    'pressure_levels':[ 1000, 950, 925, 900, 875, 850, 825, 800, 775, 700, 600, 500, 400, 300, 250, 200, 150, 100 ],
+    'steps':[0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48]
+}
+
+if __name__ == '__main__':
+    load_data('test_icon_eu', **debug_config)
+
diff --git a/metchart/aggregator/misc.py b/metchart/aggregator/misc.py
new file mode 100644
index 0000000..6594d0f
--- /dev/null
+++ b/metchart/aggregator/misc.py
@@ -0,0 +1,23 @@
+import os
+import numpy as np
+import datetime
+
+def np_time_convert(dt64, func=datetime.datetime.utcfromtimestamp):
+    unix_epoch = np.datetime64(0, 's')
+    one_second = np.timedelta64(1, 's')
+    seconds_since_epoch = (dt64 - unix_epoch) / one_second
+
+    return func(seconds_since_epoch)
+
+def np_time_convert_offset(init, step):
+    return np_time_convert(init) + np_time_convert(step, func=lambda x: datetime.timedelta(seconds=x))
+
+def np_time_list_convert_offset(init, steps):
+    return list(map(lambda x: np_time_convert_offset(init, x), steps))
+
+def create_output_dir(path, clear=False):
+    if not os.path.exists(path):
+        os.makedirs(path)
+    elif clear:
+        raise Exception('clear not implemented')
+
diff --git a/metchart/aggregator/wyoming_sounding.py b/metchart/aggregator/wyoming_sounding.py
new file mode 100755
index 0000000..617d462
--- /dev/null
+++ b/metchart/aggregator/wyoming_sounding.py
@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+import os
+import datetime
+import requests
+
+import csv
+
+import xarray as xr
+
+import numpy as np
+
+from metpy.units import units
+import metpy.calc as mpcalc
+
+from .. import misc
+
+def get_current_run():
+    date=(datetime.date.today() - datetime.timedelta(days = 1)).strftime('%Y-%m-%d')
+    # TODO we also want noon
+    hour='23:00:00'
+    return (hour, date)
+
+def download_wyoming_csv(station, date, hour, target):
+    url=f'http://weather.uwyo.edu/cgi-bin/bufrraob.py?datetime={date}%20{hour}&id={station}&type=TEXT:CSV'
+    result = requests.get(url)
+
+    if result.status_code >= 400:
+        raise Exception('Failed to Download sounding csv!')
+
+    with open(target, 'w') as f:
+        f.write(result.text)
+
+def load_wyoming_csv(filepath, hour, date):
+    p = []
+    T = []
+    Td = []
+    wind_speed = []
+    wind_dir = []
+    r = []
+
+    with open(filepath,'r', newline='') as f:
+        reader = csv.reader(f)
+        next(reader) # Skip header
+        for row in reader:
+            if sum(map(lambda s : len(s.strip()) == 0, row)):
+                # skip any line with empty values
+                continue
+
+            if float(row[3]) in p: # Skip double p entries
+                continue
+
+            p.append(float(row[3]))
+            T.append(float(row[5]))
+            Td.append(float(row[6]))
+            r.append(float(row[8]))
+            wind_speed.append(float(row[12]))
+            wind_dir.append(float(row[11]))
+
+    T = T * units.degC
+    Td = Td * units.degC
+    wind_speed = wind_speed * units.knots
+    wind_dir = wind_dir * units.degrees
+    u, v = mpcalc.wind_components(wind_speed, wind_dir)
+
+    time = np.datetime64(f'{date}T{hour}')
+
+    # recreate the structure a DWD GRIB produces
+    return xr.Dataset(
+        {
+            "t": (["step", "isobaricInhPa"], [T.to(units.kelvin).magnitude]),
+            "td": (["step", "isobaricInhPa"], [Td.to(units.kelvin).magnitude]),
+            "r": (["step", "isobaricInhPa"], [r]),
+            "u": (["step", "isobaricInhPa"], [u.to('m/s').magnitude]),
+            "v": (["step", "isobaricInhPa"], [v.to('m/s').magnitude]),
+        },
+        coords={
+            "isobaricInhPa":  p,
+            "step": [np.timedelta64(0, 'ns')],
+            "valid_time": (['step'], [time]),
+            "time": time,
+        },
+        attrs={
+            "source": "uwyo.edu",
+        }
+    )
+
+def load_data(name, output, station):
+    hour, date = get_current_run()
+    misc.create_output_dir(output)
+
+    target = os.path.join(output, f'{name}_{date}_{hour}.csv')
+
+    if not os.path.exists(target):
+        download_wyoming_csv(station, date, hour, target)
+    else:
+        print(f'{target} alreasy exists. Using the cached version.')
