def create_angle_uncertainty_variable(angle_name, height):
variable = tu.create_float_variable(SWATH_WIDTH,
height,
long_name="uncertainty of " +
angle_name,
fill_value=np.NaN)
tu.add_units(variable, "degree")
return variable
def _create_counts_uncertainty_variable(height, long_name):
variable = tu.create_float_variable(SWATH_WIDTH,
height,
long_name=long_name,
fill_value=np.NaN)
tu.add_units(variable, "count")
tu.add_geolocation_attribute(variable)
tu.add_chunking(variable, CHUNKS_2D)
return variable
def _create_angle_uncertainty_variable(angle_name, height):
variable = tu.create_float_variable(SWATH_WIDTH,
height,
long_name="uncertainty of " +
angle_name,
fill_value=np.NaN)
tu.add_units(variable, "degree")
tu.add_geolocation_attribute(variable)
tu.add_chunking(variable, CHUNKS_2D)
return variable
def add_full_fcdr_variables(dataset, height):
# height is ignored - supplied just for interface compatibility tb 2017-02-05
# count_vis
default_array = DefaultData.create_default_array(FULL_SIZE, FULL_SIZE, np.uint8)
variable = Variable(["y", "x"], default_array)
tu.add_fill_value(variable, DefaultData.get_default_fill_value(np.uint8))
variable.attrs["long_name"] = "Image counts"
tu.add_units(variable, "count")
tu.add_chunking(variable, CHUNKSIZES)
dataset["count_vis"] = variable
dataset["u_latitude"] = MVIRI._create_angle_variable_int(1.5E-05, long_name="Uncertainty in Latitude", unsigned=True)
MVIRI._add_geo_correlation_attributes(dataset["u_latitude"])
dataset["u_longitude"] = MVIRI._create_angle_variable_int(1.5E-05, long_name="Uncertainty in Longitude", unsigned=True)
MVIRI._add_geo_correlation_attributes(dataset["u_longitude"])
# u_time
default_array = DefaultData.create_default_vector(IR_SIZE, np.float32, fill_value=np.NaN)
variable = Variable([IR_Y_DIMENSION], default_array)
variable.attrs["standard_name"] = "Uncertainty in Time"
tu.add_units(variable, "s")
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.009155273)
variable.attrs["pdf_shape"] = "rectangle"
dataset["u_time"] = variable
dataset["u_satellite_zenith_angle"] = MVIRI._create_angle_variable_int(7.62939E-05, long_name="Uncertainty in Satellite Zenith Angle", unsigned=True)
dataset["u_satellite_azimuth_angle"] = MVIRI._create_angle_variable_int(7.62939E-05, long_name="Uncertainty in Satellite Azimuth Angle", unsigned=True)
dataset["u_solar_zenith_angle"] = MVIRI._create_angle_variable_int(7.62939E-05, long_name="Uncertainty in Solar Zenith Angle", unsigned=True)
dataset["u_solar_azimuth_angle"] = MVIRI._create_angle_variable_int(7.62939E-05, long_name="Uncertainty in Solar Azimuth Angle", unsigned=True)
dataset["a0_vis"] = tu.create_scalar_float_variable("Calibration Coefficient at Launch", units="Wm^-2sr^-1/count")
dataset["a1_vis"] = tu.create_scalar_float_variable("Time variation of a0", units="Wm^-2sr^-1/count day^-1 10^5")
dataset["a2_vis"] = tu.create_scalar_float_variable("Time variation of a0, quadratic term", units="Wm^-2sr^-1/count year^-2")
dataset["mean_count_space_vis"] = tu.create_scalar_float_variable("Space count", units="count")
# u_a0_vis
variable = tu.create_scalar_float_variable("Uncertainty in a0", units="Wm^-2sr^-1/count")
MVIRI._add_calibration_coeff_correlation_attributes(variable)
dataset["u_a0_vis"] = variable
# u_a1_vis
variable = tu.create_scalar_float_variable("Uncertainty in a1", units="Wm^-2sr^-1/count day^-1 10^5")
MVIRI._add_calibration_coeff_correlation_attributes(variable)
dataset["u_a1_vis"] = variable
# u_a2_vis
variable = tu.create_scalar_float_variable("Uncertainty in a2", units="Wm^-2sr^-1/count year^-2")
