Updated RGBs for MTG and new NOAA RGBs

src/goes2go/accessors.py

@@ -741,6 +741,75 @@ def DayCloudPhase(self):
 
         return ds["DayCloudPhase"]
 
+    def DayCloudPhaseEUMETSAT(self):
+        """Create the Day Cloud Phase EUMETSAT RGB.
+
+        (See `Quick Guide <https://eumetrain.org/sites/default/files/2023-01/CloudPhaseRGB.pdf>`__ for reference)
+
+        .. image:: /_static/DayCloudPhaseEUMETSAT.png
+
+
+        """
+        ds = self._obj
+
+        # Load the three channels into appropriate R, G, and B variables
+        R, G, B = self._load_RGB_channels((5, 6, 2))
+
+        # _normalize each channel by the appropriate range of values. (Clipping happens inside function)
+        R = _normalize(R, 0, .5)
+        G = _normalize(G, 0, .5)
+        B = _normalize(B, 0, 1)
+
+        # The final RGB array :)
+        RGB = np.dstack([R, G, B])
+
+        ds["DayCloudPhaseEUMETSAT"] = (("y", "x", "rgb"), RGB)
+        ds["rgb"] = ["R", "G", "B"]
+        ds["DayCloudPhaseEUMETSAT"].attrs["Quick Guide"] = (
+            "https://eumetrain.org/sites/default/files/2023-01/CloudPhaseRGB.pdf"
+        )
+        ds["DayCloudPhaseEUMETSAT"].attrs["long_name"] = "Day Cloud Phase EUMETSAT"
+
+        return ds["DayCloudPhaseEUMETSAT"]
+
+    def DayCloudType(self):
+        """Create the Day Cloud Phase Type RGB.
+
+        (See `Quick Guide <https://eumetrain.org/sites/default/files/2021-05/CloudTypeRGB.pdf>`__ for reference)
+
+        .. image:: /_static/DayCloudType.png
+
+
+        """
+        ds = self._obj
+
+        # Load the three channels into appropriate R, G, and B variables
+        R, G, B = self._load_RGB_channels((4, 2, 5))
+
+        # _normalize each channel by the appropriate range of values. (Clipping happens inside function)
+        R = _normalize(R, 0, .1)
+        G = _normalize(G, 0, .8)
+        B = _normalize(B, 0, .8)
+
+        # Apply the gamma correction to Red channel.
+        #   corrected_value = value^(1/gamma)
+        gamma = 1.5
+        R = _gamma_correction(R, gamma)
+        gamma = .75
+        G = _gamma_correction(G, gamma)
+
+        # The final RGB array :)
+        RGB = np.dstack([R, G, B])
+
+        ds["DayCloudType"] = (("y", "x", "rgb"), RGB)
+        ds["rgb"] = ["R", "G", "B"]
+        ds["DayCloudType"].attrs["Quick Guide"] = (
+            "https://eumetrain.org/sites/default/files/2021-05/CloudTypeRGB.pdf"
+        )
+        ds["DayCloudType"].attrs["long_name"] = "Day Cloud Type"
+
+        return ds["DayCloudType"]
+
     def DayConvection(self):
         """Create the Day Convection RGB.
 
@@ -1309,3 +1378,40 @@ def SeaSpray(self, **kwargs):
         ds["SeaSpray"].attrs["long_name"] = "Sea Spray"
 