+
+    return load_wyoming_csv(target, hour, date)
+
+config_debug = {
+    'output': 'wyoming_test',
+    'station': '10548'
+}
+
+if __name__ == '__main__':
+    ds = load_data('test_wyoming_sounding', **config_debug)
+    print(ds)
+    print(ds.coords['step'])
diff --git a/metchart/misc.py b/metchart/misc.py
new file mode 100644
index 0000000..6594d0f
--- /dev/null
+++ b/metchart/misc.py
@@ -0,0 +1,23 @@
+import os
+import numpy as np
+import datetime
+
+def np_time_convert(dt64, func=datetime.datetime.utcfromtimestamp):
+    unix_epoch = np.datetime64(0, 's')
+    one_second = np.timedelta64(1, 's')
+    seconds_since_epoch = (dt64 - unix_epoch) / one_second
+
+    return func(seconds_since_epoch)
+
+def np_time_convert_offset(init, step):
+    return np_time_convert(init) + np_time_convert(step, func=lambda x: datetime.timedelta(seconds=x))
+
+def np_time_list_convert_offset(init, steps):
+    return list(map(lambda x: np_time_convert_offset(init, x), steps))
+
+def create_output_dir(path, clear=False):
+    if not os.path.exists(path):
+        os.makedirs(path)
+    elif clear:
+        raise Exception('clear not implemented')
+
diff --git a/metchart/modifier/__init__.py b/metchart/modifier/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/metchart/modifier/__init__.py
diff --git a/metchart/modifier/merge.py b/metchart/modifier/merge.py
new file mode 100644
index 0000000..1fb7fda
--- /dev/null
+++ b/metchart/modifier/merge.py
@@ -0,0 +1,4 @@
+import xarray as xr
+
+def run(data):
+    return xr.merge(data)
diff --git a/metchart/plotter/__init__.py b/metchart/plotter/__init__.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/metchart/plotter/__init__.py
diff --git a/metchart/plotter/debug_data.py b/metchart/plotter/debug_data.py
new file mode 100644
index 0000000..560d13c
--- /dev/null
+++ b/metchart/plotter/debug_data.py
@@ -0,0 +1,4 @@
+def run(data, **kwargs):
+    print(data)
+
+    return []
diff --git a/metchart/plotter/horizontal.py b/metchart/plotter/horizontal.py
new file mode 100755
index 0000000..89945c3
--- /dev/null
+++ b/metchart/plotter/horizontal.py
@@ -0,0 +1,123 @@
+#!/usr/bin/env python3
+import os
+import json
+
+import xarray as xr
+
+import numpy as np
+import matplotlib.pyplot as plt
+from metpy.plots import MapPanel, PanelContainer, RasterPlot, ContourPlot
+
+from . import misc
+
+config = {
+    'source': 'dwd_icon-eu/combined.grib2',
+    'plots': [
+        {
+            'name':'r_t-750',
+            'area': None,
+            'layers': [
+                {
+                    'layertype': 'raster',
+                    'field': 'r',
+                    'level': 750,
+                },
+                {
+                    'layertype': 'contour',
+                    'field': 't',
+                    'level': 750,
+                    'contours': 5,
+                    'clabels': True
+                },
+            ]
+        },
+    ]
+}
+
+def run(data, plots, output='.'):
+    misc.create_output_dir(output)
+    index = []
+
+    for plot in plots:
+        index.append(_plot(data, output, **plot))
+
+    return index
+
+def _plot(data, output, name, layers, area = None):
+    index = []
+
+    for step in data.coords['step']:
+        this_step = data.sel(step=step)
+
+        map_layers = []
+
+        for layer in layers:
+            map_layers.append(_layer(this_step, **layer))
+
+        valid = misc.np_time_convert(step.valid_time.values)
+        init = misc.np_time_convert(step.time.values)
+
+        valid_str = valid.strftime('%d %b %Y - %HUTC')
+        init_str = init.strftime('%d %b %Y - %HUTC')