MVIRI._add_calibration_coeff_correlation_attributes(variable)
dataset["u_a2_vis"] = variable
# u_zero_vis
variable = tu.create_scalar_float_variable("Uncertainty zero term", units="Wm^-2sr^-1/count")
MVIRI._add_calibration_coeff_correlation_attributes(variable, image_correlation_scale=[-np.inf, np.inf])
dataset["u_zero_vis"] = variable
# covariance_a_vis
variable = tu.create_float_variable(COV_SIZE, COV_SIZE, long_name="Covariance of calibration coefficients from fit to calibration runs", dim_names=["cov_size", "cov_size"], fill_value=np.NaN)
tu.add_fill_value(variable, np.NaN)
tu.add_units(variable, "Wm^-2sr^-1/count")
MVIRI._add_calibration_coeff_correlation_attributes(variable, image_correlation_scale=[-np.inf, np.inf])
dataset["covariance_a_vis"] = variable
dataset["u_electronics_counts_vis"] = tu.create_scalar_float_variable("Uncertainty due to Electronics noise", units="count")
dataset["u_digitization_counts_vis"] = tu.create_scalar_float_variable("Uncertainty due to digitization", units="count")
# allan_deviation_counts_space_vis
variable = tu.create_scalar_float_variable("Uncertainty of space count", units="count")
variable.attrs[corr.SCAN_CORR_FORM] = corr.RECT_ABS
variable.attrs[corr.SCAN_CORR_UNIT] = corr.LINE
variable.attrs[corr.SCAN_CORR_SCALE] = [-np.inf, np.inf]
variable.attrs["pdf_shape"] = "digitised_gaussian"
dataset["allan_deviation_counts_space_vis"] = variable
# u_mean_counts_space_vis
variable = tu.create_scalar_float_variable("Uncertainty of space count", units="count")
variable.attrs[corr.PIX_CORR_FORM] = corr.RECT_ABS
variable.attrs[corr.PIX_CORR_UNIT] = corr.PIXEL
variable.attrs[corr.PIX_CORR_SCALE] = [-np.inf, np.inf]
variable.attrs[corr.SCAN_CORR_FORM] = corr.RECT_ABS
variable.attrs[corr.SCAN_CORR_UNIT] = corr.LINE
variable.attrs[corr.SCAN_CORR_SCALE] = [-np.inf, np.inf]
variable.attrs["pdf_shape"] = "digitised_gaussian"
dataset["u_mean_counts_space_vis"] = variable
# sensitivity_solar_irradiance_vis
variable = tu.create_scalar_float_variable()
variable.attrs["virtual"] = "true"
variable.attrs["dimension"] = "y, x"
variable.attrs[
"expression"] = "distance_sun_earth * distance_sun_earth * PI * (count_vis - mean_count_space_vis) * (a2_vis * years_since_launch * years_since_launch + a1_vis * years_since_launch + a0_vis) / (cos(solar_zenith_angle * PI / 180.0) * solar_irradiance_vis * solar_irradiance_vis)"
dataset["sensitivity_solar_irradiance_vis"] = variable
# sensitivity_count_vis
variable = tu.create_scalar_float_variable()
variable.attrs["virtual"] = "true"
variable.attrs["dimension"] = "y, x"
variable.attrs[
"expression"] = "distance_sun_earth * distance_sun_earth * PI * (a2_vis * years_since_launch * years_since_launch + a1_vis * years_since_launch + a0_vis) / (cos(solar_zenith_angle * PI / 180.0) * solar_irradiance_vis)"
dataset["sensitivity_count_vis"] = variable
# sensitivity_count_space
variable = tu.create_scalar_float_variable()
variable.attrs["virtual"] = "true"
variable.attrs["dimension"] = "y, x"
variable.attrs[
"expression"] = "-1.0 * distance_sun_earth * distance_sun_earth * PI * (a2_vis * years_since_launch * years_since_launch + a1_vis * years_since_launch + a0_vis) / (cos(solar_zenith_angle * PI / 180.0) * solar_irradiance_vis)"
dataset["sensitivity_count_space"] = variable
# sensitivity_a0_vis
variable = tu.create_scalar_float_variable()
variable.attrs["virtual"] = "true"
variable.attrs["dimension"] = "y, x"
variable.attrs["expression"] = "distance_sun_earth * distance_sun_earth * PI * (count_vis - mean_count_space_vis) / (cos(solar_zenith_angle * PI / 180.0) * solar_irradiance_vis)"
