FIX: Fix example scripts to improve interpolation (#1695)

* Set `nb` value for grid interpolation

* Update email address

* Update citations

* Update qpe.py

* Fix linting errors

* Fix linting errors take 2

---------

Co-authored-by: Max Grover <[email protected]>

examples/plotting/plot_nexrad_image_muted_reflectivity.py

@@ -11,17 +11,14 @@
 with just snow and just rain are depicted in a corresponding full-color scale.
 The ultimate utility of image muting radar reflectivity is to reduce the misinterpretation
 of regions of melting or mixed precipitation as opposed to heavy snow or heavy rain.
+See Tomkins et al. (2022) for full details.
 
 """
 
 print(__doc__)
 
-# Author: Laura Tomkins ([email protected])
+# Author: Laura Tomkins ([email protected])
 # License: BSD 3 clause
-# citation: Tomkins, L. M., Yuter, S. E., Miller, M. A., and Allen, L. R., 2022:
-# Image muting of mixed precipitation to improve identification of regions
-# of heavy snow in radar data. Atmos. Meas. Tech., 15, 5515–5525,
-# https://doi.org/10.5194/amt-15-5515-2022
 
 import matplotlib.colors as mcolors
 import matplotlib.pyplot as plt
@@ -65,3 +62,10 @@
 display.set_limits((-300, 300), (-300, 300))
 ax.set_aspect("equal")
 plt.show()
+
+# References
+# ----------
+# Tomkins, L. M., Yuter, S. E., Miller, M. A., and Allen, L. R., 2022:
+# Image muting of mixed precipitation to improve identification of regions
+# of heavy snow in radar data. Atmos. Meas. Tech., 15, 5515–5525,
+# https://doi.org/10.5194/amt-15-5515-2022

examples/retrieve/plot_cfad.py

@@ -7,7 +7,7 @@
 
 print(__doc__)
 
-# Author: Laura Tomkins ([email protected])
+# Author: Laura Tomkins ([email protected])
 # License: BSD 3 clause
 
 

examples/retrieve/plot_feature_detection.py

@@ -9,7 +9,7 @@
 
 print(__doc__)
 
-# Author: Laura Tomkins ([email protected])
+# Author: Laura Tomkins ([email protected])
 # License: BSD 3 clause
 
 
@@ -28,8 +28,8 @@
 # varies with the background value. The algorithm is heavily customizable and is designed to work with a variety of
 # datasets. Here, we show several examples of how to use the algorithm with different types of radar data.
 #
-# See Steiner et al. (1995), Yuter and Houze (1997), and Yuter et al. (2005) for full details on the algorithm. A
-# manuscript (Tomkins et al. 2024) is in prep to describe feature detection in cool-season events (part 2).
+# See Steiner et al. (1995), Yuter and Houze (1997), and Yuter et al. (2005) for full details on the algorithm. Tomkins
+# et al. 2024 builds on this work to describe feature detection in cool-season events (part 2).
 
 ######################################
 # Part 1: Warm-season convective-stratiform classification
@@ -51,6 +51,7 @@
     grid_shape=(1, 201, 201),
     grid_limits=((0, 10000), (-50000.0, 50000.0), (-50000.0, 50000.0)),
     fields=["reflectivity_horizontal"],
+    nb=1.5,
 )
 
 # get dx dy
@@ -189,6 +190,7 @@
     grid_shape=(1, 201, 201),
     grid_limits=((0, 10000), (-200000.0, 200000.0), (-200000.0, 200000.0)),
     fields=["reflectivity"],
+    nb=1.5,
 )
 
 # get dx dy
@@ -421,6 +423,7 @@
     grid_shape=(1, 201, 201),
     grid_limits=((0, 10000), (-200000.0, 200000.0), (-200000.0, 200000.0)),
     fields=["reflectivity", "cross_correlation_ratio"],
+    nb=1.5,
 )
 
 # image mute grid object
@@ -807,3 +810,8 @@ def quick_image_mute(field, muted_ref):
 # Image muting of mixed precipitation to improve identification of regions
 # of heavy snow in radar data. Atmos. Meas. Tech., 15, 5515–5525,
 # https://doi.org/10.5194/amt-15-5515-2022
+#
+# Tomkins, L. M., Yuter, S. E., and Miller, M. A., 2024: Dual adaptive differential
+# threshold method for automated detection of faint and strong echo features
+# in radar observations of winter storms. Atmos. Meas. Tech., 17, 3377–3399,
+# https://doi.org/10.5194/amt-17-3377-2024

pyart/retrieve/cfad.py

@@ -19,6 +19,10 @@ def create_cfad(
     histogram that is normalized by the number of points at each altitude. Altitude bins are masked where the counts
     are less than a minimum fraction of the largest number of counts for any altitude row.
 
+    Author: Laura Tomkins ([email protected])
+
+    Parameters
+    ----------
     radar : Radar
         Radar object used. Can be Radar or Grid object.
     field_bins : list

pyart/retrieve/echo_class.py

@@ -326,10 +326,10 @@ def feature_detection(
 ):
     """
     This function can be used to detect features in a field (e.g. reflectivity, rain rate, snow rate,
-    etc.) described by Tomkins et al. (2023) and based on original convective-stratiform algorithms developed by
+    etc.) described by Tomkins et al. (2024) and based on original convective-stratiform algorithms developed by
     Steiner et al. (1995), Yuter et al. (2005) and Yuter and Houze (1997) algorithm.
 
-    Author: Laura Tomkins (@lauratomkins)
+    Author: Laura Tomkins ([email protected])
 
     Parameters
     ----------
@@ -422,8 +422,10 @@ def feature_detection(
     2005: Physical characterization of tropical oceanic convection observed in
     KWAJEX. J. Appl. Meteor., 44, 385-415. https://doi.org/10.1175/JAM2206.1
 
-    Tomkins, L. M., S. E. Yuter, and M. A. Miller, 2024: Objective identification
-    of faint and strong features in radar observations of winter storms. in prep.
+    Tomkins, L. M., Yuter, S. E., and Miller, M. A., 2024: Dual adaptive differential
+    threshold method for automated detection of faint and strong echo features
+    in radar observations of winter storms. Atmos. Meas. Tech., 17, 3377–3399.
+    https://doi.org/10.5194/amt-17-3377-2024
 
     """
 

pyart/retrieve/qpe.py

@@ -127,7 +127,7 @@ def est_rain_rate_kdp(radar, alpha=None, beta=None, kdp_field=None, rr_field=Non
     rain : dict
         Field dictionary containing the rainfall rate.
 
-    Reference
+    References
     ---------
     Figueras et al. Long-term monitoring of French polarimetric radar data
     quality and evaluation of several polarimetric quantitative precipitation
@@ -696,7 +696,7 @@ def ZtoR(radar, ref_field="reflectivity", a=300, b=1.4, save_name="NWS_primary_p
     """
     Convert reflectivity (dBZ) to precipitation rate (mm/hr)
 
-    Author: Laura Tomkins
+    Author: Laura Tomkins ([email protected])
 
     Parameters
     ----------

pyart/util/radar_utils.py

@@ -613,7 +613,7 @@ def image_mute_radar(radar, field, mute_field, mute_threshold, field_threshold=N
     the correlation coefficient is less than a certain threshold to discern
     melting precipitation.
 
-    Author: Laura Tomkins (@lauratomkins)
+    Author: Laura Tomkins ([email protected])
 
     Parameters
     ----------