+        hours_since_init_str = str(int(this_step.step.values / np.timedelta64(1,'h'))).zfill(2)
+        init_for_filename = init.strftime('%Y-%m-%d-%HUTC')
+
+        panel = MapPanel()
+        if area is not None:
+            panel.area = area
+        panel.projection = 'mer'
+        panel.layers = ['coastline', 'borders']
+        panel.plots = map_layers
+        panel.left_title = f'{name} VALID: {valid_str} (INIT +{hours_since_init_str}) INIT: {init_str}'
+        if '_description' in data.attrs:
+            panel.right_title = data.attrs['_description']
+
+        pc = PanelContainer()
+        pc.size = (12.8, 9.6)
+        #pc.figure.layout='constrained'
+        pc.panels = [panel]
+        pc.draw()
+        #pc.show()
+        outname = f'{name}_{init_for_filename}+{hours_since_init_str}.png'
+        pc.save(os.path.join(output, outname))
+        plt.close('all')
+
+        index.append(
+            {
+                'file': outname,
+                'init': init_str,
+                'valid': valid_str,
+                'valid_offset': hours_since_init_str,
+                'display_name': name,
+                'id': name
+            }
+        )
+
+    with open(os.path.join(output, f'{name}.index.json'), 'w') as f:
+        f.write(json.dumps(index, indent=4))
+
+    return { 'name': name, 'indexfile': f'{name}.index.json', 'list_title': 'INIT+' }
+
+def _layer(data, layertype, **kwargs):
+    layertypes={
+        'raster': {
+            'obj': RasterPlot,
+            'defaults': {
+                'colorbar': 'vertical',
+            }
+        },
+        'contour': {
+            'obj': ContourPlot,
+            'defaults': {}
+        }
+    }
+
+    args = layertypes[layertype]['defaults'] | kwargs
+
+    ret = layertypes[layertype]['obj'](**args)
+    ret.data = data
+
+    return ret
+
+if __name__ == '__main__':
+    run(**config)
diff --git a/metchart/plotter/meteogram.py b/metchart/plotter/meteogram.py
new file mode 100755
index 0000000..8335247
--- /dev/null
+++ b/metchart/plotter/meteogram.py
@@ -0,0 +1,164 @@
+#!/usr/bin/env python3
+import os
+import json
+
+import numpy as np
+
+import matplotlib.pyplot as plt
+
+import metpy.calc as mpcalc
+
+from .. import misc
+
+HEIGHT = 13
+
+def run(data, plots, output='.', name='meteogram'):
+    misc.create_output_dir(output)
+    index = []
+
+    for plot in plots:
+        index.append(_plot(data, output, **plot))
+
+    with open(os.path.join(output, f'{name}.index.json'), 'w') as f:
+        f.write(json.dumps(index, indent=4))
+
+    return [{ 'name': name, 'indexfile': f'{name}.index.json', 'list_title': 'Location' }]
+
+def _get_next_subplot(size, counter=0):
+    ret = (counter + 1, counter + size)
+    counter += size
+    return counter, ret
+
+def _add_cloudcov(ax, data):
+    ax.set_ylabel('Pressure level [hPa]')
+
+    clc = ax.contourf(data.valid_time, data.isobaricInhPa, data.ccl.transpose(), cmap='clcov', vmin=0, vmax=100, levels=9)
+
+    # use Format parameter for n/8
+    plt.colorbar(clc, label='cloudcov', extendfrac=None, ticks=[100*n/8 for n in range(9)], format=lambda x,_: f'{int(x/12.5)}/8', pad=0.0, fraction=0.015)
+
+    cf = ax.contour(data.valid_time, data.isobaricInhPa, data.t.metpy.convert_units('degC').transpose())
+    ax.clabel(cf, inline=True, fontsize=10)
+
+    ax.barbs(
+            data.valid_time,
+            data.isobaricInhPa,
+            data.u.metpy.convert_units('kt').transpose(), 
+            data.v.metpy.convert_units('kt').transpose()
+        )
+
+    ax.invert_yaxis()
+
+def _add_temp_dewpoint(ax, data):