dataset["sensitivity_a0_vis"] = variable
# sensitivity_a1_vis
variable = tu.create_scalar_float_variable()
variable.attrs["virtual"] = "true"
variable.attrs["dimension"] = "y, x"
variable.attrs[
"expression"] = "distance_sun_earth * distance_sun_earth * PI * (count_vis - mean_count_space_vis) * years_since_launch / (cos(solar_zenith_angle * PI / 180.0) * solar_irradiance_vis)"
dataset["sensitivity_a1_vis"] = variable
# sensitivity_a2_vis
variable = tu.create_scalar_float_variable()
variable.attrs["virtual"] = "true"
variable.attrs["dimension"] = "y, x"
variable.attrs[
"expression"] = "distance_sun_earth * distance_sun_earth * PI * (count_vis - mean_count_space_vis) * years_since_launch*years_since_launch / (cos(solar_zenith_angle * PI / 180.0) * solar_irradiance_vis)"
dataset["sensitivity_a2_vis"] = variable
effect_names = ["u_solar_irradiance_vis", "u_a0_vis", "u_a1_vis", "u_a2_vis", "u_zero_vis", "u_solar_zenith_angle", "u_mean_count_space_vis"]
dataset["Ne"] = Coordinate("Ne", effect_names)
num_effects = len(effect_names)
default_array = DefaultData.create_default_array(num_effects, num_effects, np.float32, fill_value=np.NaN)
variable = Variable(["Ne", "Ne"], default_array)
tu.add_encoding(variable, np.int16, -32768, 3.05176E-05)
variable.attrs["valid_min"] = -1
variable.attrs["valid_max"] = 1
variable.attrs["long_name"] = "Channel error correlation matrix for structured effects."
variable.attrs["description"] = "Matrix_describing correlations between errors of the uncertainty_effects due to spectral response function errors (determined using Monte Carlo approach)"
dataset["effect_correlation_matrix"] = variable
def _create_angle_variable(height, standard_name):
variable = tu.create_float_variable(SWATH_WIDTH, height, standard_name)
tu.add_units(variable, "degree")
tu.add_encoding(variable, np.uint16, 65535, 0.01)
return variable
def add_full_fcdr_variables(dataset, height):
# c_earth
default_array = DefaultData.create_default_array_3d(SWATH_WIDTH, height, NUM_RAD_CHANNELS, np.uint16, dims_names=["rad_channel", "y", "x"])
variable = Variable(["rad_channel", "y", "x"], default_array)
tu.add_fill_value(variable, DefaultData.get_default_fill_value(np.uint16))
variable.attrs["long_name"] = "counts_earth"
tu.add_units(variable, "count")
variable.attrs["ancilliary_variables"] = "scnlinf quality_scanline_bitmask quality_channel_bitmask mnfrqualflags"
dataset["c_earth"] = variable
# L_earth
default_array = DefaultData.create_default_array_3d(SWATH_WIDTH, height, NUM_RAD_CHANNELS, np.float32, np.NaN, ["rad_channel", "y", "x"])
variable = Variable(["rad_channel", "y", "x"], default_array)
tu.add_encoding(variable, np.uint32, DefaultData.get_default_fill_value(np.uint32), 0.0001)
variable.attrs["standard_name"] = "toa_outgoing_inband_radiance"
tu.add_units(variable, "W/Hz/m ** 2/sr")
variable.attrs["long_name"] = "Channel radiance, NOAA/EUMETSAT calibrated"
variable.attrs["ancilliary_variables"] = "scnlinf quality_scanline_bitmask quality_channel_bitmask mnfrqualflags"
dataset["L_earth"] = variable
# u_lat
variable = HIRS._create_angle_variable(height, "uncertainty_latitude")
dataset["u_lat"] = variable
# u_lon
variable = HIRS._create_angle_variable(height, "uncertainty_longitude")
dataset["u_lon"] = variable
# u_time
variable = tu.create_float_variable(SWATH_WIDTH, height, "uncertainty_time")
tu.add_encoding(variable, np.uint16, 65535, 0.01)
tu.add_units(variable, "s")
dataset["u_time"] = variable
