improver.orographic_enhancement module

This module contains a plugin to calculate the enhancement of precipitation over orography.

class improver.orographic_enhancement.OrographicEnhancement

Bases: improver.BasePlugin

Class to calculate orographic enhancement from horizontal wind components, temperature and relative humidity.

References

Alpert, P. and Shafir, H., 1989: Meso-Gamma-Scale Distribution of

Orographic Precipitation: Numerical Study and Comparison with Precipitation Derived from Radar Measurements. Journal of Applied Meteorology, 28, 1105-1117.

Roe, G., 2005: Orographic Precipitation. Annual Review of Earth

and Planetary Sciences, 33, 645-671.

__init__()

Initialise the plugin with thresholds from STEPS code. Usage as follows:

Criteria for site orographic enhancement calculation:

• 3x3 mean topography height >= self.orog_thresh_m (20 m)

• Relative humidity (fraction) >= self.rh_thresh_ratio (0.8)

• v dot grad z (wind x topography gradient) >= self.vgradz_thresh_ms (0.0005 m/s)

Parameters for calculating upstream contribution:

• Maximum range of an upstream cell to contribute to the total enhancement (self.upstream_range_of_influence_km). This is 15 km in STEPS.

• Cloud lifetime (self.cloud_lifetime_s) defines the standard deviation of the distance weighting function for upstream enhancement contributions. This is 102 seconds in STEPS.

• Scaling factor by which to multiply the weighted sum of upstream contributions (self.efficiency_factor). This is 0.23265 in STEPS.

Create placeholder class members for regridded variable cubes (orography, temperature, humidity, pressure and wind components), saturation vapour pressure, V.gradZ (uplift) array and grid spacing.

_abc_cache = <_weakrefset.WeakSet object>

_abc_negative_cache = <_weakrefset.WeakSet object>

_abc_negative_cache_version = 213

_abc_registry = <_weakrefset.WeakSet object>

_add_upstream_component(point_orogenh)

Add upstream component to site orographic enhancement

Parameters

point_orogenh (numpy.ndarray) – Site orographic enhancement in mm h-1

Returns

Total orographic enhancement in mm h-1

Return type

numpy.ndarray

_compute_weighted_values(point_orogenh, x_source, y_source, distance, wind_speed)

Extract orographic enhancement values from source points and weight according to source-destination distance.

Parameters

• point_orogenh (numpy.ndarray) – 2D array of point orographic enhancement values

• x_source (numpy.ndarray) – 3D array of x-coordinates of source points from which to read upstream contribution

• y_source (numpy.ndarray) – 3D array of y-coordinates of source points from which to read upstream contribution

• distance – 3D array of grid point source-to-destination distances

• wind_speed – 2D array of wind speeds

Returns

tuple containing:

orogenh (numpy.ndarray):

2D array containing a weighted sum of orographic enhancement components from upstream source points

sum_of_weights (numpy.ndarray):

2D array containing weights for normalisation

Return type

(tuple)

_create_output_cube(orogenh_data, reference_cube)

Creates a cube containing orographic enhancement values in SI units.

Parameters

• orogenh_data (numpy.ndarray) – Orographic enhancement value in mm h-1

• reference_cube (iris.cube.Cube) – Cube with the correct time and forecast period coordinates on the UK standard grid

Returns

Orographic enhancement cube (m s-1)

Return type

iris.cube.Cube

_generate_mask()

Generates a boolean mask of areas NOT to calculate orographic enhancement. Criteria for calculating orographic enhancement are that all of the following are true:

• 3x3 mean topography height >= threshold (20 m)

• Relative humidity (fraction) >= threshold (0.8)

• v dot grad z (wind x topography gradient) >= threshold (0.0005)

The mask is therefore “True” if any of these conditions are false.