+    ### Temp + Dewpoint
+    ax.plot(data.valid_time, data.t2m.metpy.convert_units('degC').transpose(), color='red', label='Temperature (2m)')
+    ax.plot(data.valid_time, mpcalc.dewpoint_from_relative_humidity(data.t2m, data.r2).transpose(), color='blue', label='Dewpoint (2m)')
+    ax.plot(data.valid_time, data.sel(isobaricInhPa=850.0).t.metpy.convert_units('degC').transpose(), color='grey', label='Temperature (850hPa)')
+    ax.set_ylabel('Temperature [degC]')
+    ax.legend(loc='lower right')
+
+def _add_mslp(ax, data):
+    ax.plot(data.valid_time, data.prmsl.metpy.convert_units('hPa').transpose(), color='black', label='Temperature (2m)')
+    ax.set_ylabel('Mean Sea Level Pressure [hPa]')
+
+def _add_convective_clouds(ax, data):
+    # TODO: ADD HBAS_CON, HTOP_CON
+    # If none: -500m
+    ax.set_ylim(0, 14)
+    ax.set_ylabel('Convective Clouds Height [km]')
+    ax.bar(data.valid_time, alpha=0.5,
+            bottom=data.HBAS_CON.metpy.convert_units('km').transpose(),
+            height=(data.HTOP_CON.metpy.convert_units('km')-data.HBAS_CON.metpy.convert_units('km')).transpose(),
+            align='edge', width=np.timedelta64(3, 'h'))
+
+def _add_precip(ax, data):
+    ax.set_ylabel('Total precipitation [mm]')
+    ax.set_ylim(0, 30)
+    ax.bar(data.valid_time[:-1], data.tp.diff('step').transpose(), width=np.timedelta64(3, 'h'),
+            align='edge', alpha=0.7, color='green')
+
+    ax_p = ax.twinx()
+    ax_p.set_ylabel('Snow depth [m]')
+    ax_p.set_ylim(bottom=0)
+    ax_p.plot(data.valid_time, data.sde.transpose(), color='blue')
+
+def _add_surface_wind(ax, data):
+    ax.plot(data.valid_time, mpcalc.wind_speed(data.u10.transpose(), data.v10.transpose()), color='black', label='Wind (10m)')
+    ax.plot(data.valid_time, data.fg10.transpose(), color='red', label='Gust (10m)')
+
+    ax_b = ax.twinx()
+    ax_b.barbs(
+            data.valid_time,
+            [1 for _ in data.valid_time],
+            data.u10.metpy.convert_units('kt').transpose(), 
+            data.v10.metpy.convert_units('kt').transpose()
+        )
+    ax_b.axis('off')
+
+    ax.set_ylabel('Wind Speed [m/s]')
+    ax.legend(loc='lower right')
+
+def _plot(data, output, name, lat, lon):
+    data = data.sel(latitude=lat, longitude = lon, method='nearest')
+
+    fig = plt.figure(figsize=(12, 12), layout="constrained")
+
+    sp_cnt, spec = _get_next_subplot(4)
+    ax = fig.add_subplot(HEIGHT,1,spec)
+    _add_cloudcov(ax, data)
+
+    sp_cnt, spec2 = _get_next_subplot(2,sp_cnt)
+    ax2 = fig.add_subplot(HEIGHT,1,spec2,sharex=ax)
+    _add_temp_dewpoint(ax2, data)
+
+    sp_cnt, spec3 = _get_next_subplot(2,sp_cnt)
+    ax3 = fig.add_subplot(HEIGHT,1,spec3,sharex=ax)
+    #ax3.legend(loc='lower right')
+    _add_mslp(ax3, data)
+
+    ax4 = ax3.twinx()
+    _add_convective_clouds(ax4, data)
+
+    sp_cnt, spec4 = _get_next_subplot(2,sp_cnt)
+    ax5 = fig.add_subplot(HEIGHT,1,spec4,sharex=ax)
+    _add_precip(ax5, data)
+
+    sp_cnt, spec5 = _get_next_subplot(2,sp_cnt)
+    ax6 = fig.add_subplot(HEIGHT,1,spec5,sharex=ax)
+    _add_surface_wind(ax6, data)
+
+    ### Info Lines
+    sp_cnt, spec5 = _get_next_subplot(1,sp_cnt)
+    ax_text = fig.add_subplot(HEIGHT, 1, spec5)
+
+    info_lines = []
+    init = misc.np_time_convert(data.time.values)
+    init_str = init.strftime('%d %b %Y - %HUTC')
+    init_for_filename = init.strftime('%Y-%m-%d-%HUTC')
+
+    info_lines.append(f'{name}')
+    info_lines.append(f"INIT : {init_str}")
+    info_lines.append(f"LAT {lat} LON {lon}")
+
+    if '_description' in data.attrs:
+        info_lines.append(data.attrs['_description'])
+