         return ds["SeaSpray"]
+
+    def BlowingSnow(self, **kwargs):
+        """Create the Blowing Snow RGB.
+
+        (See `Quick Guide <https://rammb2.cira.colostate.edu/wp-content/uploads/2024/11/GOES-BlowingSnowRGB1_QuickGuide_24April2024.pdf>`__ for reference)
+
+        .. image:: /_static/BlowingSnow.png
+
+        """
+        ds = self._obj
+
+        # Load the three channels into appropriate R, G, and B variables
+        R = ds["CMI_C02"].data
+        G = ds["CMI_C05"].data
+        B = ds["CMI_C07"].data - ds["CMI_C13"].data
+
+        # Normalize each channel by the appropriate range of values. e.g. R = (R-minimum)/(maximum-minimum)
+        R = _normalize(R, 0, .5)    # values for this channel go from 0 to 1.
+        G = _normalize(G, 0, 0.2)   # values for this channel go from 0 to 1.
+        B = _normalize(B, 0, 30)
+
+        # Apply a gamma correction to each R, G, B channel
+        R = _gamma_correction(R, 1/0.7)
+        G = _gamma_correction(G, 1.0)
+        B = _gamma_correction(B, 1/0.7)
+
+        # The final RGB array :)
+        RGB = np.dstack([R, G, B])
+
+        ds["BlowingSnow"] = (("y", "x", "rgb"), RGB)
+        ds["rgb"] = ["R", "G", "B"]
+        ds["BlowingSnow"].attrs["Quick Guide"] = (
+            "https://rammb2.cira.colostate.edu/wp-content/uploads/2024/11/GOES-BlowingSnowRGB1_QuickGuide_24April2024.pdf"
+        )
+        ds["BlowingSnow"].attrs["long_name"] = "Blowing Snow"
+
+        return ds["BlowingSnow"]

src/goes2go/rgb.py

@@ -20,7 +20,10 @@
     - TrueColor
     - FireTemperature
     - AirMass
+    - BlowingSnow
     - DayCloudPhase
+    - DayCloudPhaseEUMETSAT
+    - DayCloudType
     - DayConvection
     - DayCloudConvection
     - DayLandCloud
@@ -30,6 +33,7 @@
     - DaySnowFog
     - NighttimeMicrophysics
     - Dust
+    - SeaSpray
     - SulfurDioxide
     - Ash
     - SplitWindowDifference
@@ -562,6 +566,42 @@ def AirMass(C, **kwargs):
 
     return rgb_as_dataset(C, RGB, "Air Mass", **kwargs)
 
+def BlowingSnow(C, **kwargs):
+    """
+    Blowing Snow RGB:
+    (See `Quick Guide <https://rammb2.cira.colostate.edu/wp-content/uploads/2024/11/GOES-BlowingSnowRGB1_QuickGuide_24April2024.pdf>`__ for reference)
+
+    .. image:: /_static/BlowingSnow.png
+
+    Parameters
+    ----------
+    C : xarray.Dataset
+        A GOES ABI multichannel file opened with xarray.
+    \*\*kwargs :
+        Keyword arguments for ``rgb_as_dataset`` function.
+        - latlon : derive latitude and longitude of each pixel
+
+    """
+    # Load the three channels into appropriate R, G, and B variables
+    R = C["CMI_C02"].data
+    G = C["CMI_C05"].data
+    B = C["CMI_C07"].data - C["CMI_C13"].data
+
+    # Normalize each channel by the appropriate range of values. e.g. R = (R-minimum)/(maximum-minimum)
+    R = normalize(R, 0, 0.5)
+    G = normalize(G, 0, 0.2)
+    B = normalize(B, 0, 30)
+
+    # Apply the gamma correction to Red channel.
+    #   corrected_value = value^(1/gamma)
+    gamma = 1/.7
+    R = gamma_correction(R, gamma)
+    B = gamma_correction(B, gamma)
+
+    # The final RGB array :)
+    RGB = np.dstack([R, G, B])
+
+    return rgb_as_dataset(C, RGB, "Blowing Snow", **kwargs)
 
 def DayCloudPhase(C, **kwargs):
     """
@@ -595,6 +635,71 @@ def DayCloudPhase(C, **kwargs):
 
     return rgb_as_dataset(C, RGB, "Day Cloud Phase", **kwargs)
 