# u_c_earth
default_array = DefaultData.create_default_array(NUM_CALIBRATION_CYCLE, NUM_CHANNELS, np.uint16, dims_names=["channel", "calibration_cycle"])
variable = Variable(["channel", "calibration_cycle"], default_array)
tu.add_fill_value(variable, DefaultData.get_default_fill_value(np.uint16))
tu.add_units(variable, "count")
variable.attrs["long_name"] = "uncertainty counts for Earth views"
variable.attrs["ancilliary_variables"] = "u_c_earth_chan_corr"
variable.attrs["channels_affected"] = "all"
variable.attrs["parameter"] = "C_E"
variable.attrs["pdf_shape"] = "gaussian"
dataset["u_c_earth"] = variable
# u_L_earth_independent
variable = HIRS._create_3d_rad_uncertainty_variable(height, "uncertainty_radiance_Earth_random")
tu.add_encoding(variable, np.uint32, DefaultData.get_default_fill_value(np.uint32), 0.01)
tu.add_units(variable, "mW m^-2 sr^-1 cm")
dataset["u_L_earth_independent"] = variable
# u_L_earth_structured
variable = HIRS._create_3d_rad_uncertainty_variable(height, "uncertainty_radiance_Earth_structured")
tu.add_encoding(variable, np.uint32, DefaultData.get_default_fill_value(np.uint32), 0.01)
tu.add_units(variable, "mW m^-2 sr^-1 cm")
dataset["u_L_earth_structured"] = variable
# u_L_earth_systematic
variable = HIRS._create_3d_rad_uncertainty_variable(height, "uncertainty_radiance_Earth_systematic")
tu.add_encoding(variable, np.uint32, DefaultData.get_default_fill_value(np.uint32), 0.01)
tu.add_units(variable, "mW m^-2 sr^-1 cm")
dataset["u_L_earth_systematic"] = variable
# u_L_earth_total
variable = HIRS._create_3d_rad_uncertainty_variable(height, "uncertainty_radiance_Earth_total")
tu.add_encoding(variable, np.uint32, DefaultData.get_default_fill_value(np.uint32), 0.01)
tu.add_units(variable, "mW m^-2 sr^-1 cm")
dataset["u_L_earth_total"] = variable
# S_u_L_earth
variable = tu.create_float_variable(NUM_RAD_CHANNELS, NUM_RAD_CHANNELS, "covariance_radiance_Earth", dim_names=["rad_channel", "rad_channel"])
tu.add_encoding(variable, np.uint32, DefaultData.get_default_fill_value(np.uint32), 0.01)
dataset["S_u_L_earth"] = variable
# u_bt_random
variable = HIRS._create_3d_bt_uncertainty_variable(height, "uncertainty_bt_random")
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01)
tu.add_units(variable, "K")
dataset["u_bt_random"] = variable
# u_bt_structured
variable = HIRS._create_3d_bt_uncertainty_variable(height, "uncertainty_bt_structured")
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01)
tu.add_units(variable, "K")
dataset["u_bt_structured"] = variable
# u_bt_systematic
variable = HIRS._create_3d_bt_uncertainty_variable(height, "uncertainty_bt_systematic")
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01)
tu.add_units(variable, "K")
dataset["u_bt_systematic"] = variable
# u_bt_total
variable = HIRS._create_3d_bt_uncertainty_variable(height, "uncertainty_bt_total")
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01)
tu.add_units(variable, "K")
dataset["u_bt_total"] = variable
# S_bt
variable = tu.create_float_variable(NUM_RAD_CHANNELS, NUM_RAD_CHANNELS, "covariance_brightness_temperature", dim_names=["rad_channel", "rad_channel"])
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01)
dataset["S_bt"] = variable
# l1b_calcof
default_array = DefaultData.create_default_array(height, NUM_COEFFS, np.float32, dims_names=["coeffs", "y"])
variable = Variable(["coeffs", "y"], default_array)
tu.add_encoding(variable, np.int32, DefaultData.get_default_fill_value(np.int32), 0.01)
variable.attrs["standard_name"] = "calibration_coefficients"
dataset["l1b_calcof"] = variable