+    ax_text.text(0, 0, '\n'.join(info_lines), ha='left', va='center',
+            size=10, fontfamily='monospace')
+    ax_text.axis("off")
+
+    ### Output
+
+    outname = f'{name}_{init_for_filename}.png'
+    plt.savefig(os.path.join(output, outname))
+    plt.close('all')
+
+    return (
+        {
+            'file': outname,
+            'init': init_str,
+            'valid': init_str,
+            'valid_offset': '00',
+            'display_name': name,
+            'id': name
+        })
diff --git a/metchart/plotter/vertical_from_grib.py b/metchart/plotter/vertical_from_grib.py
new file mode 100755
index 0000000..c632b0b
--- /dev/null
+++ b/metchart/plotter/vertical_from_grib.py
@@ -0,0 +1,101 @@
+#!/usr/bin/env python3
+import os
+
+import datetime
+import json
+
+import matplotlib.pyplot as plt
+
+import xarray as xr
+from metpy.units import units
+import metpy.calc as mpcalc
+import numpy as np
+
+import skewt
+
+from . import misc
+
+config = {
+    'source':'dwd_icon-eu/combined.grib2',
+    'plots':[
+        {
+            'lat':47.9626,
+            'lon':11.9964,
+            'name':'Antersberg',
+            'analysis':'lcl'
+        },
+    ]
+}
+
+def run(data, plots, output='.'):
+    misc.create_output_dir(output)
+    index = []
+
+    for plot in plots:
+        index.append(_plot(data, output, **plot))
+
+    return index
+
+def _plot(data, output, name, lat=None, lon=None, analysis=None):
+    for_temp = data[['r', 't', 'u', 'v']]
+
+    if not (lat is None and lon is None):
+        for_temp = for_temp.sel(latitude=lat, longitude=lon, method='nearest')
+
+    index = []
+
+    for step in for_temp.coords['step']:
+        this_step = for_temp.sel(step=step)
+
+        p = this_step.coords['isobaricInhPa'].values * units.hPa
+        T = this_step.t.values * units.K
+        relHum = this_step.r.values * units.percent
+        Td = mpcalc.dewpoint_from_relative_humidity(T, relHum)
+        u = this_step.u.values * (units.m / units.s)
+        v = this_step.v.values * (units.m / units.s)
+
+        valid = misc.np_time_convert(step.valid_time.values)
+        init = misc.np_time_convert(step.time.values)
+
+        valid_str = valid.strftime('%d %b %Y - %HUTC')
+        init_str = init.strftime('%d %b %Y - %HUTC')
+        hours_since_init_str = str(int(this_step.step.values / np.timedelta64(1,'h'))).zfill(2)
+
+        skt = skewt.Skewt(p=p, T=T, Td=Td)
+        skt.addWindUV(u, v)
+        skt.addInfo(f'{name} INIT+' + hours_since_init_str)
+        skt.addInfo(f"VALID: {valid_str}")
+        skt.addInfo(f"INIT : {init_str}")
+        skt.addInfo(f"LAT {lat} LON {lon}")
+
+        if analysis is not None:
+            skt.addAnalysis(shade=True, analysis=analysis)
+
+        if '_description' in data.attrs:
+            skt.addInfo(data.attrs['_description'])
+
+        init_for_filename = init.strftime('%Y-%m-%d-%HUTC')
+
+        outname = f'skewt_{name}_{init_for_filename}+{hours_since_init_str}.png'
+        skt.plot(filename=os.path.join(output, outname))
+
+        plt.close('all')
+
+        index.append(
+            {
+                'file': outname,
+                'init': init_str,
+                'valid': valid_str,
+                'valid_offset': hours_since_init_str,
+                'display_name': name,
+                'id': name
+            }
+        )
+
+    with open(os.path.join(output, f'skewt_{name}.index.json'), 'w') as f:
+        f.write(json.dumps(index, indent=4))
+
+    return {'name': name, 'indexfile': f'skewt_{name}.index.json', 'list_title': 'Location'}
+
+if __name__ == '__main__':
+    run(**config)