+def DayCloudPhaseEUMETSAT(C, **kwargs):
+    """
+    Day Cloud Phase EUMETSAT RGB:
+    (See `Quick Guide <https://eumetrain.org/sites/default/files/2023-01/CloudPhaseRGB.pdf>`__ for reference)
+
+    .. image:: /_static/DayCloudPhaseEUMETSAT.png
+
+    Parameters
+    ----------
+    C : xarray.Dataset
+        A GOES ABI multichannel file opened with xarray.
+    \*\*kwargs :
+        Keyword arguments for ``rgb_as_dataset`` function.
+        - latlon : derive latitude and longitude of each pixel
+
+    """
+    # Load the three channels into appropriate R, G, and B variables
+    R, G, B = load_RGB_channels(C, (5, 6, 2))
+
+    # Normalize each channel by the appropriate range of values. (Clipping happens inside function)
+    R = normalize(R, 0, .5)
+    G = normalize(G, 0, .5)
+    B = normalize(B, 0, 1)
+
+    # The final RGB array :)
+    RGB = np.dstack([R, G, B])
+
+    return rgb_as_dataset(C, RGB, "Day Cloud Phase EUMETSAT", **kwargs)
+
+def DayCloudType(C, **kwargs):
+    """
+    Day Cloud Type RGB:
+    (See `Quick Guide <https://eumetrain.org/sites/default/files/2021-05/CloudTypeRGB.pdf>`__ for reference)
+
+    .. image:: /_static/DayCloudType.png
+
+    Parameters
+    ----------
+    C : xarray.Dataset
+        A GOES ABI multichannel file opened with xarray.
+    \*\*kwargs :
+        Keyword arguments for ``rgb_as_dataset`` function.
+        - latlon : derive latitude and longitude of each pixel
+
+    """
+    # Load the three channels into appropriate R, G, and B variables
+    R, G, B = load_RGB_channels(C, (4, 2, 5))
+
+    # Normalize each channel by the appropriate range of values. (Clipping happens inside function)
+    R = normalize(R, 0, .1)
+    G = normalize(G, 0, .8)
+    B = normalize(B, 0, .8)
+
+    # Apply the gamma correction to Red channel.
+    #   corrected_value = value^(1/gamma)
+    gamma = 1.5
+    R = gamma_correction(R, gamma)
+    gamma = .75
+    G = gamma_correction(G, gamma)
+
+    # The final RGB array :)
+    RGB = np.dstack([R, G, B])
+
+    return rgb_as_dataset(C, RGB, "Day Cloud Type", **kwargs)
+
 
 def DayConvection(C, **kwargs):
     """
@@ -910,6 +1015,42 @@ def Dust(C, **kwargs):
 
     return rgb_as_dataset(C, RGB, "Dust", **kwargs)
 
+def SeaSpray(C, **kwargs):
+    """
+    Sea Spray RGB:
+    (See `Quick Guide <https://rammb.cira.colostate.edu/training/visit/quick_guides/VIIRS_Sea_Spray_RGB_Quick_Guide_v2.pdf
+>`__ for reference)
+
+    .. image:: /_static/SeaSpray.png
+
+    Parameters
+    ----------
+    C : xarray.Dataset
+        A GOES ABI multichannel file opened with xarray.
+    \*\*kwargs :
+        Keyword arguments for ``rgb_as_dataset`` function.
+        - latlon : derive latitude and longitude of each pixel
+
+    """
+    # Load the three channels into appropriate R, G, and B variables
+    R = C["CMI_C07"].data - C["CMI_C13"].data
+    G = C["CMI_C03"].data
+    B = C["CMI_C02"].data
+
+    # Normalize values
+    R = normalize(R, 0, 5)
+    G = normalize(G, .01, .09)
+    B = normalize(B, .02, .12)
+
+    # Apply a gamma correction to the image
+    gamma = 1/.6
+    G = gamma_correction(G, gamma)
+    B = gamma_correction(B, gamma)
+
+    # The final RGB array :)
+    RGB = np.dstack([R, G, B])
+
+    return rgb_as_dataset(C, RGB, "Sea Spray", **kwargs)
 
 def SulfurDioxide(C, **kwargs):
     """