diff --git a/components/groundstation.py b/components/groundstation.py
new file mode 100644
index 0000000000000000000000000000000000000000..d0ca43878f45415dbb2edeec695263b013263131
--- /dev/null
+++ b/components/groundstation.py
@@ -0,0 +1,93 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import sys
+from argparse import ArgumentParser, FileType
+from pathlib import Path
+
+this_dir = Path(__file__).parent
+
+def lonlat(string):
+ pair = string.split(",")
+ return (float(pair[0]), float(pair[1]))
+
+parser = ArgumentParser()
+parser.add_argument("--descriptorfile", type=FileType('r'), default=this_dir.parent/"descriptorfiles"/"icon_1mom.py", help="")
+parser.add_argument("--coords", type=lonlat, nargs="+", required=True, help="Coordinates of the groundstations")
+parser.add_argument("--frequency", type=float, nargs="+", default=94)
+parser.add_argument("--dt", type=str, default=None, help="Timestep")
+parser.add_argument("--source_component", type=str, default="atmo_output", help="component name of the source component")
+parser.add_argument("--source_grid", type=str, default="icon_atmos_grid", help="grid name of the source grid")
+args = parser.parse_args()
+
+from yac import YAC, UnstructuredGrid, Location, Field, TimeUnit, \
+ InterpolationStack, NNNReductionType, Reduction, Action
+import pyPamtra
+
+yac = YAC()
+
+comp = yac.def_comp("pamtra")
+
+coords = np.array(args.coords)
+ncoords = len(args.coords)
+grid = UnstructuredGrid("pamtra-grid", [3]*ncoords,
+ [*coords[0,:], *(coords[0,:]+0.1), *coords[0,:]],
+ [*coords[1,:], *coords[1,:], *(coords[1,:]+0.1)],
+ zip(range(ncoords), range(ncoords, 2*ncoords), range(2*ncoords, 3*ncoords)))
+points = grid.def_points(Location.CELL,
+ coords[0,:], coords[1,:])
+
+yac.sync_def()
+
+#print(yac.get_field_names(*source), file=sys.stderr)
+
+interp = InterpolationStack()
+interp.add_nnn(NNNReductionType.AVG, 1, 1.0)
+
+source = (args.source_component, args.source_grid)
+
+dt = args.dt or yac.get_field_timestep(*source, "temp")
+
+fields = {}
+for name in ["temp", "pres", "qv", "qi", "qc", "qs", "qr", "qg", "z_ifc", "u", "v", "w"]:
+ nlevel = yac.get_field_collection_size(*source, name)
+ fields[name] = Field.create(name, comp, points, nlevel,
+ dt, TimeUnit.ISO_FORMAT)
+ yac.def_couple(*source, name,
+ "pamtra", "pamtra-grid", name,
+ dt, TimeUnit.ISO_FORMAT, Reduction.TIME_NONE,
+ interp)
+
+yac.enddef()
+
+with open(args.descriptorfile, "r") as dfile:
+ exec(dfile.read()) # adds a variable "descriptorFile"
+
+def call_pamtra(temp, pres, qv, qi, qc, qs, qr, qg, z_ifc, u, v, w,
+ datetime):
+ pamtra = pyPamtra.pyPamtra()
+ for hydro in descriptorFile:
+ pamtra.df.addHydrometeor(hydro)
+ pamtra.nmlSet["passive"] = False
+ pamtra.nmlSet["active"] = True
+ pamtra.nmlSet["radar_mode"] = "simple"
+ rh = 100*pyPamtra.meteoSI.q2rh(qv, temp, pres)
+ pamtra.createProfile(hgt_lev=z_ifc.T[None, :, ::-1],
+ press=pres.T[None, :, ::-1],
+ temp=temp.T[None, :, ::-1],
+ relhum=rh.T[None, :, ::-1],
+ hydro_q=np.stack([qc.T, qi.T, qr.T, qs.T, qg.T], axis=-1)[:, ::-1, :],
+ )
+ pamtra.runPamtra(args.frequency)
+ pamtra.writeResultsToNetCDF(f"output_{datetime}.nc", xarrayCompatibleOutput=True)
+
+while True:
+ datetime = fields["temp"].datetime
+ data = {}
+ for v, f in fields.items():
+ data[v], info = f.get()
+ print(v, data[v].shape, file=sys.stderr)
+ call_pamtra(**data, datetime=datetime)
+ if info == Action.GET_FOR_RESTART:
+ break
+
diff --git a/descriptorfiles/icon_1mom.py b/descriptorfiles/icon_1mom.py
new file mode 100644
index 0000000000000000000000000000000000000000..c385361663977f3d93d5b37a9204bca65ab43153
--- /dev/null
+++ b/descriptorfiles/icon_1mom.py
@@ -0,0 +1,12 @@
+import numpy as np
+# Define descriptorFiles
+descriptorFile = np.array([ # TODO to be reviewed, coefficients for m-D and v-D are changin
+
+ ('cwc_q', 1.0, 1, -99.0, -99.0, -99.0, -99.0, -99.0, 3, 1, 'mono', -99.0, -99.0, -99.0, -99.0, 2.0e-5, -99.0, 'mie-sphere', 'corPowerLaw_24388657.6_2.0', -99.0),
+ ('iwc_q', 0.2, -1, -99.0, 130.0, 3.0, 0.684, 2.0, 3, 1, 'mono_cosmo_ice', -99.0, -99.0, -99.0, -99.0, -99.0, -99.0, 'ssrg-rt3_0.18_0.89_2.06_0.08', 'corPowerLaw_30.606_0.5533', -99.0),
+ ('rwc_q', 1.0, 1, -99.0, -99.0, -99.0, -99.0, -99.0, 3, 100, 'exp', -99.0, -99.0, 8.0e6, -99.0, 1.2e-4, 6.0e-3, 'mie-sphere', 'corPowerLaw_130.0_0.5', -99.0),
+ ('swc_q', 0.6, -1, -99.0, 0.038, 2.0, 0.3971, 1.88, 3, 100, 'exp_cosmo_snow', -99.0, -99.0, -99.0, -99.0, 5.1e-11, 1.0e-2, 'ssrg-rt3_0.25_1.00_1.66_0.04', 'corPowerLaw_4.9_0.25', -99.0),
+ ('gwc_q', 1.0, -1, -99.0, 169.6, 3.1, -99.0, -99.0, 3, 100, 'exp', -99.0, -99.0, 4.0e6, -99.0, 1.0e-10, 1.0e-2, 'mie-sphere', 'corPowerLaw_406.67_0.85', -99.0)
+],)
+
+#pam.df.addHydrometeor(df)