Combine low level moisture with a cloud mask

satpy/etc/composites/fci.yaml

@@ -430,3 +430,77 @@ composites:
       - name: ir_38
         modifiers: [nir_reflectance]
     standard_name: snow
+
+  masked_colorized_low_level_moisture:
+    description: >
+      Like essl_colorized_low_level_moisture, but with clouds masked out
+      according to the EUMETSAT FCI L2 CLM product.  Note that due to the
+      categorical nature of the mask, resampling this composite should
+      only be done with nearest neighbour.  The colormap for the cloudfree
+      part has been developed by the European Severe Storms Laboratory (ESSL).
+    compositor: !!python/name:satpy.composites.MaskingCompositor
+    standard_name: masked_essl_colorized_low_level_moisture
+    prerequisites:
+      - essl_colorized_low_level_moisture
+      - cloud_state
+    conditions:
+      - method: equal
+        value: Not processed (no or corrupt data)
+        transparency: 100
+      - method: equal
+        value: Cloud free (no cloud, snow or ice)
+        transparency: 0
+      - method: equal
+        value: Cloud contaminated (partial or semitransparent cloud)
+        transparency: 100
+      - method: equal
+        value: Cloud filled (opaque cloud filled)
+        transparency: 100
+      - method: equal
+        value: Dust contaminated
+        transparency: 100
+      - method: equal
+        value: Dust filled (opaque)
+        transparency: 100
+      - method: equal
+        value: Ash contaminated
+        transparency: 100
+      - method: equal
+        value: Ash filled (opaque)
+        transparency: 100
+      - method: equal
+        value: Snow or ice contaminated
+        transparency: 0
+      - method: equal
+        value: Undefined
+        transparency: 0
+    mode: LA
+
+  colorized_low_level_moisture_with_vis06:
+    description: >
+      Like essl_colorized_low_level_moisture, but with clouds shown according
+      to the vis_06 channel (enhanced with effective_solar_pathlength_corrected).
+      Note that due to the categorical nature of the mask, resampling this
+      composite should only be done with nearest neighbour.  The colormap
+      for the cloudfree part has been developed by the European Severe Storms
+      Laboratory (ESSL)
+    compositor: !!python/name:satpy.composites.BackgroundCompositor
+    standard_name: image_ready
+    prerequisites:
+      - masked_colorized_low_level_moisture
+      - name: vis_06
+        modifiers: [effective_solar_pathlength_corrected]
+
+  colorized_low_level_moisture_with_ir105:
+    description: >
+      Like essl_colorized_low_level_moisture, but with clouds shown according
+      to the in_105 channel (inverted so clouds are white).
+      Note that due to the categorical nature of the mask, resampling this
+      composite should only be done with nearest neighbour.  The colormap
+      for the cloudfree part has been developed by the European Severe Storms
+      Laboratory (ESSL).
+    compositor: !!python/name:satpy.composites.BackgroundCompositor
+    standard_name: image_ready
+    prerequisites:
+      - masked_colorized_low_level_moisture
+      - night_ir105

satpy/etc/composites/visir.yaml

@@ -603,9 +603,11 @@ composites:
       European Severe Storms Laboratory (ESSL).  For a color version,
       see essl_colorized_low_level_moisture.
     compositor: !!python/name:satpy.composites.RatioCompositor
-    prerequisites:
-    - wavelength: 0.905
-    - wavelength: 0.86
+    prerequisites: &llm
+      - wavelength: 0.905  # workaround for https://github.com/pytroll/satpy/issues/1913
+        calibration: reflectance
+      - wavelength: 0.86
+        calibration: reflectance
     standard_name: essl_low_level_moisture
 
   day_essl_low_level_moisture:
@@ -625,9 +627,7 @@ composites:
       European Severe Storms Laboratory (ESSL).  The colorization
       is still under development and may be subject to change.
     compositor: !!python/name:satpy.composites.RatioCompositor
-    prerequisites:
-    - wavelength: 0.905
-    - wavelength: 0.86
+    prerequisites: *llm
     standard_name: essl_colorized_low_level_moisture
 
   day_essl_colorized_low_level_moisture:

satpy/etc/enhancements/generic.yaml

@@ -1241,8 +1241,10 @@ enhancements:
     operations: []
 
   essl_colorized_low_level_moisture:
+    # this enhancement is only found if using name but not standard_name
+    # The colormap was developed by the European Severe Storms Laboratory (ESSL).
     name: essl_colorized_low_level_moisture
-    operations:
+    operations: &masked_llm
       - name: colorize
         method: !!python/name:satpy.enhancements.colorize
         kwargs:
@@ -1352,6 +1354,11 @@ enhancements:
               - [255, 249, 183]
               - [255, 255, 191]
 
+  masked_essl_colorized_low_level_moisture:
+    # this enhancement is only found if using standard_name but not name
+    standard_name: masked_essl_colorized_low_level_moisture
+    operations: *masked_llm
+
   rocket_plume:
     standard_name: rocket_plume
     operations:

satpy/tests/behave/features/image_comparison.feature

@@ -2,15 +2,16 @@ Feature: Image Comparison
 
   Scenario Outline: Compare generated image with reference image
     Given I have a <composite> reference image file from <satellite> resampled to <area>
-    When I generate a new <composite> image file from <satellite> case <case> with <reader> for <area> with clipping <clip>
+    When I generate a new <composite> image file from <satellite> case <case> with <reader> for <area> resampling with <resampler> with clipping <clip>
     Then the generated image should be the same as the reference image
 