# navigation_status
variable = HIRS._create_int32_vector(height, standard_name="status_flag", long_name="Navigation status bit field", orig_name="hrs_navstat")
dataset["navigation_status"] = variable
# quality_flags
variable = HIRS._create_int32_vector(height, standard_name="status_flag", long_name="Quality indicator bit field", orig_name="hrs_qualind")
dataset["quality_flags"] = variable
variable = HIRS._create_scaled_uint16_vector(height, long_name="Platform altitude", original_name="hrs_scalti")
tu.add_units(variable, "km")
dataset["platform_altitude"] = variable
variable = HIRS._create_scaled_int16_vector(height, long_name="Platform pitch angle", original_name="hrs_pitchang")
tu.add_units(variable, "degree")
dataset["platform_pitch_angle"] = variable
variable = HIRS._create_scaled_int16_vector(height, long_name="Platform roll angle", original_name="hrs_rollang")
tu.add_units(variable, "degree")
dataset["platform_roll_angle"] = variable
variable = HIRS._create_scaled_int16_vector(height, long_name="Platform yaw angle", original_name="hrs_yawang")
tu.add_units(variable, "degree")
dataset["platform_yaw_angle"] = variable
# scan_angles
default_array = DefaultData.create_default_array(NUM_SCAN_ANGLES, height, np.float32, dims_names=["y", "num_scan_angles"], fill_value=np.NaN)
variable = Variable(["y", "num_scan_angles"], default_array)
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), scale_factor=0.01)
tu.add_units(variable, "degree")
variable.attrs["long_name"] = "Scan angles"
variable.attrs["orig_name"] = "hrs_ang"
dataset["scan_angles"] = variable
dataset["l1b_scanline_number"] = HIRS._create_int16_vector(height, long_name="scanline number", orig_name="hrs_scnlin")
dataset["scanline_position"] = HIRS._create_int8_vector(height, long_name="Scanline position number in 32 second cycle", orig_name="hrs_scnpos")
# second_original_calibration_coefficients
default_array = DefaultData.create_default_array(WIDTH_TODO, height, np.float32, fill_value=np.NaN)
variable = Variable(["y", "width_todo"], default_array)
tu.add_encoding(variable, np.int32, DefaultData.get_default_fill_value(np.int32), scale_factor=0.01)
variable.attrs["long_name"] = "Second original calibration coefficients (unsorted)"
variable.attrs["orig_name"] = "hrs_scalcof"
dataset["l1b_second_original_calibration_coefficients"] = variable
dataset["Tc_baseplate"] = HIRS._create_counts_vector(height, "temperature_baseplate_counts")
dataset["Tc_ch"] = HIRS._create_counts_vector(height, "temperature_coolerhousing_counts")
dataset["Tc_elec"] = HIRS._create_counts_vector(height, "temperature_electronics_counts")
dataset["Tc_fsr"] = HIRS._create_counts_vector(height, "temperature_first_stage_radiator_counts")
dataset["Tc_fwh"] = HIRS._create_counts_vector(height, "temperature_filter_wheel_housing_counts")
dataset["Tc_fwm"] = HIRS._create_counts_vector(height, "temperature_filter_wheel_monitor_counts")
dataset["Tc_icct"] = HIRS._create_counts_vector(height, "temperature_internal_cold_calibration_target_counts")
dataset["Tc_iwct"] = HIRS._create_counts_vector(height, "temperature_internal_warm_calibration_target_counts")
dataset["Tc_patch_exp"] = HIRS._create_counts_vector(height, "temperature_patch_expanded_scale_counts")
dataset["Tc_patch_full"] = HIRS._create_counts_vector(height, "temperature_patch_full_range_counts")
dataset["Tc_tlscp_prim"] = HIRS._create_counts_vector(height, "temperature_telescope_primary_counts")
dataset["Tc_tlscp_sec"] = HIRS._create_counts_vector(height, "temperature_telescope_secondary_counts")
dataset["Tc_tlscp_tert"] = HIRS._create_counts_vector(height, "temperature_telescope_tertiary_counts")