diff --git a/metchart/run.py b/metchart/run.py
new file mode 100755
index 0000000..17a0a97
--- /dev/null
+++ b/metchart/run.py
@@ -0,0 +1,110 @@
+#!/usr/bin/env python3
+
+import sys
+import yaml
+import json
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+from matplotlib.colors import LinearSegmentedColormap
+
+from metpy.units import units
+
+def create_aggregators(cfg):
+    ret = {}
+    for aggregator in cfg:
+        aggconf = cfg[aggregator]
+        classname = aggconf['module']
+        del aggconf['module']
+
+        module = __import__(classname, fromlist=[None])
+
+        ret[aggregator] = module.load_data(name=aggregator, **aggconf)
+
+    return ret
+
+def create_modifiers(aggregators, cfg):
+    # naming is scuffed
+    ret = {}
+    for modifier in cfg:
+        mod = cfg[modifier]
+        modname = mod['module']
+        del mod['module']
+
+        if 'aggregator' in mod:
+            if type(mod['aggregator']) == list:
+                mod['data'] = []
+                for ag in mod['aggregator']:
+                    mod['data'].append(aggregators[ag])
+
+                del mod['aggregator']
+            else:
+                mod['data'] = aggregators[mod['aggregator']]
+                del mod['aggregator']
+
+        pymod = __import__(modname, fromlist=[None])
+        ret[modifier] = pymod.run(**mod)
+
+    return ret
+
+def main():
+    mpl.use('agg')
+
+    # Define custom gpm and gpdm units. The default gpm in metpy is aliased to meter.
+    # We need the correct definition
+    units.define('_gpm = 9.80665 * J/kg')
+    units.define('_gpdm = 10 * _gpm')
+
+    # Define custom colormap
+    clcov_cmap = {
+        'red': (
+            (0.0, 0.0, 0.0),
+            (0.1, 0.9, 0.9),
+            (1.0, 0.3, 0.3),
+        ),
+        'green': (
+            (0.0, 0.5, 0.5),
+            (0.1, 0.9, 0.9),
+            (1.0, 0.3, 0.3),
+        ),
+        'blue': (
+            (0.0, 0.9, 0.9),
+            (0.1, 0.9, 0.9),
+            (1.0, 0.3, 0.3),
+        ),
+    }
+
+    mpl.colormaps.register(LinearSegmentedColormap('clcov', clcov_cmap))
+
+    FILE = 'config.yaml'
+    if len(sys.argv) > 1:
+        FILE = sys.argv[1]
+
+    conf = None
+    with open(FILE, 'r') as f:
+        conf = yaml.safe_load(f)
+
+    aggregators = create_aggregators(conf['aggregator'])
+
+    if 'modifier' in conf:
+        aggregators.update(create_modifiers(aggregators, conf['modifier']))
+
+    index = []
+
+    for plotter in conf['plotter']:
+        modname = plotter['module']
+        del plotter['module']
+
+        if 'aggregator' in plotter:
+            plotter['data'] = aggregators[plotter['aggregator']]
+            del plotter['aggregator']
+
+        mod = __import__(modname, fromlist=[None])
+        index.extend(mod.run(**plotter))
+
+        plt.close('all')
+
+    with open(conf['index'], 'w') as f:
+        f.write(json.dumps(index, indent=4))
+
+if __name__ == '__main__':
+    main()
diff --git a/metchart/skewt.py b/metchart/skewt.py
new file mode 100644
index 0000000..e674d09
--- /dev/null
+++ b/metchart/skewt.py
@@ -0,0 +1,118 @@
+import matplotlib.gridspec as gridspec
+import matplotlib.pyplot as plt
+
+import numpy as np
+
+import metpy.calc as mpcalc
+from metpy.cbook import get_test_data
+from metpy.plots import add_metpy_logo, Hodograph, SkewT
+from metpy.units import units
+
+class Skewt:
+    def __init__(self, p, T, Td, max_barbs=20, title=None):
+        self._p = p
+        self._T = T
+        self._Td = Td
+
+        self._info_lines = []
+
+        self.barb_div = int(max(len(p)/max_barbs,1))
+
+