Returns

Boolean mask - where True, set orographic enhancement to a default zero value

Return type

numpy.ndarray

_get_point_distances(wind_speed, max_sin_cos)

Generate 3d array of distances to upstream components

Parameters

• wind_speed (numpy.ndarray) – 2D array of wind speeds

• max_roi (numpy.ndarray) – 2D array of maximum ranges of influence in grid squares

• max_sin_cos (numpy.ndarray) – 2D array containing the larger of sin(wind_direction) or cos(wind_direction) with respect to grid north

Returns

3D array of source-to-destination distances in grid points, with np.nan filled in for out of range values

Return type

numpy.ndarray

static _locate_source_points(wind_speed, distance, sin_wind_dir, cos_wind_dir)

Generate 3D arrays of source points from which to add upstream orographic enhancement contribution. Assumes spatial coordinate ordering [y, x].

Parameters

• wind_speed (numpy.ndarray) – 2D array of wind speed magnitudes

• distance (numpy.ndarray) – 3D array of grid point source-to-destination distances

• sin_wind_dir (numpy.ndarray) – 2D array of sin wind direction wrt grid north

• cos_wind_dir (numpy.ndarray) – 2D array of cos wind direction wrt grid north

Returns

tuple containing:

x_source (numpy.ndarray):

3D array of source point x-coordinates

y_source (numpy.ndarray):

3D array of source point y-coordinates

Return type

(tuple)

_orography_gradients()

Calculates the dimensionless gradient of self.topography along both spatial axes, smoothed along the perpendicular axis. If spatial coordinates are not in the same units as topography height (m), converts coordinate units in place.

Returns

tuple containing:

gradx (iris.cube.Cube):

2D cube of dimensionless topography gradients in the positive x direction

grady (iris.cube.Cube):

2D cube of dimensionless topography gradients in the positive y direction

Return type

(tuple)

_point_orogenh()

Calculate the grid-point precipitation enhancement contribution due to orographic uplift using:

orogenh = ((humidity * svp * vgradz) /

(R_WATER_VAPOUR * temperature)) * 60 * 60

Returns

Orographic enhancement values in mm/h

Return type

numpy.ndarray

_regrid_and_populate(temperature, humidity, pressure, uwind, vwind, topography)

Regrids input variables onto the high resolution orography field, then populates the class instance with regridded variables before converting to SI units. Also calculates V.gradZ as a class member.

Parameters

• temperature (iris.cube.Cube) – Temperature at top of boundary layer

• humidity (iris.cube.Cube) – Relative humidity at top of boundary layer

• pressure (iris.cube.Cube) – Pressure at top of boundary layer

• uwind (iris.cube.Cube) – Positive eastward wind vector component at top of boundary layer

• vwind (iris.cube.Cube) – Positive northward wind vector component at top of boundary layer

• topography (iris.cube.Cube) – Height of topography above sea level on 1 km UKPP domain grid

_regrid_variable(var_cube, unit)

Sorts spatial coordinates in ascending order, regrids the input variable onto the topography grid and converts to the required units. This function does not modify the input variable cube.

Parameters

• var_cube (iris.cube.Cube) – Cube containing input variable data

• unit (str) – Required unit for this variable

Returns

Cube containing regridded variable data

Return type

iris.cube.Cube

process(temperature, humidity, pressure, uwind, vwind, topography)

Calculate precipitation enhancement over orography on high resolution grid. Input diagnostics are all expected to be on the same grid, and are regridded to match the orography.

Parameters

• temperature (iris.cube.Cube) – Temperature at top of boundary layer

• humidity (iris.cube.Cube) – Relative humidity at top of boundary layer

• pressure (iris.cube.Cube) – Pressure at top of boundary layer

• uwind (iris.cube.Cube) – Positive eastward wind vector component at top of boundary layer

• vwind (iris.cube.Cube) – Positive northward wind vector component at top of boundary layer

• topography (iris.cube.Cube) – Height of topography above sea level on high resolution (1 km) UKPP domain grid

Returns

Precipitation enhancement due to orography in m/s.

Return type

iris.cube.Cube