dataset["Tc_scanmirror"] = HIRS._create_counts_vector(height, "temperature_scanmirror_counts")
dataset["Tc_scanmotor"] = HIRS._create_counts_vector(height, "temperature_scanmotor_counts")
dataset["u_Tc_baseplate"] = HIRS._create_counts_uncertainty_vector(height, "uncertainty_temperature_baseplate_counts")
dataset["u_Tc_ch"] = HIRS._create_counts_uncertainty_vector(height, "uncertainty_temperature_coolerhousing_counts")
dataset["u_Tc_elec"] = HIRS._create_counts_uncertainty_vector(height, "uncertainty_temperature_electronics_counts")
dataset["u_Tc_fsr"] = HIRS._create_counts_uncertainty_vector(height, "uncertainty_temperature_first_stage_radiator_counts")
dataset["u_Tc_fwh"] = HIRS._create_counts_uncertainty_vector(height, "uncertainty_temperature_filter_wheel_housing_counts")
dataset["u_Tc_fwm"] = HIRS._create_counts_uncertainty_vector(height, "uncertainty_temperature_filter_wheel_monitor_counts")
dataset["u_Tc_icct"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_internal_cold_calibration_target_counts")
dataset["u_Tc_iwct"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_internal_warm_calibration_target_counts")
dataset["u_Tc_patch_exp"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_patch_expanded_scale_counts")
dataset["u_Tc_patch_full"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_patch_full_range_counts")
dataset["u_Tc_tlscp_prim"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_telescope_primary_counts")
dataset["u_Tc_tlscp_sec"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_telescope_secondary_counts")
dataset["u_Tc_tlscp_tert"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_telescope_tertiary_counts")
dataset["u_Tc_scanmirror"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_scanmirror_counts")
dataset["u_Tc_scanmotor"] = HIRS._create_counts_uncertainty_vector_uint32(height, "uncertainty_temperature_scanmotor_counts")
dataset["u_sol_za"] = HIRS._create_geo_angle_uncertainty_variable("uncertainty_solar_zenith_angle", height, FILL_VALUE)
dataset["u_sol_aa"] = HIRS._create_geo_angle_uncertainty_variable("uncertainty_solar_azimuth_angle", height, FILL_VALUE)
dataset["u_sat_za"] = HIRS._create_geo_angle_uncertainty_variable("uncertainty_satellite_zenith_angle", height, FILL_VALUE)
dataset["u_sat_aa"] = HIRS._create_geo_angle_uncertainty_variable("uncertainty_local_azimuth_angle", height, FILL_VALUE)
# u_c_earth_chan_corr
dataset["u_c_earth_chan_corr"] = HIRS._create_channel_correlation_variable("u_c_earth channel correlations", np.int16)
# u_c_space
default_array = DefaultData.create_default_array(NUM_CALIBRATION_CYCLE, NUM_CHANNELS, np.uint16, dims_names=["channel", "calibration_cycle"])
variable = Variable(["channel", "calibration_cycle"], default_array)
tu.add_fill_value(variable, DefaultData.get_default_fill_value(np.uint16))
tu.add_units(variable, "count")
tu.add_scale_factor(variable, 0.005)
variable.attrs["long_name"] = "uncertainty counts for space views"
variable.attrs["ancilliary_variables"] = "u_c_space_chan_corr"
variable.attrs["channels_affected"] = "all"
variable.attrs["parameter"] = "C_s"
variable.attrs["pdf_shape"] = "gaussian"
dataset["u_c_space"] = variable
# u_c_space_chan_corr
dataset["u_c_space_chan_corr"] = HIRS._create_channel_correlation_variable("u_c_space channel correlations", np.uint16)
# u_Earthshine
dataset["u_Earthshine"] = HIRS._create_channel_uncertainty_uint16(height)
# u_O_Re
dataset["u_O_Re"] = HIRS._create_channel_uncertainty_uint16(height)
# u_O_TIWCT
default_array = DefaultData.create_default_vector(height, np.float32, np.NaN)