     Examples:
-      |satellite | case | composite  | reader | area | clip |
-      |Meteosat-12 | scan_night | cloudtop | fci_l1c_nc | sve | True |
-      |Meteosat-12 | scan_night | night_microphysics | fci_l1c_nc | sve | True |
-      |Meteosat-12 | mali_day | essl_colorized_low_level_moisture | fci_l1c_nc | mali | False |
-      |GOES17   | americas_night | airmass  | abi_l1b | null | null |
-      |GOES16   | americas_night | airmass  | abi_l1b | null | null |
-      |GOES16   | americas_night | ash      | abi_l1b | null | null |
-      |GOES17   | americas_night | ash      | abi_l1b | null | null |
+      |satellite | case | composite  | reader | area | resampler | clip |
+      |Meteosat-12 | scan_night | cloudtop | fci_l1c_nc | sve | gradient_search | True |
+      |Meteosat-12 | scan_night | night_microphysics | fci_l1c_nc | sve | gradient_search | True |
+      |Meteosat-12 | mali_day | essl_colorized_low_level_moisture | fci_l1c_nc | mali | gradient_search | False |
+      |Meteosat-12 | spain_day | colorized_low_level_moisture_with_vis06 | fci_l1c_nc,fci_l2_nc | spain | nearest | False |
+      |GOES17   | americas_night | airmass  | abi_l1b | null | null | null |
+      |GOES16   | americas_night | airmass  | abi_l1b | null | null | null |
+      |GOES16   | americas_night | ash      | abi_l1b | null | null | null |
+      |GOES17   | americas_night | ash      | abi_l1b | null | null | null |

satpy/tests/behave/features/steps/image_comparison.py

@@ -27,6 +27,7 @@
 import numpy as np
 from behave import given, then, when
 
+import satpy
 from satpy import Scene
 
 ext_data_path = "/app/ext_data"
@@ -64,28 +65,28 @@
 
 
 @when("I generate a new {composite} image file from {satellite} case {case} "
-      "with {reader} for {area} with clipping {clip}")
-def step_when_generate_image(context, composite, satellite, case, reader, area, clip):
+      "with {reader} for {area} resampling with {resampler} with clipping {clip}")
+def step_when_generate_image(context, composite, satellite, case, reader, area, resampler, clip):
     """Generate test images."""
     os.environ["OMP_NUM_THREADS"] = os.environ["MKL_NUM_THREADS"] = "2"
     os.environ["PYTROLL_CHUNK_SIZE"] = "1024"
     warnings.simplefilter("ignore")
     dask.config.set(scheduler="threads", num_workers=4)
 
     # Get the list of satellite files to open
     filenames = glob(f"{ext_data_path}/satellite_data/{satellite}/{case}/*.nc")
 
-    reader_kwargs = {}
-    if clip != "null":
-        reader_kwargs["clip_negative_radiances"] = clip
-    scn = Scene(reader=reader, filenames=filenames, reader_kwargs=reader_kwargs)
 
-    scn.load([composite])
+    if "," in reader:
+        reader = reader.split(",")
+    with satpy.config.set({"readers.clip_negative_radiances": False if clip == "null" else clip}):
+        scn = Scene(reader=reader, filenames=filenames)
+        scn.load([composite])
 
     if area == "null":
         ls = scn
     else:
-        ls = scn.resample(area, resampler="gradient_search")
+        ls = scn.resample(area, resampler=resampler)
 
     # Save the generated image in the generated folder
     generated_image_path = os.path.join(context.test_results_dir, "generated",

satpy/tests/etc/readers/fake1.yaml

@@ -60,6 +60,7 @@ datasets:
   ds8:
     name: ds8
     wavelength: [0.7, 0.8, 0.9]
+    calibration: "reflectance"
     file_type: fake_file1
     coordinates: [lons, lats]
   ds9_fail_load:
@@ -70,6 +71,7 @@ datasets:
   ds10:
     name: ds10
     wavelength: [0.75, 0.85, 0.95]
+    calibration: "reflectance"
     file_type: fake_file1
     coordinates: [lons, lats]
   ds11:

utils/create_reference.py

@@ -45,13 +45,19 @@ def generate_images(props):
     filenames = (props.basedir / "satellite_data" / props.satellite /
                  props.case).glob("*")
 
-    scn = Scene(reader=props.reader, filenames=filenames)
+    if "," in props.reader:
+        reader = props.reader.split(",")
+        resampler = "nearest"  # use nearest when combining with cloud mask
+    else:
+        reader = props.reader
+        resampler = "gradient_search"
+    scn = Scene(reader=reader, filenames=filenames)
 
     scn.load(props.composites)
     if props.area == "native":
         ls = scn.resample(resampler="native")
     elif props.area is not None:
-        ls = scn.resample(props.area, resampler="gradient_search")
+        ls = scn.resample(props.area, resampler=resampler)
     else:
         ls = scn
 
@@ -74,7 +80,7 @@ def get_parser():
 
     parser.add_argument(
             "reader", action="store", type=str,
-            help="Reader name.")
+            help="Reader name.  Multiple readers (if needed) can be comma-seperated.")
 
     parser.add_argument(
             "case", help="case to generate", type=str)