+        # Create a new figure. The dimensions here give a good aspect ratio
+        self._fig = plt.figure(figsize=(9, 9))
+        plt.rcParams["font.family"] = "monospace"
+        #self._fig = plt.figure()
+
+        if title is not None:
+            plt.suptitle(title, x=0, y=0, va='bottom', ha='left')
+
+        # Grid for plots
+        self._gs = gridspec.GridSpec(3, 3)
+        self._skew = SkewT(self._fig, rotation=45, subplot=self._gs[:, :2])
+
+        # Plot the data using normal plotting functions, in this case using
+        # log scaling in Y, as dictated by the typical meteorological plot
+        self._skew.plot(p, T, 'r')
+        self._skew.plot(p, Td, 'b')
+
+        plt.xlabel('$T$ $[^o C]$')
+        plt.ylabel('$p$ $[hPa]$')
+
+    def addWindUV(self, u, v):
+        self._u = u
+        self._v = v
+
+        ax = self._fig.add_subplot(self._gs[0, -1])
+        h = Hodograph(ax, component_range=max(u + v).magnitude)
+        h.add_grid(increment=20)
+        h.plot_colormapped(u, v, self._p)
+        plt.tight_layout()
+        plt.xlabel('$m/s$')
+        plt.ylabel('$m/s$')
+
+        self._skew.plot_barbs(self._p[::self.barb_div], u[::self.barb_div], v[::self.barb_div])
+
+    def addInfo(self, line):
+        self._info_lines.append(line)
+
+    def addAnalysis(self, analysis='ccl', shade=False):
+        f = {'ccl': self._cclAnalysis, 'lcl': self._lclAnalysis}
+
+        lvl, parcel = f[analysis]()
+
+        self._skew.plot(self._p, parcel, 'y')
+        self._skew.plot(lvl[0], lvl[1], 'o', markerfacecolor='red', linewidth=1)
+
+        # TODO why exception on cape_cin()?
+        # ValueError: zero-size array to reduction operation minimum which has no identity
+        # https://github.com/Unidata/MetPy/pull/3132
+        try:
+            cape, cin = mpcalc.cape_cin(self._p, self._T, self._Td, parcel, which_el='top')
+            self.addInfo(f'CAPE {int(cape.magnitude)} $J/kg$ CIN {int(cin.magnitude)} $J/kg$')
+        except ValueError:
+            print('CAPE/CIN Failed with ValueError')
+            self.addInfo('CAPE #### CIN ####')
+
+        if shade:
+            self._skew.shade_cape(self._p,self._T,parcel)
+            self._skew.shade_cin(self._p,self._T,parcel)
+
+    def _cclAnalysis(self):
+        #p = np.arange(max(self._p).magnitude, min(self._p).magnitude, -50) * units.hPa
+
+        ccl = mpcalc.ccl(self._p,self._T,self._Td)
+        ccl_ground=mpcalc.dry_lapse(self._p[:1], ccl[1], ccl[0])
+        ccl_ground_parcel= mpcalc.parcel_profile(self._p, ccl_ground[0], self._Td[0])
+
+        return (ccl, ccl_ground_parcel)
+
+    def _lclAnalysis(self):
+        ground_parcel= mpcalc.parcel_profile(self._p, self._T[0], self._Td[0])
+        lcl = mpcalc.lcl(self._p[0],self._T[0],self._Td[0])
+
+        return (lcl, ground_parcel)
+
+    def _buildInfoBox(self):
+        ax = self._fig.add_subplot(self._gs[1,-1])
+        ax.text(0, 0, '\n'.join(self._info_lines), ha='left', va='center',
+                size=10, fontfamily='monospace')
+        ax.axis("off")
+
+    def plot(self, filename=None):
+        self._buildInfoBox()
+
+        # Add the relevant special lines
+        #self._skew.ax.set_ylim(max(self._p), min(self._p))
+        self._skew.ax.set_ylim(1000, 100)
+        self._skew.plot_dry_adiabats(linewidth=1)
+        self._skew.plot_moist_adiabats(linewidth=1)
+        self._skew.plot_mixing_lines(linewidth=1)
+
+        # Good bounds for aspect ratio
+        self._skew.ax.set_xlim(-30, 40)
+
+        if filename is not None:
+            plt.savefig(filename)
+        else:
+            plt.show()