variable = Variable(["y"], default_array)
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01)
dataset["u_O_TIWCT"] = variable
# u_O_TPRT
default_array = DefaultData.create_default_vector(height, np.uint16, DefaultData.get_default_fill_value(np.uint16))
variable = Variable(["y"], default_array)
tu.add_fill_value(variable, 65535)
tu.add_scale_factor(variable, 0.01)
tu.add_units(variable, "K")
variable.attrs["channels_affected"] = "all"
variable.attrs[corr.PIX_CORR_FORM] = corr.RECT_ABS
variable.attrs[corr.PIX_CORR_UNIT] = corr.PIXEL
variable.attrs[corr.PIX_CORR_SCALE] = [-np.inf, np.inf]
variable.attrs[corr.SCAN_CORR_FORM] = corr.RECT_ABS
variable.attrs[corr.SCAN_CORR_UNIT] = corr.LINE
variable.attrs[corr.SCAN_CORR_SCALE] = [-np.inf, np.inf]
variable.attrs[corr.IMG_CORR_FORM] = corr.RECT_ABS
variable.attrs[corr.IMG_CORR_UNIT] = corr.IMG
variable.attrs[corr.IMG_CORR_SCALE] = [-np.inf, np.inf]
variable.attrs["parameter"] = "O_TPRT"
variable.attrs["pdf_shape"] = "gaussian"
variable.attrs["short_name"] = "O_TPRT"
variable.attrs["ancilliary_variables"] = "u_O_TPRT_chan_corr"
dataset["u_O_TPRT"] = variable
dataset["u_Rself"] = HIRS._create_channel_uncertainty_uint16(height)
dataset["u_SRF_calib"] = HIRS._create_channel_uncertainty_uint16(height)
default_array = DefaultData.create_default_array(PRT_NUMBER_IWT, PRT_READING, dtype=np.float32, dims_names=["prt_number_iwt", "prt_reading"], fill_value=np.NaN)
variable = Variable(["prt_number_iwt", "prt_reading"], default_array)
tu.add_encoding(variable, np.uint16, DefaultData.get_default_fill_value(np.uint16), 0.01)
dataset["u_d_PRT"] = variable
dataset["u_electronics"] = HIRS._create_channel_uncertainty_uint16(height)
dataset["u_periodic_noise"] = HIRS._create_channel_uncertainty_uint16(height)
dataset["u_nonlinearity"] = HIRS._create_scaled_uint16_vector(NUM_CHANNELS, dimension_name=["channel"], scale_factor=0.01)
dataset["emissivity"] = tu.create_scalar_float_variable("emissivity", units="1")
dataset["temp_corr_slope"] = tu.create_scalar_float_variable("Slope for effective temperature correction", units="1")
dataset["temp_corr_offset"] = tu.create_scalar_float_variable("Offset for effective temperature correction", units="1")
# mnfrqualflags
default_array = DefaultData.create_default_array(NUM_MINOR_FRAME, height, np.int32, dims_names=["y", "minor_frame"], fill_value=0)
variable = Variable(["y", "minor_frame"], default_array)
variable.attrs["standard_name"] = "status_flag"
variable.attrs["long_name"] = "minor_frame_quality_flags_bitfield"
dataset["mnfrqualflags"] = variable
# scnlintime
variable = HIRS._create_int32_vector(height, standard_name="time", long_name="Scan line time of day", orig_name="hrs_scnlintime")
tu.add_units(variable, "ms")
dataset["scnlintime"] = variable
# scnlinf
default_array = DefaultData.create_default_vector(height, np.int16, fill_value=0)
variable = Variable(["y"], default_array)
variable.attrs["standard_name"] = "status_flag"
variable.attrs["long_name"] = "scanline_bitfield"
variable.attrs["flag_masks"] = "16384, 32768"
variable.attrs["flag_meanings"] = "clock_drift_correction southbound_data"
dataset["scnlinf"] = variable
# scantype
default_array = DefaultData.create_default_vector(height, np.int8, fill_value=0)
variable = Variable(["y"], default_array)
variable.attrs["standard_name"] = "status_flag"
variable.attrs["long_name"] = "scantype_bitfield"
variable.attrs["flag_values"] = "0, 1, 2, 3"
variable.attrs["flag_meanings"] = "earth_view space_view cold_bb_view main_bb_view"
dataset["scantype"] = variable
