Fig 2c in (new) Adade & Albuquerque 2024 example; new physics submodu…

…le: bulk phase partitioning with one impl as in Kaul et al. 2015 (#1365)

PySDM/formulae.py

@@ -55,6 +55,7 @@ def __init__(  # pylint: disable=too-many-locals
         particle_shape_and_density: str = "LiquidSpheres",
         terminal_velocity: str = "GunnKinzer1949",
         air_dynamic_viscosity: str = "ZografosEtAl1987",
+        bulk_phase_partitioning: str = "Null",
         handle_all_breakups: bool = False,
     ):
         # initialisation of the fields below is just to silence pylint and to enable code hints
@@ -86,6 +87,7 @@ def __init__(  # pylint: disable=too-many-locals
         self.particle_shape_and_density = particle_shape_and_density
         self.air_dynamic_viscosity = air_dynamic_viscosity
         self.terminal_velocity = terminal_velocity
+        self.bulk_phase_partitioning = bulk_phase_partitioning
 
         self._components = tuple(
             i
@@ -101,8 +103,18 @@ def __init__(  # pylint: disable=too-many-locals
                 getattr(defaults, k), (numbers.Number, pint.Quantity, pint.Unit)
             )
         }
+
+        physics.constants_defaults.compute_derived_values(constants_defaults)
+        if constants is not None:
+            for key in constants:
+                if key not in constants_defaults:
+                    raise ValueError(
+                        f"constant override provided for unknown key: {key}"
+                    )
+
         constants_defaults = {**constants_defaults, **(constants or {})}
         physics.constants_defaults.compute_derived_values(constants_defaults)
+
         constants = namedtuple("Constants", tuple(constants_defaults.keys()))(
             **constants_defaults
         )

PySDM/physics/__init__.py

@@ -45,5 +45,6 @@
     ventilation,
     air_dynamic_viscosity,
     terminal_velocity,
+    bulk_phase_partitioning,
 )
 from .constants import convert_to, in_unit, si

PySDM/physics/bulk_phase_partitioning/__init__.py

@@ -0,0 +1,4 @@
+""" phase partitioning formulae for bulk description of cloud water """
+
+from PySDM.impl.null_physics_class import Null
+from .kaul_et_al_2015 import KaulEtAl2015

PySDM/physics/bulk_phase_partitioning/kaul_et_al_2015.py

@@ -0,0 +1,27 @@
+"""
+Eq. 1 in [Kaul et al. 2015](https://doi.org/10.1175/MWR-D-14-00319.1)
+"""
+
+import numpy as np
+
+
+class KaulEtAl2015:  # pylint: disable=too-few-public-methods
+    def __init__(self, const):
+        assert np.isfinite(const.bulk_phase_partitioning_exponent)
+
+    @staticmethod
+    def liquid_fraction(const, T):
+        return np.minimum(
+            1,
+            np.power(
+                np.maximum(
+                    0,
+                    (T - const.bulk_phase_partitioning_T_cold)
+                    / (
+                        const.bulk_phase_partitioning_T_warm
+                        - const.bulk_phase_partitioning_T_cold
+                    ),
+                ),
+                const.bulk_phase_partitioning_exponent,
+            ),
+        )

PySDM/physics/constants_defaults.py

@@ -424,3 +424,7 @@ def compute_derived_values(c: dict):
 B80W_G2 = 243.5 * si.K
 
 one_kelvin = 1 * si.K
+
+bulk_phase_partitioning_T_cold = 235 * si.K
+bulk_phase_partitioning_T_warm = 273 * si.K
+bulk_phase_partitioning_exponent = np.nan

examples/PySDM_examples/Abade_and_Albuquerque_2024/__init__.py

@@ -0,0 +1,8 @@
+# pylint: disable=invalid-name
+"""
+mixed-phase example using parcel environment based on
+[Abade & Albuquerque 2024 (QJRMS)](https://doi.org/10.1002/qj.4775)
+"""
+
+from .simulation import Simulation
+from .settings import Settings